Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

2014-01-01

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

Detection of underground structures using UAV and field spectroscopy for defence and security in Cyprus

NASA Astrophysics Data System (ADS)

Melillos, George; Themistocleous, Kyriacos; Prodromou, Maria; Hadjimitsis, Diofantos G.

2017-10-01

The purpose of this paper is to present the results obtained from unmanned aerial vehicle (UAV) and field spectroscopy campaigns for detecting underground structures. Underground structures can affect their surrounding landscapes in different ways, such as soil moisture content, soil composition and vegetation vigor. The last is often observed on the ground as a crop mark; a phenomenon which can be used as a proxy to denote the presence of underground non-visible structures. A number of vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), Difference Vegetation Index (DVI) and Soil Adjusted Vegetation Index (SAVI) were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices or other in-band algorithms. The measurements were taken at the following test areas such as: (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure.

Assessing corn water stress using spectral reflectance

NASA Astrophysics Data System (ADS)

Mefford, Brenna S.

Multiple remote sensing techniques have been developed to identify crop water stress, but some methods may be difficult for farmers to apply. Unlike most techniques, shortwave vegetation indices can be calculated using satellite, aerial, or ground imagery from the green (525-600 nm), red (625-700 nm), and near infrared (750-900 nm) spectral bands. If vegetation indices can be used to monitor crop water stress, growers could use this information as a quick low-cost guideline for irrigation management, thus helping save water by preventing over irrigating. This study occurred in the 2013 growing season near Greeley, CO, where pressurized drip irrigation was used to irrigate twelve corn ( Zea mays L.) treatments of varying water deficit. Multispectral data was collected and four different vegetation indices were evaluated: Normalized Difference Vegetation Index (NDVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Green Normalized Difference Vegetation Index (GNDVI), and the Wide Dynamic Range Vegetation Index (WDRVI). The four vegetation indices were compared to corn water stress as indicated by the stress coefficient (Ks) and water deficit in the root zone, calculated by using a water balance that monitors crop evapotranspiration (ET), irrigation events, precipitation events, and deep percolation. ET for the water balance was calculated using two different methods for comparison purposes: (1) calculation of the stress coefficient (Ks) using FAO-56 standard procedures; (2) use of canopy temperature ratio (Tc ratio) of a stressed crop to a non-stressed crop to calculate Ks. It was found that obtaining Ks from Tc ratio is a viable option, and requires less data to obtain than Ks from FAO-56. In order to compare the indices to Ks, vegetation ratios were developed in the process of normalization. Vegetation ratios are defined as the non-stressed vegetation index divided by the stressed vegetation index. Results showed that vegetation ratios were sensitive to water stress as indicated by good R2 values (Nratio = 0.53, G ratio=0.46, Oratio=0.49) and low RMSE values (Nratio = 0.076, Gratio=0.062, Oratio=0.076) when compared to Ks. Therefore it can be concluded that corn spectral reflectance is sensitive to water stress. In order to use spectral reflectance to manage crop water stress an irrigation trigger point of 0.93 for the vegetation ratios was determined. These results were validated using data collected by a MSR5 multispectral sensor in an adjacent field (SWIIM Field). The results from the second field proved better than in the main field giving higher R 2 values (Nratio = 0.66, Gratio = 0.63, Oratio = 0.66), and lower RMSE values (Nratio = 0.043, Gratio = 0.036, Oratio = 0.043) between Ks and the vegetation indices. SWIIM field further validated the results that spectral reflectance can be used to monitor corn water stress.

Vegetation canopy and physiological control of GPP decline during drought and heat wave

NASA Astrophysics Data System (ADS)

Zhang, Y.; Xiao, X.; Zhou, S.; McCarthy, H. R.; Ciais, P.; Luo, Y.

2015-12-01

Different vegetation indices derived from satellites were often used as a proxy of vegetation activity to monitor and evaluate the impacts of drought and heat wave on ecosystem carbon fluxes (gross primary production, respiration) through the production efficiency models (PEMs). However, photosynthesis is also regulated by a series of physiological processes which cannot be directly observed through satellites. In this study, we analyzed the response of drought and heat wave induced GPP and climate anomaly from 15 Euroflux sites and the corresponding vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Correlation analysis suggests that the vegetation indices are more responsive to GPP variation in grasslands and open shrublands, but less responsive in forest ecosystems. Physiology control can be up to 20% of the total GPP during the drought period without changing the canopy structure. At temporal scale for each site, VPD and vegetation indices can be used to track the GPP for forest and non-forest, respectively. However, different stand characteristics should be taken into consideration for forest ecosystems. Based on the above findings, a conceptual model is built to illuminate the physiological and canopy control on the GPP during the drought period. Improvement for future PEMs should incorporate better indicators to deal with drought conditions for different ecosystems.

A MODIS-based begetation index climatology

USDA-ARS?s Scientific Manuscript database

Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

PubMed

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

Vegetation-terrain feature relationships in southeast Arizona

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Mouat, D. A.

1972-01-01

There are no author-identified significant results in this report. Studies of relationships of vegetation distribution to geomorphic characteristics of the landscape and of plant phenological patterns to vegetation identification of satellite imagery indicate that there exists positive relationships between certain plant species and certain terrain features. Not all species were found to exhibit positive relationships with all terrain feature variables, but enough positive relationships seem to exist to indicate that terrain feature variable-vegetation relationship studies have a definite place in plant ecological investigations. Even more importantly, the vegetation groups examined appeared to be successfully discriminated by the terrain feature variables. This would seem to indicate that spatial interpretations of vegetation groups may be possible. While vegetational distributions aren't determined by terrain feature differences, terrain features do mirror factors which directly influence vegetational response and hence distribution. As a result, those environmental features which can be readily and rapidly ascertained on relatively small-scale imagery may prove to be valuable indicators of vegetation distribution.

Pathfinder, Volume 7, Number 6, November/December 2009

DTIC Science & Technology

2009-12-01

identified forest vegetation between 2005 and 2008 using normalized difference vegetation index ( NDVI ) measurements derived from low-resolution, com...posite images. Vegetation indices, including NDVI , are helpful for monitoring the health and vigor of vegetation and are used in products displaying

Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study

USGS Publications Warehouse

Gallo, Kevin P.; Eidenshink, Jeffery C.

1988-01-01

This study evaluates the differences in the visible and near-IR responses of the Advanced Very High Resolution Radiometers (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)-9 and -10 satellites for coincident sample locations. The study also evaluates the differences in vegetation indices computed from those data. Data were acquired of the southeast portion of the United States for the 6 December 1986 daylight orbits of NOAA-9 and NOAA-10 satellites. The results suggest that, with appropriate gain and offset, the vegetation indices of the two sensor systems may be interchangeable for assessment of land surfaces.

Biodiversity Measurement Using Indices Based on Hyperspectral Reflectance on the Coast of Lagos

NASA Astrophysics Data System (ADS)

Omodanisi, E. O.; Salami, A. T.

2013-12-01

Hyperspectral measurements provide explicit measurements which can be used in the analysis of biodiversity change. This study was carried out in the coastal area of Lagos State, Nigeria. The objective of this study was to determine if gasoline seepage affects vegetation species distribution and reflectance; with the view to analyzing the vegetation condition. To evaluate the potential of different reflectance spectroscopy of species, the ASD Handheld2 Spectrometer was used. Three identified impacted plots of 30m by 30m were selected randomly and a control plot established in relatively undisturbed vegetated areas away from but perpendicular to the source of seepage. Each identified plot and the control consisted of five transects and measurement were taken at every 2m with about four reflectance measurement per sample point, to average out differences in reflectance as a result of different leaf angles. The radiance output of the spectrometer was converted into reflectance using the reflectance of a white reference over a standardized white spectralon panel. Indices such as Normalized Differential Vegetation Index, RedEdge Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Ratio Vegetation Index and Volgelmann RedEdge Index 1 were calculated to accurately estimate the chlorophyll content in the vegetation within optimal band wavelength. Shannon-Weiner's index, Spearman's rank correlation and Analysis of Variance were used to analyze the data. Cocos nucifera was observed to be the most dominant species with a relative abundance of 47.27% while Ananas comosus recorded the lowest relative abundance of 21.8%. In the control plot, Cocos nucifera had the highest relative abundance of 42.3% and Mangifera indica with the least relative abundance of 16.7%. The relationship between the indices and chlorophyll content of the vegetation were significantly higher at (p>0.01) for all the indices in all the plots; however, RedEdgeNDVI and VOG1 indices had the highest occurring frequency among the entire plots. Thus they were used to distinguish relatively healthy from relatively unhealthy vegetation and it was statistically higher at F-ratio 4.825 (p<0.01) and 3.194 (p<0.01) respectively. It was concluded that gasoline affected the condition of vegetation.Table 2: Spearman's rank correlation analysis for relating indices with chlorophyll content for the field data at p>0.01, rho - correlation coefficient. (Source: Author: 2012) Field Spectral Indices Measurement The measurement above is the averaged value for the entire transect in each plot.(Source: Author, 2012)

Evaluating Hyperspectral Vegetation Indices for Leaf Area Index Estimation of Oryza sativa L. at Diverse Phenological Stages

PubMed Central

Din, Mairaj; Zheng, Wen; Rashid, Muhammad; Wang, Shanqin; Shi, Zhihua

2017-01-01

Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measurements were carried out over 2 years (2015 and 2016) in Meichuan, Hubei, China. Different N fertilization, 0, 45, 82, 127, 165, 210, 247, and 292 kg ha-1, were applied to generate various scales of VIs and LAI values. Regression models were used to perform quantitative analyses between spectral VIs and LAI measured under different phenological stages. In addition, the coefficient of determination and RMSE were employed to evaluate these models. Among the nine VIs, the ratio vegetation index, normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), modified triangular vegetation index (MTVI2) and exhibited strong and significant relationships with the LAI estimation at different phenological stages. The enhanced vegetation index performed moderately. However, the green normalized vegetation index and blue normalized vegetation index confirmed that there is potential for crop LAI estimation at early phenological stages; the soil-adjusted vegetation index and optimized soil-adjusted vegetation index were more related to the soil optical properties, which were predicted to be the least accurate for LAI estimation. The noise equivalent accounted for the sensitivity of the VIs and MSAVI, MTVI2, and NDVI for the LAI estimation at phenological stages. The results note that LAI at different crop phenological stages has a significant influence on the potential of hyperspectral derived VIs under different N management practices. PMID:28588596

Classification of Liss IV Imagery Using Decision Tree Methods

NASA Astrophysics Data System (ADS)

Verma, Amit Kumar; Garg, P. K.; Prasad, K. S. Hari; Dadhwal, V. K.

2016-06-01

Image classification is a compulsory step in any remote sensing research. Classification uses the spectral information represented by the digital numbers in one or more spectral bands and attempts to classify each individual pixel based on this spectral information. Crop classification is the main concern of remote sensing applications for developing sustainable agriculture system. Vegetation indices computed from satellite images gives a good indication of the presence of vegetation. It is an indicator that describes the greenness, density and health of vegetation. Texture is also an important characteristics which is used to identifying objects or region of interest is an image. This paper illustrate the use of decision tree method to classify the land in to crop land and non-crop land and to classify different crops. In this paper we evaluate the possibility of crop classification using an integrated approach methods based on texture property with different vegetation indices for single date LISS IV sensor 5.8 meter high spatial resolution data. Eleven vegetation indices (NDVI, DVI, GEMI, GNDVI, MSAVI2, NDWI, NG, NR, NNIR, OSAVI and VI green) has been generated using green, red and NIR band and then image is classified using decision tree method. The other approach is used integration of texture feature (mean, variance, kurtosis and skewness) with these vegetation indices. A comparison has been done between these two methods. The results indicate that inclusion of textural feature with vegetation indices can be effectively implemented to produce classifiedmaps with 8.33% higher accuracy for Indian satellite IRS-P6, LISS IV sensor images.

Effects and Mechanisms of Fruit and Vegetable Juices on Cardiovascular Diseases

PubMed Central

Zheng, Jie; Zhou, Yue; Li, Sha; Zhang, Pei; Zhou, Tong; Xu, Dong-Ping; Li, Hua-Bin

2017-01-01

Many studies have indicated that consumption of vegetables and fruits are positively related to lower incidence of several chronic noncommunicable diseases. Although composition of fruit and vegetable juices is different from that of the edible portion of fruits and vegetables, they contain polyphenols and vitamins from fruits and vegetables. Drinking vegetable and fruit juices is very popular in many countries, and also an efficient way to improve consumption of fruits and vegetables. The studies showed that fruit and vegetable juices affect cardiovascular risk factors, such as lowering blood pressure and improving blood lipid profiles. The main mechanisms of action included antioxidant effects, improvement of the aspects of the cardiovascular system, inhibition of platelet aggregation, anti-inflammatory effects, and prevention of hyperhomocysteinemia. Drinking juices might be a potential way to improve cardiovascular health, especially mixtures of juices because they contain a variety of polyphenols, vitamins, and minerals from different fruits and vegetables. This review summarizes recent studies on the effects of fruit and vegetable juices on indicators of cardiovascular disease, and special attention is paid to the mechanisms of action. PMID:28273863

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

NASA Astrophysics Data System (ADS)

Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

Assessment of the capability of remote sensing and GIS techniques for monitoring reclamation success in coal mine degraded lands.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan; Maiti, Subodh Kumar

2016-11-01

The objective of the present study is to monitor reclamation activity in mining areas. Monitoring of these reclaimed sites in the vicinity of mining areas and on closed Over Burden (OB) dumps is critical for improving the overall environmental condition, especially in developing countries where area around the mines are densely populated. The present study evaluated the reclamation success in the Block II area of Jharia coal field, India, using Landsat satellite images for the years 2000 and 2015. Four image processing methods (support vector machine, ratio vegetation index, enhanced vegetation index, and normalized difference vegetation index) were used to quantify the change in vegetation cover between the years 2000 and 2015. The study also evaluated the relationship between vegetation health and moisture content of the study area using remote sensing techniques. Statistical linear regression analysis revealed that Normalized Difference Vegetation Index (NDVI) coupled with Normalized Difference Moisture Index (NDMI) is the best method for vegetation monitoring in the study area when compared to other indices. A strong linear relationship (r(2) > 0.86) was found between NDVI and NDMI. An increase of 21% from 213.88 ha in 2000 to 258.9 ha in 2015 was observed in the vegetation cover of the reclaimed sites for an open cast mine, indicating satisfactory reclamation activity. NDVI results indicated that vegetation health also improved over the years. Copyright © 2016 Elsevier Ltd. All rights reserved.

Monitoring Coastal Marshes for Persistent Saltwater Intrusion

DTIC Science & Technology

2010-06-01

for the normalized difference indices (vegetation, soil, and water– NDVI , NDSI, and NDWI) for both MODIS and Landsat 5 and 7, referred to as the...Normalized Difference Index transformation [4]. The MODIS indices are 250 m ( NDVI ) and 500 m (NDWI and NDSI), and the Landsat indices are 30 m...indices are shown for two locations in Fig. 1 and Fig 2. Each figure shows the NDSI (soil), NDVI (vegetation), and NDWI (water) index as a function of

[Quantitative relationships between hyper-spectral vegetation indices and leaf area index of rice].

PubMed

Tian, Yong-Chao; Yang, Jie; Yao, Xia; Zhu, Yan; Cao, Wei-Xing

2009-07-01

Based on field experiments with different rice varieties under different nitrogen application levels, the quantitative relationships of rice leaf area index (LAI) with canopy hyper-spectral parameters at different growth stages were analyzed. Rice LAI had good relationships with several hyper-spectral vegetation indices, the correlation coefficient being the highest with DI (difference index), followed by with RI (ratio index), and NI (normalized index), based on the spectral reflectance or the first derivative spectra. The two best spectral indices for estimating LAI were the difference index DI (854, 760) (based on two spectral bands of 850 nm and 760 nm) and the difference index DI (D676, D778) (based on two first derivative bands of 676 nm and 778 nm). In general, the hyper-spectral vegetation indices based on spectral reflectance performed better than the spectral indices based on the first derivative spectra. The tests with independent dataset suggested that the rice LAI monitoring models with difference index DI (854,760) as the variable could give an accurate LAI estimation, being available for estimation of rice LAI.

Evaluation and cross-comparison of vegetation indices for crop monitoring from sentinel-2 and worldview-2 images

NASA Astrophysics Data System (ADS)

Psomiadis, Emmanouil; Dercas, Nicholas; Dalezios, Nicolas R.; Spyropoulos, Nikolaos V.

2017-10-01

Farmers throughout the world are constantly searching for ways to maximize their returns. Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop vigor problems. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. However, due to the various sensor characteristics, there are differences among VIs derived from multiple sensors for the same target. Therefore, multi-sensor VI capability and effectiveness are critical but complicated issues in the application of multi-sensor vegetation observations. Various factors such as the atmospheric conditions during acquisition, sensor and geometric characteristics, such as viewing angle, field of view, and sun elevation influence direct comparability of vegetation indicators among different sensors. In the present study, two experimental areas were used which are located near the villages Nea Lefki and Melia of Larissa Prefecture in Thessaly Plain area, containing a wheat and a cotton crop, respectively. Two satellite systems with different spatial resolution, WorldView-2 (W2) and Sentinel-2 (S2) with 2 and 10 meters pixel size, were used. Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were calculated and a statistical comparison of the VIs was made to designate their correlation and dependency. Finally, several other innovative indices were calculated and compared to evaluate their effectiveness in the detection of problematic plant growth areas.

Earth Observation and Science: Monitoring Vegetation Dynamics from Deep Space Gateway

NASA Astrophysics Data System (ADS)

Knyazikhin, Y.; Park, T.; Hu, B.

2018-02-01

Retrieving diurnal courses of sunlit (SLAI) and shaded (ShLAI) leaf area indices, fraction of photosynthetically active radiation (PAR) absorbed by vegetation (FPAR), and Normalized Difference Vegetation Index (NDVI) from Deep Space Gateway data.

Revealing livestock effects on bunchgrass vegetation with Landsat ETM+ data across a grazing season

NASA Astrophysics Data System (ADS)

Jansen, Vincent S.

Remote sensing provides monitoring solutions for more informed grazing management. To investigate the ability to detect the effects of cattle grazing on bunchgrass vegetation with Landsat Enhanced Thematic Mapper Plus (ETM+) data, we conducted a study on the Zumwalt Prairie in northeastern Oregon across a gradient of grazing intensities. Biophysical vegetation data was collected on vertical structure, biomass, and cover at three different time periods during the grazing season: June, August, and October 2012. To relate these measures to the remotely sensed Landsat ETM+ data, Pearson's correlations and multiple regression models were computed. Using the best models, predicted vegetation metrics were then mapped across the study area. Results indicated that models using common vegetation indices had the ability to discern different levels of grazing across the study area. Results can be distributed to land managers to help guide grassland conservation by improving monitoring of bunchgrass vegetation for sustainable livestock management.

Soybean varieties discrimination using non-imaging hyperspectral sensor

NASA Astrophysics Data System (ADS)

da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo

2018-03-01

Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.

Comparison of remote sensing indices for monitoring of desert cienegas

USGS Publications Warehouse

Wilson, Natalie R.; Norman, Laura M.; Villarreal, Miguel; Gass, Leila; Tiller, Ron; Salywon, Andrew

2016-01-01

This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.

Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

USGS Publications Warehouse

Chen, Xuexia; Vogelmann, James E.; Rollins, Matt; Ohlen, Donald; Key, Carl H.; Yang, Limin; Huang, Chengquan; Shi, Hua

2011-01-01

It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can providemultitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas.

Use of vegetation indices to estimate intercepted solar radiation and net carbon dioxide exchange of a grass canopy

NASA Technical Reports Server (NTRS)

Bartlett, David S.; Whiting, Gary J.; Hartman, Jean M.

1989-01-01

Results are presented from field experiments relating spectral reflectance to intercepted photosynthetically active radiation (PAR) and net CO2 exchange in a natural canopy composed of the marsh cordgrass (Spartina alterniflora). Reflectance measurements made by a hand-held radiometer with Landsat TM spectral wavebands are used to compute remote sensing indices such as the normalized difference vegetation index. Consideration is given to the impact of standing dead canopy material on the relationship between intercepted PAR and spectral vegetation indices and the impact of changes in photosynthetic efficiency on the relationship between vegetation indices and CO2 exchange rates. The results suggest that quantitative remote assessment of photosynthesis and net gas exchange in natural vegetation is feasible, especially if the analysis incorporates information on biological responses to environmental variables.

Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

Biophysical characterization and management effects on semiarid rangeland observed from Landsat ETM+ data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Hongliang; Liang, Shunlin; McClaran, Mitchell P.

2005-01-20

Semi-arid rangelands are very sensitive to global climatic change; studies of their biophysical attributes are crucial to understanding the dynamics of rangeland ecosystems under human disturbance. In the Santa Rita Experimental Range (SRER), Arizona, the vegetation has changed considerably and there have been many management activities applied. This study calculates seven surface variables: the enhanced vegetation index (EVI), the normalized difference vegetation index (NDVI), surface albedos (total shortwave, visible and near-infrared), leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by green vegetation (FPAR) from the Enhanced Thematic Mapper (ETM+) data. Comparison with the MODIS (Moderate Resolutionmore » Imaging Spectroradiometer) vegetation index and albedo products indicate they agree well with our estimates from ETM+ while their LAI and FPAR are larger than ETM+. Human disturbance has significantly changed the cover types and biophysical conditions. Statistical tests indicate that surface albedos increased and FPAR decreased at all sites. The recovery will require more than 67 years, and is about 50% complete within 40 years at the higher elevation. Grass cover, vegetation indices, albedos and LAI recovered from cutting faster at the higher elevation. Woody plants, vegetation indices and LAI have recovered to their original characteristics after 65 years at the lower elevation. More studies are needed to examine the spectral characteristics of different ground components.« less

Assessing the Ability of Vegetation Indices to Identify Shallow Subsurface Water Flow Pathways from Hyperspectral Imagery Using Machine Learning: Methodology

NASA Astrophysics Data System (ADS)

Byers, J. M.; Doctor, K.

2017-12-01

A common application of the satellite and airborne acquired hyperspectral imagery in the visible and NIR spectrum is the assessment of vegetation. Various absorption features of plants related to both water and chlorophyll content can be used to measure the vigor and access to underlying water sources of the vegetation. The typical strategy is to form hand-crafted features from the hyperspectral data cube by selecting two wavelengths to form difference or ratio images in the pixel space. The new image attempts to provide greater contrast for some feature of the vegetation. The Normalized Difference Vegetation Index (NDVI) is a widely used example formed from the ratio of differences and sums at two different wavelengths. There are dozens of these indices that are ostensibly formed using insights about the underlying physics of the spectral absorption with claims to efficacy in representing various properties of vegetation. In the language of machine learning these vegetation indices are features that can be used as a useful data representation within an algorithm. In this work we use a powerful approach from machine learning, probabilistic graphical models (PGM), to balance the competing needs of using existing hydrological classifications of terrain while finding statistically reliable features within hyperspectral data for identifying the generative process of the data. The algorithm in its simplest form is called a Naïve Bayes (NB) classifier and can be constructed in a data-driven estimation procedure of the conditional probability distributions that form the PGM. The Naïve Bayes model assumes that all vegetation indices (VI) are independent of one another given the hydrological class label. We seek to test its validity in a pilot study of detecting subsurface water flow pathways from VI. A more sophisticated PGM will also be explored called a tree-augmented NB that accounts for the probabilistic dependence between VI features. This methodology provides a general approach for classifying hydrological structures from hyperspectral data.

Drought in the Rockies

NASA Technical Reports Server (NTRS)

2002-01-01

This image shows the difference between the amount of vegetation in July 2000 and the average July vegetation for North America. Of particular interest are the dry conditions in the western United States. This spring and summer the Rocky Mountains have been relatively dry, and the brown regions stretching from the Canadian to the Mexican border, indicate the effect on the regions' forests. Western Montana and eastern Idaho are particularly parched, and appear darker brown. The dry conditions have contributed to this year's devastating fire season, during which millions of acres have burned in the west. Scientists find that during the growing season, land plants can be used to measure drought. Healthy, thriving plants reflect and absorb visible and near-infrared light differently than plants under stress. These variations in reflectance and absorption can be measured by satellites to produce maps of healthy and stressed vegetation. This image shows Normalized Difference Vegetation Index (NDVI) anomaly, which indicates where vegetation growth was above average (green pixels), below average (brown pixels), or normal (white pixels). For more images and information about measuring vegetation and drought from space visit: Drought and Vegetation Monitoring. Image courtesy NASA Goddard Space Flight Center Biospheric Sciences Branch, based on data from NOAA.

Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

NASA Astrophysics Data System (ADS)

Mundava, C.; Helmholz, P.; Schut, A. G. T.; Corner, R.; McAtee, B.; Lamb, D. W.

2014-09-01

The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of two years (2011-2013). The sites were divided into three groups (Open plains, Bunch grasses and Spinifex) based on similarities in dominant vegetation types. Dry and green biomass fractions were measured at these sites. Single and multiple regression relationships between vegetation indices and green and total AGB were calibrated and validated using a "leave site out" cross validation. Four tests were compared: (1) relationships between AGB and vegetation indices combining all sites; (2) separate relationships per site group; (3) multiple regressions including selected vegetation indices per site group; and (4) as in 3 but including rainfall and elevation data. Results indicate that relationships based on single vegetation indices are moderately accurate for green biomass in wide open plains covered with annual grasses. The cross-validation results for green AGB improved for a combination of indices for the Open plains and Bunch grasses sites, but not for Spinifex sites. When rainfall and elevation data are included, cross validation improved slightly with a Q2 of 0.49-0.72 for Open plains and Bunch grasses sites respectively. Cross validation results for total AGB were moderately accurate (Q2 of 0.41) for Open plains but weak or absent for other site groups despite good calibration results, indicating strong influence of site-specific factors.

Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

NASA Astrophysics Data System (ADS)

Georgopoulou, Danai; Koutsias, Nikos

2015-04-01

Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we explore the strength and the use of these time series satellite data to characterize vegetation phenology as an a aid to monitor vegetation recovery in fire affected-areas. In a recent study we found that the original spectral channels, based on which these indices are estimated, are sensitive to external vegetation parameters such as the spectral reflectance of the background soil. In such cases, the influence of the soil in the reflectance values is different in the various spectral regions depending on its type. The use of such indices is also justified according to a recent study on the sensitivity of spectral reflectance values to different burn and vegetation ratios, who concluded that the Near Infrared (NIR) and Short-Wave Infrared (SWIR) are the most important channels to estimate the percentage of burned area, whereas the NIR and red channels are the most important to estimate the percentage of vegetation in fire-affected areas. Additionally, it has been found that semi-burned classes are spectrally more consistent to their different fractions of scorched and non-scorched vegetation, than the original spectral channels based on which these indices are estimated.

[Effects of re-vegetation on soil microbial functional diversity in purple soils at different re-vegetation stages on sloping-land in Hengyang, Hunan Province, China.

PubMed

Wen, Dong Xin; Yang, Ning; Yang, Man Yuan

2016-08-01

The aim of the study was to explore the effects of re-vegetation on soil microbial functio-nal diversity in purple soils at different re-vegetation stages on sloping-land in Hengyang, Hunan Province, China. By using the spatial series to replace time series, four typical sampling plots, grass (Setaria viridi, GS), frutex and grass (Lagerstroemia indica-Setaria viridi, FG), frutex (Vitex negundo var. cannabifolia+Robinia pseudoacacia, FX), as well as arbor and frutex (Liquidamdar formosana+Melia azedarach-Vitex negundo var. cannabifolia, AF) community were selected to study the soil microbial functional diversity by using the Biolog-ECO micro-plate technique. The four communities in purple soils on sloping-land were similar and denoted four different re-vegetation stages. The results showed that the soil microbial metabolic activity increased after re-vegetation significantly, and the average well color development (AWCD) which represented soil microbial activity and functional diversity followed the order of AF community＞FX community＞FG community＞GS community at different re-vegetation stages, and followed the order of 0-10 cm ＞10-20 cm in different soil layers. Principal component analysis (PCA) identified that FG and FX community had similar C sources utilization mode and metabolic function, and GS and AF community were diffe-rent. The carbohydrates, amino acids, intermediate metabolites, and secondary metabolites were the main carbon sources separating the two principal component factors. The Shannon species richness index (H), Shannon evenness index (E), Simpson dominance index (D), McIntosh index (U) at four re-vegetation stages were the highest in AF community, the second in FG and FX community, and the lowest in GS community. The results of correlation analysis indicated that the content of soil water content (SWC), soil total organic carbon (STOC), total nitrogen (TN), total phospho-rus (TP) and available phosphorus (AP) had important influence on the soil microbial metabolic function and functional diversity indices. There existed significant correlation between the activities of urease (URE), alk-phosphatase (APE), invertase (INV), catalase (CAT) and the soil microbial metabolic function and functional diversity indices. All the results indicated that re-vegetation could enhance the soil microbial metabolic function, which was beneficial to the reproduction of soil micro-organisms, thereby promoting an increase of soil carbon source utilization intensity.

Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images

NASA Technical Reports Server (NTRS)

Menenti, M.; Azzali, S.; Verhoef, W.; Van Swol, R.

1993-01-01

Examples are presented of applications of a fast Fourier transform algorithm to analyze time series of images of Normalized Difference Vegetation Index values. The results obtained for a case study on Zambia indicated that differences in vegetation development among map units of an existing agroclimatic map were not significant, while reliable differences were observed among the map units obtained using the Fourier analysis.

Effects of experimental protocol on global vegetation model accuracy: a comparison of simulated and observed vegetation patterns for Asia

USGS Publications Warehouse

Tang, Guoping; Shafer, Sarah L.; Barlein, Patrick J.; Holman, Justin O.

2009-01-01

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO2 concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO2 concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO2 concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.

Dynamics of Vegetatin Indices in Tropical and Subtropical Savannas Defined by Ecoregions and Moderate Resolution Imaging Spectoradiometer (MODIS) Land Cover

NASA Technical Reports Server (NTRS)

Hill, Michael J.; Roman, Miguel O.; Schaaf, Crytal B.

2011-01-01

In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed.

Foliar anthocyanin content - Sensitivity of vegetation indices using green reflectance

NASA Astrophysics Data System (ADS)

Vina, A.; Gitelson, A. A.

2009-12-01

The amount and composition of photosynthetic and non-photosynthetic foliar pigments varies primarily as a function of species, developmental and phenological stages, and environmental stresses. Information on the absolute and relative amounts of these pigments thus provides insights onto the physiological conditions of plants and their responses to stress, and has the potential to be used for evaluating plant species composition and diversity across broad geographic regions. Anthocyanins in particular, are non-photosynthetic pigments associated with the resistance of plants to environmental stresses (e.g., drought, low soil nutrients, high radiation, herbivores, and pathogens). As they absorb radiation primarily in the green region of the electromagnetic spectrum (around 540-560 nm), broad-band vegetation indices that use this region in their formulation will respond to their presence. We evaluated the sensitivity of three vegetation indices using reflectance in the green spectral region (the green Normalized Difference Vegetation Index, gNDVI, the green Chlorophyll Index, CIg, and the Visible Atmospherically Resistant Vegetation Index, VARI) to foliar anthocyanins in five different species. For comparison purposes the widely used Normalized Difference Vegetation Index, NDVI was also evaluated. Among the four indices tested, the VARI, which uses only spectral bands in the visible region of the electromagnetic spectrum, was found to be inversely and linearly related to the relative amount of foliar anthocyanins. While this result was obtained at leaf level, it opens new possibilities for analyzing anthocyanin content across multiple scales, by means of currently operational aircraft- and spacecraft-mounted broad-band sensor systems. Further studies that evaluate the sensitivity of the VARI to the relative content of anthocyanins across space (e.g., at canopy and regional scales) and time, and its relationship with plant biodiversity and vegetation stresses, are needed.

Relative sensitivity of Normalized Difference Vegetation Index (NDVI) and Microwave Polarization Difference Index (MPDI) for vegetation and desertification monitoring

NASA Technical Reports Server (NTRS)

Becker, Francois; Choudhury, Bhaskar J.

1988-01-01

A simple equation relating the Microwave Polarization Difference Index (MPDI) and the Normalized Difference Vegetation Index (NDVI) is proposed which represents well data obtained from Nimbus 7/SMMR at 37 GHz and NOAA/AVHRR Channels 1 and 2. It is found that there is a limit which is characteristic of a particular type of cover for which both indices are equally sensitive to the variation of vegetation, and below which MPDI is more efficient than NDVI. The results provide insight into the relationship between water content and chlorophyll absorption at pixel size scales.

How useful are meteorological drought indicators to assess agricultural drought impacts across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Tanguy, Maliko; Hannaford, Jamie; Stahl, Kerstin

2016-04-01

Drought monitoring and early warning (M&EW) is an important component of agricultural and silvicultural risk management. Meteorological indicators such as the Standardized Precipitation Index (SPI) are widely used in operational M&EW systems and for drought hazard assessment. Meteorological drought yet does not necessarily equate to agricultural drought given differences in drought susceptibility, e.g. crop-specific vulnerability, soil water holding capacity, irrigation and other management practices. How useful are meteorological indicators such as SPI to assess agricultural drought? Would the inclusion of vegetation indicators into drought M&EW systems add value for the agricultural sector? To answer these questions, it is necessary to investigate the link between meteorological indicators and agricultural impacts of drought. Crop yield or loss data is one source of information for drought impacts, yet mostly available as aggregated data at the annual scale. Remotely sensed vegetation stress data offer another possibility to directly assess agricultural impacts with high spatial and temporal resolution and are already used by some M&EW systems. At the same time, reduced crop yield and satellite-based vegetation stress potentially suffer from multi-causality. The aim of this study is therefore to investigate the relation between meteorological drought indicators and agricultural drought impacts for Europe, and to intercompare different agricultural impact variables. As drought indicators we used SPI and the Standardized Precipitation Evaporation Index (SPEI) for different accumulation periods. The focus regarding drought impact variables was on remotely sensed vegetation stress derived from MODIS NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) data, but the analysis was complemented with crop yield data and text-based information from the European Drought Impact report Inventory (EDII) for selected countries. A correlation analysis between meteorological drought indicators and remotely sensed vegetation stress at the EU NUTS3 region level revealed a high correlation between the two types of indicators for many regions; however some spatial variability was observed in (i) strength of correlation, (ii) performance of SPI versus SPEI, and (iii) best linked SPI/SPEI time scale. We additionally explored whether geographic properties like climate, soil texture, land use, and location explain the observed spatial patterns. Our study revealed that climatically dryer areas (water limited) showed high correlations between SPI/SPEI and vegetation stress, whereas the wettest parts of Europe (radiation limited regions) showed negative correlations especially for short accumulation periods, suggesting that for these regions, short droughts could actually be beneficial for vegetation growth. These findings suggest that relying solely on meteorological indicators for agricultural risk assessment in some regions might be inadequate. Overall, such information may help to tailor agricultural drought M&EW systems to specific regions.

Using vegetation indices as input into ramdom forest for soybean and weed classification

USDA-ARS?s Scientific Manuscript database

Weed management is a major component of a soybean (Glycine max L.) production system; thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The o...

Land Fire impacts assessment on the Rice Watershed, California. 2007

NASA Astrophysics Data System (ADS)

Zahraei, A.; Imam, B.; Sorooshian, S.

2009-12-01

Burn impacts assessment is a key factor for the post-fire disaster management. For example, assessing wildfire impacts on vegetation is an important component of improving the prediction of hydrologic and ecologic impacts of wildfires within the affected watershed. Many studies have analyzed satellite derived indices of vegetation vigor as indicator of burning effects. This poster reports a study in which Landsat (TM) data was used to compute three indices, NDVI, MASAVI and NBR, which are commonly used in assessing wildfire impacts. The study focused on the Rice watershed southern California, which was affected by a major wildfire in the 2007 fire season. A series of before and after Landsat images were used to evaluate these indices evaluated before and after the wildfire. Comparison between the three indices reveals that the affects of the fire were not very prominently present in the Satellite observation due to the length of time separating the fire from the next available Lansat scene. Such separation may include a period of vegetation recovery. However, when compared with the scenes from the previous year, but for the same season, post fire vegetation show marked differences from pre-fire conditions. The ability of NDVI, MSAVI and NBR to monitor post-fire impacts on vegetation is further evaluated by comparing precipitation patterns in 2006 and 2007, which may shed more light on whether the marked difference in these indices are due to dry/wet differences or to the impacts of fire. NDVI shows more reliability and better representation of both long-term and short-term impacts of wild-fire.

Radiative transfer in shrub savanna sites in Niger: Preliminary results from HAPEX-Sahel. Part 3: Optical dynamics and vegetation index sensitivity to biomass and plant cover

NASA Technical Reports Server (NTRS)

vanLeeuwen, W. J. D.; Huete, A. R.; Duncan, J.; Franklin, J.

1994-01-01

A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (6) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large 6 dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.

Geomorphology and reflectance patterns of vegetation-covered dunes at the Tsodilo Hills, north-west Botswana

NASA Technical Reports Server (NTRS)

Jacobberger, P. A.; Hooper, D. M.

1991-01-01

Seasonal reflectance variations in semigrid environments provide a means of assessing vegetation health and density as well as monitoring landform processes. Multitemporal Landsat Thematic Mapper scenes with field measurements are used to map geomorphology and vegetation density in a stabilized dune environment and to measure seasonal reflectance changes for a series of ten geomorphological and vegetation units on the Kalahari-age linear dunes. Units were chosen based on differences in landform and proportion of trees, forbs and bare soil. Reflectance curves and normalized-difference vegetation indices (NDVI) show that dune crests have the strongest seasonal variability in color and brightness. The geomorphological link with reflectance and NDVI values are linked to biomass production and zoning of vegetation with slope, drainage and subtle soil differences.

Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance

NASA Astrophysics Data System (ADS)

Xue, Lihong; Yang, Linzhang

Different nitrogen (N) treatments of four common green-leafy vegetable varieties with different leaf color: lettuce ( Lactuca sativa L. var. crispa L.) with yellow green leaves, pakchoi ( Brassica chinensis L.) var. aijiaohuang in Chinese (AJH) with middle green leaves, spinach ( Spinacia oleracea L.) with green leaves and pakchoi ( B. chinensis L.) var. shanghaiqing in Chinese (SHQ) with dark green leaves, were carried out to achieve a wide range of chlorophyll content. The relationship of vegetable leaf hyperspectral response to its chlorophyll content was examined in this study. Almost all reported successful leaf chlorophyll indices in the literature were evaluated for their ability to predict the chlorophyll content in vegetable leaves. Some new indices based on the first derivative curve were also developed, and compared with the chlorophyll indices published. The results showed that most of the indices showed a strong relation with leaf chlorophyll content. In general, modified indices with the blue or near red edge wavelength performed better than their simple counterpart without modification, ratio indices performed a little better than normalized indices when chlorophyll expressed on area basis and reversed when chlorophyll expressed on fresh weight basis. A normalized derivative difference ratio (BND: (D722-D700)/(D722+D700) calibrated by Maire et al. [Maire, G., Francois, C., Dufrene, E., 2004. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment 89 (1), 1-28]) gave the best results among all published indices in this study (RMSE=22.1 mg m -2), then the mSR-like indices with the RMSE between 22.6 and 23.0 mg m -2. The new indices EBAR (ratio of the area of red and blue, ∑ dRE/∑ dB), EBFN (normalized difference of the amplitude of red and blue, (dRE-dB)/(dRE+dB)) and EBAN (normalized difference of the area of red and blue, (∑ dRE-∑ dB)/(∑ dRE+∑ dB)) calculated with the derivatives also showed a good performance with the RMSE of 23.3, 24.15 and 24.33 mg m -2, respectively. The study suggests that spectral reflectance measurements hold promise for the assessment of chlorophyll content at the leaf level for green-leafy vegetables. Further investigation is needed to evaluate the effectiveness of such techniques on other vegetable varieties or at the canopy level.

Combining ground-based measurements and satellite-based spectral vegetation indices to track biomass accumulation in post-fire chaparral

NASA Astrophysics Data System (ADS)

Uyeda, K. A.; Stow, D. A.; Roberts, D. A.; Riggan, P. J.

2015-12-01

Multi-temporal satellite imagery can provide valuable information on patterns of vegetation growth over large spatial extents and long time periods, but corresponding ground-referenced biomass information is often difficult to acquire, especially at an annual scale. In this study, I test the relationship between annual biomass estimated using shrub growth rings and metrics of seasonal growth derived from Moderate Resolution Imaging Spectroradiometer (MODIS) spectral vegetation indices (SVIs) for a small area of southern California chaparral to evaluate the potential for mapping biomass at larger spatial extents. The site had most recently burned in 2002, and annual biomass accumulation measurements were available from years 5 - 11 post-fire. I tested metrics of seasonal growth using six SVIs (Normalized Difference Vegetation Index, Enhanced Vegetation Index, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Normalized Difference Infrared Index 6, and Vegetation Atmospherically Resistant Index). While additional research would be required to determine which of these metrics and SVIs are most promising over larger spatial extents, several of the seasonal growth metrics/ SVI combinations have a very strong relationship with annual biomass, and all SVIs have a strong relationship with annual biomass for at least one of the seasonal growth metrics.

Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data

NASA Astrophysics Data System (ADS)

Chemura, Abel; Mutanga, Onisimo; Odindi, John; Kutywayo, Dumisani

2018-04-01

Nitrogen (N) is the most limiting factor to coffee development and productivity. Therefore, development of rapid, spatially explicit and temporal remote sensing-based approaches to determine spatial variability of coffee foliar N are imperative for increasing yields, reducing production costs and mitigating environmental impacts associated with excessive N applications. This study sought to assess the value of Sentinel-2 MSI spectral bands and vegetation indices in empirical estimation of coffee foliar N content at landscape level. Results showed that coffee foliar N is related to Sentinel-2 MSI B4 (R2 = 0.32), B6 (R2 = 0.49), B7 (R2 = 0.42), B8 (R2 = 0.57) and B12 (R2 = 0.24) bands. Vegetation indices were more related to coffee foliar N as shown by the Inverted Red-Edge Chlorophyll Index - IRECI (R2 = 0.66), Relative Normalized Difference Index - RNDVI (R2 = 0.48), CIRE1 (R2 = 0.28), and Normalized Difference Infrared Index - NDII (R2 = 0.37). These variables were also identified by the random forest variable optimisation as the most valuable in coffee foliar N prediction. Modelling coffee foliar N using vegetation indices produced better accuracy (R2 = 0.71 with RMSE = 0.27 for all and R2 = 0.73 with RMSE = 0.25 for optimized variables), compared to using spectral bands (R2 = 0.57 with RMSE = 0.32 for all and R2 = 0.58 with RMSE = 0.32 for optimized variables). Combining optimized bands and vegetation indices produced the best results in coffee foliar N modelling (R2 = 0.78, RMSE = 0.23). All the three best performing models (all vegetation indices, optimized vegetation indices and combining optimal bands and optimal vegetation indices) established that 15.2 ha (4.7%) of the total area under investigation had low foliar N levels (<2.5%). This study demonstrates the value of Sentinel-2 MSI data, particularly vegetation indices in modelling coffee foliar N at landscape scale.

Comparison modeling for alpine vegetation distribution in an arid area.

PubMed

Zhou, Jihua; Lai, Liming; Guan, Tianyu; Cai, Wetao; Gao, Nannan; Zhang, Xiaolong; Yang, Dawen; Cong, Zhentao; Zheng, Yuanrun

2016-07-01

Mapping and modeling vegetation distribution are fundamental topics in vegetation ecology. With the rise of powerful new statistical techniques and GIS tools, the development of predictive vegetation distribution models has increased rapidly. However, modeling alpine vegetation with high accuracy in arid areas is still a challenge because of the complexity and heterogeneity of the environment. Here, we used a set of 70 variables from ASTER GDEM, WorldClim, and Landsat-8 OLI (land surface albedo and spectral vegetation indices) data with decision tree (DT), maximum likelihood classification (MLC), and random forest (RF) models to discriminate the eight vegetation groups and 19 vegetation formations in the upper reaches of the Heihe River Basin in the Qilian Mountains, northwest China. The combination of variables clearly discriminated vegetation groups but failed to discriminate vegetation formations. Different variable combinations performed differently in each type of model, but the most consistently important parameter in alpine vegetation modeling was elevation. The best RF model was more accurate for vegetation modeling compared with the DT and MLC models for this alpine region, with an overall accuracy of 75 % and a kappa coefficient of 0.64 verified against field point data and an overall accuracy of 65 % and a kappa of 0.52 verified against vegetation map data. The accuracy of regional vegetation modeling differed depending on the variable combinations and models, resulting in different classifications for specific vegetation groups.

Developing a Method to Mask Trees in Commercial Multispectral Imagery

NASA Astrophysics Data System (ADS)

Becker, S. J.; Daughtry, C. S. T.; Jain, D.; Karlekar, S. S.

2015-12-01

The US Army has an increasing focus on using automated remote sensing techniques with commercial multispectral imagery (MSI) to map urban and peri-urban agricultural and vegetative features; however, similar spectral profiles between trees (i.e., forest canopy) and other vegetation result in confusion between these cover classes. Established vegetation indices, like the Normalized Difference Vegetation Index (NDVI), are typically not effective in reliably differentiating between trees and other vegetation. Previous research in tree mapping has included integration of hyperspectral imagery (HSI) and LiDAR for tree detection and species identification, as well as the use of MSI to distinguish tree crowns from non-vegetated features. This project developed a straightforward method to model and also mask out trees from eight-band WorldView-2 (1.85 meter x 1.85 meter resolution at nadir) satellite imagery at the Beltsville Agricultural Research Center in Beltsville, MD spanning 2012 - 2015. The study site included tree cover, a range of agricultural and vegetative cover types, and urban features. The modeling method exploits the product of the red and red edge bands and defines accurate thresholds between trees and other land covers. Results show this method outperforms established vegetation indices including the NDVI, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Simple Ratio, and Normalized Difference Red Edge Index in correctly masking trees while preserving the other information in the imagery. This method is useful when HSI and LiDAR collection are not possible or when using archived MSI.

Correcting the influence of vegetation on surface soil moisture indices by using hyperspectral artificial 3D-canopy models

NASA Astrophysics Data System (ADS)

Spengler, D.; Kuester, T.; Frick, A.; Scheffler, D.; Kaufmann, H.

2013-10-01

Surface soil moisture content is one of the key variables used for many applications especially in hydrology, meteorology and agriculture. Hyperspectral remote sensing provides effective methodologies for mapping soil moisture content over a broad area by different indices such as NSMI [1,2] and SMGM [3]. Both indices can achieve a high accuracy for non-vegetation influenced soil samples, but their accuracy is limited in case of the presence of vegetation. Since, the increase of the vegetation cover leads to non-linear variations of the indices. In this study a new methodology for moisture indices correcting the influence of vegetation is presented consisting of several processing steps. First, hyperspectral reflectance data are classified in terms of crop type and growth stage. Second, based on these parameters 3D plant models from a database used to simulate typical canopy reflectance considering variations in the canopy structure (e.g. plant density and distribution) and the soil moisture content for actual solar illumination and sensor viewing angles. Third, a vegetation correction function is developed, based on the calculated soil moisture indices and vegetation indices of the simulated canopy reflectance data. Finally this function is applied on hyperspectral image data. The method is tested on two hyperspectral image data sets of the AISA DUAL at the test site Fichtwald in Germany. The results show a significant improvements compared to solely use of NSMI index. Up to a vegetation cover of 75 % the correction function minimise the influences of vegetation cover significantly. If the vegetation is denser the method leads to inadequate quality to predict the soil moisture content. In summary it can be said that applying the method on weakly to moderately overgrown with vegetation locations enables a significant improvement in the quantification of soil moisture and thus greatly expands the scope of NSMI.

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

NASA Astrophysics Data System (ADS)

Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

2018-06-01

This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

Relationship of multispectral satellite data to land surface evaporation from the Australian continent

NASA Technical Reports Server (NTRS)

Smith, R. C. G.; Choudhury, B. J.

1990-01-01

Based on NOAA-9 AVHRR and Nimbus-7 SMMR satellite data, satellite indices of vegetation from the Australian continent are calculated for the period of May 1986 to April 1987. Visible (VIS) and near infrared (NIR) reflectances and the normalized difference (ND) vegetation index are calculated from the AVHRR sensor. The microwave polarization difference (PD) is also calculated as the difference between the vertically and horizontally polarized brightness temperatures at 37 GHz. ND, PD, VIS, and NIR indices were plotted against rainfall and water balance estimates of evaporation. It is concluded that direct satellite monitoring of annual evaporation across the Australian continent using PD or VIS satellite indices of vegetation biomass appears possible for areas with evaporation less than 600 mm/y and that use of the ND relationship at continental scale may underpredict monthly evaporation of forests relative to agriculture.

Salinity modeling by remote sensing in central and southern Iraq

NASA Astrophysics Data System (ADS)

Wu, W.; Mhaimeed, A. S.; Platonov, A.; Al-Shafie, W. M.; Abbas, A. M.; Al-Musawi, H. H.; Khalaf, A.; Salim, K. A.; Chrsiten, E.; De Pauw, E.; Ziadat, F.

2012-12-01

Salinization, leading to a significant loss of cultivated land and crop production, is one of the most active land degradation phenomena in the Mesopotamian region in Iraq. The objectives of this study (under the auspices of ACIAR and Italian Government) are to investigate the possibility to use remote sensing technology to establish salinity-sensitive models which can be further applied to local and regional salinity mapping and assessment. Case studies were conducted in three pilot sites namely Musaib, Dujaila and West Garraf in the central and southern Iraq. Fourteen spring (February - April), seven June and four summer Landsat ETM+ images in the period 2009-2012, RapidEye data (April 2012), and 95 field EM38 measurements undertaken in this spring and summer, 16 relevant soil laboratory analysis result (Dujaila) were employed in this study. The procedure we followed includes: (1) Atmospheric correction using FLAASH model; (2) Multispectral transformation of a set of vegetation and non-vegetation indices such as GDVI (Generalized Difference Vegetation Index), NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), SAVI (Soil Adjusted Vegetation Index), SARVI (Soil Adjusted and Atmospherically Resistant Vegetation Index), NDII (Normalized Difference Infrared Index), Principal Components and surface temperature (T); (3) Derivation of the spring maximum (Musaib) and annual maximum (Dujaila and West Garraf) value in each pixel of each index of the observed period to avoid problems related to crop rotation (e.g. fallow) and the SLC-Off gaps in ETM+ images; (4) Extraction of the values of each vegetation and non-vegetation index corresponding to the field sampling locations (about 3 to 5 controversial samples very close to the roads or located in fallow were excluded); and (5) Coupling remote sensing indices with the available EM38 and soil electrical conductivity (EC) data using multiple linear least-square regression model at the confidence level of 95% in a stepwise (forward) manner. The results reveal that soil salinity and EM38 readings are negatively correlated with the different vegetation indices, especially, GDVI and NDVI, and positively correlated with T. The models obtained for the pilot sites are presented in Table 1. Although we are still waiting for more laboratory analytical result and satellite imagery for more comprehensive analysis, it is clearly possible to build up salinity models by remote sensing, on which further salinity mapping and assessment can be based. It is also noted that among all the vegetation indices, GDVI is the best salinity indicator followed by NDVI and T. RapidEye image shows lower correlation with EM38 measurements and EC because fallow and crop rotation issue cannot be sorted out by one acquisition image.Table 1: Salinity models obtained from the pilot sitesNote: EMV- Vertical reading of EM38, EC - Electrical conductivity in dS/m

A Sensitivity Analysis of NDWI and SRWI to Different types of Vegetation Moisture

NASA Astrophysics Data System (ADS)

Chai, Linna; Chen, Zhizhong

2017-04-01

There are many definitions of vegetation moisture, such as fuel moisture content (FMC), gravimetric water content (GWC), relative water content (RWC), leaf water content (LWC), canopy water content (CWC) and vegetation water content (VWC). They were introduced because of different applications. For example, FMC is with superiority in monitoring wildfire potential, and GWC responses well to determine whether the plant is in health. RWC is suitable for estimating vegetation water stress. LWC and CWC are often used in optical remote sensing and are always related to equivalent water thickness (EWT). For VWC, the main application is for improving retrievals of soil moisture content from microwave sensors. For optical remote sensing technique, the absorption features of liquid water in plant leaves are readily detectable by spectroscopy. Spectral reflectance at 970nm, 1200nm, 1450nm, 1930nm and 2500nm are the basis of numerous remote-sensing indices that could be used in estimating vegetation moisture. Foregoing studies have introduced different spectral indices based on these bands to retrieve vegetation moisture. These spectral indices often fall into two categories, one is Normalized Different Water Index (NDWI), and the other is Simple Ratio Water Index (SRWI). NDWIs take the form of normalized difference spectral index, while SRWIs are in the form of ratio type. They were calculated from different combinations of spectral channels. Since the sensitivities to vegetation moisture of reflectance at different spectral channel are distinguished from each other, the capabilities of these NDWIs and SRWIs in estimating different types of vegetation moisture will be distinguished from one to one. In this work, based on in-situ measurements collected in the north China plain from wheat and corn (Fig. 1), a sensitivity analysis of NDWI and SRWI to different types of vegetation moisture, such as VWC, FMC and GWC, was carried out. They were calculated from different combinations of spectral channels of MODIS and Landsat-8 OLI. Result shows that: 1) NDWI and SRWI are more sensitive to VWC than to FMC and GWC; 2) SRWI and NDWI calculated from reflectances of green band at about 550nm and shortwave infrared band at about 1240nm often yielded relatively higher correlation coefficients with VWC; 3) For a fixed two-band combination, SRWI shows a slight superiority to NDWI. PIC Fig.1 The north China plain and the experimental area with corn and winter wheat sample locations A detailed description to this study work will be demonstrated in the fullpaper.

Comparisons among a new soil index and other two- and four-dimensional vegetation indices

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Richardson, A. J. (Principal Investigator)

1982-01-01

The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in LANDSAT MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS 5 and MSS 6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation.

Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

NASA Astrophysics Data System (ADS)

Dung Nguyen, The; Kappas, Martin

2017-04-01

In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

Biogeomorphic feedback between plant growth and flooding causes alternative stable states in an experimental floodplain

NASA Astrophysics Data System (ADS)

Wang, Chen; Wang, Qiao; Meire, Dieter; Ma, Wandong; Wu, Chuanqing; Meng, Zhen; Van de Koppel, Johan; Troch, Peter; Verhoeven, Ronny; De Mulder, Tom; Temmerman, Stijn

2016-07-01

It is important to understand the mechanisms of vegetation establishment on bare substrate in a disturbance-driven ecosystem because of many valuable ecosystem services. This study tested for empirical indications of local alternative stable states controlled by biogeomorphic feedbacks using flume experiments with alfalfa: (1) single flood experiments different in flood intensity and plant growth, (2) long-term evolution experiments with repeated flooding and seeding. We observed: (1) a combination of thresholds in plant growth and flooding magnitude for upgrowing seedlings to survive; (2) bimodality in vegetation biomass after floods indicating the existence of two alternative states, either densely vegetated or bare; (3) facilitation of vegetation establishment by the spatial pattern formation of channels and sand bars. In conclusion, empirical indicators were demonstrated for local alternative stable states in a disturbance-driven ecosystem associated with biogeomorphic feedbacks, which could contribute to the protection and restoration of vegetation in such ecosystems.

Do invasive alien plants really threaten river bank vegetation? A case study based on plant communities typical for Chenopodium ficifolium-An indicator of large river valleys.

PubMed

Nobis, Agnieszka; Nowak, Arkadiusz; Rola, Kaja

2018-01-01

Riparian zones are very rich in species but subjected to strong anthropogenic changes and extremely prone to alien plant invasions, which are considered to be a serious threat to biodiversity. Our aim was to determine the spatial distribution of Chenopodium ficifolium, a species demonstrating strong confinement to large river valleys in Central Europe and an indicator of annual pioneer nitrophilous vegetation developing on river banks, which are considered to be of importance to the European Community. Additionally, the habitat preferences of the species were analysed. Differences in the richness and abundance of species diagnostic for riverside habitats, as well as the contribution of resident and invasive alien species in vegetation plots along three rivers differing in terms of size and anthropogenic impact were also examined. Finally, the effect of invaders on the phytocoenoses typical for C. ficifolium was assessed. The frequency of C. ficifolium clearly decreased with an increasing distance from the river. Among natural habitats, the species mostly preferred the banks of large rivers. The vegetation plots developing on the banks of the three studied rivers differed in total species richness, the number and cover of resident, diagnostic and invasive alien species, as well as in species composition. Our research indicates that abiotic and anthropogenic factors are the most significant drivers of species richness and plant cover of riverbank vegetation, and invasive alien plants affect this type of vegetation to a small extent.

Do invasive alien plants really threaten river bank vegetation? A case study based on plant communities typical for Chenopodium ficifolium—An indicator of large river valleys

PubMed Central

Nowak, Arkadiusz; Rola, Kaja

2018-01-01

Riparian zones are very rich in species but subjected to strong anthropogenic changes and extremely prone to alien plant invasions, which are considered to be a serious threat to biodiversity. Our aim was to determine the spatial distribution of Chenopodium ficifolium, a species demonstrating strong confinement to large river valleys in Central Europe and an indicator of annual pioneer nitrophilous vegetation developing on river banks, which are considered to be of importance to the European Community. Additionally, the habitat preferences of the species were analysed. Differences in the richness and abundance of species diagnostic for riverside habitats, as well as the contribution of resident and invasive alien species in vegetation plots along three rivers differing in terms of size and anthropogenic impact were also examined. Finally, the effect of invaders on the phytocoenoses typical for C. ficifolium was assessed. The frequency of C. ficifolium clearly decreased with an increasing distance from the river. Among natural habitats, the species mostly preferred the banks of large rivers. The vegetation plots developing on the banks of the three studied rivers differed in total species richness, the number and cover of resident, diagnostic and invasive alien species, as well as in species composition. Our research indicates that abiotic and anthropogenic factors are the most significant drivers of species richness and plant cover of riverbank vegetation, and invasive alien plants affect this type of vegetation to a small extent. PMID:29543919

Investigations of possible contributions NDVI's have to misclassification in AVHRR data analysis

Treesearch

David L. Evans; Raymond L. Czaplewski

1996-01-01

Numerous subcontinental-scale projects have placed significant emphasis on the use of Normalized Difference Vegetation Indices (NDVI's) derived from Advanced Very High Resolution Radiometer (AVHRR) satellite data for vegetation type recognition. In multi-season AVHRR data, overlap of NDVI ranges for vegetation classes may degrade overall classification performance...

Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models

PubMed Central

de la Estrella, Manuel; Mateo, Rubén G.; Wieringa, Jan J.; Mackinder, Barbara; Muñoz, Jesús

2012-01-01

Objectives Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. Methodology Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. Results/Conclusions Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused. PMID:22911808

Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation

NASA Astrophysics Data System (ADS)

Huete, Alfredo R.; Didan, Kamel; van Leeuwen, Willem J. D.; Vermote, Eric F.

1999-12-01

Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various 'continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types with continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types.

Evaluating Evapotranspiration of Pine Forest, Switchgrass, and Pine- Switchgrass Intercroppings using Remote Sensing and Ground-based Methods

NASA Astrophysics Data System (ADS)

Amatya, D. M.; Panda, S.; Chescheir, G. M.; Nettles, J. E.; Appelboom, T.; Skaggs, R. W.

2011-12-01

Vast areas of the land in the Southeastern United States are under pine forests managed primarily for timber and related byproducts. Evapotranspiration (ET) is the major loss in the water balance of this forest ecosystem. A long-term (1988-2008) study to evaluate hydrologic and nutrient balance during a life cycle of a pine stand was just completed. The study used both monitoring and modeling approaches to evaluate hydrologic and water quality effects of silvicultural and water management treatments on three 25 ha experimental watersheds in eastern North Carolina (NC). The research was extended in 2009 to include a dedicated energy crop, switchgrass (Panicum virgatum), by adding an adjacent 25 ha watershed. These multiple watersheds are being used to evaluate the hydrologic and water quality effects of switchgrass alone, young pine with natural understory, and young pine with switchgrass intercropping compared to the control (pine stand with a natural understory). The biofuels study has been further expanded to two other southern states, Alabama (AL) and Mississippi (MS). Each has five small watersheds (< 25 ha size) consisting of the above treatments and an additional woody biomass removal treatment. In this presentation we provide methods for estimating ET for these treatment watersheds in all three states (NC, AL, and MS) using remote sensing based spatial high resolution multispectral satellite imagery data with ground truthing, where possible, together with sensor technology. This technology is making ET parameter estimation a reality for various crops and vegetation surfaces. Slope-based vegetation indices like Normalized Difference Vegetation Index (NDVI) and Green Vegetation Index (GVI) and distance-based vegetation indices like Soil Adjusted Vegetation Index (SAVI) and Perpendicular Vegetation Index (PVI) will be developed using the R and NIR bands, vegetation density, and background soil reflectance as necessary. Landsat and high resolution aerial imageries of vegetation and soils will be used. IDRISI Taiga software will be used for the indices development. The forested vegetation health will be correlated to the leaf chlorophyll content for determining the vegetation health with a subsequent derivation of available plant water for radiation. Models will be developed to correlate the plant and soil available water to different vegetation indices. Correlation models will also be developed to obtain information on climatic parameters like surface air temperature, net radiation, albedo, soil moisture content, and stomatal water availability from Landsat imageries. On-site weather parameters used for the PET estimates will be combined with other vegetation parameters like leaf area index (LAI) obtained using LIDAR data and NAIP orthophotos of different seasons. That will also help detect the upper and understory vegetation. The LIDAR data will be processed to obtain the volume of vegetation to correctly estimate the total ET for each treatment.

View angle effects on relationships between leaf area index in wheat and vegetation indices

NASA Astrophysics Data System (ADS)

Chen, H.; Li, W.; Huang, W.; Niu, Z.

2016-12-01

The effects of plant types and view angles on the canopy-reflected spectrum can not be ignored in the estimation of leaf area index (LAI) using remote sensing vegetation indices. While vegetation indices derived from nadir-viewing remote sensors are insufficient in leaf area index (LAI) estimation because of its misinterpretation of structural characteristecs, vegetation indices derived from multi-angular remote sensors have potential to improve detection of LAI. However, view angle effects on relationships between these indices and LAI for low standing crops (i.e. wheat) has not been fully evaluated and thus limits them to applied for consistent and accurate monitoring of vegetation. View angles effects of two types of winter wheat (wheat 411, erectophile; and wheat 9507, planophile) on relationship between LAI and spectral reflectance are assessed and compared in this study. An evaluation is conducted with in-situ measurements of LAI and bidirectional reflectance in the principal plane from -60° (back-scattering direction ) ot 60° (forward scattering direction) in the growth cycle of winter wheat. A variety of vegetation indices (VIs) published are calculated by BRDF. Additionally, all combinations of the bands are used in order to calculate Normalized difference Spectral Indices (NDSI) and Simple Subtraction Indices (SSI). The performance of the above indices along with raw reflectance and reflectance derivatives on LAI estimation are examined based on a linearity comparison. The results will be helpful in further developing multi-angle remote sensing models for accurate LAI evaluation.

Effect of vegetable extracts on immunoglobulin production by mesenteric lymph node lymphocytes of Sprague-Dawley rats.

PubMed

Kaku, S; Yamada, K; Hassan, N; Watanabe, T; Sugano, M

1997-03-01

To clarify the immunoglobulin production-regulating activity of vegetable extracts, mesenteric lymph node lymphocytes of Sprague-Dawley rats were cultured in the presence of 25 different vegetable extracts. The immunoglobulin content in the culture medium determined by ELISA indicated that the lily family (Liliaceae) vegetables most strongly enhanced the production of IgA and IgG, whereas they suppressed IgE production.

Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data.

PubMed

Banerjee, Bikram Pratap; Raval, Simit; Zhai, Hao; Cullen, Patrick Joseph

2017-11-03

Recent advancements in hyperspectral remote sensing technology now provide improved diagnostic capabilities to assess vegetation health conditions. This paper uses a set of 13 vegetation health indices related to chlorophyll, xanthophyll, blue/green/red ratio and structure from airborne hyperspectral reflectance data collected around a derelict mining area in Yerranderie, New South Wales, Australia. The studied area has ten historic mine shafts with a legacy of heavy metals and acidic contamination in a pristine ecosystem now recognised as Great Blue Mountain World Heritage Area. The forest is predominantly comprised of different species of Eucalyptus trees. In addition to the airborne survey, ground-based spectra of the tree leaves were collected along the two accessible heavy metal contaminated pathways. The stream networks in the area were classified and the geospatial patterns of vegetation health were analysed along the Tonalli River, a major water tributary flowing through the National Park. Despite the inflow of contaminated water from the near-mine streams, the measured vegetation health indices along Tonalli River were found to remain unchanged. The responses of the vegetation health indices between the near-mine and away-mine streams were found similar. Based on the along-stream and inter-stream analysis of the spectral indices of vegetation health, no significant impact of the heavy metal pollution could be noticed. The results indicate the possibility of the vegetation having developed immunity towards the high levels of heavy metal pollution over a century of exposure.

Diurnal variations in maize and soybean vegetation indices from continuous measurements of ground-based spectral reflectance

NASA Astrophysics Data System (ADS)

Arkebauer, T. J.; Walter-Shea, E. A.

2017-12-01

Vegetation indices, based on canopy spectral reflectance, are widely used to infer physical and biological characteristics of vegetation. Understanding the changes in remotely sensed signals as vegetation responds to its changing environment is essential for full assessment of canopy structure and function. Canopy-level reflectance has been measured at Nebraska AmeriFlux sites US-Ne1, US-Ne2 and US-Ne3 for most years since flux measurements were initiated in 2001. Tower-mounted spectral sensors provided 10-minute averaged reflectance (in PAR and NIR spectral regions) every half hour through the growing season for maize and soybean. Canopy reflectance varied over diurnal and seasonal time periods which led to variations in vegetation indices. One source of variation is due to the interaction of incident solar radiant energy with canopy structure (e.g., reflectance varies with changes in solar zenith angle and direct beam fraction, vegetative fraction, and leaf angle distribution). Another source of variation results from changes in canopy function (e.g., fluctuations in gross primary production and invocation of photoprotective mechanisms with plant stress). We present here a series of diurnal "patterns" of vegetation indices (including Normalized Difference Vegetation Index and Chlorophyll Index) for maize and soybean under mostly clear sky conditions. We demonstrate that diurnal patterns change as the LAI of the canopy changes through the course of the growing season in a somewhat predictable pattern from plant emergence (low vegetative cover) through peak green LAI (full vegetation cover). However, there are changes in the diurnal pattern that we have yet to fully understand; this variation in pattern may indicate variation in canopy function. Initially, we have explored the pattern changes qualitatively and are currently developing more quantitative approaches.

Analysis of Post-Fire Vegetation Recovery in the Mediterranean Basin using MODIS Derived Vegetation Indices

NASA Astrophysics Data System (ADS)

Hawtree, Daniel; San Miguel, Jesus; Sedano, Fernando; Kempeneers, Pieter

2010-05-01

The Mediterranean basin region is highly susceptible to wildfire, with approximately 60,000 individual fires and half a million ha of natural vegetation burnt per year. Of particular concern in this region is the impact of repeated wildfires on the ability of natural lands to return to a pre-fire state, and of the possibility of desertification of semi-arid areas. Given these concerns, understanding the temporal patterns of vegetation recovery is important for the management of environmental resources in the region. A valuable tool for evaluating these recovery patterns are vegetation indices derived from remote sensing data. Previous research on post-fire vegetation recovery conducted in this region has found significant variability in recovery times across different study sites. It is unclear what the primary variables are affecting the differences in the rates of recovery, and if any geographic patterns of behavior exist across the Mediterranean basin. This research has primarily been conducted using indices derived from Landsat imagery. However, no extensive analysis of vegetation regeneration for large regions has been published, and assessment of vegetation recovery on the basis of medium-spatial resolution imagery such as that of MODIS has not yet been analyzed. This study examines the temporal pattern of vegetation recovery in a number of fire sites in the Mediterranean basin, using data derived from MODIS 16 -day composite vegetation indices. The intent is to develop a more complete picture of the temporal sequence of vegetation recovery, and to evaluate what additional factors impact variations in the recovery sequence. In addition, this study evaluates the utility of using MODIS derived vegetation indices for regeneration studies, and compares the findings to earlier studies which rely on Landsat data. Wildfires occurring between the years 2000 and 2004 were considered as potential study sites for this research. Using the EFFIS dataset, all wildfires covering an area of at least 1,000 ha were identified. The land-cover / land-use of these large fires sites were then evaluated using the CORINE land-cover data set, and the sites dominated primarily by natural vegetation were identified. Once these candidate sites were identified, a subset was selected across a range of locations and site characteristics for post-fire recovery analysis. To evaluate the post-fire recovery sequence in these locations, time-series of NDVI, EVI, and LAI were derived using 250 meter resolution MODIS data (MOD13Q). The vegetation index values were then compared to pre-fire values to determine recovery relative to the pre-fire vegetative state. The variability in rates of recovery are then considered with respect to moisture availability, vegetation type, and local site conditions to evaluate if any patterns of recovery can be determined.

Measuring habitat heterogeneity reveals new insights into bird community composition.

PubMed

Stirnemann, Ingrid A; Ikin, Karen; Gibbons, Philip; Blanchard, Wade; Lindenmayer, David B

2015-03-01

Fine-scale vegetation cover is a common variable used to explain animal occurrence, but we know less about the effects of fine-scale vegetation heterogeneity. Theoretically, fine-scale vegetation heterogeneity is an important driver of biodiversity because it captures the range of resources available in a given area. In this study we investigated how bird species richness and birds grouped by various ecological traits responded to vegetation cover and heterogeneity. We found that both fine-scale vegetation cover (of tall trees, medium-sized trees and shrubs) and heterogeneity (of tall trees, and shrubs) were important predictors of bird richness, but the direction of the response of bird richness to shrub heterogeneity differed between sites with different proportions of tall tree cover. For example, bird richness increased with shrub heterogeneity in sites with high levels of tall tree cover, but declined in sites with low levels of tall tree cover. Our findings indicated that an increase in vegetation heterogeneity will not always result in an increase in resources and niches, and associated higher species richness. We also found birds grouped by traits responded in a predictable way to vegetation heterogeneity. For example, we found small birds benefited from increased shrub heterogeneity supporting the textual discontinuity hypothesis and non-arboreal (ground or shrub) nesting species were associated with high vegetation cover (low heterogeneity). Our results indicated that focusing solely on increasing vegetation cover (e.g. through restoration) may be detrimental to particular animal groups. Findings from this investigation can help guide habitat management for different functional groups of birds.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index.

PubMed

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-07-08

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation's responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April-October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

ncreasing altitudinal spring phenology gradient of vegetation over the last decade in Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Shen, M.; Piao, S.

2013-12-01

Vegetation spring phenology in temperate and cold regions is widely expected to advance with temperature elevation and is often used as an indicator of regional climatic change. The Qinghai-Tibetan Plateau (QTP) has experienced intensive warming recently, but substantial contradictions exist about the changes of vegetation spring phenology. We investigated spatiotemporal variations in green-up dates in the QTP from 2000 to 2011 determined through five methods using four satellite-derived datasets including the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR), Système Pour l'Observation de la Terre, and MODerate resolution Imaging Spectroradiometer (MODIS), and the enhanced vegetation index from MODIS. On regional scale, no significant temporal trends (all P > 0.05) were found in the green-up dates, consistently among all the vegetation indices and methods. This insignificance was resulted from the substantial spatial heterogeneity of trends in green-up date, with delay by greater than 0.5 day yr-1 in the southwest region, and extensive advance in the other areas, although the temperature elevation was region-wide. These changes doubled the altitudinal gradient of green-up date, from 0.63 day 100m-1 in the early 2000s to 1.30 days 100m-1 in the early 2010s. The delay in the southwest region and high altitudes was likely caused by the decline in spring precipitation, despite the increasing spring temperature. This study suggests that spring precipitation is an important regulator of phenological response to climatic warming in QTP, and that, even in cold region, delay of vegetation spring phenology does not necessarily indicate spring cooling. Besides, the phenological changes retrieved from the widely used AVHRR NDVI differed from those from the other 3 vegetation indices, necessitating the use of multi-datasets while monitoring vegetation dynamics from space.

Mapping tree density in forests of the southwestern USA using Landsat 8 data

USGS Publications Warehouse

Humagain, Kamal; Portillo-Quintero, Carlos; Cox, Robert D.; Cain, James W.

2017-01-01

The increase of tree density in forests of the American Southwest promotes extreme fire events, understory biodiversity losses, and degraded habitat conditions for many wildlife species. To ameliorate these changes, managers and scientists have begun planning treatments aimed at reducing fuels and increasing understory biodiversity. However, spatial variability in tree density across the landscape is not well-characterized, and if better known, could greatly influence planning efforts. We used reflectance values from individual Landsat 8 bands (bands 2, 3, 4, 5, 6, and 7) and calculated vegetation indices (difference vegetation index, simple ratios, and normalized vegetation indices) to estimate tree density in an area planned for treatment in the Jemez Mountains, New Mexico, characterized by multiple vegetation types and a complex topography. Because different vegetation types have different spectral signatures, we derived models with multiple predictor variables for each vegetation type, rather than using a single model for the entire project area, and compared the model-derived values to values collected from on-the-ground transects. Among conifer-dominated areas (73% of the project area), the best models (as determined by corrected Akaike Information Criteria (AICc)) included Landsat bands 2, 3, 4, and 7 along with simple ratios, normalized vegetation indices, and the difference vegetation index (R2 values for ponderosa: 0.47, piñon-juniper: 0.52, and spruce-fir: 0.66). On the other hand, in aspen-dominated areas (9% of the project area), the best model included individual bands 4 and 2, simple ratio, and normalized vegetation index (R2 value: 0.97). Most areas dominated by ponderosa, pinyon-juniper, or spruce-fir had more than 100 trees per hectare. About 54% of the study area has medium to high density of trees (100–1000 trees/hectare), and a small fraction (4.5%) of the area has very high density (>1000 trees/hectare). Our results provide a better understanding of tree density for identifying areas in need of treatment and planning for more effective treatment. Our analysis also provides an integrated method of estimating tree density across complex landscapes that could be useful for further restoration planning.

The Effect of Leaf Stacking on Leaf Reflectance and Vegetation Indices Measured by Contact Probe during the Season

PubMed Central

Neuwirthová, Eva; Lhotáková, Zuzana; Albrechtová, Jana

2017-01-01

The aims of the study were: (i) to compare leaf reflectance in visible (VIS) (400–700 nm), near-infrared (NIR) (740–1140 nm) and short-wave infrared (SWIR) (2000–2400 nm) spectral ranges measured monthly by a contact probe on a single leaf and a stack of five leaves (measurement setup (MS)) of two broadleaved tree species during the vegetative season; and (ii) to test if and how selected vegetation indices differ under these two MS. In VIS, the pigment-related spectral region, the effect of MS on reflectance was negligible. The major influence of MS on reflectance was detected in NIR (up to 25%), the structure-related spectral range; and weaker effect in SWIR, the water-related spectral range. Vegetation indices involving VIS wavelengths were independent of MS while indices combining wavelengths from both VIS and NIR were MS-affected throughout the season. The effect of leaf stacking contributed to weakening the correlation between the leaf chlorophyll content and selected vegetation indices due to a higher leaf mass per area of the leaf sample. The majority of MS-affected indices were better correlated with chlorophyll content in both species in comparison with MS-unaffected indices. Therefore, in terms of monitoring leaf chlorophyll content using the contact probe reflectance measurement, these MS-affected indices should be used with caution, as discussed in the paper. If the vegetation indices are used for assessment of plant physiological status in various times of the vegetative season, then it is essential to take into consideration their possible changes induced by the particular contact probe measurement setup regarding the leaf stacking. PMID:28538685

Spatial Variations in Salinity Stress Across a Coastal Landscape Using Vegetation Indices Derived from Hyperspectral Imagery

DTIC Science & Technology

2009-01-01

NDVI , WBI970, Chlorophyll fluorescence, Salinity, Hyperspectral reflectance JC_Naumann, DR_Young, JE_Anderson Virginia Commonwealth University 800...DF=F0m for M. cerifera (r2 = 0.79) and I. frutescens (r2 = 0.72). The normalized difference vegetation index ( NDVI ), the chlorophyll index (CI), and...frutescens, while there were no differences in NDVI during the 2 years. PRI was not significantly related to NDVI , suggesting that the indices are spatially

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

A Candidate Vegetation Index of Biological Integrity Based on Species Dominance and Habitat Fidelity

USGS Publications Warehouse

Gara, Brian D; Stapanian, Martin A.

2015-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas of the USA and are used in some states to make critical management decisions. An underlying concept of all VIBIs is that they respond negatively to disturbance. The Ohio VIBI (OVIBI) is calculated from 10 metrics, which are different for each wetland vegetation class. We present a candidate vegetation index of biotic integrity based on floristic quality (VIBI-FQ) that requires only two metrics to calculate an overall score regardless of vegetation class. These metrics focus equally on the critical ecosystem elements of diversity and dominance as related to a species’ degree of fidelity to habitat requirements. The indices were highly correlated but varied among vegetation classes. Both indices responded negatively with a published index of wetland disturbance in 261 Ohio wetlands. Unlike VIBI-FQ, however, errors in classifying wetland vegetation may lead to errors in calculating OVIBI scores. This is especially critical when assessing the ecological condition of rapidly developing ecosystems typically associated with wetland restoration and creation projects. Compared to OVIBI, the VIBI-FQ requires less field work, is much simpler to calculate and interpret, and can potentially be applied to all habitat types. This candidate index, which has been “standardized” across habitats, would make it easier to prioritize funding because it would score the “best” and “worst” of all habitats appropriately and allow for objective comparison across different vegetation classes.

Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

NASA Astrophysics Data System (ADS)

Rankine, C.; Sánchez-Azofeifa, G. A.; Guzmán, J. Antonio; Espirito-Santo, M. M.; Sharp, Iain

2017-10-01

Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these already endangered forest ecosystems and should be further monitored using both ground and satellite approaches.

Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

NASA Astrophysics Data System (ADS)

Barrios, J. M.; Verstraeten, W. W.; Maes, P.; Clement, J.; Aerts, J. M.; Farifteh, J.; Lagrou, K.; Van Ranst, M.; Coppin, P.

2012-08-01

The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were tested as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.

Response of spectral vegetation indices to soil moisture in grasslands and shrublands

USGS Publications Warehouse

Zhang, Li; Ji, Lei; Wylie, Bruce K.

2011-01-01

The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.

Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; O'Neill, Peggy; Cosh, Michael; Lang, Roger; Joseph, Alicia

2015-01-01

Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

Mid Miocene Terrestrial Ecosystems: Information from Mammalian Herbivore Communities.

NASA Astrophysics Data System (ADS)

Janis, C. M.; Damuth, J.; Theodor, J. M.

2001-05-01

In present day ecosystems the numbers and proportions of different kinds of ecologically distinct ungulates (hoofed mammals) provide an indicator of the nature of the vegetation in the habitat. Different vegetation types (such as forest, savanna, or grassland) are characteristically associated with different arrays of ungulates, with species exhibiting differences in diet, body size, and type of digestive fermentation system. These biological attributes can also be inferred for fossil ungulate species, the first two from quantitative assessment of skull and dental anatomy, and the last from phylogenetic affinity. Thus fossil ungulate communities may be used as indicators of the vegetation types of the habitats in which they lived. Vegetation types, in turn, are determined largely by a number of physical environmental factors. Typical ungulate communities of the late early to early middle Miocene (17 - 15 Ma) from the Great Plains of North America contained a diversity of browsing (leaf-eating) and grazing (grass-eating) species, with proportions of dietary types and a diversity of body sizes indicative of a woodland savanna habitat. Paleobotanical evidence also indicates a woodland savanna type of vegetation. However, these communities included a much larger number of ungulate species than can be found in any present-day community. The "excess" ungulate species were primarily browsers. Throughout the rest of the middle Miocene both species numbers and the proportion of browsers in ungulate communities appear to have declined steadily. During this decline in browser species the numbers of grazer species remained relatively constant. Within-community species numbers comparable to the present day were attained by the late Miocene. We suggest that the early Miocene browser-rich communities, and their subsequent decline, carry an important paleoenvironmental signal. In particular, communities "over rich" in browsers may reflect higher levels of primary productivity in mid Miocene vegetation types in comparison with corresponding, structurally equivalent present-day vegetation types. The observed decline in species numbers may represent a gradual decline in terrestrial primary productivity, which would be consistent with one current hypothesis of a mid-Miocene decrease in atmospheric carbon dioxide concentrations from higher mid-Cenozoic values.

Performance of vegetation indices from Landsat time series in deforestation monitoring

NASA Astrophysics Data System (ADS)

Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

2016-10-01

The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

Accumulation of Heavy Metals in Vegetable Species Planted in Contaminated Soils and the Health Risk Assessment

PubMed Central

Zhou, Hang; Yang, Wen-Tao; Zhou, Xin; Liu, Li; Gu, Jiao-Feng; Wang, Wen-Lei; Zou, Jia-Ling; Tian, Tao; Peng, Pei-Qin; Liao, Bo-Han

2016-01-01

The objectives of the present study were to investigate heavy metal accumulation in 22 vegetable species and to assess the human health risks of vegetable consumption. Six vegetable types were cultivated on farmland contaminated with heavy metals (Pb, Cd, Cu, Zn, and As). The target hazard quotient (THQ) method was used to assess the human health risks posed by heavy metals through vegetable consumption. Clear differences were found in the concentrations of heavy metals in edible parts of the different vegetables. The concentrations of heavy metals decreased in the sequence as leafy vegetables > stalk vegetables/root vegetables/solanaceous vegetables > legume vegetables/melon vegetables. The ability of leafy vegetables to uptake and accumulate heavy metals was the highest, and that of melon vegetables was the lowest. This indicated that the low accumulators (melon vegetables) were suitable for being planted on contaminated soil, while the high accumulators (leafy vegetables) were unsuitable. In Shizhuyuan area, China, the total THQ values of adults and children through consumption of vegetables were 4.12 and 5.41, respectively, suggesting that the residents may be facing health risks due to vegetable consumption, and that children were vulnerable to the adverse effects of heavy metal ingestion. PMID:26959043

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Fire effects in the northern Chihuahuan Desert derived from Landsat-5 Thematic Mapper spectral indices

NASA Astrophysics Data System (ADS)

White, Joseph D.; Swint, Pamela

2014-01-01

Fire effects on desert ecosystems may be long-lasting based on ecological impact of fire in these environments which potentially is detected from multispectral sensors. To assess this, we analyzed changes in spectral characteristics from 1986 to 2010 of pixels associated with the location of fires that occurred between 1986 and 1999 in Big Bend National Park, USA, located in the northern Chihuahuan Desert. Using Landsat-5 Thematic Mapper (TM) data, we derived spectral indices including the simple ratio (SR), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and normalized burn ratio (NBR) from 1989, 1999, and 2010 from the TM data and compared changes in spectral index values for sites with and without observed fire. We found that the NDVI and SAVI had significantly different values over the time for burned sites of different fire sizes. When differences of the spectral indices were calculated from each time period, time since fire was correlated with the SR and NBR indices. These results showed that large fires potentially had a persistent and long-term change in vegetation cover and soil characteristics which were detected by the extraordinary long-data collection period of the Landsat-5 TM sensor.

Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of Spartina alterniflora under interspecies competition.

PubMed

Liu, Pudong; Shi, Runhe; Zhang, Chao; Zeng, Yuyan; Wang, Jiapeng; Tao, Zhu; Gao, Wei

2017-10-31

The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited space, directly influencing the co-exist distribution in the future. However, these two species have different growth ratios in this area, which increase the difficulty to detect the distribution situation directly by remote sensing. As chlorophyll content is a key indicator of plant growth and physiological status, the objective of this study was to reduce the effect of interspecies competition when estimating Cab content; we evaluated 79 published representative indices to determine the optimal indices for estimating the chlorophyll a and b (Cab) content. After performing a sensitivity analysis for all 79 spectral indices, five spectral indices were selected and integrated using an artificial neural network (ANN) to estimate the Cab content of different competition ratios: the Gitelson ratio green index, the transformed chlorophyll absorption ratio index/optimized soil-adjusted vegetation index, the modified normalized difference vegetation index, the chlorophyll fluorescence index, and the Vogelmann chlorophyll index. The ANN method yielded better results (R 2  = 0.7110 and RMSE = 8.3829 μg cm -2 ) on average than the best single spectral index (R 2  = 0.6319 and RMSE = 9.3535 μg cm -2 ), representing an increase of 10.78% in R 2 and a decrease of 10.38% in RMSE. Our results indicated that integrating multiple vegetation indices with an ANN can alleviate the impact of interspecies competition and achieve higher estimation accuracy than the traditional approach using a single index.

Relationship between leaf optical properties, chlorophyll fluorescence and pigment changes in senescing Acer saccharum leaves.

PubMed

Junker, Laura Verena; Ensminger, Ingo

2016-06-01

The ability of plants to sequester carbon is highly variable over the course of the year and reflects seasonal variation in photosynthetic efficiency. This seasonal variation is most prominent during autumn, when leaves of deciduous tree species such as sugar maple (Acer saccharum Marsh.) undergo senescence, which is associated with downregulation of photosynthesis and a change of leaf color. The remote sensing of leaf color by spectral reflectance measurements and digital repeat images is increasingly used to improve models of growing season length and seasonal variation in carbon sequestration. Vegetation indices derived from spectral reflectance measurements and digital repeat images might not adequately reflect photosynthetic efficiency of red-senescing tree species during autumn due to the changes in foliar pigment content associated with autumn phenology. In this study, we aimed to assess how effectively several widely used vegetation indices capture autumn phenology and reflect the changes in physiology and photosynthetic pigments during autumn. Chlorophyll fluorescence and pigment content of green, yellow, orange and red leaves were measured to represent leaf senescence during autumn and used as a reference to validate and compare vegetation indices derived from leaf-level spectral reflectance measurements and color analysis of digital images. Vegetation indices varied in their suitability to track the decrease of photosynthetic efficiency and chlorophyll content despite increasing anthocyanin content. Commonly used spectral reflectance indices such as the normalized difference vegetation index and photochemical reflectance index showed major constraints arising from a limited representation of gradual decreases in chlorophyll content and an influence of high foliar anthocyanin levels. The excess green index and green-red vegetation index were more suitable to assess the process of senescence. Similarly, digital image analysis revealed that vegetation indices such as Hue and normalized difference index are superior compared with the often-used green chromatic coordinate. We conclude that indices based on red and green color information generally represent autumn phenology most efficiently. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Associations of wintering birds with habitat in semidesert and plains grasslands in Arizona

USGS Publications Warehouse

Ruth, Janet M.; Stanley, Thomas R.; Gordon, Caleb E.

2014-01-01

We studied associations with winter habitat for seven species of birds, one species-group (eastern and western meadowlarks combined), and total sparrows at seven sites in the semidesert and plains grasslands of southeastern Arizona from 1999–2001, sampling with mist-nets and survey-transects. We measured structure and composition of vegetation, assessing vegetative differences among sites, and modeled associations between indices of avian abundance and six vegetative variables using generalized linear models. For all vegetative variables, there were significant differences among sites. Numbers of northern harriers (Circus cyaneus) were positively associated with total number of sparrows. Indices of abundance for individual species of birds were statistically correlated with various measures of structure and composition of vegetation. In particular, grasshopper (Ammodramus savannarum) and vesper (Pooecetes gramineus) sparrows were negatively associated with amount of bare ground; horned larks (Eremophila alpestris) were negatively associated with vertical grass density; Baird's sparrows (A. bairdii) were negatively associated with shrub density; meadowlarks (Sturnella magna and S. neglecta combined) were positively associated with native grass. Our results suggest that these species would benefit from management of habitat that affects the vegetative characteristics associated with their abundance.

Spectral entropy as a mean to quantify water stress history for natural vegetation and irrigated agriculture in a water-stressed tropical environment

NASA Astrophysics Data System (ADS)

Kim, Y.; Johnson, M. S.

2017-12-01

Spectral entropy (Hs) is an index which can be used to measure the structural complexity of time series data. When a time series is made up of one periodic function, the Hs value becomes smaller, while Hs becomes larger when a time series is composed of several periodic functions. We hypothesized that this characteristic of the Hs could be used to quantify the water stress history of vegetation. For the ideal condition for which sufficient water is supplied to an agricultural crop or natural vegetation, there should be a single distinct phenological cycle represented in a vegetation index time series (e.g., NDVI and EVI). However, time series data for a vegetation area that repeatedly experiences water stress may include several fluctuations that can be observed in addition to the predominant phenological cycle. This is because the process of experiencing water stress and recovering from it generates small fluctuations in phenological characteristics. Consequently, the value of Hs increases when vegetation experiences several water shortages. Therefore, the Hs could be used as an indicator for water stress history. To test this hypothesis, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data for a natural area in comparison to a nearby sugarcane area in seasonally-dry western Costa Rica. In this presentation we will illustrate the use of spectral entropy to evaluate the vegetative responses of natural vegetation (dry tropical forest) and sugarcane under three different irrigation techniques (center pivot irrigation, drip irrigation and flood irrigation). Through this comparative analysis, the utility of Hs as an indicator will be tested. Furthermore, crop response to the different irrigation methods will be discussed in terms of Hs, NDVI and yield.

[Evaluation and source analysis of the mercury pollution in soils and vegetables around a large-scale zinc smelting plant].

PubMed

Liu, Fang; Wang, Shu-Xiao; Wu, Qing-Ru; Lin, Hai

2013-02-01

The farming soil and vegetable samples around a large-scale zinc smelter were collected for mercury content analyses, and the single pollution index method with relevant regulations was used to evaluate the pollution status of sampled soils and vegetables. The results indicated that the surface soil and vegetables were polluted with mercury to different extent. Of the soil samples, 78% exceeded the national standard. The mercury concentration in the most severely contaminated area was 29 times higher than the background concentration, reaching the severe pollution degree. The mercury concentration in all vegetable samples exceeded the standard of non-pollution vegetables. Mercury concentration, in the most severely polluted vegetables were 64.5 times of the standard, and averagely the mercury concentration in the vegetable samples was 25.4 times of the standard. For 85% of the vegetable samples, the mercury concentration, of leaves were significantly higher than that of roots, which implies that the mercury in leaves mainly came from the atmosphere. The mercury concentrations in vegetable roots were significantly correlated with that in soils, indicating the mercury in roots was mainly from soil. The mercury emissions from the zinc smelter have obvious impacts on the surrounding soils and vegetables. Key words:zinc smelting; mercury pollution; soil; vegetable; mercury content

Evaluation of different shadow detection and restoration methods and their impact on vegetation indices using UAV high-resolution imageries over vineyards

NASA Astrophysics Data System (ADS)

Aboutalebi, M.; Torres-Rua, A. F.; McKee, M.; Kustas, W. P.; Nieto, H.

2017-12-01

Shadows are an unavoidable component of high-resolution imagery. Although shadows can be a useful source of information about terrestrial features, they are a hindrance for image processing and lead to misclassification errors and increased uncertainty in defining surface reflectance properties. In precision agriculture activities, shadows may affect the performance of vegetation indices at pixel and plant scales. Thus, it becomes necessary to evaluate existing shadow detection and restoration methods, especially for applications that makes direct use of pixel information to estimate vegetation biomass, leaf area index (LAI), plant water use and stress, chlorophyll content, just to name a few. In this study, four high-resolution imageries captured by the Utah State University - AggieAir Unmanned Aerial Vehicle (UAV) system flown in 2014, 2015, and 2016 over a commercial vineyard located in the California for the USDA-Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program are used for shadow detection and restoration. Four different methods for shadow detection are compared: (1) unsupervised classification, (2) supervised classification, (3) index-based method, and (4) physically-based method. Also, two different shadow restoration methods are evaluated: (1) linear correlation correction, and (2) gamma correction. The models' performance is evaluated over two vegetation indices: normalized difference vegetation index (NDVI) and LAI for both sunlit and shadowed pixels. Histogram and analysis of variance (ANOVA) are used as performance indicators. Results indicated that the performance of the supervised classification and the index-based method are better than other methods. In addition, there is a statistical difference between the average of NDVI and LAI on the sunlit and shadowed pixels. Among the shadow restoration methods, gamma correction visually works better than the linear correlation correction. Moreover, the statistical difference between sunlit and shadowed NDVI and LAI decreases after the application of the gamma restoration method. Potential effects of shadows on modeling surface energy balance and evapotranspiration using very high resolution UAV imagery over the GRAPEX vineyard will be discussed.

Application of remote sensing in the study of vegetation and soils in Idaho

NASA Technical Reports Server (NTRS)

Tisdale, E. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Comparison of ERTS-1 imagery and USGS 1:250,000 scale maps of study areas with known ground points revealed significant map errors. These errors were sufficient to render impractical the projection of ERTS-1 imagery directly onto maps of the area. Marked differences were found in the delineation of ground features by different MSS bands. Generally, Band 4 was least useful, while Band 5 proved valuable for indicating patterns of native vegetation, cultivated areas - both dry and irrigated, lava fields, drainage basins, and deep bodies of water. Band 6 was better for landforms and drainages and for shallow bodies of water than Band 5 but inferior for indicating patterns in native vegetation and most types of cultivated land. Band 7 was best of all for indicating lava flows, water bodies, and landform features. Use of a additive color viewer-projector aided greatly in separation of images. A combination of Bands 5 and 7 with appropriate color filters proved best for separating most types of native vegetation and cultivated crops. Landform features and water bodies also showed well with this combination. The addition of Band 4 imagery to these further enhanced the identification of semi-dormant vegetation.

Sleeping sickness in southeastern Uganda: a spatio-temporal analysis of disease risk, 1970-2003.

PubMed

Berrang-Ford, Lea; Berke, Olaf; Sweeney, Sean; Abdelrahman, Lubowa

2010-12-01

Sleeping sickness is a major threat to human health in sub-Saharan Africa. Southeastern Uganda has experienced a number of significant epidemics in the past 100 years, most recently from 1976 to 1989. Recent and continued spread of the disease has highlighted gaps in the ability of current research to explain and predict the distribution of infection. Vegetation cover and changes in vegetation may be important determinants of transmission and disease risk because of the habitat preferences of the tsetse fly vector. This study examines the determinants of sleeping sickness distribution and incidence in southeastern Uganda from 1970 to 2003, spanning the full epidemic region and cycle, and focusing in particular on vegetation cover and change. Sleeping sickness data were collected from records of the Ugandan Ministry of Health, individual sleeping sickness treatment centers, and interviews with public health officials. Vegetation data were acquired from satellite imagery for four dates spanning the epidemic period, 1973, 1986, 1995, and 2001. Zero-inflated regression models were used to model predictors of disease presence and magnitude. Correlations between disease incidence and the normalized difference vegetation index (NDVI) at the subcounty level were evaluated. Results indicate that sleeping sickness infection is predominantly associated with proximity to water and spatial location, while disease incidence is highest in subcounties with moderate to high NDVI. The vegetation density (NDVI) at which sleeping sickness incidence peaked differed throughout the study period. The optimal vegetation density capable of supporting sleeping sickness transmission may be lower than indicated by data from endemic regions, indicating increased potential for disease spread under suitable conditions.

Remote sensing technologies applied to the irrigation water management on a golf course

NASA Astrophysics Data System (ADS)

Pedras, Celestina; Lança, Rui; Martins, Fernando; Soares, Cristina; Guerrero, Carlos; Paixão, Helena

2015-04-01

An adequate irrigation water management in a golf course is a complex task that depends upon climate (multiple microclimates) and land cover (where crops differ in morphology, physiology, plant density, sensitivity to water stress, etc.). These factors change both in time and space on a landscape. A direct measurement provides localized values of the evapotranspiration and climate conditions. Therefore this is not a practical or economical methodology for large-scale use due to spatial and temporal variability of vegetation, soils, and irrigation management strategies. Remote sensing technology combines large scale with ground measurement of vegetation indexes. These indexes are mathematical combinations of different spectral bands mostly in the visible and near infrared regions of the electromagnetic spectrum. They represent the measures of vegetation activity that vary not only with the seasonal variability of green foliage, but also across space, thus they are suitable for detecting spatial landscape variability. The spectral vegetation indexes may enhance irrigation management through the information contained in spectral reflectance data. This study was carried out on the 18th fairway of the Royal Golf Course, Vale do Lobo, Portugal, and it aims to establish the relationship between direct measurements and vegetation indexes. For that it is required (1) to characterize the soil and climatic conditions, (2) to assessment of the irrigation system, (3) to estimate the evapotranspiration (4) and to calculate the vegetation indices. The vegetation indices were determined with basis on spectral bands red, green and blue, RGB, and near Infrared, NIR, obtained from the analysis of images acquired from a unpiloted aerial vehicle, UAV, platform. The measurements of reference evapotranspiration (ETo) were obtained from two meteorological stations located in the study area. The landscape evapotranspiration, ETL, was determined in the fairway with multiple microclimates and managed stress. The ETL was obtained thru the use of mobile reference ET stations and also by the development of the surface renewal (SR) measurement technique. The sprinkler irrigation system installed was evaluated according to the methodology described by ASAE. The Normalized Difference Vegetation Index, NDVI, and Visible atmospherically Resistant Index, VARI, are confronted with the direct localized measurements. The NDVI is the most used indicator to assess the vigor status of the vegetation. However, this index depends of the use of NIR bands which demands quite expensive sensors. The use vegetation indexes obtained by sensors that collect data in the visible wavelength, such as VARI is less expensive and allow the vegetative vigor evaluation with a similar rigor. The information of vegetation indices is crossed with edafoclimatic data obtained in situ, in order to improve the irrigation water management based on aerial imagery.

Estimation on rubber tree disturbance caused by typhoon Damery (200518) with Landsat and MODIS data in Hainan Island of China

NASA Astrophysics Data System (ADS)

Tan, Chenyan; Fang, Weihua; Li, Jian

2016-04-01

In 2005, Typhoon Damery (200518) caused severe damage to the rubber trees in Hainan Island with its destructive winds and rainfall. Selection of proper vegetation indices using multi-source remote sensing data is critical to the assessment of forest disturbance and damage loss for this event. In this study, we will compare the performance of seven vegetation indices derived from MODIS and Landsat TM imageries prior to and after typhoon Damery, in order to select an optimal index for identifying rubber tree disturbance. The indices to be compared are normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Infrared Index (NDII), Enhanced vegetation index (EVI), Leaf area index (LAI), forest z-score (IFZ), and Disturbance Index (DI). The ground truth data of rubber tree damage collected through field investigation was used to verify and compare the results. Our preliminary result for the area with ground-truth data shows that DI has the most significant performance for disturbance detection for this typhoon event. This index DI is then applied to all the areas in Hainan Island hit by Darmey to evaluate the overall forest damage severity. At last, rubber tree damage severity is analyzed with other typhoon hazard factors such as wind, topography, soil and precipitation.

Remote Sensing Field Guide - Desert

DTIC Science & Technology

1991-09-01

rcatching on fire. Caution is advised against thorns on acacia trees, spikey Spinifex n•shes, and several different types of venomous snakes, as well as...e.g., mesquite, many acacias, Spinifex . DESERT PROCESSES WORKING GROUP PATTERN INDICATOR SHFET - DESERT DUNES PHOTOS: GROUND VEGETATION MOUNDS LOCATION...deliberate burning of natural vegetation is done episodically by the abo- rginal inhabitants. They burn the mature vegetation (primarily Spinifex ), which is

On the Mineral and Vegetal Oils Used as Electroinsulation in Transformers

NASA Astrophysics Data System (ADS)

Şerban, Mariana; Sângeorzan, Livia; Helerea, Elena

Due to the relatively large availability and reduced price, the mineral transformer oils are widely used as electrical insulating liquids. However, mineral oil drastically degrades over time in service. New efforts were made to improve mineral oils characteristics, and other types of liquids like vegetal oils are proposed. This paper deals with new comparative tests on mineral and vegetal oils using as indicator the electric strength. The samples of non-additive mineral oil type TR 30 and vegetal oils of rape, sunflower and corn have been tested with increasing voltage of 60 Hz using different electrodes. The obtained data have been statistical processed. The analyze shows different average values of electrical strength for the different type of sample. New method of testing through electrical breakdown is proposed. Experimental data confirms that it is possible to use as electroinsulation organic vegetal oils in power transformers.

Preliminary estimation of the realistic optimum temperature for vegetation growth in China.

PubMed

Cui, Yaoping

2013-07-01

The estimation of optimum temperature of vegetation growth is very useful for a wide range of applications such as agriculture and climate change studies. Thermal conditions substantially affect vegetation growth. In this study, the normalized difference vegetation index (NDVI) and daily temperature data set from 1982 to 2006 for China were used to examine optimum temperature of vegetation growth. Based on a simple analysis of ecological amplitude and Shelford's law of tolerance, a scientific framework for calculating the optimum temperature was constructed. The optimum temperature range and referenced optimum temperature (ROT) of terrestrial vegetation were obtained and explored over different eco-geographical regions of China. The results showed that the relationship between NDVI and air temperature was significant over almost all of China, indicating that terrestrial vegetation growth was closely related to thermal conditions. ROTs were different in various regions. The lowest ROT, about 7.0 °C, occurred in the Qinghai-Tibet Plateau, while the highest ROT, more than 22.0 °C, occurred in the middle and lower reaches of the Yangtze River and the Southern China region.

Preliminary Estimation of the Realistic Optimum Temperature for Vegetation Growth in China

NASA Astrophysics Data System (ADS)

Cui, Yaoping

2013-07-01

The estimation of optimum temperature of vegetation growth is very useful for a wide range of applications such as agriculture and climate change studies. Thermal conditions substantially affect vegetation growth. In this study, the normalized difference vegetation index (NDVI) and daily temperature data set from 1982 to 2006 for China were used to examine optimum temperature of vegetation growth. Based on a simple analysis of ecological amplitude and Shelford's law of tolerance, a scientific framework for calculating the optimum temperature was constructed. The optimum temperature range and referenced optimum temperature (ROT) of terrestrial vegetation were obtained and explored over different eco-geographical regions of China. The results showed that the relationship between NDVI and air temperature was significant over almost all of China, indicating that terrestrial vegetation growth was closely related to thermal conditions. ROTs were different in various regions. The lowest ROT, about 7.0 °C, occurred in the Qinghai-Tibet Plateau, while the highest ROT, more than 22.0 °C, occurred in the middle and lower reaches of the Yangtze River and the Southern China region.

Sensory determinants of stated liking for vegetable names and actual liking for canned vegetables: A cross-country study among European adolescents.

PubMed

Dinnella, Caterina; Morizet, David; Masi, Camilla; Cliceri, Danny; Depezay, Laurence; Appleton, Katherine M; Giboreau, Agnés; Perez-Cueto, Federico J A; Hartwell, Heather; Monteleone, Erminio

2016-12-01

Sensory properties are reported as one of the main factors hindering an appropriate vegetable intake by the young. In the present work the sensory determinants of likings for vegetables were explored in adolescents of four European countries (Denmark, n = 88; France, n = 206; Italy, n = 110 and United Kingdom, n = 93). A questionnaire was designed to study cross country differences in stated liking for and familiarity with a list of vegetables popular among European markets (between-vegetable approach). A within-vegetable comparison approach with actual tasting was used to analyze differences and similarities in liking for canned pea and sweet corn samples across the countries. A close positive relationship between stated liking and familiarity was found. Irrespective of the country, one group of highly liked vegetables (carrots, tomatoes, green salad) was identified, characterized by innately liked tastes (sweet, umami), delicate flavour and bright appealing colour. A second group of highly disliked vegetables consists of cauliflowers and broccoli, characterized by disliked sensations such as bitter taste and objectionable flavour. Internal Preference Maps from actual liking scores indicate that the generally disliked tastes (bitter, sour), are clearly correlated with a negative hedonic response for both peas and sweet corn. The hedonic valence of a generally well accepted taste such as salty and texture descriptors depends on the type of vegetable. Internal preference maps from actual liking data indicate that flavour and appearance descriptors of the distinct sensory properties of each type of vegetable positively affect liking, while the intensity of unusual flavours is related to sample disliking. Copyright © 2016 Elsevier Ltd. All rights reserved.

Differences in Fruit and Vegetable Intake by Race/Ethnicity and by Hispanic Origin and Nativity Among Women in the Special Supplemental Nutrition Program for Women, Infants, and Children, 2015.

PubMed

Di Noia, Jennifer; Monica, Dorothy; Cullen, Karen Weber; Pérez-Escamilla, Rafael; Gray, Heewon Lee; Sikorskii, Alla

2016-08-25

The objective of this exploratory study was to determine whether fruit and vegetable consumption differed by race/ethnicity, by origin and nativity among Hispanics, and by language preference (as an indicator of acculturation) among foreign-born Hispanics. We recruited 723 women enrolled in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) and orally administered a questionnaire containing demographic items, validated measures of food security status and social desirability trait, and the Behavioral Risk Factor Surveillance System fruit and vegetable module. Differences in intakes of 100% fruit juice, fruit, cooked or canned beans, and dark green, orange-colored, and other vegetables were assessed by using analysis of covariance with Bonferroni post hoc tests. Analyses were controlled for age, pregnancy status, breastfeeding status, food security status, educational attainment, and social desirability trait. The frequency of vegetable intake differed by race/ethnicity (cooked or canned beans were consumed more often among Hispanic than non-Hispanic black and non-Hispanic white or other participants, orange-colored vegetables were consumed more often among Hispanics than non-Hispanic black participants, and other vegetables were consumed more often among non-Hispanic white or other than among non-Hispanic black and Hispanic participants), origin (other vegetables were consumed more often among Columbian and other Hispanics than Dominican participants) and nativity (orange-colored vegetables were consumed more often among foreign-born than US-born Hispanics). Fruit and vegetable intake did not differ by language preference among foreign-born Hispanics. Differences in fruit and vegetable consumption among WIC participants by race/ethnicity and by Hispanic origin and nativity may have implications for WIC nutrition policies and nutrition education efforts.

Differences in Fruit and Vegetable Intake by Race/Ethnicity and by Hispanic Origin and Nativity Among Women in the Special Supplemental Nutrition Program for Women, Infants, and Children, 2015

PubMed Central

Monica, Dorothy; Cullen, Karen Weber; Pérez-Escamilla, Rafael; Gray, Heewon Lee; Sikorskii, Alla

2016-01-01

Introduction The objective of this exploratory study was to determine whether fruit and vegetable consumption differed by race/ethnicity, by origin and nativity among Hispanics, and by language preference (as an indicator of acculturation) among foreign-born Hispanics. Methods We recruited 723 women enrolled in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) and orally administered a questionnaire containing demographic items, validated measures of food security status and social desirability trait, and the Behavioral Risk Factor Surveillance System fruit and vegetable module. Differences in intakes of 100% fruit juice, fruit, cooked or canned beans, and dark green, orange-colored, and other vegetables were assessed by using analysis of covariance with Bonferroni post hoc tests. Analyses were controlled for age, pregnancy status, breastfeeding status, food security status, educational attainment, and social desirability trait. Results The frequency of vegetable intake differed by race/ethnicity (cooked or canned beans were consumed more often among Hispanic than non-Hispanic black and non-Hispanic white or other participants, orange-colored vegetables were consumed more often among Hispanics than non-Hispanic black participants, and other vegetables were consumed more often among non-Hispanic white or other than among non-Hispanic black and Hispanic participants), origin (other vegetables were consumed more often among Columbian and other Hispanics than Dominican participants) and nativity (orange-colored vegetables were consumed more often among foreign-born than US-born Hispanics). Fruit and vegetable intake did not differ by language preference among foreign-born Hispanics. Conclusion Differences in fruit and vegetable consumption among WIC participants by race/ethnicity and by Hispanic origin and nativity may have implications for WIC nutrition policies and nutrition education efforts. PMID:27560723

Temporal variation (seasonal and interannual) of vegetation indices of maize and soybeans across multiple years in central Iowa

NASA Astrophysics Data System (ADS)

Prueger, J. H.; Hatfield, J. L.

2015-09-01

Remotely sensed reflectance parameters from corn and soybean surfaces can be correlated to crop production. Surface reflectance of a typical Upper Midwest corn /soybean region in central Iowa across multiple years reveal subtle dynamics in vegetative surface response to a continually varying climate. From 2006 through 2014 remotely sensed data have been acquired over production fields of corn and soybeans in central IA, U.S.A. with the fields alternating between corn and soybeans. The data have been acquired using ground-based radiometers with 16 wavebands covering the visible, near infrared, shortwave infrared wavebands and combined into a series of vegetative indices. These data were collected on clear days with the goal of collecting data at a minimum of once per week from prior to planting until after fall tillage operations. Within each field, five sites were established and sampled during the year to reduce spatial variation and allow for an assessment of changes in the vegetative indices throughout the growing season. Ancillary data collected for each crop included the phenological stage at each sampling date along with biomass sampled at the onset of the reproductive stage and at physiological maturity. Evaluation of the vegetative indices for the different years revealed that patterns were related to weather effects on corn and soybean growth. Remote sensing provides a method to evaluate changes within and among growing seasons to assess crop growth and development as affected by differences in weather variability.

Modelling high arctic percent vegetation cover using field digital images and high resolution satellite data

NASA Astrophysics Data System (ADS)

Liu, Nanfeng; Treitz, Paul

2016-10-01

In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR - RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx - Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2's ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season.

Monitoring global vegetation using Nimbus-7 37 GHz data - Some empirical relations

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Tucker, C. J.

1987-01-01

The difference of the vertically and horizontally polarized brightness temperatures observed by the 37 GHz channel of the SMMR on board the Nimbus-7 satellite are correlated temporally with three indicators of vegetation density, namely the temporal variation of the atmospheric CO2 concentration at Mauna Loa (Hawaii), rainfall over the Sahel and the normalized difference vegetation index derived from the AVHRR on board the NOAA-7 satellite. SMMR 37 GHz and AVHRR provide complementary data sets for monitoring global vegetation, the 37 GHz data being more suitable for arid and semiarid regions as these data are more sensitive to changes in sparse vegetation. The 37-GHz data might be useful for understanding desertification and indexing Co2 exchange between the biosphere and the atmosphere.

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil.

PubMed

Guimarães, Ricardo J P S; Freitas, Corina C; Dutra, Luciano V; Scholte, Ronaldo G C; Amaral, Ronaldo S; Drummond, Sandra C; Shimabukuro, Yosio E; Oliveira, Guilherme C; Carvalho, Omar S

2010-07-01

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

Nitrite Contents in Fresh Vegetables of Different Families and Genus

NASA Astrophysics Data System (ADS)

Cui, Yuqian; Li, Xiao; Xu, Lingyi; Pang, Meixia; Qi, Jinghua; Wang, Fang

2017-12-01

The aim of this study is firstly aimed at investigating the contents of nitrite in common consumed vegetables according to families and genus classification. The vegetables were randomly collected and analyzed in quartile sampling according to GB5009.30-2016. The vegetables were analyzed by the software of Spss20.0 and statistically significant Duncan multiple comparisons. The data indicates that the nitrite contents in different families and different genus vegetables in same family were significant (P<0.01). A relatively high nitrite concentration was observed in Chenopodiaceae which is 0.5920mg/kg dry weight. A relatively low nitrite concentration was observed in Dioscoreaceae that contentration is 0.0032mg/kg dry weight. The nitrite contents of different genus are large, in which the relatively high concentration samples were red beet root (0.886mg/kg dry weight), peanut (0.7485mg/kg dry weight), corn kernels (0.7119mg/kg dry weight), Lotus root (0.592mg/kg dry weight).

Increased wetness confounds Landsat-derived NDVI trends in the central Alaska North Slope region, 1985-2011

NASA Astrophysics Data System (ADS)

Raynolds, Martha K.; Walker, Donald A.

2016-08-01

Satellite data from the circumpolar Arctic have shown increases in vegetation indices correlated to warming air temperatures (e.g. Bhatt et al 2013 Remote Sensing 5 4229-54). However, more information is needed at finer scales to relate the satellite trends to vegetation changes on the ground. We examined changes using Landsat TM and ETM+ data between 1985 and 2011 in the central Alaska North Slope region, where the vegetation and landscapes are relatively well-known and mapped. We calculated trends in the normalized difference vegetation index (NDVI) and tasseled-cap transformation indices, and related them to high-resolution aerial photographs, ground studies, and vegetation maps. Significant, mostly negative, changes in NDVI occurred in 7.3% of the area, with greater change in aquatic and barren types. Large reflectance changes due to erosion, deposition and lake drainage were evident. Oil industry-related changes such as construction of artificial islands, roads, and gravel pads were also easily identified. Regional trends showed decreases in NDVI for most vegetation types, but increases in tasseled-cap greenness (56% of study area, greatest for vegetation types with high shrub cover) and tasseled-cap wetness (11% of area), consistent with documented degradation of polygon ice wedges, indicating that increasing cover of water may be masking increases in vegetation when summarized using the water-sensitive NDVI.

Response of vegetation phenology to urbanization in the conterminous United States

DOE PAGES

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.; ...

2016-12-18

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days.Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. In conclusion, the quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

A Physically-Based Drought Product Using Thermal Remote Sensing of Evapotranspiration

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonst...

Relations between soil moisture and satellite vegetation indices in the U.S. Corn Belt

USGS Publications Warehouse

Adegoke, Jimmy O.; Carleton, A.M.

2002-01-01

Satellite-derived vegetation indices extracted over locations representative of midwestern U.S. cropland and forest for the period 1990–94 are analyzed to determine the sensitivity of the indices to neutron probe soil moisture measurements of the Illinois Climate Network (ICN). The deseasoned (i.e., departures from multiyear mean annual cycle) soil moisture measurements are shown to be weakly correlated with the deseasoned full resolution (1 km × 1 km) normalized difference vegetation index (NDVI) and fractional vegetation cover (FVC) data over both land cover types. The association, measured by the Pearson-moment-correlation coefficient, is stronger over forest than over cropland during the growing season (April–September). The correlations improve successively when the NDVI and FVC pixel data are aggregated to 3 km × 3 km, 5 km × 5 km, and 7 km × 7 km areas. The improved correlations are partly explained by the reduction in satellite navigation errors as spatial aggregation occurs, as well as the apparent scale dependence of the NDVI–soil moisture association. Similarly, stronger relations are obtained with soil moisture data that are lagged by up to 8 weeks with respect to the vegetation indices, implying that soil moisture may be a useful predictor of warm season satellite-derived vegetation conditions. This study suggests that a “long-term” memory of several weeks is present in the near-surface hydrological characteristics, especially soil water content, of the Midwest Corn Belt. The memory is integrated into the satellite vegetation indices and may be useful for predicting crop yield estimates and surface temperature anomalies.

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

NASA Technical Reports Server (NTRS)

Anderson, J. H. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Two new, as yet unfinished vegetation maps are presented. These tend further to substantiate the belief that ERTS-1 imagery is a valuable mapping tool. Newly selected scenes show that vegetation interpretations can be refined through use of non-growing season imagery, particularly through the different spectral characteristics of vegetation lacking foliage and through the effect of vegetation structure on apparent snow cover. Scenes now are available for all test area north of the Alaska Range except Mt. McKinley National Park. No support was obtained for the hypothesis that similar interband ratios, from two areas apparently different spectrally because of different sun angles, would indicate similar surface features. However, attempts to test this hypothesis have so far been casual.

Retronasal olfaction in vegetable liking and disliking.

PubMed

Lim, Juyun; Padmanabhan, Arthi

2013-01-01

While previous research has suggested that bitterness is a key determinant of vegetable rejection, it is unknown what role odor may play. We therefore investigated the impact of retronasal odors on hedonic responses to 4 vegetables. Subjects (N = 132) tasted small samples with the nose open and closed and rated the degree of liking/disliking, as well as the perceived intensity of sweetness, bitterness, saltiness, and vegetable flavor. The subjects were classified as "likers" or "dislikers" of each vegetable. The degree to which "likers" liked and "dislikers" disliked the vegetables was significantly less in the nose-closed condition, indicating that retronasal odor was a significant driver of vegetable hedonics. In contrast, bitterness ratings for all 4 vegetables did not differ significantly between the groups. The perceived intensity of vegetable flavor also did not differ significantly between groups, implying that the quality of vegetable odors rather than their perceived intensity drove the hedonic ratings. In a follow-up experiment, returning subjects (N = 89) rated the degree of liking/disliking of the vegetable odors alone, which were presented retronasally. Liking/disliking of specific odors was positively correlated with that for the sampled vegetables across all stimuli (r = 0.32~0.57). Overall, these results suggest that retronasal odor plays an important role in vegetable liking/disliking.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

PubMed Central

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-01-01

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages. PMID:26184243

Development Of Index To Assess Drought Conditions Using Geospatial Data A Case Study Of Jaisalmer District, Rajasthan, India

NASA Astrophysics Data System (ADS)

Chhajer, Vaidehi; Prabhakar, Sumati; Rama Chandra Prasad, P.

2015-12-01

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006-2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

NASA Astrophysics Data System (ADS)

Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

2015-02-01

Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance resampling, VIs inter-calibration and spatial resampling.

Post-fire vegetation recovery in Portugal based on spot/vegetation data

NASA Astrophysics Data System (ADS)

Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2010-04-01

A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

Differences in fruit and vegetable intake by race/ethnicity and by Hispanic origin and nativity among women in the Special Supplemental Nutrition Program for Women, Infants, and Children, 2015

USDA-ARS?s Scientific Manuscript database

The objective of this exploratory study was to determine whether fruit and vegetable consumption differed by race/ethnicity, by origin and nativity among Hispanics, and by language preference (as an indicator of acculturation) among foreign-born Hispanics. We recruited 723 women enrolled in the Spec...

Understory vegetation as an indicator for floodplain forest restoration in the Mississippi River Alluvial Valley, U.S.A.

USGS Publications Warehouse

De Steven, Diane; Faulkner, Stephen; Keeland, Bobby D.; Baldwin, Michael; McCoy, John W.; Hughes, Steven C.

2015-01-01

In the Mississippi River Alluvial Valley (MAV), complete alteration of river-floodplain hydrology allowed for widespreadconversion of forested bottomlands to intensive agriculture, resulting in nearly 80% forest loss. Governmental programs haveattempted to restore forest habitat and functions within this altered landscape by the methods of tree planting (afforestation)and local hydrologic enhancement on reclaimed croplands. Early assessments identified factors that influenced whetherplanting plus tree colonization could establish an overstory community similar to natural bottomland forests. The extentto which afforested sites develop typical understory vegetation has not been evaluated, yet understory composition may beindicative of restored site conditions. As part of a broad study quantifying the ecosystem services gained from restorationefforts, understory vegetation was compared between 37 afforested sites and 26 mature forest sites. Differences in vegetationattributes for species growth forms, wetland indicator classes, and native status were tested with univariate analyses;floristic composition data were analyzed by multivariate techniques. Understory vegetation of restoration sites was generallyhydrophytic, but species composition differed from that of mature bottomland forest because of young successional age anddiffering responses of plant growth forms. Attribute and floristic variation among restoration sites was related to variationin canopy development and local wetness conditions, which in turn reflected both intrinsic site features and outcomes ofrestoration practices. Thus, understory vegetation is a useful indicator of functional progress in floodplain forest restoration.

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas.

PubMed

Wang, Zhiwei; Wang, Qian; Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the environmental factors (including permafrost) related to the underlying surface conditions.

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas

PubMed Central

Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the environmental factors (including permafrost) related to the underlying surface conditions. PMID:28068392

The identification of selected vegetation types in Arizona through the photointerpretation of intermediate scale aerial photography. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ross, G. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Nine photography interpretation tests were performed with a total of 19 different interpreters. Three tests were conducted with black and white intermediate scale photography and six tests with color infrared intermediate scale photography. The black and white test results show that the interpretation of vegetation mapped at the association level of classification is reliable for all the classes used at 61%. The color infrared tests indicate that the association level of mapping is unsatisfactory for vegetation interpretation of classes 1 and 6. Students' t-test indicated that intermediate scale black and white photography is significantly better than this particular color infrared photography for the interpretation of southeastern Arizona vegetation mapped at the association level.

European vegetation during Marine Oxygen Isotope Stage-3

NASA Astrophysics Data System (ADS)

Huntley, Brian; Alfano, Mary J. o.; Allen, Judy R. M.; Pollard, Dave; Tzedakis, Polychronis C.; de Beaulieu, Jacques-Louis; Grüger, Eberhard; Watts, Bill

2003-03-01

European vegetation during representative "warm" and "cold" intervals of stage-3 was inferred from pollen analytical data. The inferred vegetation differs in character and spatial pattern from that of both fully glacial and fully interglacial conditions and exhibits contrasts between warm and cold intervals, consistent with other evidence for stage-3 palaeoenvironmental fluctuations. European vegetation thus appears to have been an integral component of millennial environmental fluctuations during stage-3; vegetation responded to this scale of environmental change and through feedback mechanisms may have had effects upon the environment. The pollen-inferred vegetation was compared with vegetation simulated using the BIOME 3.5 vegetation model for climatic conditions simulated using a regional climate model (RegCM2) nested within a coupled global climate and vegetation model (GENESIS-BIOME). Despite some discrepancies in detail, both approaches capture the principal features of the present vegetation of Europe. The simulated vegetation for stage-3 differs markedly from that inferred from pollen analytical data, implying substantial discrepancy between the simulated climate and that actually prevailing. Sensitivity analyses indicate that the simulated climate is too warm and probably has too short a winter season. These discrepancies may reflect incorrect specification of sea surface temperature or sea-ice conditions and may be exacerbated by vegetation-climate feedback in the coupled global model.

VEGETATION COVER ANALYSIS OF HAZARDOUS WASTE SITES IN UTAH AND ARIZONA USING HYPERSPECTRAL REMOTE SENSING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Serrato, M.; Jungho, I.; Jensen, J.

2012-01-17

Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using threemore » different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R{sup 2} > 0.80). The use of REPs failed to accurately predict LAI (R{sup 2} < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.« less

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Spatiotemporal changes of normalized difference vegetation index (NDVI) and response to climate extremes and ecological restoration in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Zhao, Anzhou; Zhang, Anbing; Liu, Xianfeng; Cao, Sen

2018-04-01

Extreme drought, precipitation, and other extreme climatic events often have impacts on vegetation. Based on meteorological data from 52 stations in the Loess Plateau (LP) and a satellite-derived normalized difference vegetation index (NDVI) from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset, this study investigated the relationship between vegetation change and climatic extremes from 1982 to 2013. Our results showed that the vegetation coverage increased significantly, with a linear rate of 0.025/10a ( P < 0.001) from 1982 to 2013. As for the spatial distribution, NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend ( P < 0.05). Some temperature extreme indices, including TMAXmean, TMINmean, TN90p, TNx, TX90p, and TXx, increased significantly at rates of 0.77 mm/10a, 0.52 °C/10a, 0.62 °C/10a, 0.80 °C/10a, 5.16 days/10a, and 0.65 °C/10a, respectively. On the other hand, other extreme temperature indices including TX10p and TN10p decreased significantly at rates of -2.77 days/10a and 4.57 days/10a ( P < 0.01), respectively. Correlation analysis showed that only TMINmean had a significant relationship with NDVI at the yearly time scale ( P < 0.05). At the monthly time scale, vegetation coverage and different vegetation types responded significantly positively to precipitation and temperature extremes (TMAXmean, TMINmean, TNx, TNn, TXn, and TXx) ( P < 0.01). All of the precipitation extremes and temperature extremes exhibited significant positive relationships with NDVI during the spring and autumn ( P < 0.01). However, the relationship between NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter ( P < 0.05). In terms of human activity, our results indicate a strong correlation between the cumulative afforestation area and NDVI in Yan'an and Yulin during 1998-2013, r = 0.859 and 0.85, n = 16, P < 0.001.

Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA

EPA Science Inventory

Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g. climate change) versus direct and ...

Vegetation recovery following fire and harvest disturbance in central Labrador — a landscape perspective

Treesearch

Brian Miranda; Brian R. Sturtevant; Isabelle Schmelzer; Frederik Doyon; Peter Wolter

2016-01-01

Understanding vegetation recovery patterns following wildfire and logging disturbance is essential for long-term planning in sustainable forestry. Plot-scale studies indicate differences in revegetation rates and postdisturbance composition in Labrador, Canada, following fire in comparison with harvest but do not necessarily capture the...

Assessing phenological change in China from 1982 to 2006 using AVHRR imagery

USDA-ARS?s Scientific Manuscript database

Long term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and climate. In this study, we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT progra...

The response of vegetation dynamics of the different alpine grassland types to temperature and precipitation on the Tibetan Plateau.

PubMed

Sun, Jian; Qin, Xiaojing; Yang, Jun

2016-01-01

The spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) of three vegetation types (alpine steppe, alpine meadow, and alpine desert steppe) across the Tibetan Plateau was analyzed from 1982 to 2013. In addition, the annual mean temperature (MAT) and annual mean precipitation (MAP) trends were quantified to define the spatiotemporal climate patterns. Meanwhile, the relationships between climate factors and NDVI were analyzed in order to understand the impact of climate change on vegetation dynamics. The results indicate that the maximum of NDVI increased by 0.3 and 0.2 % per 10 years in the entire regions of alpine steppe and alpine meadow, respectively. However, no significant change in the NDVI of the alpine desert steppe has been observed since 1982. A negative relationship between NDVI and MAT was found in all these alpine grassland types, while MAP positively impacted the vegetation dynamics of all grasslands. Also, the effects of temperature and precipitation on different vegetation types differed, and the correlation coefficient for MAP and NDVI in alpine meadow is larger than that for other vegetation types. We also explored the percentages of precipitation and temperature influence on NDVI variation, using redundancy analysis at the observation point scale. The results show that precipitation is a primary limiting factor for alpine vegetation dynamic, rather than temperature. Most importantly, the results can serve as a tool for grassland ecosystem management.

Desertification and its effect on the erosion of vegetation in the south-western region of Saudi Arabia.

PubMed

Abd El-Salam, Magda Magdy; Elhakem, Abeer Hamdy

2016-03-01

This study was conducted in Jazan region of south-western Saudi Arabia. Vegetation cover, frequency, abundance and soil characteristics were analysed at three locations with different quantitative and descriptive vegetation characteristics. Plant species were classified into three primary communities dominated by Salvadora persic, Acacia tortilis and Ziziphus spini-Christi. The results indicated that the distribution of plant species is controlled by soil characteristics. Very limited water resources are also limiting factor in vegetation growth. Among the three studied sites, desert and coastal environments are affected by desertification. Rehabilitation of the degraded lands requires collaborative efforts and support from the different related governmental sectors. Ecological conservation and sustainable development must be adopted as tools of rehabilitation.

Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

NASA Astrophysics Data System (ADS)

Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

2016-04-01

Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map CC based on seasonal features with possibility to integrate medium resolution satellite observation from several sensors (e.g. Landsat and Sentinel-2) in the future.

Differences in hydrological responses for different vegetation types on a steep slope on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Duan, Liangxia; Huang, Mingbin; Zhang, Luodan

2016-06-01

Extensive vegetation restoration practices have been implemented to control soil erosion on the Loess Plateau, China. However, no strict guidelines are available to determine the most suitable plant species for vegetation restoration within a given area. The objective of this study was to quantify the changes of each component (soil water storage, surface runoff, and actual evapotranspiration) of a water balance model and soil loss over time under eight different vegetation types, and to further determine the optimal vegetation type for soil and water conservation and sustainable ecological restoration on the steep slopes (>25°) on the Loess Plateau. The results indicated that vegetation type substantially affected soil water storage and that the greatest soil water storage in both the shallow (0-2 m) and the deep soil layers (2-5 m) occurred under Bothriochloa ischaemum L. (BOI). Vegetation type also affected surface runoff and soil losses. The most effective vegetation types for reducing soil erosion were BOI and Sea-buckthorn (Hippophae rhamnoides L.), while Chinese pine (Pinus tabulaeformis Carr.) and Chinese pine + Black locust (Robinia pseudoacacia L.) were the most ineffective types. Soil water dynamics and evapotranspiration varied considerably among the different vegetation types. A soil water surplus was only found under BOI, while insufficient water replenishment existed under the other seven vegetation types. The higher water consumption rates of the seven vegetation types could result in soil desiccation, which could lead to severe water stresses that would adversely affect plant growth. This study suggested that both vegetation type and its effect on controlling soil erosion should be considered when implementing vegetation restoration and that BOI should be highly recommended for vegetation restoration on the steep slopes of the Loess Plateau. A similar approach to the one used in this study could be applied to other regions of the world confronted by the same problems of water scarcity along with the need for vegetation restoration.

Deriving a light use efficiency estimation algorithm using in situ hyperspectral and eddy covariance measurements for a maize canopy in Northeast China.

PubMed

Zhang, Feng; Zhou, Guangsheng

2017-07-01

We estimated the light use efficiency ( LUE ) via vegetation canopy chlorophyll content ( CCC canopy ) based on in situ measurements of spectral reflectance, biophysical characteristics, ecosystem CO 2 fluxes and micrometeorological factors over a maize canopy in Northeast China. The results showed that among the common chlorophyll-related vegetation indices (VIs), CCC canopy had the most obviously exponential relationships with the red edge position (REP) ( R 2  = .97, p  <   .001) and normalized difference vegetation index (NDVI) ( R 2  = .91, p  <   .001). In a comparison of the indicating performances of NDVI, ratio vegetation index (RVI), wide dynamic range vegetation index (WDRVI), and 2-band enhanced vegetation index (EVI2) when estimating CCC canopy using all of the possible combinations of two separate wavelengths in the range 400-1300 nm, EVI2 [1214, 1259] and EVI2 [726, 1248] were better indicators, with R 2 values of .92 and .90 ( p  <   .001). Remotely monitoring LUE through estimating CCC canopy derived from field spectrometry data provided accurate prediction of midday gross primary productivity ( GPP ) in a rainfed maize agro-ecosystem ( R 2  = .95, p  <   .001). This study provides a new paradigm for monitoring vegetation GPP based on the combination of LUE models with plant physiological properties.

Monitoring the state of vegetation in Hungary using 15 years long MODIS Data

NASA Astrophysics Data System (ADS)

Kern, Anikó; Bognár, Péter; Pásztor, Szilárd; Barcza, Zoltán; Timár, Gábor; Lichtenberger, János; Ferencz, Csaba

2015-04-01

Monitoring the state and health of the vegetation is essential to understand causes and severity of environmental change and to prepare for the negative effects of climate change on plant growth and productivity. Satellite remote sensing is the fundamental tool to monitor and study the changes of vegetation activity in general and to understand its relationship with the climate fluctuations. Vegetation indices and other vegetation related measures calculated from remotely sensed data are widely used to monitor and characterize the state of the terrestrial vegetation. Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are among the most popular indices that can be calculated from measurements of the MODerate resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS-AM1/Terra and EOS-PM1/Aqua satellites (since 1999 and 2002 respectively). Based on the available, 15 years long MODIS data (2000-2014) the vegetation characteristics of Hungary was investigated in our research, primarily using vegetation indices. The MODIS NDVI and EVI (both part of the so-called MOD13 product of NASA) are freely available with a finest spatial resolution of 250 meters and a temporal resolution of 16 days since 2000/2002 (for Terra and Aqua respectively). The accuracy, the spatial resolution and temporal continuity of the MODIS products makes these datasets highly valuable despite of its relatively short temporal coverage. NDVI is also calculated routinely from the raw MODIS data collected by the receiving station of Eötvös Loránd University. In order to characterize vegetation activity and its variability within the Carpathian Basin the area-averaged annual cycles and their interannual variability were determined. The main aim was to find those years that can be considered as extreme according to specific indices. Using archive meteorological data the effects of extreme weather on vegetation activity and growth were investigated with emphasis on drought and heat waves. Te relationship between anomalies of vegetation characteristics and crop yield decrease in agricultural regions were characterised as well. The mean NDVI values of Hungary during the 15 years reveal the behaviour of the vegetation in the country, where the main land cover types (forest, agriculture and grassland) were distinguished as well. NDVI anomalies are analyzed separately for the main land cover types. Deviations from the potential maximum vegetation greenness are also calculated for the entire time period.

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

Thermal remote sensing approach combined with field spectroscopy for detecting underground structures intended for defence and security purposes in Cyprus

NASA Astrophysics Data System (ADS)

Melillos, George; Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.

2018-04-01

The purpose of this paper is to present the results obtained from unmanned aerial vehicle (UAV) using multispectral with thermal imaging sensors and field spectroscopy campaigns for detecting underground structures. Airborne thermal prospecting is based on the principle that there is a fundamental difference between the thermal characteristics of underground structures and the environment in which they are structure. This study aims to combine the flexibility and low cost of using an airborne drone with the accuracy of the registration of a thermal digital camera. This combination allows the use of thermal prospection for underground structures detection at low altitude with high-resolution information. In addition vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR), were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices or other in-band algorithms. The measurements were taken at the following test areas such as: (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure. It is important to highlight that this research is undertaken at the ERATOSTHENES Research Centre which received funding to be transformed to an EXcellence Research Centre for Earth SurveiLlance and Space-Based MonItoring Of the EnviRonment (Excelsior) from the HORIZON 2020 Widespread-04-2017: Teaming Phase 1(Grant agreement no: 763643).

Estimation of photosynthetic capacity using MODIS polarization: 1988 proposal to NASA Headquarters

NASA Technical Reports Server (NTRS)

Vanderbilt, Vern C.

1992-01-01

The remote sensing community has clearly identified the utility of NDVI (normalized difference vegetation index) and SR (simple ratio) and other vegetation indices for estimating such metrics of landscape ecology as green foliar biomass, photosynthetic capacity, and net primary production. Both theoretical and empirical investigations have established cause and effect relationships between the photosynthetic process in plant canopies and these combinations of remotely sensed data. Yet it has also been established that the relationships exhibit considerable variability that appears to be ecosystem-dependent and may represent a source of ecologically important information. The overall hypothesis of this proposal is that the ecosystem-dependent variability in the various vegetation indices is in part attributable to the effects of specular reflection. The polarization channels on MODIS provide the potential to estimate this specularly reflected light and allow the modification of the vegetation indices to better measure the photosynthetic process in plant canopies. In addition, these polarization channels potentially provide additional ecologically important information about the plant canopy.

Remotely-sensed detection of effects of extreme droughts on gross primary production.

PubMed

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-06-15

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days.Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. In conclusion, the quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in rural areas starts earlier (start of season, SOS) and ends latermore » (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.« less

(How) Can We Use Satellite Data to Estimate Effects of Extreme Drought on Photosynthesis?

NASA Astrophysics Data System (ADS)

Vicca, S.; Balzarolo, M.; Filella, I.; Granier, A.; Herbst, M.; Knohl, A.; Longdoz, B.; Mund, M.; Nagy, Z.; Pintér, K.; Rambal, S.; Verbesselt, J.; Verger, A.; Zeileis, A.; Zhang, C.; Penuelas, J.

2017-12-01

Severe droughts can strongly impact photosynthesis (GPP), but the tool best suited for large-scale and long-term monitoring, satellite imagery, has yet to prove its ability to detect drought effects on GPP. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect effect of a strong drought (that started during the European heatwave of 2003) on GPP in a beech forest in France (Hesse). While vegetation state remained largely unaffected by the drought, Eddy Covariance data revealed a substantial decrease in GPP and GPP recovered only after about three years. This three-year reduction in GPP was, however not detected by severaly commonly used reflectance indices (like NDVI and FAPAR) or by MODIS GPP product. Only he Enhanced Vegetation Index (EVI) and the Photochemical Reflectance Index (PRI) detected the drought effect, but the PRI only after normalization for absorbed light. These results were compared to a two other forests where a severe drought event had affected GPP and these data confirmed that especially the PRI normalized for absorbed light provides useful information about vegetation functioning that is not captured by other remote sensing indicators under test.

Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose.

PubMed

Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K; Abaidoo, Robert C; Dalsgaard, Anders; Hald, Tine

2017-12-01

The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10 -5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10 -4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10 -6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose. Copyright © 2017 Elsevier B.V. All rights reserved.

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

The impact of home freezing on the sensory characteristics of ready-to-use leafy vegetables.

PubMed

Mohammadi, Mehrdad; Koushki, Mohammad Reza; Ahmadian, Fariba Seyed; Moslemy, Masoumeh

2011-02-01

Owing to the increasing trend of consumption of ready-to-use leafy vegetables, the necessity of determining the best conditions for their frozen storage and the considerable impact of freezing on their sensory attributes, research was carried out to determine the best freezing temperature and storage time for a mixture of Allium ampeloprasum, Lepidium sativum and Stureia hortensis. The results for freezing temperature at three different storage times showed that colour and overall acceptability at - 18 °C were always ranked first (P < 0.05), while taste at - 18 °C was ranked first on days 120 and 150. The results for frozen storage time at three different temperatures indicated that colour, taste and acceptability were not significantly different. Overall, the results of this research indicated that the sensory attributes of leafy vegetables during 180 days of frozen storage were affected mainly by freezing temperature rather than frozen storage time. 2010 Society of Chemical Industry.

The red edge in arid region vegetation: 340-1060 nm spectra

NASA Technical Reports Server (NTRS)

Ray, Terrill W.; Murray, Bruce C.; Chehbouni, A.; Njoku, Eni

1993-01-01

The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno-cellulose absorptions at 2090 nm and 2300 nm. Ray et al. detected absorption at 2100 nm in AVIRIS spectra of an abandoned field known to be covered by a great deal of dead plant litter. In order to better study arid region vegetation remote sensing data, it is necessary to better characterize the reflectance spectra of in situ, living, arid region plants.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observationsmore » (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.« less

Effect of Phosphate levels on vegetables irrigated with wastewater

NASA Astrophysics Data System (ADS)

Oladeji, S. O.; Saeed, M. D.

2018-04-01

This study examined accumulation of phosphate ions in wastewater and vegetables through man-made activities. Phosphate level was determined in wastewater and vegetables collected on seasonal basis along Kubanni stream in Zaria using UV/Visible and Smart Spectro Spectrophotometers for their analyses. Results obtained show that phosphate concentrations ranged from 3.85 – 42.33 mg/L in the first year and 15.60 – 72.80 mg/L in the second year for wastewater whereas the vegetable had levels of 3.80 – 23.65 mg/kg in the year I and 7.48 – 27.15 mg/kg in the year II. Further statistical tests indicated no significant difference in phosphate levels across the locations and seasons for wastewater and vegetables evaluated. Correlation results for these two years indicated negative (r = -0.062) relationship for wastewater while low (r = 0.339) relationship noticed for vegetables planted in year I to that of year II. Phosphate concentrations obtained in this study was higher than Maximum Contaminant Levels set by Standard Organization such as WHO and FAO for wastewater whereas vegetables of the sampling sites were not contaminated with phosphate ions. Irrigating farmland with untreated wastewater has negative consequence on the crops grown with it.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Variable responses to CO2 of the duration of vegetative growth within maturity group IV soybeans

USDA-ARS?s Scientific Manuscript database

Prior experiments in indoor chambers and in the field using free-air carbon dioxide enrichment (FACE) systems indicated variation among soybean cultivars in whether and how much elevated CO2 prolonged vegetative development. However, the cultivars tested differed in maturity group, and it is not kn...

Estimating leaf area and above-ground biomass of forest regeneration areas using a corrected normalized difference vegetation index

Treesearch

Tommy L. Coleman; James H. Miller; Bruce R. Zutter

1992-01-01

The objective of this study was to investigate the regression relations between vegetation indices derived from remotely-sensed data of single and mixed forest regeneration plots. Loblolly pine (Pinus taeda L.) seedlings, sweelgum (Liquidambar styraciflua L.) seedlings and broomsedge (Andropogon virginicus L.)...

Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rahilly, P.J.A.; Li, D.; Guo, Q.

2010-01-15

This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothymore » biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal wetlands.« less

Effects of food processing on pesticide residues in fruits and vegetables: a meta-analysis approach.

PubMed

Keikotlhaile, B M; Spanoghe, P; Steurbaut, W

2010-01-01

Pesticides are widely used in food production to increase food security despite the fact that they can have negative health effects on consumers. Pesticide residues have been found in various fruits and vegetables; both raw and processed. One of the most common routes of pesticide exposure in consumers is via food consumption. Most foods are consumed after passing through various culinary and processing treatments. A few literature reviews have indicated the general trend of reduction or concentration of pesticide residues by certain methods of food processing for a particular active ingredient. However, no review has focused on combining the obtained results from different studies on different active ingredients with differences in experimental designs, analysts and analysis equipment. In this paper, we present a meta-analysis of response ratios as a possible method of combining and quantifying effects of food processing on pesticide residue levels. Reduction of residue levels was indicated by blanching, boiling, canning, frying, juicing, peeling and washing of fruits and vegetables with an average response ratio ranging from 0.10 to 0.82. Baking, boiling, canning and juicing indicated both reduction and increases for the 95% and 99.5% confidence intervals. Copyright 2009 Elsevier Ltd. All rights reserved.

Applications of Remote Sensing and In-Situ Measurements for the Purpose of Understanding Lateral Carbon Fluxes between Tidal Marshes and Connected Estuarine Waters

NASA Astrophysics Data System (ADS)

Van, U. A.; Lamb, B. T.

2016-12-01

Wetlands are biologically diverse ecosystems that provide a number of ecosystems services, including flood protection, erosion prevention, and carbon sequestration. Wetlands often act as carbon sinks because the abundant plant life in wetlands does not decompose easily in the saturated conditions, leading to carbon accumulating in wetland soils. Due to the motion of tides, however, this stored carbon can be transported to the adjacent estuary. Our study site is in the northwestern shore of the Chesapeake Bay, focusing on the Kirkpatrick Marsh and the adjacent Rhode River estuary. The goal of this project is to use remotely sensed data and in situ measurements to understand carbon fluxes between the Kirkpatrick marsh and the Rhode river estuary. Satellite earth images are obtained from the Optical Land Imager (OLI) sensor aboard the Landsat 8 satellite through the USGS Earth Explorer online interface. Landsat imagery is then processed using various spatial analysis tools to calculate for vegetation indices such as Normalized Density Vegetation Index (NDVI), Transformed Vegetation Index (TVI) and Green Normalized Density Vegetation Index (GNDVI). One goal of this project is to compare the vegetation data obtained from the different indices and find out which index can optimize the wide categorization of vegetation over the wetland. We evaluated lesser known vegetation indices (TVI and GNDVI) to compare to NDVI. Preliminary results have shown TVI to be most effective when compared against NDVI and has a correlating factor of 0.987. In addition to using marsh vegetation indices, we are using water quality indices such as the Red/Green index to compare to in-situ water samples in the Rhode River. A YSI EXO2 sensor sits at the marsh-estuary interface and continuously measures water parameters such as turbidity, depth, fDOM and chlorophyll-A. We are attempting to understand if the marsh vegetation indices, water quality indices (remote sensing), and in-situ measurements of water quality are related to one another. Initial comparison between remotely sensed NDVI data and in-situ fDOM data have a correlating factor of 0.93. Understanding the processes affecting carbon cycling within wetlands is pivotal to knowing how to manage them in the future.

Herbivore Impact on Tundra Plant Community Dynamics Using Long-term Remote Sensing Observation

NASA Astrophysics Data System (ADS)

Yu, Q.; Engstrom, R.; Shiklomanov, N. I.

2014-12-01

Arctic tundra biome is now experiencing dramatic environmental changes accentuated by summer sea-ice decline, permafrost thaw, and shrub expansion. Multi-decadal time-series of the Normalized Difference Vegetation Index (NDVI, a spectral metric of vegetation productivity) shows an overall "greening" trend across the Arctic tundra biome. Regional trends in climate plausibly explain large-scale patterns of increasing plant productivity, as diminished summer sea-ice extent warms the adjacent land causing tundra vegetation to respond positively (increased photosynthetic aboveground biomass). However, at more local scales, there is a great deal of spatial variability in NDVI trends that likely reflects differences in hydrology and soil conditions, disturbance history, and use by wildlife and humans. Particularly, habitat use by large herbivores, such as reindeer and caribou, has large impacts on vegetation dynamics at local and regional scales, but the role of herbivores in modulating the response of vegetation to warming climate has received little attention. This study investigates regional tundra plant community dynamics within inhabits of different sizes of wild caribou/reindeer herds across the Arctic using GIMMS NDVI (Normalized Difference Vegetation Index) 3g data product. The Taimyr herd in Russia is one of the largest herds in the world with a population increase from 450,000 in 1975 to about 1 million animals in 2000. The population of the porcupine caribou herd has fluctuated in the past three decades between 100,000 and 180,000. Time-series of the maximum NDVI within the inhabit area of the Taimyr herd has increased about 2% per decade over the past three decades, while within the inhabit area of the Porcupine herd the maximum NDVI has increased about 5% per decade. Our results indicate that the impact of large herbivores can be detected from space and further analyses on seasonal dynamics of vegetation indices and herbivore behavior may provide more understanding of the plant-herbivore interactions within the context of a 'greening' Arctic.

Modified vegetation indices for Ganoderma disease detection in oil palm from field spectroradiometer data

NASA Astrophysics Data System (ADS)

Shafri, Helmi Z. M.; Anuar, M. Izzuddin; Saripan, M. Iqbal

2009-10-01

High resolution field spectroradiometers are important for spectral analysis and mobile inspection of vegetation disease. The biggest challenges in using this technology for automated vegetation disease detection are in spectral signatures pre-processing, band selection and generating reflectance indices to improve the ability of hyperspectral data for early detection of disease. In this paper, new indices for oil palm Ganoderma disease detection were generated using band ratio and different band combination techniques. Unsupervised clustering method was used to cluster the values of each class resultant from each index. The wellness of band combinations was assessed by using Optimum Index Factor (OIF) while cluster validation was executed using Average Silhouette Width (ASW). 11 modified reflectance indices were generated in this study and the indices were ranked according to the values of their ASW. These modified indices were also compared to several existing and new indices. The results showed that the combination of spectral values at 610.5nm and 738nm was the best for clustering the three classes of infection levels in the determination of the best spectral index for early detection of Ganoderma disease.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

Phenological indicators derived with CO2 flux, MODIS image and ground monitor at a temperate mixed forest and an alpine shrub

NASA Astrophysics Data System (ADS)

Zhang, Leiming; Cao, Peiyu; Li, Shenggong; Yu, Guirui; Zhang, Junhui; Li, Yingnian

2016-04-01

To accurately assess the change of phenology and its relationship with ecosystem gross primary productivity (GPP) is one of the key issues in context of global change study. In this study, an alpine shrubland meadow in Haibei (HBS) of Qinghai-Tibetan plateau and a broad-leaved Korean pine forest in Changbai Mountain (CBM) of Northeastern China were selected. Based on the long-term GPP from eddy flux measurements and the Normalized Difference Vegetation Index (NDVI) from remote sensed vegetation index, phenological indicators including the start of growing season (SOS), the end of growing season (EOS), and the growing season length (GSL) since 2003 were derived via multiple methods, and then the influences of phenology variation on GPP were explored. Compared with ground phenology observations of dominant plant species, both GPP- and NDVI-derived SOS and EOS exhibited a similar interannual trend. GPP-derived SOS was quite close to NDVI-derived SOS, but GPP-derived EOS differed significantly from NDVI-derived EOS, and thus leading to a significant difference between GPP- and NDVI-derived GSL. Relative to SOS, EOS presented larger differences between the extraction methods, indicating large uncertainties to accurately define EOS. In general, among the methods used, the threshold methods produced more satisfactory assessment on phenology change. This study highlights that how to harmonize with the flux measurements, remote sensing and ground monitoring are a big challenge that needs further consideration in phenology study, especially the accurate extraction of EOS. Key words: phenological variation, carbon flux, vegetation index, vegetation grwoth, interannual varibility

Relationship of young-of-the-year northern pike to aquatic vegetation types in backwaters of the upper Mississippi River

USGS Publications Warehouse

Holland, L.E.; Huston, M.L.

1984-01-01

The association of young-of-the-year northern pike (Esox lucius) with different aquatic plant types (e.g., submerged, emergent, floating) was studied to evaluate the impacts of a potential loss of backwaters on available fish nursery habitats in the upper Mississippi River. Eight biweekly collections were made at each of six representative lentic habitats in Navigation Pool 7. In the spring, average catches of northern pike from areas with submerged vegetation were nearly three times greater than from areas with emergent vegetation, and more than 10 times greater than from an area with no vegetation. This pattern was consistent until late summer, when the young became more common in the more highly oxygenated, less heavily vegetated waters. Food and growth were examined as possible indicators for the selection of areas with submerged vegetation over other habitats. Food varied among fish in the different vegetation types; however, no significant patterns of improved growth or condition were apparent. Young northern pike apparently were successful, opportunistic feeders. Although preference for habitats with submerged vegetation was seemingly not related to food, the overall production of young was clearly best in these habitats.

Response of vegetation phenology to urbanization in the conterminous United States.

PubMed

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R; Mao, Jiafu; Li, Xiaoma; Li, Wenyu

2017-07-01

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003-2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6-6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology. © 2016 John Wiley & Sons Ltd.

Response of vegetation indices to changes in three measures of leaf water stress

NASA Technical Reports Server (NTRS)

Cohen, Warren B.

1991-01-01

The responses of vegetation indices to changes in water stress were evaluated in two separate laboratory experiments. In one experiment the normalized difference vegetation index (NDVI), the near-IR to red ratio (near-IR/red), the Infrared Index (II), and the Moisture Stress Index (MSI) were more highly correlated to leaf water potential in lodgepole pine branches than were the Leaf Water Content Index (LWCI), the mid-IR ratio (Mid-IR), or any of the single Thematic Mapper (TM) bands. In the other experiment, these six indices and the TM Tasseled Cap brightness, greenness, and wetness indices responded to changes in leaf relative water content (RWC) differently than they responded to changes in leaf water content (WC) of three plant species, and the responses were dependent on how experimental replicates were pooled. With no pooling, the LWCI was the most highly correlated index to both RWC and WC among replications, followed by the II, MSI, and wetness. Only the LWCI was highly correlated to RWC and WC when replications were pooled within species. With among species pooling the LWCI was the only index highly correlated with RWC, while the II, MSI, Mid-IR, and wetness were most highly correlated with WC.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Vegetation colonization of permafrost-related landslides, Ellesmere Island, Canadian High Arctic

NASA Astrophysics Data System (ADS)

Cannone, Nicoletta; Lewkowicz, Antoni G.; Guglielmin, Mauro

2010-12-01

Relationships between vegetation colonization and landslide disturbance are analyzed for 12 active-layer detachments of differing ages located in three areas of the Fosheim Peninsula, Ellesmere Island (80°N). We discuss vegetation as an age index for landslides and a way to assess the time needed for complete recolonization of the surfaces since landslide detachment. Vegetation on undisturbed terrain is similar in the three areas but is more highly developed and complex inland due to a warmer summer climate. On a regional scale, the location of the area is as important as the effect of landslide age on vegetation colonization because of the influence of mesoclimatic conditions on vegetation development. On a landscape scale, there is a positive relationship between landslide age and vegetation development, as represented by total vegetation cover, floristic composition, and successional stage. Consequently, vegetation can be used at this scale as an indicator of landslide age. Fifty years are required to restore vegetation patches to a floristic composition similar to communities occurring in undisturbed conditions, but with lower floristic richness and a discontinuous cover and without well-developed layering. The shorter time needed for landslide recovery in the area with the warmest summer climate confirms the sensitivity of arctic vegetation to small differences in air temperature. This could trigger a set of interlinked feedbacks that would amplify future rates of climate warming.

Comparison of NDVI fields obtained from different remote sensors

NASA Astrophysics Data System (ADS)

Escribano Rodriguez, Juan; Alonso, Carmelo; Tarquis, Ana Maria; Benito, Rosa Maria; Hernandez Díaz-Ambrona, Carlos

2013-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI and their interpretation as a drought index. During 2012 three locations (at Salamanca, Granada and Córdoba) were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 and MODIS of the chosen places. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. By contranst, MODIS images present a much lower spatial resolution (500x500 m). The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. MTM2009-14621 and i-MATH No. CSD2006-00032 is greatly appreciated.

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2003-01-01

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

Assessing the Influence of Precipitation Variability on the Vegetation Dynamics of the Mediterranean Rangelands using NDVI and Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis; Tsanis, Ioannis

2017-04-01

Mitigating the vulnerability of Mediterranean rangelands against degradation is limited by our ability to understand and accurately characterize those impacts in space and time. The Normalized Difference Vegetation Index (NDVI) is a radiometric measure of the photosynthetically active radiation absorbed by green vegetation canopy chlorophyll and is therefore a good surrogate measure of vegetation dynamics. On the other hand, meteorological indices such as the drought assessing Standardised Precipitation Index (SPI) are can be easily estimated from historical and projected datasets at the global scale. This work investigates the potential of driving Random Forest (RF) models with meteorological indices to approximate NDVI-based vegetation dynamics. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The updated E-OBS-v13.1 dataset of the ENSEMBLES EU FP6 program provides observed monthly meteorological input to estimate SPI over the Mediterranean rangelands. RF models are trained to depict vegetation dynamics using the latest version (3g.v1) of the third generation GIMMS NDVI generated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensors. Analysis is conducted for the period 1981-2015 at a gridded spatial resolution of 25 km. Preliminary results demonstrate the potential of machine learning algorithms to effectively mimic the underlying physical relationship of drought and Earth Observation vegetation indices to provide estimates based on precipitation variability.

Linking in situ LAI and fine resolution remote sensing data to map reference LAI over cropland and grassland using geostatistical regression method

NASA Astrophysics Data System (ADS)

He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua

2016-08-01

Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.

Relationships between canopy greenness and CO2 dynamics of a Mediterranean deciduous forest assessed with webcam imagery and MODIS vegetation indices

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Papale, D.; Richardson, A. D.

2009-04-01

Phenological observations of foliar development and senescence are needed to understand the relationship between canopy properties and seasonal productivity dynamics (e.g., carbon uptake) of terrestrial ecosystems. Traditional phenological ground observations based on a visual observation of different vegetation growth phases (from first leaf opening, to first leaf flowering, full bloom until senescence) are laborious and typically limited to observations on just a few individual subjects. On the contrary, remote sensing techniques appear to offer the potential for assessing long-term variability in primary productivity at a global scale (Field et al., 1993). Recent studies have shown that biochemical and biophysical canopy properties can be measured with a quantifiable uncertainty that can be incorporated in the land-biosphere models (Ustin et al., 2004a; Ollinger et al 2008). Canopy greenness can be quantified by the use of vegetation indices (VIs) as, for example, Normalized Difference Vegetation Index (NDVI, Rouse et al., 1974; Deering, 1978), but a disadvantage of this approach is that there are uncertainties associated with these indices (due to the spatial and temporal resolution of the data), and the interpretation of a specific VI value, in the context of on-the-ground phenology, is not clear. Improved ground-based datasets are needed to validate and improve remotely-sensed phenological indices. Continuous monitoring of vegetation canopies with digital webcams (Richardson et al. 2007) may offer a direct link between phenological changes in canopy state and what is "seen" by satellite sensors. The general objective of this study is to analyze the relationship between biosphere-atmosphere CO2 exchange (measured by eddy covariance) and phenological canopy status, or greenness, of a Mediterranean deciduous broadleaf forest in central Italy (Roccarespampani, 42°24' N, 11°55' E). Canopy greenness is quantify using two different approaches: from digital webcam images, using indices derived from red, green and blue (RGB) color channel brightness (RGBi, after Richardson et al. 2007) and with VIs (e.g. NDVI, SR, MSR, GRDI, NCI, CI and SLAVI) derived from MODIS surface reflectance data (MOD09A1). Since MOD09A1 reflectance data represent the maximum surface reflectance of each band for a consecutive 8-day period, webcam imagery, as fluxes data, acquired whit half-hourly temporal resolution have been time averaged on 8 day period. Evaluation of performance of RGBi-VIs, RGBi-CO2flux and MODIS-CO2flux relationships were performed by linear regression analyses using the classical least squares (LS) statistical technique. Among all calculated vegetation indexes, GRDI (Green Red Difference Index: Gitelson et al., 2002) and SLAVI (Specific Leaf Area Vegetation Index: Lymburner et al., 2000) showed best linear fit with webcam RGBi greenness. SLAVI was also one of the vegetation indices best correlated with mean daily CO2 flux (R2=0.79). Finally, the relationship between RGBi and CO2 flux had a R2 of 0.67. Concluding, both webcam and MODIS greenness indices offer potential for assessing seasonal variation in the productivity of terrestrial ecosystems. Future work will focus on reducing the uncertainties inherent in these approaches, and integrating field observations of phenology into this study.

A Comparison of Treating Metabolic Acidosis in CKD Stage 4 Hypertensive Kidney Disease with Fruits and Vegetables or Sodium Bicarbonate

PubMed Central

Goraya, Nimrit; Simoni, Jan; Jo, Chan-Hee

2013-01-01

Summary Background and objectives Current guidelines recommend Na+-based alkali for CKD with metabolic acidosis and plasma total CO2 (PTCO2) < 22 mM. Because diets in industrialized societies are typically acid-producing, we compared base-producing fruits and vegetables with oral NaHCO3 (HCO3) regarding the primary outcome of follow-up estimated GFR (eGFR) and secondary outcomes of improved metabolic acidosis and reduced urine indices of kidney injury. Design, setting, participants, & measurements Individuals with stage 4 (eGFR, 15–29 ml/min per 1.73 m2) CKD due to hypertensive nephropathy, had a PTCO2 level < 22 mM, and were receiving angiotensin-converting enzyme inhibition were randomly assigned to 1 year of daily oral NaHCO3 at 1.0 mEq/kg per day (n=35) or fruits and vegetables dosed to reduce dietary acid by half (n=36). Results Plasma cystatin C–calculated eGFR did not differ at baseline and 1 year between groups. One-year PTCO2 was higher than baseline in the HCO3 group (21.2±1.3 versus 19.5±1.5 mM; P<0.01) and the fruits and vegetables group (19.9±1.7 versus 19.3±1.9 mM; P<0.01), consistent with improved metabolic acidosis, and was higher in the HCO3 than the fruits and vegetable group (P<0.001). One-year urine indices of kidney injury were lower than baseline in both groups. Plasma [K+] did not increase in either group. Conclusions One year of fruits and vegetables or NaHCO3 in individuals with stage 4 CKD yielded eGFR that was not different, was associated with higher-than-baseline PTCO2, and was associated with lower-than-baseline urine indices of kidney injury. The data indicate that fruits and vegetables improve metabolic acidosis and reduce kidney injury in stage 4 CKD without producing hyperkalemia. PMID:23393104

Choosing indicators of natural resource condition: A case study in Arches National Park, Utah, USA

USGS Publications Warehouse

Belnap, J.

1998-01-01

Heavy visitor use in many areas of the world have necessitated development of ways to assess visitation impacts. Arches National Park recently completed a Visitor Experience and Resource Protection (VERP) plan. Integral to this plan was developing a method to identify biological indicators that would both measure visitor impacts and response to management actions. The process used in Arches for indicator selection is outlined here as a model applicable to many areas facing similar challenges. The steps were: (1) Vegetation types most used by visitors were identified. Impacted and unimpacted areas in these types were sampled, comparing vegetation and soil factors. (2) Variables found to differ significantly between compared sites were used as potential indicators. (3) Site-specific criteria for indicators were developed, and potential indicators evaluated using these criteria. (4) Chosen indicators were further researched for ecological relevancy. (5) Final indicators were chosen, field tested, and monitoring sites designated. In Arches, indicators were chosen for monitoring annually (soil crust index, soil compaction, number of used social trails and soil aggregate stability) and every five years (vegetation cover and frequency; ground cover; soil chemistry; and plant tissue chemistry).

Accumulation status, sources and phytoavailability of metals in greenhouse vegetable production systems in Beijing, China.

PubMed

Xu, Li; Lu, Anxiang; Wang, Jihua; Ma, Zhihong; Pan, Ligang; Feng, Xiaoyuan; Luan, Yunxia

2015-12-01

The accumulation status, sources and phytoavailability of selected metals in greenhouse vegetable production systems in peri-urban areas of Beijing were investigated. The mean concentrations of As, Cd, Cr, Hg and Pb in greenhouse soils were 8.44, 0.25, 69.0, 0.09 and 22.0 mg kg(-1), dw, respectively. According to principal component analysis, As, Cd, Cr and Hg are mainly from anthropogenic source, but Pb is likely from natural source. Metal concentrations in all vegetable samples were decreased in the order of Cr>As>Pb>Cd>Hg. Compared with root and fruit vegetables, leaf vegetables had relatively high concentrations and transfer factors of heavy metals, except for Cd. By including soil pH, OM and greenhouse soil metals, 10 empirical models were derived using stepwise multiple linear regression analysis to predict heavy metal concentrations in the edible parts of different vegetables. Among the different vegetable groups, the highest intakes of metals occurred through consumption of leaf vegetables for the two age groups, except for Cd. The HI value of the studied metals were all below 1, indicating that consumption of vegetables grown in greenhouse soils was of low risk to consumers in our study area. Copyright © 2015 Elsevier Inc. All rights reserved.

The contribution of brown vegetation to vegetation dynamics

USDA-ARS?s Scientific Manuscript database

Indices of vegetation dynamics that include both green vegetation (GV) and non-photosynthetic vegetation (NPV), that is, brown vegetation, were applied to MODIS surface reflectance data from 2000 to 2006 for the southwestern United States. These indices reveal that the cover of NPV, a measure of veg...

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Combining remote sensing and eddy covariance data to monitor the gross primary production of an estuarine wetland ecosystem in East China.

PubMed

Wu, Mingquan; Muhammad, Shakir; Chen, Fang; Niu, Zheng; Wang, Changyao

2015-04-01

Wetland ecosystems are very important for ecological diversity and have a strong ability to sequester carbon. Through comparisons with field measured eddy covariance data, we evaluated the relationships between the light use efficiency (LUE) index and the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface temperature (LST). Consequently, we have proposed a new model for the estimation of gross primary production (GPP) for wetland ecosystems using Moderate Resolution Imaging Spectroradiometer (MODIS) products, including these vegetation indices, LST and the fraction of photosynthetically active radiation (FAPAR) absorbed by the active vegetation. This model was developed and validated for a study site on Chongming Island, Shanghai, China. Our results show that photosynthetically active radiation (PAR) was highly correlated with the LST, with a coefficient of determination (R(2)) of 0.59 (p < 0.001). Vegetation indices, such as EVI, NDVI and LST, were highly correlated with LUE. We found that the product of vegetation indices (VIs) and a modified form of LST (Te) can be used to estimate LUE, with an R(2) of 0.82 (P < 0.0001) and an RMSE of 0.054 kg C per mol PAR. This new model can provide reliable estimates of GPP (R(2) of 0.87 and RMSE of 0.009 kg C m(-2) 8 d(-1) (P < 0.0001)).

Structural and metabolic responses of microbial community to sewage-borne chlorpyrifos in constructed wetlands.

PubMed

Zhang, Dan; Wang, Chuan; Zhang, Liping; Xu, Dong; Liu, Biyun; Zhou, Qiaohong; Wu, Zhenbin

2016-06-01

Long-term use of chlorpyrifos poses a potential threat to the environment that cannot be ignored, yet little is known about the succession of substrate microbial communities in constructed wetlands (CWs) under chlorpyrifos stress. Six pilot-scale CW systems receiving artificial wastewater containing 1mg/L chlorpyrifos were established to investigate the effects of chlorpyrifos and wetland vegetation on the microbial metabolism pattern of carbon sources and community structure, using BIOLOG and denaturing gradient gel electrophoresis (DGGE) approaches. Based on our samples, BIOLOG showed that Shannon diversity (H') and richness (S) values distinctly increased after 30days when chlorpyrifos was added. At the same time, differences between the vegetated and the non-vegetated systems disappeared. DGGE profiles indicated that H' and S had no significant differences among four different treatments. The effect of chlorpyrifos on the microbial community was mainly reflected at the physiological level. Principal component analysis (PCA) of both BIOLOG and DGGE showed that added chlorpyrifos made a difference on test results. Meanwhile, there was no difference between the vegetation and no-vegetation treatments after addition of chlorpyrifos at the physiological level. Moreover, the vegetation had no significant effect on the microbial community at the genetic level. Comparisons were made between bacteria in this experiment and other known chlorpyrifos-degrading bacteria. The potential chlorpyrifos-degrading ability of bacteria in situ may be considerable. Copyright © 2016. Published by Elsevier B.V.

[Estimating Winter Wheat Nitrogen Vertical Distribution Based on Bidirectional Canopy Reflected Spectrum].

PubMed

Yang, Shao-yuan; Huang, Wen-jiang; Liang, Dong; Uang, Lin-sheng; Yang, Gui-jun; Zhang, Gui-jan; Cai, Shu-Hong

2015-07-01

The vertical distribution of crop nitrogen is increased with plant height, timely and non-damaging measurement of crop nitrogen vertical distribution is critical for the crop production and quality, improving fertilizer utilization and reducing environmental impact. The objective of this study was to discuss the method of estimating winter wheat nitrogen vertical distribution by exploring bidirectional reflectance distribution function (BRDF) data using partial least square (PLS) algorithm. The canopy reflectance at nadir, +/-50 degrees and +/- 60 degrees; at nadir, +/- 30 degrees and +/- 40 degrees; and at nadir, +/- 20 degrees and +/- 30 degrees were selected to estimate foliage nitrogen density (FND) at upper layer, middle layer and bottom layer, respectively. Three PLS analysis models with FND as the dependent variable and vegetation indices at corresponding angles as the explicative variables were. established. The impact of soil reflectance and the canopy non-photosynthetic materials, was minimized by seven kinds of modifying vegetation indices with the ratio R700/R670. The estimated accuracy is significant raised at upper layer, middle layer and bottom layer in modeling experiment. Independent model verification selected the best three vegetation indices for further research. The research result showed that the modified Green normalized difference vegetation index (GNDVI) shows better performance than other vegetation indices at each layer, which means modified GNDVI could be used in estimating winter wheat nitrogen vertical distribution

Remotely-sensed detection of effects of extreme droughts on gross primary production

PubMed Central

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-01-01

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671

Vulnerable land ecosystems classification using spatial context and spectral indices

NASA Astrophysics Data System (ADS)

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

2017-10-01

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

An empirical, graphical, and analytical study of the relationship between vegetation indices. [derived from LANDSAT data

NASA Technical Reports Server (NTRS)

Lautenschlager, L.; Perry, C. R., Jr. (Principal Investigator)

1981-01-01

The development of formulae for the reduction of multispectral scanner measurements to a single value (vegetation index) for predicting and assessing vegetative characteristics is addressed. The origin, motivation, and derivation of some four dozen vegetation indices are summarized. Empirical, graphical, and analytical techniques are used to investigate the relationships among the various indices. It is concluded that many vegetative indices are very similar, some being simple algebraic transforms of others.

Controlling factors for infiltration on undisturbed hillslopes in unmanaged plantation forests

NASA Astrophysics Data System (ADS)

Hiraoka, Marino; Onda, Yuichi; Gomi, Takashi; Mizugaki, Shigeru; Nanko, Kazuki; Kato, Hiroaki

2017-04-01

Infiltration into the soil is a crucial factor for predicting overland flow generation. Infiltration capacity strongly relates to ground vegetation, soil characteristics, or both. For revealing controlling factors for infiltration capacity, we conducted in-situ rainfall simulation using an oscillating-nozzle type rainfall simulator at 26 plots with different ground cover conditions of unmanaged Japanese cypress (Chamaecyparis obtusa) plantations. For wide-ranging vegetation cover condition (0-100%), infiltration capacity widely varied (5-322 mm/h) and had positive correlations with indices of ground vegetation and ground litter (p < 0.01). For a limited vegetation cover condition (0-20%), the range of infiltration capacity (7-114 mm/h) was associated with ground litter thickness (p < 0.05), and difference in soil organic matter and difference in soil bulk density. Principal component analysis showed that the first and second principal components (70% of total variation) related to changes in above- and below-ground biomass and changes in pores in soil. Our findings showed that development of ground vegetation alters hydrological processes of surface soil through changes in soil characteristics via the propagation of belowground biomass development.

Upscaling from leaf to canopy chlorophyll/carotenoid pigment based vegetation indices reveal phenology of photosynthesis in temperate evergreen and deciduous trees

NASA Astrophysics Data System (ADS)

Wong, C. Y.; Bhathena, Y.; Arain, M. A.; Ensminger, I.

2017-12-01

Optically derived vegetation indices have been developed to provide information about plant status including photosynthetic activity. They reflect changes in leaf pigments, which vary seasonally in pigment composition, enabling them to be used as a proxy of photosynthetic phenology. Important pigments in photosynthetic activity are carotenoids and chlorophylls, which are associated with light harvesting and energy dissipation. In temperate forests, which consist of deciduous and evergreen trees, there are difficulties resolving evergreen phenology using the most widely used index, the normalized difference vegetation index (NDVI). NDVI works well in deciduous trees, which exhibit a "visible" phenological process of leaf growth in the spring, and leaf senescence and abscission in the autumn. Evergreen conifers stay green year-round and utilize "invisible" changes of overwintering pigment composition that NDVI cannot resolve, so carotenoid pigment sensitive vegetation indices have been suggested for evergreens. The aim of this study was to evaluate carotenoid based vegetation indices over the chlorophyll sensitive NDVI. For this purpose, we evaluated the greenness index, NDVI, and carotenoid pigment sensitive indices: photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) in red maple, white oak and eastern white pine for two years. We also measured leaf gas exchange and pigment concentrations. We observed that NDVI correlated with photosynthetic activity in deciduous trees, whereas PRI and CCI correlated with photosynthesis across both evergreen and deciduous trees. This pattern was consistent, upscaling from leaf- to canopy-scales indicating that the mechanisms involved in winter acclimation can be resolved at larger spatial scales. PRI and CCI detected seasonal changes in carotenoids and chlorophylls linked to photoprotection and are suitable as a proxy of photosynthetic activity. These findings have implications to improve our use and understanding of remotely sensed vegetation indices as proxies of photosynthetic activity in northern forests for long-term monitoring.

Detecting Anthropogenic and Climate Change Induced Land Cover and Land Use Change in the Vicinity of an Oil/gas Facility in Northwestern Siberia, Russia

NASA Astrophysics Data System (ADS)

Yu, Q.; Shiklomanov, N. I.; Streletskiy, D. A.; Engstrom, R.; Epstein, H. E.

2015-12-01

Arctic ecosystems are changing dramatically due to changes in climate, vegetation and human activities. Northwestern Siberia is one of the regions which has been undergoing various land cover and land use changes associated primarily with animal husbandry and oil/gas development. These changes have been exacerbated by warming climatic conditions over the last fifty years. In this study, we investigated land cover and land use changes associated with oil and gas development southeast of the city of Nadym within the context of climate change based on multi-source and multi-temporal remote sensing imagery. The impacts of land use on surface vegetation, radiation, and hydrological properties were evaluated using the Normalized Difference Vegetation Index (NDVI), albedo and the Normalized Difference Water Index (NDWI). The results from a comparison between high spatial resolution imagery acquired in1968 and 2006 indicate that the vegetation cover was reduced in areas disturbed by oil and gas development. Vegetation cover increased in natural landscapes over the same period,. Water logging was found along the linear structures near the oil/gas development, while in natural landscapes the drying of thermokarst lakes is evident due to permafrost degradation. Derived indices suggest that the direct impacts associated with infrastructure development are mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance.

Primary studies of trace quantities of green vegetation in Mono Lake area using 1990 AVIRIS data

NASA Technical Reports Server (NTRS)

Chen, Zhi-Kang; Elvidge, Chris D.; Groeneveld, David P.

1992-01-01

Our primary results in Jasper Ridge Biological Preserve indicate that high spectral resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data may provide a substantial advantage in vegetation, based on the chlorophyll red edge feature from 700-780 nm. The chlorophyll red edge was detected for green vegetation cover as low as 4.8 percent. The objective of our studies in Mono Lake area is to continue the experiments performed in Jasper Ridge and to examine the persistence of red edge feature of trace quantities of green vegetation for different plant communities with non-uniform soil backgrounds.

Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

USGS Publications Warehouse

,

2005-01-01

The Advanced Very High Resolution Radiometer (AVHRR) is a broad-band scanner with four to six bands, depending on the model. The AVHRR senses in the visible, near-, middle-, and thermal- infrared portions of the electromagnetic spectrum. This sensor is carried on a series of National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES), beginning with the Television InfraRed Observation Satellite (TIROS-N) in 1978. Since 1989, the United States Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has been mapping the vegetation condition of the United States and Alaska using satellite information from the AVHRR sensor. The vegetation condition composites, more commonly called greenness maps, are produced every week using the latest information on the growth and condition of the vegetation. One of the most important aspects of USGS greenness mapping is the historical archive of information dating back to 1989. This historical stretch of information has allowed the USGS to determine a 'normal' vegetation condition. As a result, it is possible to compare the current week's vegetation condition with normal vegetation conditions. An above normal condition could indicate wetter or warmer than normal conditions, while a below normal condition could indicate colder or dryer than normal conditions. The interpretation of departure from normal will depend on the season and geography of a region.

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Vegetation dynamics and responses to climate change and human activities in Central Asia.

PubMed

Jiang, Liangliang; Guli Jiapaer; Bao, Anming; Guo, Hao; Ndayisaba, Felix

2017-12-01

Knowledge of the current changes and dynamics of different types of vegetation in relation to climatic changes and anthropogenic activities is critical for developing adaptation strategies to address the challenges posed by climate change and human activities for ecosystems. Based on a regression analysis and the Hurst exponent index method, this research investigated the spatial and temporal characteristics and relationships between vegetation greenness and climatic factors in Central Asia using the Normalized Difference Vegetation Index (NDVI) and gridded high-resolution station (land) data for the period 1984-2013. Further analysis distinguished between the effects of climatic change and those of human activities on vegetation dynamics by means of a residual analysis trend method. The results show that vegetation pixels significantly decreased for shrubs and sparse vegetation compared with those for the other vegetation types and that the degradation of sparse vegetation was more serious in the Karakum and Kyzylkum Deserts, the Ustyurt Plateau and the wetland delta of the Large Aral Sea than in other regions. The Hurst exponent results indicated that forests are more sustainable than grasslands, shrubs and sparse vegetation. Precipitation is the main factor affecting vegetation growth in the Kazakhskiy Melkosopochnik. Moreover, temperature is a controlling factor that influences the seasonal variation of vegetation greenness in the mountains and the Aral Sea basin. Drought is the main factor affecting vegetation degradation as a result of both increased temperature and decreased precipitation in the Kyzylkum Desert and the northern Ustyurt Plateau. The residual analysis highlighted that sparse vegetation and the degradation of some shrubs in the southern part of the Karakum Desert, the southern Ustyurt Plateau and the wetland delta of the Large Aral Sea were mainly triggered by human activities: the excessive exploitation of water resources in the upstream areas of the Amu Darya basin and oil and natural gas extraction in the southern part of the Karakum Desert and the southern Ustyurt Plateau. The results also indicated that after the collapse of the Soviet Union, abandoned pastures gave rise to increased vegetation in eastern Kazakhstan, Kyrgyzstan and Tajikistan, and abandoned croplands reverted to grasslands in northern Kazakhstan, leading to a decrease in cropland greenness. Shrubs and sparse vegetation were extremely sensitive to short-term climatic variations, and our results demonstrated that these vegetation types were the most seriously degraded by human activities. Therefore, regional governments should strive to restore vegetation to sustain this fragile arid ecological environment. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Linking Vegetation Structure and Spider Diversity in Riparian and Adjacent Habitats in Two Rivers of Central Argentina: An Analysis at Two Conceptual Levels.

PubMed

Griotti, Mariana; Muñoz-Escobar, Christian; Ferretti, Nelson E

2017-08-01

The link between vegetation structure and spider diversity has been well explored in the literature. However, few studies have compared spider diversity and its response to vegetation at two conceptual levels: assemblage (species diversity) and ensemble (guild diversity). Because of this, we studied spider diversity in riparian and adjacent habitats of a river system from the Chacoan subregion in central Argentina and evaluated their linkage with vegetation structure at these two levels. To assess vegetation structure, we measured plant species richness and vegetation cover in the herb and shrub - tree layers. We collected spiders for over 6 months by using vacuum netting, sweep netting and pitfall traps. We collected 3,808 spiders belonging to 119 morphospecies, 24 families and 9 guilds. At spider assemblage level, SIMPROF analysis showed significant differences among studied habitats. At spider ensemble level, nevertheless, we found no significant differences among habitats. Concerning the linkage with vegetation structure, BIOENV test showed that spider diversity at either assemblage or ensemble level was not significantly correlated with the vegetation variables assessed. Our results indicated that spider diversity was not affected by vegetation structure. Hence, even though we found a pattern in spider assemblages among habitats, this could not be attributed to vegetation structure. In this study, we show that analyzing a community at two conceptual levels will be useful for recognizing different responses of spider communities to vegetation structure in diverse habitat types. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Determining relative contributions of vegetation and topography to burn severity from LANDSAT imagery.

PubMed

Wu, Zhiwei; He, Hong S; Liang, Yu; Cai, Longyan; Lewis, Bernard J

2013-10-01

Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100-1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.

Determining Relative Contributions of Vegetation and Topography to Burn Severity from LANDSAT Imagery

NASA Astrophysics Data System (ADS)

Wu, Zhiwei; He, Hong S.; Liang, Yu; Cai, Longyan; Lewis, Bernard J.

2013-10-01

Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100-1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.

Monitoring ecosystem reclamation recovery using optical remote sensing: Comparison with field measurements and eddy covariance.

PubMed

Chasmer, L; Baker, T; Carey, S K; Straker, J; Strilesky, S; Petrone, R

2018-06-12

Time series remote sensing vegetation indices derived from SPOT 5 data are compared with vegetation structure and eddy covariance flux data at 15 dry to wet reclamation and reference sites within the Oil Sands region of Alberta, Canada. This comprehensive analysis examines the linkages between indicators of ecosystem function and change trajectories observed both at the plot level and within pixels. Using SPOT imagery, we find that higher spatial resolution datasets (e.g. 10 m) improves the relationship between vegetation indices and structural measurements compared with interpolated (lower resolution) pixels. The simple ratio (SR) vegetation index performs best when compared with stem density-based indicators (R 2  = 0.65; p < 0.00), while the normalised difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) are most comparable to foliage indicators (leaf area index (LAI) and canopy cover (R 2  = 0.52-0.78; p > 0.02). Fluxes (net ecosystem production (NEP) and gross ecosystem production (GEP)) are most related to NDVI and SAVI when these are interpolated to larger 20 m × 20 m pixels (R 2  = 0.44-0.50; p < 0.00). As expected, decreased sensitivity of NDVI is problematic for sites with LAI > 3 m 2  m -2 , making this index more appropriate for newly regenerating reclamation areas. For sites with LAI < 3 m 2  m -2 , trajectories of vegetation change can be mapped over time and are within 2.7% and 3.3% of annual measured LAI changes observed at most sites. This study demonstrates the utility of remote sensing in combination with field and eddy covariance data for monitoring and scaling of reclaimed and reference site productivity within and beyond the Oil Sands Region of western Canada. Copyright © 2018 Elsevier B.V. All rights reserved.

Surface pollen and its relationship to vegetation in the Zoige Basin, eastern Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Furong; Zhao, Yan; Sun, Jinghui; Zhao, Wenwei; Guo, Xiaoli; Zhang, Ke

2011-09-01

We use a data set of 23 surface pollen samples from moss polsters in the Zoige Basin to explore the relationship between modern pollen assemblages and contemporary vegetation patterns. The surface pollen samples spanned four types of plant communities: Carex muliensis marsh, Stipa and Kobresia meadow, Carex-dominated forb meadow and Sibiraea angustata scrub. Principal-components analysis (PCA) was used to determine the relationships between modern pollen and vegetation and environmental variables. The results show that the pollen assemblages of surface moss samples generally reflect the features of the modern vegetation, basically similar in the vegetation types and the dominant genera; however, they don't show a very clear distinction between different communities. Our results also demonstrate that pollen representation of different families or genus varied. Some tree taxa, such as Pinus and Betula, and herb types, such as Artemisia are over-represented, while Asteraceae, Ranunculaceae and Cyperaceae are moderately represented, and Poaceae and Rosaceae are usually under-represented in our study region. PCA results indicate that the distribution of vegetation in the Zoige Basin is mainly controlled by precipitation and altitude.

Distance and environmental difference in alpine plant communities

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Fagre, Daniel B.

2017-01-01

Differences in plant communities are a response to the abiotic environment, species interactions, and dispersal. The role of geographic distance relative to the abiotic environment is explored for alpine tundra vegetation from 319 plots of four regions along the Rocky Mountain cordillera in the USA. The site by species data were ordinated using nonmetric multidimensional scaling to produce dependent variables for use in best-subsets regression. For independent variables, observations of local topography and microtopography were used as environmental indicators. Two methods of including distance in studies of vegetation and environment are used and contrasted. The relative importance of geographic distance in accounting for the pattern of alpine tundra similarity indicates that location is a factor in plant community composition. Mantel tests provide direct correlations between difference and distance but have known weaknesses. Moran spatial eigenvectors used in regression based approaches have greater geographic specificity, but require another step, ordination, in creating a vegetation variable. While the spatial eigenvectors are generally preferable, where species–environment relations are weak, as seems to be the case for the alpine sites studied here, the fewer abstractions of the Mantel test may be useful.

A national-scale remote sensing-based methodology for quantifying tidal marsh biomass to support "Blue Carbon" accounting

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Thomas, N.; Windham-Myers, L.; Castaneda, E.; Kroeger, K. D.; Gonneea, M. E.; O'Keefe Suttles, J.; Megonigal, P.; Troxler, T.; Schile, L. M.; Davis, M.; Woo, I.

2016-12-01

According to 2013 IPCC Wetlands Supplement guidelines, tidal marsh Tier 2 or Tier 3 accounting must include aboveground biomass carbon stock changes. To support this need, we are using free satellite and aerial imagery to develop a national scale, consistent remote sensing-based methodology for quantifying tidal marsh aboveground biomass. We are determining the extent to which additional satellite data will increase the accuracy of this "blue carbon" accounting. Working in 6 U.S. estuaries (Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA), we built a tidal marsh biomass dataset (n=2404). Landsat reflectance data were matched spatially and temporally with field plots using Google Earth Engine. We quantified percent cover of green vegetation, non-vegetation, and open water in Landsat pixels using segmentation of 1m National Agriculture Imagery Program aerial imagery. Sentinel-1A C-band backscatter data were used in Chesapeake, Mississippi Delta and Puget Sound. We tested multiple Landsat vegetation indices and Sentinel backscatter metrics in 30m scale biomass linear regression models by region. Scaling biomass by fraction green vegetation significantly improved biomass estimation (e.g. Cape Cod: R2 = 0.06 vs. R2 = 0.60, n=28). The best vegetation indices differed by region, though indices based on the shortwave infrared-1 and red bands were most predictive in the Everglades and the Mississippi Delta, while the soil adjusted vegetation index was most predictive in Puget Sound and Chesapeake. Backscatter metrics significantly improved model predictions over vegetation indices alone; consistently across regions, the most significant metric was the range in backscatter values within the green vegetation segment of the Landsat pixel (e.g. Mississippi Delta: R2 = 0.47 vs. R2 = 0.59, n=15). Results support using remote sensing of biomass stock change to estimate greenhouse gas emission factors in tidal wetlands.

VegScape: U.S. Crop Condition Monitoring Service

NASA Astrophysics Data System (ADS)

mueller, R.; Yang, Z.; Di, L.

2013-12-01

Since 1995, the US Department of Agriculture (USDA)/National Agricultural Statistics Service (NASS) has provided qualitative biweekly vegetation condition indices to USDA policymakers and the public on a weekly basis during the growing season. Vegetation indices have proven useful for assessing crop condition and identifying the areal extent of floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. With growing emphasis on more extreme weather events and food security issues rising to the forefront of national interest, a new vegetation condition monitoring system was developed. The new vegetation condition portal named VegScape was initiated at the start of the 2013 growing season. VegScape delivers web mapping service based interactive vegetation indices. Users can use an interactive map to explore, query and disseminate current crop conditions. Vegetation indices like Normal Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and mean, median, and ratio comparisons to prior years can be constructed for analytical purposes and on-demand crop statistics. The NASA MODIS satellite with 250 meter (15 acres) resolution and thirteen years of data history provides improved spatial and temporal resolutions and delivers improved detailed timely (i.e., daily) crop specific condition and dynamics. VegScape thus provides supplemental information to support NASS' weekly crop reports. VegScape delivers an agricultural cultivated crop mask and the most recent Cropland Data Layer (CDL) product to exploit the agricultural domain and visualize prior years' planted crops. Additionally, the data can be directly exported to Google Earth for web mashups or delivered via web mapping services for uses in other applications. VegScape supports the ethos of data democracy by providing free and open access to digital geospatial data layers using open geospatial standards, thereby supporting transparent and collaborative government initiatives. NASS developed VegScape in cooperation with the Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA. VegScape Ratio to Median NDVI

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Remote sensing captures varying temporal patterns of vegetation between human-altered and natural landscapes.

PubMed

Leong, Misha; Roderick, George K

2015-01-01

Global change has led to shifts in phenology, potentially disrupting species interactions such as plant-pollinator relationships. Advances in remote sensing techniques allow one to detect vegetation phenological diversity between different land use types, but it is not clear how this translates to other communities in the ecosystem. Here, we investigated the phenological diversity of the vegetation across a human-altered landscape including urban, agricultural, and natural land use types. We found that the patterns of change in the vegetation indices (EVI and NDVI) of human-altered landscapes are out of synchronization with the phenology in neighboring natural California grassland habitat. Comparing these findings to a spatio-temporal pollinator distribution dataset, EVI and NDVI were significant predictors of total bee abundance, a relationship that improved with time lags. This evidence supports the importance of differences in temporal dynamics between land use types. These findings also highlight the potential to utilize remote sensing data to make predictions for components of biodiversity that have tight vegetation associations, such as pollinators.

Assessment of heterogeneity in types of vegetables served by main household food preparers and food decision influencers.

PubMed

Yi, Sunghwan; Kanetkar, Vinay; Brauer, Paula

2015-10-01

While vegetables are often studied as one food group, global measures may mask variation in the types and forms of vegetables preferred by different individuals. To explore preferences for and perceptions of vegetables, we assessed main food preparers based on their preparation of eight specific vegetables and mushrooms. An online self-report survey. Ontario, Canada. Measures included perceived benefits and obstacles of vegetables, convenience orientation and variety seeking in meal preparation. Of the 4517 randomly selected consumers who received the invitation, 1013 responded to the survey (22·4 % response). Data from the main food preparers were analysed (n 756). Latent profile analysis indicated three segments of food preparers. More open to new recipes, the 'crucifer lover' segment (13 %) prepared and consumed substantially more Brussels sprouts, broccoli and asparagus than the other segments. Although similar to the 'average consumer' segment (54 %) in many ways, the 'frozen vegetable user' segment (33 %) used significantly more frozen vegetables than the other segments due to higher prioritization of time and convenience in meal preparation and stronger 'healthy=not tasty' perception. Perception of specific vegetables on taste, healthiness, ease of preparation and cost varied significantly across the three consumer segments. Crucifer lovers also differed with respect to shopping and cooking habits compared with the frozen vegetable users. The substantial heterogeneity in the types of vegetables consumed and perceptions across the three consumer segments has implications for the development of new approaches to promoting these foods.

A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China

PubMed Central

Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing

2016-01-01

Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs. PMID:27052108

Reconstructing vegetation response to altered hydrology and its use for restoration, Arthur R. Marshall Loxahatchee National Wildlife Refuge, Florida

USGS Publications Warehouse

Bernhardt, Christopher E.; Brandt, Laura A.; Landacre, Bryan D.; Marot, Marci E.; Willard, Debra A.

2013-01-01

We present reconstructed hydrologic and vegetation trends of the last three centuries across the Arthur R. Marshall Loxahatchee National Wildlife Refuge, Florida in order to understand the effects of 20th century water management. We analyzed pollen assemblages from cores at marsh sites along three transects to document vegetation and infer hydroperiod and water depth both before and after human alteration of Everglades hydrology. In the northern and central part of the Refuge, late Holocene water levels were higher and hydroperiods longer than the last 100 years. Post-1950 was a time of several different water management strategies. Pollen assemblages indicate drier conditions post-1950 in the northern and central parts of the Refuge, whereas sites in the southern Refuge are wetter and vegetation turnover is higher. Throughout the Refuge, Sagittaria pollen declines with the onset of water management, and may indicate a loss of greater variation in hydroperiods across years and water depths between seasons. Paleoecological evidence provides clear estimates of the vegetation response to hydrologic change under specific hydrologic regimes.

The role of cross-shore tidal dynamics in controlling intertidal sediment exchange in mangroves in Cù Lao Dung, Vietnam

NASA Astrophysics Data System (ADS)

Bryan, Karin R.; Nardin, William; Mullarney, Julia C.; Fagherazzi, Sergio

2017-09-01

Mangroves are halophytic plants common in tropical and sub-tropical environments. Their roots and pneumatophores strongly affect intertidal hydrodynamics and related sediment transport. Here, we investigate the role tree and root structures may play in altering tidal currents and the effect of these currents on the development of intertidal landscapes in mangrove-dominated environments. We use a one-dimensional Delft3D model, forced using typical intertidal slopes and vegetation characteristics from two sites with contrasting slope on Cù Lao Dung within the Mekong Delta in Vietnam, to examine the vegetation controls on tidal currents and suspended sediment transport as the tides propagate into the forest. Model results show that vegetation characteristics at the seaward fringe determine the shape of the cross-shore bottom profile, with sparse vegetation leading to profiles that are close to linear, whereas with dense vegetation resulting in a convex intertidal topography. Examples showing different profile developments are provided from a variety of published studies, ranging from linear profiles in sandier sites, and distinctive convex profiles in muddier sites. As expected, profile differences in the model are caused by increased dissipation due to enhanced drag caused by vegetation; however, the reduction of flow shoreward in sparsely vegetated or non-vegetated cases was similar, indicating that shallowing of the profile and slope effects play a dominant role in dissipation. Here, tidal velocities are measured in the field using transects of Acoustic Doppler Current Profilers, and confirm that cross-shore tidal currents diminish quickly as they move over the fringe of the forest; they then stay fairly consistent within the outer few 100 m of the forest, indicating that the fringing environment is likely a region of deposition. An understanding of how vegetation controls the development of topography is critical to predicting the resilience of these sensitive intertidal areas to changes in inundation caused by sea-level rise.

Analysis of Potential Deep-Seated Landslide in Hekeng Watershed by Environment Indices

NASA Astrophysics Data System (ADS)

Hsieh, C. J.; Chompuchan, C.

2014-12-01

Landslides are a major natural disaster in Taiwan relevant to the human life. After the catastrophic Xiaolin landslide during Typhoon Morakot in August 2009 caused around 400 casualties, the deep-seated landslide has become a serious issue. This study explored the potential deep-seated landslide in Hekeng watershed extracted from SPOT-5 imageries. The empirical topographic correction was applied to minimize effect of the mountain shaded area due to the difference of sun elevation and terrain angle. Consequently the multi-temporal environmental indices, i.e., modified Normalized Difference Vegetation Index (mNDVI) and modified Normalized Difference Water Index (mNDWI) were corrected. Seasonal vegetation cover and surface moisture change were analyzed incorporate with a slope which obtain from DEM data. The result showed that the distribution of potential deep-seated landslide vulnerable area mainly located at headstream watershed. It could be explained that the headstream watershed has less human interference, therefore the environmental indices interpreted those area as deep soil layer and dense vegetation coverage. However, the upstream canal could suffer from the long-term erosion and possibly cause slope toe collapse. In addition, the western watershed is the afforestation zone whereas the eastern watershed is natural forest zone with higher development ratio. The upslope forest management of eastern and western watershed should be discussed variously.

Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates

NASA Astrophysics Data System (ADS)

Sánchez-Ruiz, Sergio; Piles, María; Sánchez, Nilda; Martínez-Fernández, José; Vall-llossera, Mercè; Camps, Adriano

2014-08-01

Sensors in the range of visible and near-shortwave-thermal infrared regions can be used in combination with passive microwave observations to provide soil moisture maps at much higher spatial resolution than the original resolution of current radiometers. To do so, a new downscaling algorithm ultimately based on the land surface temperature (LST) - Normalized Difference Vegetation Index (NDVI) - Brightness Temperature (TB) relationship is used, in which shortwave infrared indices are used as vegetation descriptors, instead of the more common near infrared ones. The theoretical basis of those indices, calculated as the normalized ratio of the 1240, 1640 and 2130 nm shortwave infrared (SWIR) bands and the 858 nm near infrared (NIR) band indicate that they are able to provide estimates of the vegetation water content. These so-called water indices extracted from MODIS products, have been used together with MODIS LST, and SMOS TB to improve the spatial resolution of ∼40 km SMOS soil moisture estimates. The aim was to retrieve soil moisture maps with the same accuracy as SMOS, but at the same resolution of the MODIS dataset, i.e., 500 m, which were then compared against in situ measurements from the REMEDHUS network in Spain. Results using two years of SMOS and MODIS data showed a similar performance for the four indices, with slightly better results when using the index derived from the first SWIR band. For the areal-average, a coefficient of correlation (R) of ∼0.61 and ∼0.72 for the morning and afternoon orbits, respectively, and a centered root mean square difference (cRMSD) of ∼0.04 m3 m-3 for both orbits was obtained. A twofold improvement of the current versions of this downscaling approach has been achieved by using more frequent and higher spatial resolution water indexes as vegetation descriptors: (1) the spatial resolution of the resulting soil moisture maps can be enhanced from ∼40 km up to 500 m, and (2) more accurate soil moisture maps (in terms of R and cRMSD) can be obtained, especially in periods of high vegetation activity. The results of this study support the use of high resolution LST and SWIR-based vegetation indices to disaggregate SMOS observations down to 500 m soil moisture maps, meeting the needs of fine-scale hydrological applications.

Comparative validity of vitamin C and carotenoids as indicators of fruit and vegetable intake: a systematic review and meta-analysis of randomised controlled trials.

PubMed

Pennant, Mary; Steur, Marinka; Moore, Carmel; Butterworth, Adam; Johnson, Laura

2015-11-14

Circulating vitamin C and carotenoids are used as biomarkers of fruit and vegetable intake in research, but their comparative validity has never been meta-analysed. PubMed, EMBASE, CENTRAL, CINAHL and Web of Science were systematically searched up to December 2013 for randomised trials of different amounts of fruit and vegetable provision on changes in blood concentrations of carotenoids or vitamin C. Reporting followed PRISMA guidelines. Evidence quality was assessed using the GRADE system. Random effects meta-analysis combined estimates and meta-regression tested for sub-group differences. In all, nineteen fruit and vegetable trials (n 1382) measured at least one biomarker, of which nine (n 667) included five common carotenoids and vitamin C. Evidence quality was low and between-trial heterogeneity (I 2) ranged from 74% for vitamin C to 94 % for α-carotene. Groups provided with more fruit and vegetables had increased blood concentrations of vitamin C, α-carotene, β-carotene, β-cryptoxanthin and lutein but not lycopene. However, no clear dose-response effect was observed. Vitamin C showed the largest between-group difference in standardised mean change from the pre-intervention to the post-intervention period (smd 0·94; 95% CI 0·66, 1·22), followed by lutein (smd 0·70; 95% CI 0·37, 1·03) and α-carotene (smd 0·63; 95% CI 0·25, 1·01), but all CI were overlapping, suggesting that none of the biomarkers responded more than the others. Therefore, until further evidence identifies a particular biomarker to be superior, group-level compliance to fruit and vegetable interventions can be indicated equally well by vitamin C or a range of carotenoids. High heterogeneity and a lack of dose-response suggest that individual-level biomarker responses to fruit and vegetables are highly variable.

Vegetation survey in Amazonia using LANDSAT data. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Shimabukuro, Y. E.; Dossantos, J. R.; Deaquino, L. C. S.

1982-01-01

Automatic Image-100 analysis of LANDSAT data was performed using the MAXVER classification algorithm. In the pilot area, four vegetation units were mapped automatically in addition to the areas occupied for agricultural activities. The Image-100 classified results together with a soil map and information from RADAR images, permitted the establishment of the final legend with six classes: semi-deciduous tropical forest; low land evergreen tropical forest; secondary vegetation; tropical forest of humid areas, predominant pastureland and flood plains. Two water types were identified based on their sediments indicating different geological and geomorphological aspects.

Coverage-dependent amplifiers of vegetation change on global water cycle dynamics

NASA Astrophysics Data System (ADS)

Feng, Huihui; Zou, Bin; Luo, Juhua

2017-07-01

The terrestrial water cycle describes the circulation of water worldwide from one store to another via repeated evapotranspiration (E) from land and precipitation (P) back to the surface. The cycle presents significant spatial variability, which is strongly affected by natural climate and anthropogenic influences. As one of the major anthropogenic influences, vegetation change unavoidably alters surface property and subsequent the terrestrial water cycle, while its contribution is yet difficult to isolate from the mixed influences. Here, we use satellite and in-situ datasets to identify the terrestrial water cycle dynamics in spatial detail and to evaluate the impact of vegetation change. Methodologically, the water cycle is identified by the indicator of difference between evapotranspiration and precipitation (E-P). Then the scalar form of the indicator's trend (ΔE + ΔP) is used for evaluating the dynamics of water cycle, with the positive value means acceleration and negative means deceleration. Then, the contributions of climate and vegetation change are isolated by the trajectory-based method. Our results indicate that 4 accelerating and 4 decelerating water cycles can be identified, affecting 42.11% of global land. The major water cycle type is characterized by non-changing precipitation and increasing evapotranspiration (PNO-EIN), which covers 20.88% of globally land. Vegetation change amplifies both accelerating and decelerating water cycles. It tends to intensify the trend of the decelerating water cycles, while climate change weakens the trend. In the accelerating water cycles, both vegetation and climate change present positive effect to intensify the trend. The effect of plant cover change varies with the coverage. In particular, vegetation change intensifies the water cycle in moderately vegetated regions (0.1 < NDVI < 0.6), but weakens the cycle in sparsely or highly vegetated regions (NDVI < 0.1 or 0.6 < NDVI < 0.8). In extremely vegetated regions (NDVI > 0.85), the water cycle is accelerated because of the significant increase of precipitation. We conclude that vegetation change acts as an amplifier for both accelerating and decelerating terrestrial water cycles, depending on the degree of vegetation coverage.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest.

PubMed

Sitters, Holly; York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest

PubMed Central

York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD. PMID:27741290

Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

NASA Astrophysics Data System (ADS)

Wong, C. Y.; Arain, M. A.; Ensminger, I.

2016-12-01

Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

[Responses of normalized difference vegetation index (NDVI) to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015.

PubMed

Wang, Zhi Peng; Zhang, Xian Zhou; He, Yong Tao; Li, Meng; Shi, Pei Li; Zu, Jia Xing; Niu, Ben

2018-01-01

Precipitation change is an important factor in the inter-annual variation of grassland growth on the Tibetan Plateau. The total amount, distribution pattern and concentration time are three basic characteristics of precipitation change. The temporal and spatial characteristics of precipitation change were analyzed based on climate data of 145 meteorological stations on the Tibetan Plateau and nearby areas from 2000 to 2015. The total precipitation amount was characterized by annual precipitation, distribution pattern of precipitation during the year was characterized by improved precipitation concentration index (PCI), and precipitation centroid (PC) was defined to indicate the change in precipitation concentrated time. To better illustrate the response of grassland to precipitation change, vegetation growth status was characterized by the maximum value of normalized difference vegetation index (NDVI max ). Results indicated that the annual precipitation and PCI had an apparent gradient across the whole plateau and the latest PC occurred in the southern plateau. NDVI max of alpine shrub grassland was significantly correlated with the change of PCI,increased with even distribution of precipitation during growth period, and limited by the total annual precipitation. Alpine meadow did not show significantly correlations with these three indices. The inter-annual variability of NDVI max of steppe was controlled by both PCI and PC. NDVI max of alpine desert grassland was mainly controlled by annual precipitation. In addition to annual total amount of precipitation, the distribution characteristics of precipitation should be further considered when the influence of precipitation change on different types of vegetation on the Qinghai Tibet Plateau was studied.

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production

PubMed Central

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-01-01

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm−2), leaf area index (RMSE = 0.67 m2·m−2), canopy chlorophyll (RMSE = 0.24 g·m−2) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm−2, 0.85 m2·m−2, 0.28 g·m−2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CIg provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system. PMID:28629159

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production.

PubMed

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-06-18

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm -2 ), leaf area index (RMSE = 0.67 m²·m -2 ), canopy chlorophyll (RMSE = 0.24 g·m -2 ) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm -2 , 0.85 m²·m -2 , 0.28 g·m -2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CI g provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system.

A special vegetation index for the weed detection in sensor based precision agriculture.

PubMed

Langner, Hans-R; Böttger, Hartmut; Schmidt, Helmut

2006-06-01

Many technologies in precision agriculture (PA) require image analysis and image- processing with weed and background differentiations. The detection of weeds on mulched cropland is one important image-processing task for sensor based precision herbicide applications. The article introduces a special vegetation index, the Difference Index with Red Threshold (DIRT), for the weed detection on mulched croplands. Experimental investigations in weed detection on mulched areas point out that the DIRT performs better than the Normalized Difference Vegetation Index (NDVI). The result of the evaluation with four different decision criteria indicate, that the new DIRT gives the highest reliability in weed/background differentiation on mulched areas. While using the same spectral bands (infrared and red) as the NDVI, the new DIRT is more suitable for weed detection than the other vegetation indices and requires only a small amount of additional calculation power. The new vegetation index DIRT was tested on mulched areas during automatic ratings with a special weed camera system. The test results compare the new DIRT and three other decision criteria: the difference between infrared and red intensity (Diff), the soil-adjusted quotient between infrared and red intensity (Quotient) and the NDVI. The decision criteria were compared with the definition of a worse case decision quality parameter Q, suitable for mulched croplands. Although this new index DIRT needs further testing, the index seems to be a good decision criterion for the weed detection on mulched areas and should also be useful for other image processing applications in precision agriculture. The weed detection hardware and the PC program for the weed image processing were developed with funds from the German Federal Ministry of Education and Research (BMBF).

Tropical forest plantation biomass estimation using RADARSAT-SAR and TM data of south china

NASA Astrophysics Data System (ADS)

Wang, Chenli; Niu, Zheng; Gu, Xiaoping; Guo, Zhixing; Cong, Pifu

2005-10-01

Forest biomass is one of the most important parameters for global carbon stock model yet can only be estimated with great uncertainties. Remote sensing, especially SAR data can offers the possibility of providing relatively accurate forest biomass estimations at a lower cost than inventory in study tropical forest. The goal of this research was to compare the sensitivity of forest biomass to Landsat TM and RADARSAT-SAR data and to assess the efficiency of NDVI, EVI and other vegetation indices in study forest biomass based on the field survey date and GIS in south china. Based on vegetation indices and factor analysis, multiple regression and neural networks were developed for biomass estimation for each species of the plantation. For each species, the better relationships between the biomass predicted and that measured from field survey was obtained with a neural network developed for the species. The relationship between predicted and measured biomass derived from vegetation indices differed between species. This study concludes that single band and many vegetation indices are weakly correlated with selected forest biomass. RADARSAT-SAR Backscatter coefficient has a relatively good logarithmic correlation with forest biomass, but neither TM spectral bands nor vegetation indices alone are sufficient to establish an efficient model for biomass estimation due to the saturation of bands and vegetation indices, multiple regression models that consist of spectral and environment variables improve biomass estimation performance. Comparing with TM, a relatively well estimation result can be achieved by RADARSAT-SAR, but all had limitations in tropical forest biomass estimation. The estimation results obtained are not accurate enough for forest management purposes at the forest stand level. However, the approximate volume estimates derived by the method can be useful in areas where no other forest information is available. Therefore, this paper provides a better understanding of relationships of remote sensing data and forest stand parameters used in forest parameter estimation models.

A Study toward the Evaluation of ALOS Images for LAI Estimation in Rice Fields

NASA Astrophysics Data System (ADS)

Sharifi Hashjin, Sh.; Darvishzadeh, R.; Khandan, R.

2013-10-01

For expanding and managing agricultural sources, satellite data have a key role in determining required information about different factors in plants Including Leaf Area Index (LAI).This paper has studied the potential of spectral indices in estimating rice canopy LAI in Amol city as one of the main sources of rice production in Iran. Due to its importance in provision of food and calorie of a major portion of population, rice product was chosen for study. A field campaign was conducted when rice was in the max growth stage (late of June). Also, two satellite images from ALOS-AVNIR-2 were used (simultaneous with conducted field works) to extract and determine vegetation indices. Then the Regression between measured data and vegetation indices, derived from combination of different bands, was evaluated and after that suitable vegetation indices were realized. Finally, statistics and calculations for introduction of a suitable model were presented. After examination of models, the results showed that RDVI and SAVI2, by determination coefficient and RMSE of 0.12-0.59 and 0.24-0.62, have more accuracy in LAI estimation. Results of present study demonstrated the potential of ALOS images, for LAI estimation and their significant role in monitoring and managing the rice plant.

Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators

NASA Astrophysics Data System (ADS)

Gouveia, C. M.; Trigo, R. M.; Beguería, S.; Vicente-Serrano, S. M.

2017-04-01

The present work analyzes the drought impacts on vegetation over the entire Mediterranean basin, with the purpose of determining the vegetation communities, regions and seasons at which vegetation is driven by drought. Our approach is based on the use of remote sensing data and a multi-scalar drought index. Correlation maps between fields of monthly Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at different time scales (1-24 months) were computed for representative months of winter (Feb), spring (May), summer (Aug) and fall (Nov). Results for the period from 1982 to 2006 show large areas highly controlled by drought, although presenting high spatial and seasonal differences, with a maximum influence in August and a minimum in February. The highest correlation values are observed in February for 3 months' time scale and in May for 6 and 12 months. The higher control of drought on vegetation in February and May is obtained mainly over the drier vegetation communities (Mediterranean Dry and Desertic) at shorter time scales (3 to 9 months). Additionally, in February the impact of drought on vegetation is lower for Temperate Oceanic and Continental vegetation types and takes place at longer time scales (18-24). The dependence of drought time-scale response with water balance, as obtained through a simple difference between precipitation and reference evapotranspiration, varies with vegetation communities. During February and November low water balance values correspond to shorter time scales over dry vegetation communities, whereas high water balance values implies longer time scales over Temperate Oceanic and Continental areas. The strong control of drought on vegetation observed for Mediterranean Dry and Desertic vegetation types located over areas with high negative values of water balance emphasizes the need for an early warning drought system covering the entire Mediterranean basin. We are confident that these results will provide a useful tool for drought management plans and play a relevant role in mitigating the impact of drought episodes.

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Quantification of dead vegetation fraction in mixed pastures using AisaFENIX imaging spectroscopy data

NASA Astrophysics Data System (ADS)

Pullanagari, R. R.; Kereszturi, G.; Yule, I. J.

2017-06-01

New Zealand farming relies heavily on grazed pasture for feeding livestock; therefore it is important to provide high quality palatable grass in order to maintain profitable and sustainable grassland management. The presence of non-photosynthetic vegetation (NPV) such as dead vegetation in pastures severely limits the quality and productivity of pastures. Quantifying the fraction of dead vegetation in mixed pastures is a great challenge even with remote sensing approaches. In this study, a high spatial resolution with pixel resolution of 1 m and spectral resolution of 3.5-5.6 nm imaging spectroscopy data from AisaFENIX (380-2500 nm) was used to assess the fraction of dead vegetation component in mixed pastures on a hill country farm in New Zealand. We used different methods to retrieve dead vegetation fraction from the spectra; narrow band vegetation indices, full spectrum based partial least squares (PLS) regression and feature selection based PLS regression. Among all approaches, feature selection based PLS model exhibited better performance in terms of prediction accuracy (R2CV = 0.73, RMSECV = 6.05, RPDCV = 2.25). The results were consistent with validation data, and also performed well on the external test data (R2 = 0.62, RMSE = 8.06, RPD = 2.06). In addition, statistical tests were conducted to ascertain the effect of topographical variables such as slope and aspect on the accumulation of the dead vegetation fraction. Steep slopes (>25°) had a significantly (p < 0.05) higher amount of dead vegetation. In contrast, aspect showed non-significant impact on dead vegetation accumulation. The results from the study indicate that AisaFENIX imaging spectroscopy data could be a useful tool for mapping the dead vegetation fraction accurately.

Vegetation monitoring and classification using NOAA/AVHRR satellite data

NASA Technical Reports Server (NTRS)

Greegor, D. H., Jr.; Norwine, J. R.

1983-01-01

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

[Variation of soil organic carbon under different vegetation types in Karst Mountain areas of Guizhou Province, southwest China].

PubMed

Liao, Hong-kai; Long, Jian

2011-09-01

This paper studied the variation characteristics of soil organic carbon (SOC) and different particle sizes soil particulate organic carbon (POC) in normal soil and in micro-habitats under different vegetation types in typical Karst mountain areas of southwest Guizhou. Under different vegetation types, the SOC content in normal soil and in micro-habitats was all in the order of bare land < grass < shrub < forest, with the variation range being 7.18-43.42 g x kg(-1) in normal soil and being 6.62-46.47 g x kg(-1) and 9.01-52.07 g x kg(-1) in earth surface and stone pit, respectively. The POC/MOC (mineral-associated organic carbon) ratio under different vegetation types was in the order of bare land < grass < forest < shrub. Under the same vegetation types, the POC/MOC in stone pit was the highest, as compared to that in normal soil and in earth surface. In the process of bare land-grass-shrub-forest, the contents of different particle sizes soil POC increased, while the SOC mainly existed in the forms of sand- and silt organic carbon, indicating that in Karst region, soil carbon sequestration and SOC stability were weak, soil was easily subjected to outside interference and led to organic carbon running off, and thus, soil quality had the risk of decline or degradation.

High spatial resolution WorldView-2 imagery for mapping NDVI and its relationship to temporal urban landscape evapotranspiration factors

USGS Publications Warehouse

Nouri, Hamideh; Beecham, Simon; Anderson, Sharolyn; Nagler, Pamela

2014-01-01

Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET) and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences) was selected. Normalized Difference Vegetation Index (NDVI) values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January 2013 decreased the correlation between ET and NDVI with the highest relationship of ET-Landscape NDVI (Landscape Normalized Difference Vegetation Index) for shrubs (r2 = 0.66) and trees (r2 = 0.63). However, when the January data was excluded, there was a significant correlation between ET and NDVI. The highest correlation for ET-Landscape NDVI was found for the entire Veale Gardens regardless of vegetation type (r2 = 0.95, p > 0.05) and the lowest one was for turf (r2 = 0.88, p > 0.05). In support of the feasibility of ET estimation by WV2 over a longer period, an algorithm recently developed that estimates evapotranspiration rates based on the Enhanced Vegetation Index (EVI) from MODIS was employed. The results revealed a significant positive relationship between ETMODIS and ETWV2 (r2 = 0.9857, p > 0.05). This indicates that the relationship between NDVI using high resolution WorldView-2 imagery and ground-based validation approaches could provide an effective predictive tool for determining ET rates from unstressed mixed urban landscape plantings.

Vegetation Coverage Mapping and Soil Effect Correction in Estimating Vegetation Water Content and Dry Biomass from Satellites

NASA Astrophysics Data System (ADS)

Huang, J.; Chen, D.

2005-12-01

Vegetation water content (VWC) attracts great research interests in hydrology research in recent years. As an important parameter describing the horizontal expansion of vegetation, vegetation coverage is essential to implement soil effect correction for partially vegetated fields to estimate VWC accurately. Ground measurements of corn and soybeans in SMEX02 resulted in an identical expolinear relationship between vegetation coverage and leaf area index (LAI), which is used for vegetation coverage mapping. Results illustrated two parts of LAI growth quantitatively: the horizontal expansion of leaf coverage and the vertical accumulation of leaf layers. It is believed that the former part contributes significantly to LAI growth at initial vegetation growth stage and the latter is more dominant after vegetation coverage reaches a certain level. The Normalized Difference Water Index (NDWI) using short-wave infrared bands is convinced for its late saturation at high LAI values, in contrast to the Normalized Difference Vegetation Index (NDVI). NDWI is then utilized to estimate LAI, via another expolinear relationship, which is evidenced having vegetation species independency in study of corn and soybeans in SMEX02 sites. It is believed that the surface reflectance measured at satellites spectral bands are the mixed results of signals reflected from vegetation and bare soil, especially at partially vegetated fields. A simple linear mixture model utilizing vegetation coverage information is proposed to correct soil effect in such cases. Surface reflectance fractions for -rpure- vegetation are derived from the model. Comparing with ground measurements, empirical models using soil effect corrected vegetation indices to estimate VWC and dry biomass (DB) are generated. The study enhanced the in-depth understanding of the mechanisms how vegetation growth takes effect on satellites spectral reflectance with and without soil effect, which are particularly useful for modeling in hydrology, agriculture, forestry and meteorology etc.

Vegetation spatial variability and its effect on vegetation indices

NASA Technical Reports Server (NTRS)

Ormsby, J. P.; Choudhury, B. J.; Owe, M.

1987-01-01

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Relationships between woody vegetation and geomorphological patterns in three gravel-bed rivers with different intensities of anthropogenic disturbance

NASA Astrophysics Data System (ADS)

Sitzia, T.; Picco, L.; Ravazzolo, D.; Comiti, F.; Mao, L.; Lenzi, M. A.

2016-07-01

We compared three gravel-bed rivers in north-eastern Italy (Brenta, Piave, Tagliamento) having similar bioclimate, geology and fluvial morphology, but affected by different intensities of anthropogenic disturbance related particularly to hydropower dams, training works and instream gravel mining. Our aim was to test whether a corresponding difference in the interactions between vegetation and geomorphological patterns existed among the three rivers. In equally spaced and sized plots (n = 710) we collected descriptors of geomorphic conditions, and presence-absence of woody species. In the less disturbed river (Tagliamento), spatial succession of woody communities from the floodplain to the channel followed a profile where higher elevation floodplains featured more developed tree communities, and lower elevation islands and bars were covered by pioneer communities. In the intermediate-disturbed river (Piave), islands and floodplains lay at similar elevation and both showed species indicators of mature developed communities. In the most disturbed river (Brenta), all these patterns were simplified, all geomorphic units lay at similar elevations, were not well characterized by species composition, and presented similar persistence age. This indicates that in human-disturbed rivers, channel and vegetation adjustments are closely linked in the long term, and suggests that intermediate levels of anthropogenic disturbance, such as those encountered in the Piave River, could counteract the natural, more dynamic conditions that may periodically fragment vegetated landscapes in natural rivers.

Controls on vegetation structure in Southwestern ponderosa pine forests, 1941 and 2004.

PubMed

Bakker, Jonathan D; Moore, Margaret M

2007-09-01

Long-term studies can broaden our ecological understanding and are particularly important when examining contingent effects that involve changes to dominance by long-lived species. Such a change occurred during the last century in Southwestern (USA) ponderosa pine (Pinus ponderosa) forests. We used five livestock grazing exclosures established in 1912 to quantify vegetation structure in 1941 and 2004. Our objectives were to (1) assess the effects of historical livestock grazing on overstory structure and age distribution, (2) assess the effects of recent livestock grazing and overstory on understory vegetation, and (3) quantify and explain changes in understory vegetation between 1941 and 2004. In 1941, canopy cover of tree regeneration was significantly higher inside exclosures. In 2004, total tree canopy cover was twice as high, density was three times higher, trees were smaller, and total basal area was 40% higher inside exclosures. Understory species density, herbaceous plant density, and herbaceous cover were negatively correlated with overstory vegetation in both years. Most understory variables did not differ between grazing treatments in 1941 but were lower inside exclosures in 2004. Differences between grazing treatments disappeared once overstory effects were accounted for, indicating that they were due to the differential overstory response to historical livestock grazing practices. Between 1941 and 2004, species density declined by 34%, herbaceous plant density by 37%, shrub cover by 69%, total herbaceous cover by 59%, graminoid cover by 39%, and forb cover by 82%. However, these variables did not differ between grazing treatments or years once overstory effects were accounted for, indicating that the declines were driven by the increased dominance of the overstory during this period. Our results demonstrate that historical livestock grazing practices are an aspect of land-use history that can affect ecosystem development. Grazing history must be considered when extrapolating results from one site to another. In addition, the understory vegetation was more strongly controlled by the ponderosa pine overstory than by recent livestock grazing or by temporal dynamics, indicating that overstory effects must be accounted for when examining understory responses in this ecosystem.

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Measuring pasture degradation on the Qinghai-Tibet Plateau using hyperspectral dissimilarities and indices

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Bendix, Jörg

2013-10-01

Despite that relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. However, livestock grazing is widely accepted as a major factor. This study investigated spectral differences of vegetation patterns along gradients of grazing intensities using plot-based hyperspectral measurements. The measurements were used to define spectral indicators for pasture degradation, which were applied to map asserted proxies for degradation from satellite images. For this purpose, hyperspectral measurements were taken at 11 sites on the north-eastern QTP using a transect design from heavy grazing and therefore asserted degradation near the settlement to less degradation with increasing distance. Potential spectral indicators for degradation were derived from the spectra by calculating the size of continuum removed absorption features and narrow-band indices (NBI). They were compared between degraded and less degraded plots. Linear regressions between proxies and each of the potential spectral indicators were calculated to assess its predictive power. The findings were transferred to larger scales by applying the indicators on two WorldView-2 (WV-2) scenes. Spectral differences between degraded and less degraded plots were obvious regarding a wide range of tested indicators. Several NBIs were considered as good indicators for vegetation cover and species numbers. WV-2 images could be successfully classified into vegetation cover whilst the estimation of species numbers was afflicted with uncertainties. The results demonstrate the potential to estimate degradation proxies using spectrometer measurements and satellite data. Applying these techniques will contribute to a better estimation of spatial degradation patterns on the QTP.

Remote sensing techniques for monitoring drought hazards: an intercomparison (Invited)

NASA Astrophysics Data System (ADS)

Brown, J. F.; Anderson, M. C.; Wardlow, B. D.; Svoboda, M. D.

2009-12-01

Drought events are frequently described using many different terms; for example, recurring climate phenomena, creeping natural hazards, agricultural disasters, and moisture deficiencies. In addition, droughts operate at many different spatial and temporal scales and affect different societal sectors, making them quite challenging to monitor, map, and assess impacts. Because of these factors, determining drought severity often requires using a convergence of evidence assisted by an analysis of multiple drought indicators. Frequent optical and thermal observations collected by daily polar-orbiting and geostationary satellites allow for regular monitoring of the land surface. In recent decades, with the launching of more advanced sensors and the maturation of remote sensing techniques, a variety of tools have been designed for improved understanding and tracking of drought events as they are occurring. These applications are intended to provide key decision makers with timely geospatial drought information to support various drought planning and mitigation activities. Two such tools highlighted in this study, are the Vegetation Drought Response Index (VegDRI) and the Evaporative Stress Index (ESI). While both indices incorporate satellite-based inputs, they are involved in different modeling approaches and observations from different parts of the electromagnetic spectrum. The VegDRI is a hybrid remote sensing and climate based indicator of drought-induced vegetation stress that combines satellite-based vegetation index observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors with climate-based drought index data and other biophysical parameters (such as land use/land cover type and soil characteristics). VegDRI provides near real-time vegetation drought severity information at relatively higher spatial resolution (1-km2) than traditional climatic drought indices such as the Standardized Precipitation Index (SPI) or the U.S. Drought Monitor (USDM), which tend to depicted broad-scale spatial drought patterns. . The ESI is an indicator of anomalous land-surface evaporation and soil moisture deficiency. The ESI is related to the ratio of actual-to-potential evapotranspiration (ET), where actual ET is estimated with a thermal-infrared (TIR) based surface energy balance algorithm. The ESI product is generated in near-real time at 10-km2 resolution over the continental U.S. using TIR imagery from the Geostationary Operational Environmental Satellites (GOES). Because it does not use precipitation data as an input, it is a valuable complement to existing precipitation-based indices and is readily portable to data-poor regions with sparse ground-based rainfall monitoring networks. In this study, we present an intercomparison of the VegDRI and the ESI for the 2009 growing season, highlighting weekly, monthly, and seasonal patterns of moisture flux from soils and vegetation.

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions.

PubMed

Krishnaswamy, Jagdish; John, Robert; Joseph, Shijo

2014-01-01

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan-tropical belt (30°N-30°S). We analyzed decadal-scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982-2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid-1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time-dependent regression parameters to study the time evolution of NDVI-climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature-induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global-scale effects of climate warming and associated moisture stresses. © 2013 John Wiley & Sons Ltd.

Physical and chemical properties of young soils of the Icelandic highlands

NASA Astrophysics Data System (ADS)

Gísladóttir, Guðrún; Mankasingh, Utra

2015-04-01

Most of the Icelandic soils are of volcanic origin, classified as andisols (carbon content 1-12%), many of which are strongly affected by erosion and so, formation of new soils is of great interest. The effect of land cover type on the weathering patterns and the formation of new soils are of interest. The southern Icelandic highlands are characterised by harsh climate, shallow soils and limited vegetation cover. We hypothesise that in the highland regions of Iceland the progression of land cover from unvegetated to vegetated sites will impact soil development. This study describes the physical and chemical properties of highland soils in Iceland. Soil samples were collected from 12 sites in September 2013, nine sites were fully vegetated and three unvegetated: grassland (G1-G8), with moss, Carex Bigelowii and dwarf shrubs, sandy fluvial wetland (S) and unvegetated gravels (M1-M3). All soils with vegetative cover were characterized by weak or structureless soil ranging in texture from loamy sand to silty clay loam, while at unvegetated sites soil texture was structureless and sandy. On average, the bulk density of soils (range 0.53 - 1.16 g cm-3) were lower at vegetated sites than unvegetated sites. The soil depth is greater in the vegetated sites, indicating greater soil development. The average % carbon (%C), % nitrogen (%N), overall % soil organic matter (%SOM), of vegetated sites were higher than for unvegetated sites, indicating the difference in soil development: vegetated sites (mean), 1.60%C, 0.10%N, 4.9%SOM; unvegetated sites (mean), 0.27%C, 0.02%N, 1.81%SOM. All soils had significant amounts of amorphous clay minerals such as allophone, imogolite, ferrihydrite or aluminium-humus complexes and also high aluminium and iron percentages, and high phosphate retention. All of which are characteristic for andisols. There were strong associations between Fe and Al and the soil C, which are indicative of Al and Fe complexed with humus or allophane and ferrihydrite clays. The allophane and ferrihydrite content was 3.5-7.7% and 2.4-5.3%, respectively. The soils in the study had a high clay content, generally greater than 10% for all soil types. However, selective dissolutions with oxalate and with pyrophosphate indicate that more organic carbon was associated with the Fe and Al of vegetated sites than observed for the vegetated sites. These results also indicate more organic associations in sites with vascular plants and mosses vs mosses only. The %C, %SOM, Fe/Al associations, soil structure and soil depth all indicate that there is gradient of increasing soil genesis form unvegetated to vegetated sites, with evidence of greater organic associations in sites with vascular plants. Even though the soils at the vegetated sites are andisols, they are still immature , while the less developed soils at the unvegetated sites are vitrisols (

Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Caballero, Isabel; Silva, Gustavo; Parra, Pedro-Cecilio; Vázquez, Águeda; Caldeira, Rui

2017-06-01

A forest fire started on August 8th, 2016 in several places on Madeira Island causing damage and casualties. As of August 10th the local media had reported the death of three people, over 200 people injured, over 950 habitants evacuated, and 50 houses damaged. This study presents the preliminary results of the assessment of several spectral indices to evaluate the burn severity of Madeira fires during August 2016. These spectral indices were calculated using the new European satellite Sentinel-2A launched in June 2015. The study confirmed the advantages of several spectral indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVIreXn) using red-edge spectral bands to assess the post-fire conditions. Results showed high correlation between NDVI, GNDVI, NBR and NDVIre1n spectral indices and the analysis performed by Copernicus Emergency Management Service (EMSR175), considered as the reference truth. Regarding the red-edge spectral indices, the NDVIre1n (using band B5, 705 nm) presented better results compared with B6 (740 nm) and B7 (783 nm) bands. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for post-fire monitoring. In the future, the two twin Sentinel-2 satellites will offer global coverage of the Madeira Archipelago every five days, therefore allowing the simultaneous study of the evolution of the burnt area and reforestation information with high spatial (up to 10 m) and temporal resolution (5 days).

Site-specific diel mercury emission fluxes in landfill: Combined effects of vegetation and meteorological factors.

PubMed

Liu, Yang; Wu, Boran; Hao, Yongxia; Zhu, Wei; Li, Zhonggen; Chai, Xiaoli

2017-01-01

Mercury emission fluxes (MEFs) under different surface coverage conditions in a landfill were investigated in this study. The results show similar diel patterns of Hg emission flux under different coverage conditions, with peak fluxes occurring at midday and decreasing during night. We examined the effects of environmental factors on MEFs, such as the physiological characteristics of vegetation and meteorological conditions. The results suggest that growth of vegetation in the daytime facilitates the release of Hg in the anaerobic unit, while in the semi-aerobic unit, where vegetation had been removed, the higher mercury content of the cover soil prompted the photo-reduction pathway to become the main path of mercury release and increased MEFs. MEFs are positively correlated with solar radiation and air temperature, but negatively correlated with relative humidity. The correlation coefficients for MEFs with different environmental parameters indicate that in the anaerobic unit, solar radiation was the main influence on MEFs in September, while air temperature became the main determining factor in December. These observations suggest that the effects of meteorological conditions on the mercury release mechanism varies depending on the vegetation and soil pathways. Copyright © 2016. Published by Elsevier Ltd.

Humidification of the Arctic: Effects of more open ocean water on land temperatures and tundra productivity along continental and maritime bioclimate transects

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Epstein, H. E.

2017-12-01

Amplified Arctic warming linked to declining sea-ice extent led to generally enhanced productivity of the tundra biome during the period 1982-2008. After about 2002, coinciding with a recent precipitous decline in sea ice, large areas of the Arctic began showing reversals of previous positive productivity trends. To better understand these recent vegetation productivity declines and whether they are associated with differences in a general humidification of portions of the Arctic, we focus analysis on two transects with ground information: the more continental North America Arctic Transect (NAAT) and the more maritime Eurasia Arctic Transect (EAT). We compare ground information with satellite-derived trends in open water, summer terrestrial temperatures, and vegetation greenness and changes in continentality of the two transects, as indicated by the differences in the annual maximum and minimum mean monthly temperatures. Areas adjacent to perennial sea ice along in the northern parts of the NAAT exhibit climates with positive trends in summer warmth, but negative greening trends, possibly due to soil drying. Southern parts of the NAAT in the vicinity of more open water show positive greenness trends. Along the EAT, cooling midsummer conditions and reduced greenness appear to be caused by cloudier conditions, and possibly later snow melt during the period of maximum potential photosynthesis. Ground-based environmental and vegetation data indicate that biomass, particularly moss biomass is much greater along the more maritime EAT, indicating a buffering effect of the vegetation that will act to damp productivity as humidification of the Arctic proceeds. This multi-scale analysis is one step in the direction of understanding the drivers of tundra vegetation productivity in the Arctic.

Remote Estimation of Vegetation Fraction and Yield in Oilseed Rape with Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Peng, Y.; Fang, S.; Liu, K.; Gong, Y.

2017-12-01

This study developed an approach for remote estimation of Vegetation Fraction (VF) and yield in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV) when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI) vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate Flower Fraction (FF) in oilseed rape. Based on FF estimates, rape yield can be estimated using canopy reflectance data. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with estimation error below 6% and predict yield with estimation error below 20%.

Comparison of vegetation conditions along two backcountry trails in Mount Robson Provincial Park, British Columbia (Canada).

PubMed

Nepal, Sanjay K; Way, Paul

2007-01-01

Vegetation conditions, i.e., plant cover, species richness, and the presence of exotic species, are compared along a high-use trail (Berg Lake Trail--BLT) and a low use trail (Mt. Fitzwilliam Trail--FWT) in Canada's Mt. Robson Provincial Park. We established 71 paired quadrats (1 m x 1 m), and assessed the amount of vegetation cover and species richness by four main lifeforms, i.e., woody species, herbaceous species, ferns, and moss, lichen and fungi. The following hypotheses were tested: (1) differences exist between control and trailside quadrats in vegetation cover, species richness and floristic diversity, and (2) differences exist between the high and low-use trails in the above-mentioned three parameters. Results show that for the majority of variables the differences between the control and trailside quadrats are statistically not significant. Variables showing significant differences are relative vegetation cover (for BLT only), exposed soil (BLT and FWT), herbaceous cover (FWT), moss, lichen and fungi cover (BLT), overall species richness (BLT), and herbaceous species richness (BLT). Ruderal and exotic species are present but only on trailside quadrats of the high-use trail. Results indicate that the Park administration's strategy to disperse use in the Mt. Robson Provincial Park should be examined critically, and some guidelines for acceptability of changes should be developed.

Recovery of perennial vegetation in military target sites in the eastern Mohave Desert, Arizona

USGS Publications Warehouse

Steiger, John W.; Webb, Robert H.

2000-01-01

The effect of the age of geomorphic surfaces on the recovery of desert vegetation in military target sites was studied in the Mohave and Cerbat Mountains of northwestern Arizona. The target sites were cleared of all vegetation during military exercises in 1942-1943 and have not been subsequently disturbed. The degree of recovery was measured by calculating percentage-similarity (PS) and correlation-coefficient indices on the basis of differences in cover, density, and volume of species growing in and out of each target site. PS values, ranging from 22.7 to 95.1 percent (100 percent = identical composition), indicate a wide range of recovery that is partially controlled by the edaphic properties of the geomorphic surfaces. Statistical analyses show a strong pattern that indicates a greater variability in the degree of recovery for sites on older surfaces than on younger surfaces and a weak pattern that indicates an inverse relation between the degree of recovery and geomorphic age. Comparisons of the different effects of target site construction on the edaphic characteristics of each target site provides an explanation for these patterns and suggests the soil properties critical to the recovery process. Statistically significant negative or positive response to disturbance for most species are independent of the age of the geomorphic surfaces; however, there is strong evidence for a shift in response for the common perennial species Acamptopappus sphaerocephalus, and to a lesser extent, Salazaria mexicana, Encelia farinosa, and Coldenia canescens, among different geomorphic surfaces.

Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

NASA Astrophysics Data System (ADS)

Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

2016-12-01

Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (<1 m) and land cover features such as substrate exposure that may affect estimates of vegetation structure in satellite data. Yet it is unclear how differences in spatial and spectral resolution between UAS and satellite data affect their relationships to each other, and to common field measurements of leaf area (e.g. LiCOR photosensors) and land cover. Constraining these relationships is important for leveraging UAS data to improve scaling of field data on leaf area and biomass to satellite data from Landsat, Sentinel-2, and increasing numbers of commercial sensors. Here, we quantify relationships among field, UAS and satellite estimates of vegetation leaf area and biomass in three case study landscapes spanning semi-arid Mediterranean (Matera, Southern Italy and Mallorca, Spain) and North American temperate ecosystems (New Jersey, USA). We assess how land cover and sensor spectral characteristics affect UAS and satellite-derived NDVI, leaf-area and biomass estimates. Then, we assess the fidelity of UAS, WorldView-2, and Landsat leaf-area and biomass estimates to field-measured landscape changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

Impacts of deer herbivory on vegetation in Rock Creek Park, 2001-2009

USGS Publications Warehouse

Kraft, Cairn C.; Hatfield, Jeff S.

2011-01-01

Starting in 2001, vegetation data have been collected annually in 16 study modules consisting of paired (1x4 m) fenced plots and unfenced control plots located in the upland forests of Rock Creek Park, Washington, D.C. Vegetation data collected from 2001-2009 have been analyzed to determine impacts of deer herbivory on vegetation in the park. Differences between fenced plots and unfenced control plots were analyzed for the following variables: cover provided by various groups of species (woody, herbaceous, native, non-native, trees, shrubs, and woody vines), as well as by individual dominant species, vegetation thickness (a measure of percent cover projected horizontally that provides information on the vertical distribution of vegetation), and species richness overall and for groups of species (woody, herbaceous, native, non-native, trees, shrubs, and woody vines). The analyses were performed using repeated measures analysis of variance (ANOVA) and associated tests. Vegetation in plots protected from deer herbivory for 9 years showed significantly greater vegetative cover compared to plots not protected from deer herbivory. This effect was most pronounced for woody and shrub cover. Cover by the dominant species was not significantly greater in the fenced plots compared to the unfenced control plots, indicating that the significant differences observed for groups were not driven by single species within those groups. With respect to vegetation thickness, results indicate that protection from deer herbivory produced significantly higher levels of vegetation in the fenced plots compared to the unfenced control plots for both the Low (0-30 cm) and Middle (30-110 cm) height classes. Protection from deer herbivory has led to higher overall species richness and higher species richness for woody species, natives, and shrubs compared to plots not receiving protection. There is also evidence that plots protected from deer herbivory and those not receiving this protection are diverging over time with respect to a number of variables such as cover by woody and shrub species, cover in the lowest height class, and species richness of woody and native species. Recommendations were made regarding future sampling.

Socioeconomic differences in fruit and vegetable consumption among middle-aged French adults: adherence to the 5 A Day recommendation.

PubMed

Estaquio, Carla; Druesne-Pecollo, Nathalie; Latino-Martel, Paule; Dauchet, Luc; Hercberg, Serge; Bertrais, Sandrine

2008-12-01

Numerous studies support the protective effect of high fruit and vegetable consumption on chronic disease risk, mainly against cancer and cardiovascular diseases. The increase of fruit and vegetable intake has become a public health priority in many countries. The aim of the study was to investigate the relationships of socioeconomic, demographic, and behavioral factors with both quantity and variety of fruit and vegetable consumption. Fruit and vegetable intake was assessed using repeated 24-hour dietary records collected during a 2-year period from 4,282 French subjects (2,373 men and 1,909 women), aged 45 to 62 years, who participated in a large prospective study. Both education level and occupation categories were used as socioeconomic indicators. Logistic regression models were applied to assess factors related to meeting the 5 A Day fruit and vegetable recommendation. Covariance analyses were performed to compare the fruit and vegetable variety scores and the contributions of fruit and vegetables to the total daily diet cost across socioeconomic indicators within each sex. Meeting the 5 A Day recommendation was more likely in subjects aged 50 years and older, higher education levels, nonsmokers, moderate alcohol drinkers and in women engaging in regular physical activity. The odds ratio (95% confidence interval) for the lower vs higher education level was 0.70 (0.54 to 0.92) in men and 0.65 (0.48 to 0.85) in women. No significant difference was observed between occupation categories. A positive relationship between vegetable variety and education level was found in both sexes. Fruit variety was positively associated with both education and occupation categories, but only in men. The contribution of fruits to the total daily diet cost increased with occupation (P<0.02) and education (P<0.0001) in men, but decreased with occupation in women (P<0.05). Although cost constraints may explain the lower fruit and vegetable intake in lower socioeconomic groups, the relative influence of budgetary resources, nutrition knowledge, and social and environmental barriers in socioeconomic disparities need further investigation.

Mineral Elements Bio-Accessibility and Antioxidant Indices of Blanched Basella rubra at Different Phases of in vitro Gastrointestinal Digestion

PubMed Central

Olukemi, Bukola Eugenia; Asikhia, Ikuosho Charity; Akindahunsi, Akintunde Afolabi

2018-01-01

The present investigation was designed to evaluate the mineral element bio-accessibility and antioxidant indices of blanched Basella rubra at different phases of simulated in vitro digestion (oral, gastric, and intestinal). The phenolic composition of processed vegetable was determined using high-performance liquid chromatography (HPLC)-diode-array detection method. Mineral composition, total phenolic content (TPC), total flavonoid content (TFC), ferric reducing antioxidant power (FRAP), and total antioxidant activity (TAA) of the in vitro digested blanched and raw vegetable were also determined. HPLC analysis revealed the presence of some phenolic compounds, with higher levels (mg/g) of polyphenols in raw B. rubra (catechin, 1.12; p-coumaric acid, 6.17; caffeic acid, 2.05) compared with the blanched counterpart, with exeption of chlorogenic acid (2.84), that was higher in blanched vegetable. The mineral content (mg/100 g) showed a higher value in enzyme treated raw vegetable compared to their blanched counterparts, with few exceptions. The results revealed a higher level of some of the evaluated minerals at the intestinal phase of digestion (Zn, 6.36/5.31; Mg, 5.29/8.97; Ca, 2,307.69/1,565.38; Na, 5,128/4,128.21) for raw and blanched respectively, with the exception of Fe, K, and P. The results of the antioxidant indices of in vitro digested B. rubra revealed a higher value at the intestinal phase of in vitro digestion, with raw vegetal matter ranking higher (TPC, 553.56 mg/g; TFC, 518.88 mg/g; FRAP, 8.15 mg/g; TAA, 5,043.16 μM Trolox equivalent/g) than the blanched counterpart. The studied vegetable contains important minerals and antioxidant molecules that would be readily available after passing through the gastrointestinal tract and could be harnessed as functional foods. PMID:29662844

Hydrological and Vegetation Variability from Mediterranean Leaf Wax Biomarkers Before and After the Rise of East African C4 Grasslands

NASA Astrophysics Data System (ADS)

Meyers, C.; deMenocal, P. B.; Tierney, J. E.; Polissar, P. J.

2012-12-01

Terrestrial and marine paleoclimate records and changes in African fossil mammal taxa indicate that a transition towards more open, C4-dominated grasslands occurred in East Africa near 2 Ma. In contrast, the Mediterranean sapropel record documents pervasive precession-paced wet/dry cycles in the strength of the African monsoon and Nile runoff since at least the late Miocene. This study investigates whether the East African vegetation shift after 2 Ma was accompanied by a change in the monsoonal wet/dry cycle response to orbital precession forcing. We sampled eastern Mediterranean ODP Site 967 at 2-3 ka resolution in two 200 kyr intervals near 3.0 and 1.7 Ma. Nearly identical orbital configurations in these intervals allow us to compare mean conditions and orbital-paced variations before and after the 2 Ma transition. We used leaf wax biomarker concentrations and δD and δ13C compositions as proxies for monsoonal strength and vegetation type, and the δ18O composition of G. ruber as a proxy for Nile River runoff. Leaf wax biomarker concentrations varied over three orders of magnitude, with much higher concentrations in sapropels. During sapropel intervals, large-amplitude negative excursions occur in δDwax, δ13Cwax, and δ18Oruber, corresponding to a strengthened monsoon and less abundant C4 plants. Carbonate-rich intervals have positive isotope excursions indicating a weakened monsoon and more abundant C4 plants. The mean and variance of δDwax and δ13Cwax values are not significantly different between the 3.0 Ma and 1.7 Ma intervals indicating Northern Africa did not experience the vegetation and climate shifts observed in East Africa. While surprising, our finding suggests that the average monsoonal response to precession forcing, and corresponding vegetation variability, did not substantially change across the 2 Ma transition. This implies that North and East Africa exhibited different climate and vegetation behavior since 3 Ma.

[Object-oriented aquatic vegetation extracting approach based on visible vegetation indices.

PubMed

Jing, Ran; Deng, Lei; Zhao, Wen Ji; Gong, Zhao Ning

2016-05-01

Using the estimation of scale parameters (ESP) image segmentation tool to determine the ideal image segmentation scale, the optimal segmented image was created by the multi-scale segmentation method. Based on the visible vegetation indices derived from mini-UAV imaging data, we chose a set of optimal vegetation indices from a series of visible vegetation indices, and built up a decision tree rule. A membership function was used to automatically classify the study area and an aquatic vegetation map was generated. The results showed the overall accuracy of image classification using the supervised classification was 53.7%, and the overall accuracy of object-oriented image analysis (OBIA) was 91.7%. Compared with pixel-based supervised classification method, the OBIA method improved significantly the image classification result and further increased the accuracy of extracting the aquatic vegetation. The Kappa value of supervised classification was 0.4, and the Kappa value based OBIA was 0.9. The experimental results demonstrated that using visible vegetation indices derived from the mini-UAV data and OBIA method extracting the aquatic vegetation developed in this study was feasible and could be applied in other physically similar areas.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Determination of Elemental Composition of Malabar spinach, Lettuce, Spinach, Hyacinth Bean, and Cauliflower Vegetables Using Proton Induced X-Ray Emission Technique at Savar Subdistrict in Bangladesh

PubMed Central

Fahad, S. M.; Islam, A. F. M. Mahmudul; Ahmed, Mahiuddin; Alam, Md. Rezaul; Alam, Md. Ferdous; Khalik, Md. Farhan; Hossain, Md. Lokman; Abedin, Md. Joynal

2015-01-01

The concentrations of 18 different elements (K, Ca, Fe, Cl, P, Zn, S, Mn, Ti, Cr, Rb, Co, Br, Sr, Ru, Si, Ni, and Cu) were analyzed in five selected vegetables through Proton Induced X-ray Emission (PIXE) technique. The objective of this study was to provide updated information on concentrations of elements in vegetables available in the local markets at Savar subdistrict in Bangladesh. These elements were found in varying concentrations in the studied vegetables. The results also indicated that P, Cl, K, Ca, Mn, Fe, and Zn were found in all vegetables. Overall, K and Ca exhibited the highest concentrations. Cu and Ni exhibited the lowest concentrations in vegetables. The necessity of these elements was also evaluated, based on the established limits of regulatory standards. The findings of this study suggest that the consumption of these vegetables is not completely free of health risks. PMID:26229953

Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time.

PubMed

Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Björk, Robert G; Bjorkman, Anne D; Callaghan, Terry V; Collier, Laura Siegwart; Cooper, Elisabeth J; Cornelissen, Johannes H C; Day, Thomas A; Fosaa, Anna Maria; Gould, William A; Grétarsdóttir, Járngerður; Harte, John; Hermanutz, Luise; Hik, David S; Hofgaard, Annika; Jarrad, Frith; Jónsdóttir, Ingibjörg Svala; Keuper, Frida; Klanderud, Kari; Klein, Julia A; Koh, Saewan; Kudo, Gaku; Lang, Simone I; Loewen, Val; May, Jeremy L; Mercado, Joel; Michelsen, Anders; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Pieper, Sara; Post, Eric; Rixen, Christian; Robinson, Clare H; Schmidt, Niels Martin; Shaver, Gaius R; Stenström, Anna; Tolvanen, Anne; Totland, Orjan; Troxler, Tiffany; Wahren, Carl-Henrik; Webber, Patrick J; Welker, Jeffery M; Wookey, Philip A

2012-02-01

Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site-specificity of results and uncertainty about the power of short-term studies to anticipate longer term change. We address these issues with a synthesis of 61 experimental warming studies, of up to 20 years duration, in tundra sites worldwide. The response of plant groups to warming often differed with ambient summer temperature, soil moisture and experimental duration. Shrubs increased with warming only where ambient temperature was high, whereas graminoids increased primarily in the coldest study sites. Linear increases in effect size over time were frequently observed. There was little indication of saturating or accelerating effects, as would be predicted if negative or positive vegetation feedbacks were common. These results indicate that tundra vegetation exhibits strong regional variation in response to warming, and that in vulnerable regions, cumulative effects of long-term warming on tundra vegetation - and associated ecosystem consequences - have the potential to be much greater than we have observed to date. © 2011 Blackwell Publishing Ltd/CNRS.

Pollen assemblages as paleoenvironmental proxies in the Florida Everglades

USGS Publications Warehouse

Willard, D.A.; Weimer, L.M.; Riegel, W.L.

2001-01-01

Analysis of 170 pollen assemblages from surface samples in eight vegetation types in the Florida Everglades indicates that these wetland sub-environments are distinguishable from the pollen record and that they are useful proxies for hydrologic and edaphic parameters. Vegetation types sampled include sawgrass marshes, cattail marshes, sloughs with floating aquatics, wet prairies, brackish marshes, tree islands, cypress swamps, and mangrove forests. The distribution of these vegetation types is controlled by specific environmental parameters, such as hydrologic regime, nutrient availability, disturbance level, substrate type, and salinity; ecotones between vegetation types may be sharp. Using R-mode cluster analysis of pollen data, we identified diagnostic species groupings; Q-mode cluster analysis was used to differentiate pollen signatures of each vegetation type. Cluster analysis and the modern analog technique were applied to interpret vegetational and environmental trends over the last two millennia at a site in Water Conservation Area 3A. The results show that close modern analogs exist for assemblages in the core and indicate past hydrologic changes at the site, correlated with both climatic and land-use changes. The ability to differentiate marshes with different hydrologic and edaphic requirements using the pollen record facilitates assessment of relative impacts of climatic and anthropogenic changes on this wetland ecosystem on smaller spatial and temporal scales than previously were possible. ?? 2001 Elsevier Science B.V.

Processing of airborne laser scanning data to generate accurate DTM for floodplain wetland

NASA Astrophysics Data System (ADS)

Szporak-Wasilewska, Sylwia; Mirosław-Świątek, Dorota; Grygoruk, Mateusz; Michałowski, Robert; Kardel, Ignacy

2015-10-01

Structure of the floodplain, especially its topography and vegetation, influences the overland flow and dynamics of floods which are key factors shaping ecosystems in surface water-fed wetlands. Therefore elaboration of the digital terrain model (DTM) of a high spatial accuracy is crucial in hydrodynamic flow modelling in river valleys. In this study the research was conducted in the unique Central European complex of fens and marshes - the Lower Biebrza river valley. The area is represented mainly by peat ecosystems which according to EU Water Framework Directive (WFD) are called "water-dependent ecosystems". Development of accurate DTM in these areas which are overgrown by dense wetland vegetation consisting of alder forest, willow shrubs, reed, sedges and grass is very difficult, therefore to represent terrain in high accuracy the airborne laser scanning data (ALS) with scanning density of 4 points/m2 was used and the correction of the "vegetation effect" on DTM was executed. This correction was performed utilizing remotely sensed images, topographical survey using the Real Time Kinematic positioning and vegetation height measurements. In order to classify different types of vegetation within research area the object based image analysis (OBIA) was used. OBIA allowed partitioning remotely sensed imagery into meaningful image-objects, and assessing their characteristics through spatial and spectral scale. The final maps of vegetation patches that include attributes of vegetation height and vegetation spectral properties, utilized both the laser scanning data and the vegetation indices developed on the basis of airborne and satellite imagery. This data was used in process of segmentation, attribution and classification. Several different vegetation indices were tested to distinguish different types of vegetation in wetland area. The OBIA classification allowed correction of the "vegetation effect" on DTM. The final digital terrain model was compared and examined within distinguished land cover classes (formed mainly by natural vegetation of the river valley) with archival height models developed through interpolation of ground points measured with GPS RTK and also with elevation models from the ASTER-GDEM and SRTM programs. The research presented in this paper allowed improving quality of hydrodynamic modelling in the surface water-fed wetlands protected within Biebrza National Park. Additionally, the comparison with other digital terrain models allowed to demonstrate the importance of accurate topography products in such modelling. The ALS data also significantly improved the accuracy and actuality of the river Biebrza course, its tributaries and location of numerous oxbows typical in this part of the river valley in comparison to previously available data. This type of data also helped to refine the river valley cross-sections, designate river banks and to develop the slope map of the research area.

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

NASA Astrophysics Data System (ADS)

Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

NASA Astrophysics Data System (ADS)

Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

2018-05-01

Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

Effects of tailoring ingredients in auditory persuasive health messages on fruit and vegetable intake.

PubMed

Elbert, Sarah P; Dijkstra, Arie; Rozema, Andrea D

2017-07-01

Health messages can be tailored by applying different tailoring ingredients, among which personalisation, feedback and adaptation. This experiment investigated the separate effects of these tailoring ingredients on behaviour in auditory health persuasion. Furthermore, the moderating effect of self-efficacy was assessed. The between-participants design consisted of four conditions. A generic health message served as a control condition; personalisation was applied using the recipient's first name, feedback was given on the personal state, or the message was adapted to the recipient's value. The study consisted of a pre-test questionnaire (measuring fruit and vegetable intake and perceived difficulty of performing these behaviours, indicating self-efficacy), exposure to the auditory message and a follow-up questionnaire measuring fruit and vegetable intake two weeks after message exposure (n = 112). ANCOVAs showed no main effect of condition on either fruit or vegetable intake, but a moderation was found on vegetable intake: When self-efficacy was low, vegetable intake was higher after listening to the personalisation message. No significant differences between the conditions were found when self-efficacy was high. Individuals with low self-efficacy seemed to benefit from incorporating personalisation, but only regarding vegetable consumption. This finding warrants further investigation in tailoring research.

Assessing the Ability of Vegetation Indices to Identify Shallow Subsurface Water Flow Pathways from Hyperspectral Imagery Using Machine Learning: Application

NASA Astrophysics Data System (ADS)

Doctor, K.; Byers, J. M.

2017-12-01

Shallow underground water flow pathways expressed as slight depressions are common in the land surface. Under conditions of saturated overland flow, such as during heavy rain or snow melt, these areas of preferential flow might appear on the surface as very shallow flowing streams. When there is no water flowing in these ephemeral channels it can be difficult to identify them. It is especially difficult to discern the slight depressions above the subsurface water flow pathways (SWFP) when the area is covered by vegetation. Since the soil moisture content in these SWFP is often greater than the surrounding area, the vegetation growing on top of these channels shows different vigor and moisture content than the vegetation growing above the non-SWFP area. Vegetation indices (VI) are used in visible and near infrared (VNIR) hyperspectral imagery to enhance biophysical properties of vegetation, and so the brightness values between vegetation atop SWFP and the surrounding vegetation were highlighted. We performed supervised machine learning using ground-truth class labels to determine the conditional probability of a SWFP at a given pixel given either the spectral distribution or VI at that pixel. The training data estimates the probability distributions to a determined finite sampling accuracy for a binary Naïve Bayes classifier between SWFP and non-SWFP. The ground-truth data provides a test bed for understanding the ability to build SWFP classifiers using hyperspectral imagery. SWFP were distinguishable in the imagery within corn and grass fields and in areas with low-lying vegetation. However, the training data is limited to particular types of terrain and vegetation cover in the Shenandoah Valley, Virginia and this would limit the resulting classifier. Further training data could extend its use to other environments.

Spatial And Temporal Trends Of Organic Pollutants In Vegetation From Remote And Rural Areas

NASA Astrophysics Data System (ADS)

Bartrons, Mireia; Catalan, Jordi; Penuelas, Josep

2016-05-01

Persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs) used in agricultural, industrial, and domestic applications are widely distributed and bioaccumulate in food webs, causing adverse effects to the biosphere. A review of published data for 1977-2015 for a wide range of vegetation around the globe indicates an extensive load of pollutants in vegetation. On a global perspective, the accumulation of POPs and PAHs in vegetation depends on the industrialization history across continents and distance to emission sources, beyond organism type and climatic variables. International regulations initially reduced the concentrations of POPs in vegetation in rural areas, but concentrations of HCB, HCHs, and DDTs at remote sites did not decrease or even increased over time, pointing to a remobilization of POPs from source areas to remote sites. The concentrations of compounds currently in use, PBDEs and PAHs, are still increasing in vegetation. Differential congener specific accumulation is mostly determined by continent—in accordance to the different regulations of HCHs, PCBs and PBDEs in different countries—and by plant type (PAHs). These results support a concerning general accumulation of toxic pollutants in most ecosystems of the globe that for some compounds is still far from being mitigated in the near future.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

PubMed

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

2008-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

2009-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

Latent heat exchange in the boreal and arctic biomes.

PubMed

Kasurinen, Ville; Alfredsen, Knut; Kolari, Pasi; Mammarella, Ivan; Alekseychik, Pavel; Rinne, Janne; Vesala, Timo; Bernier, Pierre; Boike, Julia; Langer, Moritz; Belelli Marchesini, Luca; van Huissteden, Ko; Dolman, Han; Sachs, Torsten; Ohta, Takeshi; Varlagin, Andrej; Rocha, Adrian; Arain, Altaf; Oechel, Walter; Lund, Magnus; Grelle, Achim; Lindroth, Anders; Black, Andy; Aurela, Mika; Laurila, Tuomas; Lohila, Annalea; Berninger, Frank

2014-11-01

In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling. © 2014 John Wiley & Sons Ltd.

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China.

PubMed

Yue, Yuemin; Wang, Kelin; Zhang, Bing; Chen, Zhengchao; Jiao, Quanjun; Liu, Bo; Chen, Hongsong

2010-01-01

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.

Assessment of Vegetation Responses and Sensitivity to the Millennium Drought in Australia

NASA Astrophysics Data System (ADS)

Jiao, T.; Williams, C. A.

2017-12-01

During the period from 1997 to 2009, Australia experienced one of the most severe and persistent drought known as the Millennium Drought (MD). Major water shortages were reported across the Australian continent as well as a great many tree mortality during and post this drought event. Given the projection of hotter and drier conditions for much of the continent (Hughes 2003), it is critical to analyze the impacts of climate extremes like MD as an indicator of possible impacts of future trends. A few drought assessments have been performed for the MD but their utilization of single-source Remote sensing data like vegetation indices makes it difficult to produce a comprehensive understanding of drought responses for diverse ecosystems in Australia. Furthermore, methods adopted in past drought assessments did not distinguish vegetation responses to drought events with different intensity, duration and sequence, which are critically important in determining the magnitude of vegetation responses to drought. Here, multi-source remote sensing datasets and an event-based drought assessment method were employed to assess the impacts of MD on vegetation in Australia in terms of the magnitude and sensitivity. Vegetation variables examined include fraction of photosynthetically absorbed radiation (Fpar), vegetation optical depth (VOD) and aboveground biomass (AGB). Drought indicators were calculated based on precipitation and potential evapotranspiration. Results show that most of Eastern Australia experienced abnormal water deficit during the MD and drought intensity was greatest in humid regions. The decline in aboveground biomass (ABC) demonstrates consistent variation with drought intensity across aridity levels. Drought impacts on Fpar and VOD were greatest at intermediate dryness and for woodier ecosystems, with impacts appearing in Fpar before VOD. Drought sensitivity was also greatest at intermediate dryness and for woodier ecosystems. The small difference in drought sensitivity, in terms of Fpar and VOD, across biomes suggests that trees, shrubs, and herbaceous are equally vulnerable to canopy dieback while the high drought sensitivity of trees as shown in ABC implies that a large amount of carbon could be released to the atmosphere if intense and long-duration drought occurs in forested areas.

Implications of Topographically Induced Variations in Solar Radiation for Water Balance, Vegetation and Soil Development.

NASA Astrophysics Data System (ADS)

Seyfried, M. S.; Flerchinger, G. N.; Link, T. E.; McNamara, J. P.

2016-12-01

Vegetation cover and stature in semiarid regions are highly sensitive to variations in evaporative demand and precipitation. Where the terrain is complex, this may result in a spatial mosaic of vegetation cover related to topographically induced variations in solar radiation and hence evaporative demand. The associated energy and water fluxes and carbon stocks probably do not scale linearly, but are potentially predictable. Johnston Draw, a small, semiarid, granitic catchment in the Reynolds Creek Experimental Watershed in Idaho, is dominated by steep north and south-facing slopes. Vegetation on North-facing slopes is more complete. We made spatially extensive, periodic measurements of soil temperature (Ts) soil water content (Ws) to establish the spatial variability of those parameters. In addition, we monitored Ts and Ws in profiles to bedrock, snow depth and meteorological parameters at three paired, north- and south-facing slope locations. These data were compared to simulations of water and energy flux calculated using the Simultaneous Heat and Water (SHAW) model. We found dramatic differences in Ts, with the annual average soil temperature about 5 C warmer on south-facing slopes. Differences varied seasonally, with the biggest differences in the summer, exactly out of phase with the solar radiation differences. Each year soils dried to consistent, low values, but the north-facing soils retained water about one month longer, on average, owing mostly to the greater depth, and hence available water, on those soils. Modeling results indicate that water is retained longer in north-facing soils and the differences in Ts are due to differences in soil cover, primarily from the greater density of vegetative cover. These differences appear to have evolved over time as the result of feedbacks between atmospheric forcings and vegetation response, which promote greater carbon accumulations and deeper soil formation.

Standardized principal components for vegetation variability monitoring across space and time

NASA Astrophysics Data System (ADS)

Mathew, T. R.; Vohora, V. K.

2016-08-01

Vegetation at any given location changes through time and in space. In what quantity it changes, where and when can help us in identifying sources of ecosystem stress, which is very useful for understanding changes in biodiversity and its effect on climate change. Such changes known for a region are important in prioritizing management. The present study considers the dynamics of savanna vegetation in Kruger National Park (KNP) through the use of temporal satellite remote sensing images. Spatial variability of vegetation is a key characteristic of savanna landscapes and its importance to biodiversity has been demonstrated by field-based studies. The data used for the study were sourced from the U.S. Agency for International Development where AVHRR derived Normalized Difference Vegetation Index (NDVI) images available at spatial resolutions of 8 km and at dekadal scales. The study area was extracted from these images for the time-period 1984-2002. Maximum value composites were derived for individual months resulting in an image dataset of 216 NDVI images. Vegetation dynamics across spatio-temporal domains were analyzed using standardized principal components analysis (SPCA) on the NDVI time-series. Each individual image variability in the time-series is considered. The outcome of this study demonstrated promising results - the variability of vegetation change in the area across space and time, and also indicated changes in landscape on 6 individual principal components (PCs) showing differences not only in magnitude, but also in pattern, of different selected eco-zones with constantly changing and evolving ecosystem.

Disaggregating tree and grass phenology in tropical savannas

NASA Astrophysics Data System (ADS)

Zhou, Qiang

Savannas are mixed tree-grass systems and as one of the world's largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment.

How well do meteorological indicators represent agricultural and forest drought across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, S.; Tanguy, M.; Hannaford, J.; Stahl, K.

2018-03-01

Drought monitoring and early warning (M&EW) systems are an important component of agriculture/silviculture drought risk assessment. Many operational information systems rely mostly on meteorological indicators, and a few incorporate vegetation state information. However, the relationships between meteorological drought indicators and agricultural/silvicultural drought impacts vary across Europe. The details of this variability have not been elucidated sufficiently on a continental scale in Europe to inform drought risk management at administrative scales. The objective of this study is to fill this gap and evaluate how useful the variety of meteorological indicators are to assess agricultural/silvicultural drought across Europe. The first part of the analysis systematically linked meteorological drought indicators to remote sensing based vegetation indices (VIs) for Europe at NUTs3 administrative regions scale using correlation analysis for crops and forests. In a second step, a stepwise multiple linear regression model was deployed to identify variables explaining the spatial differences observed. Finally, corn crop yield in Germany was chosen as a case study to verify VIs’ representativeness of agricultural drought impacts. Results show that short accumulation periods of SPI and SPEI are best linked to crop vegetation stress in most cases, which further validates the use of SPI3 in existing operational drought monitors. However, large regional differences in correlations are also revealed. Climate (temperature and precipitation) explained the largest proportion of variance, suggesting that meteorological indices are less informative of agricultural/silvicultural drought in colder/wetter parts of Europe. These findings provide important context for interpreting meteorological indices on widely used national to continental M&EW systems, leading to a better understanding of where/when such M&EW tools can be indicative of likely agricultural stress and impacts.

Monitoring Phenology as Indicator for Timing of Nutrient Inputs in Northern Gulf Watersheds

DTIC Science & Technology

2010-06-01

region and compared to nutrient monitoring data. A. Image Data This project uses MODIS normalized difference vegetation index ( NDVI ) to create a time...series of land vegetation canopies. MODIS provides a near-daily repeat time for the elimination of cloud contamination, and NDVI has been widely adopted...steps and NDVI was calculated by the defined formula NDVI = (near-infrared reflectance - red reflectance) / (near-infrared reflectance + red

Soil TPH Concentration Estimation Using Vegetation Indices in an Oil Polluted Area of Eastern China

PubMed Central

Zhu, Linhai; Zhao, Xuechun; Lai, Liming; Wang, Jianjian; Jiang, Lianhe; Ding, Jinzhi; Liu, Nanxi; Yu, Yunjiang; Li, Junsheng; Xiao, Nengwen; Zheng, Yuanrun; Rimmington, Glyn M.

2013-01-01

Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m−2 to 5.3 g m−2 with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg−1 to 652 mg kg−1. The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R 2 = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg−1). For other vegetation indices and red edge parameters, the R2 and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg−1 to 106.8 mg kg−1 respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R 2 = 0.70 and RMSE = 110.1 mg kg−1) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable. PMID:23342066

Effects of post-fire wood management strategies on vegetation recovery and land surface temperature (LST) estimated from Landsat images

NASA Astrophysics Data System (ADS)

Vlassova, Lidia; Pérez-Cabello, Fernando

2016-02-01

The study contributes remote sensing data to the discussion about effects of post-fire wood management strategies on forest regeneration. Land surface temperature (LST) and Normalized Differenced Vegetation Index (NDVI), estimated from Landsat-8 images are used as indicators of Pinus halepensis ecosystem recovery after 2008 fire in areas of three post-fire treatments: (1) salvage logging with wood extraction from the site on skidders in suspended position (SL); (2) snag shredding in situ leaving wood debris in place (SS) performed two years after the event; and (3) non-intervention control areas (CL) where all snags were left standing. Six years after the fire NDVI values ∼0.5 estimated from satellite images and field radiometry indicate considerable vegetation recovery due to efficient regeneration traits developed by the dominant plant species. However, two years after management activities in part of the burnt area, the effect of SL and SS on ecosystem recovery is observed in terms of both LST and NDVI. Statistically significant differences are detected between the intervened areas (SL and SS) and control areas of non-intervention (CL); no difference is registered between zones of different intervention types (SL and SS). CL areas are on average 1 °C cooler and 10% greener than those corresponding to either SL or SS, because of the beneficial effects of burnt wood residuals, which favor forest recovery through (i) enhanced nutrient cycling in soils, (ii) avoidance of soil surface disturbance and mechanical damage of seedlings typical to the managed areas, and (iii) ameliorated microclimate. The results of the study show that in fire-resilient ecosystems, such as P. halepensis forests, NDVI is higher and LST is lower in areas with no management intervention, being an indication of more favorable conditions for vegetation regeneration.

Assessment of Vegetation Indices Derived by UAV Imagery for Durum Wheat Phenotyping under a Water Limited and Heat Stressed Mediterranean Environment.

PubMed

Kyratzis, Angelos C; Skarlatos, Dimitrios P; Menexes, George C; Vamvakousis, Vasileios F; Katsiotis, Andreas

2017-01-01

There is growing interest for using Spectral Vegetation Indices (SVI) derived by Unmanned Aerial Vehicle (UAV) imagery as a fast and cost-efficient tool for plant phenotyping. The development of such tools is of paramount importance to continue progress through plant breeding, especially in the Mediterranean basin, where climate change is expected to further increase yield uncertainty. In the present study, Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Green Normalized Difference Vegetation Index (GNDVI) derived from UAV imagery were calculated for two consecutive years in a set of twenty durum wheat varieties grown under a water limited and heat stressed environment. Statistically significant differences between genotypes were observed for SVIs. GNDVI explained more variability than NDVI and SR, when recorded at booting. GNDVI was significantly correlated with grain yield when recorded at booting and anthesis during the 1st and 2nd year, respectively, while NDVI was correlated to grain yield when recorded at booting, but only for the 1st year. These results suggest that GNDVI has a better discriminating efficiency and can be a better predictor of yield when recorded at early reproductive stages. The predictive ability of SVIs was affected by plant phenology. Correlations of grain yield with SVIs were stronger as the correlations of SVIs with heading were weaker or not significant. NDVIs recorded at the experimental site were significantly correlated with grain yield of the same set of genotypes grown in other environments. Both positive and negative correlations were observed indicating that the environmental conditions during grain filling can affect the sign of the correlations. These findings highlight the potential use of SVIs derived by UAV imagery for durum wheat phenotyping under low yielding Mediterranean conditions.

Feeding preferences of West Indian manatees in Florida, Belize, and Puerto Rico as indicated by stable isotope analysis

USGS Publications Warehouse

Alves-Stanley, Christy D.; Worthy, Graham A.J.; Bonde, Robert K.

2010-01-01

The endangered West Indian manatee Trichechus manatus has 2 recognized subspecies: the Florida T. m. latirostris and Antillean T. m. manatus manatee, both of which are found in freshwater, estuarine, and marine habitats. A better understanding of manatee feeding preferences and habitat use is essential to establish criteria on which conservation plans can be based. Skin from manatees in Florida, Belize, and Puerto Rico, as well as aquatic vegetation from their presumed diet, were analyzed for stable carbon and nitrogen isotope ratios. This is the first application of stable isotope analysis to Antillean manatees. Stable isotope ratios for aquatic vegetation differed by plant type (freshwater, estuarine, and marine), collection location, and in one instance, season. Carbon and nitrogen isotope ratios for manatee skin differed between collection location and in one instance, season, but did not differ between sex or age class. Signatures in the skin of manatees sampled in Belize and Puerto Rico indicated a diet composed primarily of seagrasses, whereas those of Florida manatees exhibited greater regional variation. Mixing model results indicated that manatees sampled from Crystal River and Homosassa Springs (Florida, USA) ate primarily freshwater vegetation, whereas manatees sampled from Big Bend Power Plant, Ten Thousand Islands, and Warm Mineral Springs (Florida) fed primarily on seagrasses. Possible diet-tissue discrimination values for 15N were estimated to range from 1.0 to 1.5 per mil. Stable isotope analysis can be used to interpret manatee feeding behavior over a long period of time, specifically the use of freshwater vegetation versus seagrasses, and can aid in identifying critical habitats and improving conservation efforts.

Evaluating the capabilities of vegetation spectral indices on chlorophyll content estimation at Sentinel-2 spectral resolutions

NASA Astrophysics Data System (ADS)

Sun, Qi; Jiao, Quanjun; Dai, Huayang

2018-03-01

Chlorophyll is an important pigment in green plants for photosynthesis and obtaining the energy for growth and development. The rapid, nondestructive and accurate estimation of chlorophyll content is significant for understanding the crops growth, monitoring the disease and insect, and assessing the yield of crops. Sentinel-2 equipped with the Multi-Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region and a spatial resolution of 20nm, which can be used to derive vegetation indices using red-edge bands. In this paper, we will focus on assessing the potential of vegetation spectral indices for retrieving chlorophyll content from Sentinel-2 at different angles. Subsequently, we used in-situ spectral data and Sentinel-2 data to test the relationship between VIs and chlorophyll content. The REP, MTCI, CIred-edge, CIgreen, Macc01, TCARI/OSAVI [705,750], NDRE1 and NDRE2 were calculated. NDRE2 index displays a strongly similar result for hyperspectral and simulated Sentinel-2 spectral bands (R2 =0.53, R2 =0.51, for hyperspectral and Sentinel-2, respectively). At different observation angles, NDRE2 has the smallest difference in performance (R2 = 0.51, R2 =0.64, at 0° and 15° , respectively).

A Multi-proxy Approach to Using Cave Sediment Carbon Isotopes for Late Holocene Paleoenvironmental Reconstruction in Florida

NASA Astrophysics Data System (ADS)

Polk, J. S.; van Beynen, P.

2007-12-01

Carbon isotopes from cave sediments collected from Jennings Cave in Marion County, Florida were analyzed using a multi-proxy approach. Fulvic acids (FAs), humic acids (HAs), black carbon, phytoliths, and bulk organic matter were extracted from the sediments for carbon isotope analysis to determine periods of vegetation change caused by climatic influences during the Late Holocene (~\\ 2,800 years BP). The carbon isotope record ranges from -35‰ to -14‰, exhibiting variability of ~\\ -21‰, within the different proxies, which indicates changes between C3 and C4 vegetation. This likely indicates changes between a sub-tropical forested environment and more arid, grassy plains conditions. These changes in plant assemblages were in response to changes in available water resources, with increased temperatures and evapotranspiration leading to arid conditions and a shift toward less C3 vegetation (increased C4 vegetation) during the MWP. The cave sediment fulvic acid cabon isotopes record agrees well with ä13C values from a speleothem collected nearby that covers the same time period. Prolonged migration of the NAO and ITCZ affects precipitation in Florida and likely caused vegetation changes during these climatic shifts.

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

PubMed Central

Jiang, Hao; Zhao, Dehua; Cai, Ying; An, Shuqing

2012-01-01

In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT), the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI) as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal) thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV) of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling) normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3%) and overall (92.0%–93.1%) accuracies. Our results suggest that Method of 0.1% index scaling provides a feasible way to apply CT models directly to images from sensors or time periods that differ from those of the images used to develop the original models.

Floral and Vegetative Morphometrics of Five Pleurothallis (Orchidaceae) Species: Correlation with Taxonomy, Phylogeny, Genetic Variability and Pollination Systems

PubMed Central

BORBA, EDUARDO L.; SHEPHERD, GEORGE J.; BERG, CÁSSIO VAN DEN; SEMIR, JOÃO

2002-01-01

Morphometric analyses of vegetative and floral characters were conducted in 21 populations of five Pleurothallis (Orchidaceae) species occurring in Brazilian ‘campo rupestre’ vegetation. A phylogenetic analysis of this species group was also carried out using nuclear ribosomal DNA internal transcribed spacers (ITS1 and ITS2). Results of the ordination and cluster analyses agree with species’ delimitation revealed by taxonomic and allozyme studies. The groups formed in ordination analysis correspond to the pollinator groups determined in a previous pollination study. Relationships among the species in the cluster analysis using only vegetative characters are similar to those found in a previous allozyme study, but those indicated by cluster analysis using only floral characters differ. These results support the hypothesis that floral similarities are due to convergence driven by similar pollination mechanisms, and therefore floral traits may not be good indicators of phylogenetic relationships in this group. The results of the phylogenetic analysis support this conclusion to some extent. There is no correlation between genetic (allozyme) and morphological variability in the populations nor in the way this variability is distributed among conspecific populations. We describe a new subspecies of Pleurothallis ochreata based on differences in vegetative and chemical characters as well as geographic distribution. Absence of differentiation in floral characters, attraction of the same pollinator species, interfertility and genetic similarity support the argument for subspecific rather than specific status. PMID:12197519

A systematic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables.

PubMed

Irala-Estévez, J D; Groth, M; Johansson, L; Oltersdorf, U; Prättälä, R; Martínez-González, M A

2000-09-01

To evaluate the differences in the consumption of fruit and vegetables between groups with different socio-economic status (SES) in the adult population of European countries. A systematic review of published and unpublished surveys of food habits conducted between 1985 and 1999 in 15 European countries. Educational level and occupational status were used as indicators of SES. A pooled estimate of the mean difference between the highest and the lowest level of education and occupation was calculated separately for men and women, using DerSimonian and Laird's random effects model. The inclusion criteria of studies were: use of a validated method for assessing intake at the individual level; selection of a nationwide sample or a representative sample of a region; and providing the mean and standard deviation of overall fruit and vegetable consumption for each level of education or occupation, and separately for men and women. Participants in the individual surveys had to be adults (18-85 y). Eleven studies from seven countries met the criteria for being included in the meta-analysis. A higher SES was associated with a greater consumption of both fruit and vegetables. The pooled estimate of the difference in the intake of fruit was 24.3 g/person/day (95% confidence interval (CI) 14.0-34.7) between men in the highest level of education and those in the lowest level of education. Similarly, this difference was 33.6 g/person/day for women (95% CI 22.5-44.8). The differences regarding vegetables were 17.0 g/person/day (95% CI 8.6-25.5) for men and 13.4 g/person/day (95% CI 7.1-19.7) for women. The results were in the same direction when occupation instead of education was used as an indicator of SES. Although we cannot exclude over-reporting of intake by those with highest SES, it is unlikely that this potential bias could fully explain the differences we have found. Our results suggest that an unhealthier nutrition pattern may exist among adults belonging to lower socio-economic levels in Europe. The present study was supported by the European Union's FAIR programme (FAIR-97-3096).

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion.

PubMed

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-05

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies.

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion

PubMed Central

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-01

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies. PMID:28067770

Runoff and erosion in a pinon-juniper woodland: Influence of vegetation patches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reid, K.D.; Wilcox, B.P.; Breshears, D.D.

1999-12-01

In many semiarid regions, runoff and erosion differ according to vegetation patch type. These differences, although hypothesized to fundamentally affect ecological processes, have been poorly quantified. In a semiarid pinion-juniper woodland [Pinus edulis Engelm. and Juniperus monosperma (Engelm) Sarg.] in northern New Mexico, the authors measured runoff and erosion from the three patch types that compose these woodlands: Canopy patches (those beneath woody plants), vegetated patched in intercanopy areas, and bare patches in intercanopy areas. The bare intercanopy patches exhibited the highest rates, followed by vegetated intercanopy patches and then by canopy patches. Large convective summer storms, though relatively infrequent,more » generated much of the runoff and most of the sediment; prolonged frontal storms were capable of generating considerable runoff but little sediment. A portion of the runoff and most of the sediment generated from bare intercanopy patches was redistributed down-slope, probably to adjacent vegetated intercanopy patches, demonstrating connectivity between these two patch types. Their results indicate that there are significant and important differences in runoff and sediment production from the three patch types; that bare intercanopy patches act as sources of both water and sediment for the vegetated intercanopy patches; and that the transfer of water and sediment at small scales is both frequent enough and substantial enough to be considered ecologically significant.« less

What You See Depends on Your Point of View: Comparison of Greenness Indices Across Spatial and Temporal Scales and What That Means for Mule Deer Migration and Fitness

NASA Astrophysics Data System (ADS)

Miller, B. W.; Chong, G.; Steltzer, H.; Aikens, E.; Morisette, J. T.; Talbert, C.; Talbert, M.; Shory, R.; Krienert, J. M.; Gurganus, D.

2015-12-01

Climate change models for the north­ern Rocky Mountains predict warming and changes in water availability that may alter vegetation. Changes to vegetation may include timing of plant life-history events, or phenology, such as green-up, flower­ing, and senescence. These changes could make forage available earlier in the growing season, but shifts in phenol­ogy may also result in earlier senescence (die-off or dormancy) and reduced overall production. Greenness indices such as the normalized difference vegetation index (NDVI) are regularly used to quantify greenness over large areas using remotely sensed reflectance data. The timing and scale of current satellite data, however, may be insufficient to capture fine-scale differences in phenology that are important indicators of habitat quality. The Wyoming Range Mule Deer herd is one of the largest in the west but it declined precipitously in the early 1990s and has not recovered. Accurate measurement of greenness over space and time would allow managers to better understand the role of plant phenology and productivity in mule deer population dynamics, for example. To connect spatial and temporal patterns of plant productivity with habitat quality, we compare greenness patterns (MODIS data) with migratory mule deer movement (GPS collars). Sagebrush systems provide winter habitat for mule deer. To understand sagebrush phenology as an indicator of productivity, we constructed NDVI time series and compared dates of phenological stages and magnitudes of greenness from three perspectives: at-surface/species-specific (mantis sensors: downward looking, <1m above vegetation); near surface/site-specific (PhenoCam: oblique, 2m); and satellite/landscape-scale (varied platforms). Greenness indices from these sensors contribute unique insights to understanding vegetation phenology, snow cover and reflectance. Understanding phenology and productivity at multiple scales can help guide resource management decisions related to habitat quality, and evaluate what remotely sensed phenology measurements mean on the ground. Monitoring changes in phenology and productivity over the long-term can provide insight into ecosystem responses to climate change.

Species Composition at the Sub-Meter Level in Discontinuous Permafrost in Subarctic Sweden

NASA Astrophysics Data System (ADS)

Anderson, S. M.; Palace, M. W.; Layne, M.; Varner, R. K.; Crill, P. M.

2013-12-01

Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which results in changes in vegetative cover. Specific species have been associated with greenhouse gas emissions therefore knowledge of species compositional shift allows for the systematic change and quantification of emissions and changes in such emissions. Species composition varies on the sub-meter scale based on topography and other microsite environmental parameters. This complexity and the need to scale vegetation to the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane (CH4) emissions and dynamics. Stordalen Mire (68°21'N, 18°49'E) in Abisko and is located at the edge of discontinuous permafrost zone. This provides a unique opportunity to analyze multiple vegetation communities in a close proximity. To do this, we randomly selected 25 1x1 meter plots that were representative of five major cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub. We used a quadrat with 64 sub plots and measured areal percent cover for 24 species. We collected ground based remote sensing (RS) at each plot to determine species composition using an ADC-lite (near infrared, red, green) and GoPro (red, blue, green). We normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity. A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection. We found statistical difference in species composition and diversity indices between vegetation cover types. In addition, we were able to build regression model to significantly estimate vegetation cover type as well as percent cover for specific key vegetative species. This ground-based remote sensing allows for quick quantification of vegetation cover and species and also provides the framework for scaling to satellite image data to estimate species composition and shift on the landscape level. To determine diversity within our plots we calculated species richness and Shannon Index. We found that there were statistically different species composition within each vegetation cover type and also determined which species were indicative for cover type. Our logistical regression was able to significantly classify vegetation cover types based on RS parameters. Our multiple regression analysis indicated Betunla nana (Dwarf Birch) (r2= .48, p=<0.0001) and Sphagnum (r2=0.59, p=<0.0001) were statistically significant with respect to RS parameters. We suggest that ground based remote sensing methods may provide a unique and efficient method to quantify vegetation across the landscape in northern latitude wetlands.

Predicting Phenologic Response to Water Stress and Implications for Carbon Uptake across the Southeast U.S.

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2016-12-01

Representation of plant photosynthesis in modeling studies requires phenologic indicators to scale carbon assimilation by plants. These indicators are typically the fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI) which represent plant responses to light and water availability, as well as temperature constraints. In this study, a prognostic phenology model based on the growing season index is adapted to determine the phenologic indicators of LAI and FPAR at the sub-daily scale based on meteorological and soil conditions. Specifically, we directly model vegetation green-up and die-off responses to temperature, vapor pressure deficit, soil water potential, and incoming solar radiation. The indices are based on the properties of individual plant functional types, driven by observational data and prior modeling applications. First, we describe and test the sensitivity of the carbon uptake response to predicted phenology for different vegetation types. Second, the prognostic phenology model is incorporated into a land-surface hydrology model, the Duke Coupled Hydrology Model with Prognostic Vegetation (DCHM-PV), to demonstrate the impact of dynamic phenology on modeled carbon assimilation rates and hydrologic feedbacks. Preliminary results show reduced carbon uptake rates when incorporating a prognostic phenology model that match well against the eddy-covariance flux tower observations. Additionally, grassland vegetation shows the most variability in LAI and FPAR tied to meteorological and soil conditions. These results highlight the need to incorporate vegetation-specific responses to water limitation in order to accurately estimate the terrestrial carbon storage component of the global carbon budget.

Post-hurricane forest damage assessment using satellite remote sensing

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu; J.A. Stanturf

2010-01-01

This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was...

[Soils salinity content of greenhouse in Shanghai suburb].

PubMed

Yao, Chun-Xia; Chen, Zhen-Lou; Xu, Shi-Yuan

2007-06-01

Salinity content and characteristic of farmland soil in Shanghai suburb was studied. Result indicates that soils in greenhouse in Shanghai suburb are partially salted. Soils of suburb where melons or vegetables grow in Shanghai city, 88.52% soil is non-salted while 10.37% mildly salted, 0.74% obviously salted and 0.37% badly salted. Anions component of salt salinity in soil are mainly SO4(2-), Cl-, NO3(-) and cations component are mainly Ca2+, Na+, Mg2+, K+. These ions are mostly from fertilizer auxiliary component or fertilizer transformation component besides some original deposition in soil. The formation of soil secondary salted in greenhouse cultivation in suburbs of Shanghai has a close relationship with improper fertilization or employing too much fertilizer. Soil salinity is different with different cultivation mode and utilization time. From high to low, sequence of soil salinity content in 0 - 20 cm cultivation layer of different crop mode is greenhouse vegetable soil, melon soil, vegetable melon rotation soil and hypaethral vegetable soil respectively. In the same region, salinity in greenhouse soil continually increases and accumulates from underlayer to surface along with more utilization years.

State Indicator Report on Fruits and Vegetables, 2009

ERIC Educational Resources Information Center

Centers for Disease Control and Prevention, 2009

2009-01-01

The "State Indicator Report on Fruits and Vegetables, 2009" provides for the first time information on fruit and vegetable (F&V) consumption and policy and environmental support within each state. Fruits and vegetables, as part of a healthy diet, are important for optimal child growth, weight management, and chronic disease…

Effects of Different Vegetation Zones on CH4 and N2O Emissions in Coastal Wetlands: A Model Case Study

PubMed Central

Liu, Yuhong; Wang, Lixin; Bao, Shumei; Liu, Huamin; Yu, Junbao; Wang, Yu; Shao, Hongbo; Ouyang, Yan; An, Shuqing

2014-01-01

The coastal wetland ecosystems are important in the global carbon and nitrogen cycle and global climate change. For higher fragility of coastal wetlands induced by human activities, the roles of coastal wetland ecosystems in CH4 and N2O emissions are becoming more important. This study used a DNDC model to simulate current and future CH4 and N2O emissions of coastal wetlands in four sites along the latitude in China. The simulation results showed that different vegetation zones, including bare beach, Spartina beach, and Phragmites beach, produced different emissions of CH4 and N2O in the same latitude region. Correlation analysis indicated that vegetation types, water level, temperature, and soil organic carbon content are the main factors affecting emissions of CH4 and N2O in coastal wetlands. PMID:24892044

Characterization of nonstarch polysaccharides content from different edible organs of some vegetables, determined by GC and HPLC: comparative study.

PubMed

Villanueva-Suárez, M J; Redondo-Cuenca, A; Rodríguez-Sevilla, M D; de las Heras Martínez, M

2003-09-24

Content and composition of dietary fiber as nonstarch polysaccharides (NSP) was determined in vegetables belonging to different types of edible organs, using GC and HPLC. Samples analyzed were subterranean organs (radish and leek), leaves (celery, swiss chard, and lettuce), stalks (celery, swiss chard, and asparagus), inflorescence (broccoli), and fruits (tomato, green pepper, and marrow). The results indicate that though the monomeric profile is similar in all these samples quantitative differences were found for neutral sugars and uronic acids among samples of the same type of vegetal organ. The NSP values determined using CG method were in good agreement with HPLC method (R(2) = 0.9005). However, arabinose, mannose, and galactose plus rhamnose are more influenced by the analytical method used than the rest of the monomers in nearly all the samples analyzed. Final values of NSP depend on the method used in celery stalks, broccoli, and green pepper.

The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index.

PubMed

Strong, Conor J; Burnside, Niall G; Llewellyn, Dan

2017-01-01

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future research and study.

The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index

PubMed Central

Strong, Conor J.; Llewellyn, Dan

2017-01-01

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future research and study. PMID:29023504

CRMS vegetation analytical team framework: Methods for collection, development, and use of vegetation response variables

USGS Publications Warehouse

Cretini, Kari F.; Visser, Jenneke M.; Krauss, Ken W.; Steyer, Gregory D.

2011-01-01

This document identifies the main objectives of the Coastwide Reference Monitoring System (CRMS) vegetation analytical team, which are to provide (1) collection and development methods for vegetation response variables and (2) the ways in which these response variables will be used to evaluate restoration project effectiveness. The vegetation parameters (that is, response variables) collected in CRMS and other coastal restoration projects funded under the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) are identified, and the field collection methods for these parameters are summarized. Existing knowledge on community and plant responses to changes in environmental drivers (for example, flooding and salinity) from published literature and from the CRMS and CWPPRA monitoring dataset are used to develop a suite of indices to assess wetland condition in coastal Louisiana. Two indices, the floristic quality index (FQI) and a productivity index, are described for herbaceous and forested vegetation. The FQI for herbaceous vegetation is tested with a long-term dataset from a CWPPRA marsh creation project. Example graphics for this index are provided and discussed. The other indices, an FQI for forest vegetation (that is, trees and shrubs) and productivity indices for herbaceous and forest vegetation, are proposed but not tested. New response variables may be added or current response variables removed as data become available and as our understanding of restoration success indicators develops. Once indices are fully developed, each will be used by the vegetation analytical team to assess and evaluate CRMS/CWPPRA project and program effectiveness. The vegetation analytical teams plan to summarize their results in the form of written reports and/or graphics and present these items to CRMS Federal and State sponsors, restoration project managers, landowners, and other data users for their input.

Consumer Acceptance Comparison Between Seasoned and Unseasoned Vegetables

PubMed Central

Feng, Yiming; Albiol Tapia, Marta; Okada, Kyle; Castaneda Lazo, Nuria Blanca; Chapman‐Novakofski, Karen; Phillips, Carter

2018-01-01

Abstract Recent findings show that approximately 87% of the U.S. population fail to meet the vegetable intake recommendations, with unpleasant taste of vegetables being listed as the primary reason for this shortfall. In this study, spice and herb seasoning was used to enhance palatability of vegetables, in order to increase consumer acceptance. In total, 749 panelists were screened and recruited as specific vegetable likers of the vegetable being tested or general vegetable likers. Four sessions were designed to evaluate the effect of seasoning within each type of vegetable, including broccoli, cauliflower, carrot, and green bean. Each panelist was only allowed to participate in one test session to evaluate only one vegetable type, so as to mitigate potential learning effect. Overall, the results showed that seasoned vegetables were significantly preferred over unseasoned vegetables (P < 0.001), indicating the sensory properties were significantly improved with seasoning. When general vegetable likers and specific vegetable likers were compared in terms of their preference between seasoned and unseasoned vegetables, the pattern varied across different vegetables; however, general trend of seasoned vegetable being preferred remained. The findings from this study demonstrate the effect of seasoning in enhancing consumer liking of vegetables, which may lead to increased consumption to be assessed in future studies. Practical Application To improve the sensory properties of vegetables, masking the bitter taste of vegetables using spice and herb seasoning are gaining increasing attention. Our findings suggest that the overall liking of vegetables could be improved by incorporating spice and herb seasonings that are specifically formulated for each vegetable. Ultimately, developing and commercializing spice and herb seasonings may aid to increase vegetable consumption, as well as expanding the vegetable seasoning market. PMID:29337353

Consumer Acceptance Comparison Between Seasoned and Unseasoned Vegetables.

PubMed

Feng, Yiming; Albiol Tapia, Marta; Okada, Kyle; Castaneda Lazo, Nuria Blanca; Chapman-Novakofski, Karen; Phillips, Carter; Lee, Soo-Yeun

2018-02-01

Recent findings show that approximately 87% of the U.S. population fail to meet the vegetable intake recommendations, with unpleasant taste of vegetables being listed as the primary reason for this shortfall. In this study, spice and herb seasoning was used to enhance palatability of vegetables, in order to increase consumer acceptance. In total, 749 panelists were screened and recruited as specific vegetable likers of the vegetable being tested or general vegetable likers. Four sessions were designed to evaluate the effect of seasoning within each type of vegetable, including broccoli, cauliflower, carrot, and green bean. Each panelist was only allowed to participate in one test session to evaluate only one vegetable type, so as to mitigate potential learning effect. Overall, the results showed that seasoned vegetables were significantly preferred over unseasoned vegetables (P < 0.001), indicating the sensory properties were significantly improved with seasoning. When general vegetable likers and specific vegetable likers were compared in terms of their preference between seasoned and unseasoned vegetables, the pattern varied across different vegetables; however, general trend of seasoned vegetable being preferred remained. The findings from this study demonstrate the effect of seasoning in enhancing consumer liking of vegetables, which may lead to increased consumption to be assessed in future studies. To improve the sensory properties of vegetables, masking the bitter taste of vegetables using spice and herb seasoning are gaining increasing attention. Our findings suggest that the overall liking of vegetables could be improved by incorporating spice and herb seasonings that are specifically formulated for each vegetable. Ultimately, developing and commercializing spice and herb seasonings may aid to increase vegetable consumption, as well as expanding the vegetable seasoning market. © 2018 The Authors Journal of Food Science published by Wiley Periodicals, Inc. on behalf of Institute of Food Technologists.

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less

Synergy between Sentinel-1 radar time series and Sentinel-2 optical for the mapping of restored areas in Danube delta

NASA Astrophysics Data System (ADS)

Niculescu, Simona; Lardeux, Cédric; Hanganu, Jenica

2018-05-01

Wetlands are important and valuable ecosystems, yet, since 1900, more than 50 % of wetlands have been lost worldwide. An example of altered and partially restored coastal wetlands is the Danube Delta in Romania. Over time, human intervention has manifested itself in more than a quarter of the entire Danube surface. This intervention was brutal and has rendered ecosystem restoration very difficult. Studies for the rehabilitation / re-vegetation were started immediately after the Danube Delta was declared as a Biosphere Reservation in 1990. Remote sensing offers accurate methods for detecting and mapping change in restored wetlands. Vegetation change detection is a powerful indicator of restoration success. The restoration projects use vegetative cover as an important indicator of restoration success. To follow the evolution of the vegetation cover of the restored areas, satellite images radar and optical of last generation have been used, such as Sentinel-1 and Sentinel-2. Indeed the sensor sensitivity to the landscape depends on the wavelength what- ever radar or optical data and their polarization for radar data. Combining this kind of data is particularly relevant for the classification of wetland vegetation, which are associated with the density and size of the vegetation. In addition, the high temporal acquisition frequency of Sentinel-1 which are not sensitive to cloud cover al- low to use temporal signature of the different land cover. Thus we analyse the polarimetric and temporal signature of Sentinel-1 data in order to better understand the signature of the different study classes. In a second phase, we performed classifications based on the Random Forest supervised classification algorithm involving the entire Sentinel-1 time series, then starting from a Sentinel-2 collection and finally involving combinations of Sentinel-1 and -2 data.

Present, Future, and Novel Bioclimates of the San Francisco, California Region

PubMed Central

Torregrosa, Alicia; Taylor, Maxwell D.; Flint, Lorraine E.; Flint, Alan L.

2013-01-01

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space. PMID:23526985

Present, future, and novel bioclimates of the San Francisco, California region

USGS Publications Warehouse

Torregrosa, Alicia; Taylor, Maxwell D.; Flint, Lorraine E.; Flint, Alan L.

2013-01-01

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 2; Implementation, Analysis and Validation

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Samanta, Arindam; Schull, Mitchell A.; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramajrushna R,; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia

USGS Publications Warehouse

Wakie, Tewodros; Evangelista, Paul H.; Jarnevich, Catherine S.; Laituri, Melinda

2014-01-01

We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species-occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

Water temperature differences by plant community and location in re-established wetlands in the Sacramento-San Joaquin Delta, California, July 2005 to February 2008

USGS Publications Warehouse

Crepeau, Kathryn L.; Miller, Robin L.

2014-01-01

Rates of carbon storage in wetlands are determined by the balance of its inputs and losses, both of which are affected by environmental factors such as water temperature and depth. In the autumn of 1997, the U.S. Geological Survey re-established two wetlands with different shallow water depths—about 25 and 55 centimeters deep—to investigate the potential to reverse subsidence of delta islands by preserving and accumulating organic substrates derived from plant biomass inputs over time. Because cooler water temperatures can slow decomposition rates and increase accretion of plant biomass, water temperature was recorded from July 2005 to February 2008 in the deeper of the two wetlands, where areas of emergent and submerged vegetation persisted throughout the study, to assess differences in water temperature between the two vegetation types. Water temperature was compared at three depths in the water column between areas of emergent and submerged vegetation and between areas near the water inflow and in the wetland interior in both vegetation types. The latter comparison was a way of evaluating the effect of the length of time water had resided in the wetland on water temperatures. There were statistically significant differences in water temperature at all depths between the two vegetation types. Overall, in areas of emergent marsh vegetation, the mean water temperature at the surface was 1.4 degrees Celsius (°C) less than it was in areas of submerged vegetation; however, when analyses accounted for the changes in temperature due to seasonal and diurnal cycles, differences in the mean water temperature between the vegetation types were even greater than this. For example, in the spring, the mean temperatures in areas of emergent marsh vegetation at the surface, mid-point, and near the sediment in the water column were 2.0, 2.3, and 2.1 °C less, respectively, than water temperatures in areas of submerged vegetation. When diurnal changes in temperature were accounted for by comparing temperatures in mid-afternoon (at 3 p.m.), water-temperature differences were even greater than the seasonal means indicated. In areas of emergent vegetation, the mean temperatures were cooler than temperatures in areas of submerged vegetation at the surface, the mid-point, and near the sediment in the water column by 3.9, 3.6, and 2.3 °C, respectively. Furthermore, from July 2005 through December 2006, water temperatures at the surface in the interior of the wetland were significantly cooler than in areas near the inflow supplying water from the San Joaquin River by 1.0 °C in areas of submerged vegetation and by 1.1 °C in areas of emergent vegetation.

Seasonal Differences in Climatic Controls of Vegetation Growth in the Beijing-Tianjin Sand Source Region of China.

NASA Astrophysics Data System (ADS)

Wang, H.

2017-12-01

Seasonal differences in climatic controls of vegetation growth in the Beijing-Tianjin Sand Source Region of China Bin He1 , Haiyan Wan11 State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China Corresponding author: Bin He, email addresses: hebin@bnu.edu.cnPhone:+861058806506, Address: Beijing Normal University, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China. Email addresses of co-authors: wanghaiyan@mail.bnu.edu.cnABSTRACTLaunched in 2000, the Beiing-Tainjin Sand Source Controlling Project (BTSSCP) is an ecological restoration project intended to prevent desertification in China. Evidence from multiple sources has confirmed increases in vegetation growth in the BTSSCP region since the initiation of the project. Precipitation and related soil moisture conditions typically are considered to be the main drivers of vegetation growth in this arid region. However, by investigating the relationships between vegetation growth and corresponding climatic factors, we identified seasonal variation in the climatic constraints of vegetation growth. In spring, vegetation growth is stimulated mainly by elevated temperature, whereas precipitation is the lead driver of summer greening. In autumn, positive effects of both temperature and precipitation on vegetation growth were observed. Furthermore, strong biosphere-atmosphere interactions were observed in this region. Spring warming promotes vegetation growth, but also reduces soil moisture. Summer greening has a strong cooling effect on land surface temperature. These results indicate that 1) precipitation-based projections of vegetation growth may be misleading; and 2) the ecological and environment consequences of ecological projects should be comprehensively evaluated. KEYWORDS: vegetation growth, climatic drivers, seasonal variation, BTSSCP

Socio-economic dietary inequalities in UK adults: an updated picture of key food groups and nutrients from national surveillance data.

PubMed

Maguire, Eva R; Monsivais, Pablo

2015-01-14

Socio-economic differences in diet are a potential contributor to health inequalities. The present study provides an up-to-date picture of socio-economic differences in diet in the UK, focusing on the consumption of three food groups and two nutrients of public health concern: fruit and vegetables; red and processed meat; oily fish; saturated fats; non-milk extrinsic sugars (NMES). We analysed data for 1491 adults (age ≥ 19 years) from the National Diet and Nutrition Survey 2008-2011. Socio-economic indicators were household income, occupational social class and highest educational qualification. Covariate-adjusted estimates for intakes of fruit and vegetables, red and processed meat, and both nutrients were estimated using general linear models. Covariate-adjusted OR for oily fish consumption were derived with logistic regression models. We observed consistent socio-economic gradients in the consumption of the three food groups as estimated by all the three indicators. Contrasting highest and lowest levels of each socio-economic indicator, we observed significant differences in intakes for the three food groups and NMES. Depending on the socio-economic indicator, highest socio-economic groups consumed up to 128 g/d more fruit and vegetables, 26 g/d less red and processed meat, and 2·6% points less NMES (P< 0·05 for all). Relative to lowest socio-economic groups, highest socio-economic groups were 2·4 to 4·0 times more likely to eat oily fish. No significant patterns in saturated fat consumption were apparent. In conclusion, socio-economic differences were identified in the consumption of food groups and one nutrient of public health importance. Aligning dietary intakes with public health guidance may require interventions specifically designed to reduce health inequalities.

The changing Arctic carbon cycle: using the past to understand terrestrial-aquatic linkages

NASA Astrophysics Data System (ADS)

Anderson, N. J.; van Hardenbroek, M.; Jones, V.; McGowan, S.; Langdon, P. G.; Whiteford, E.; Turner, S.; Edwards, M. E.

2016-12-01

Predicted shifts in terrestrial vegetation cover associated with Arctic warming are altering the delivery and processing of carbon to aquatic ecosystems. This process could determine whether lakes are net carbon sources or sinks and, because lake density is high in many Arctic areas, may alter regional carbon budgets. Lake sediment records integrate information from within the lake and its catchment and can be used quantify past vegetation shifts associated with known climatic episodes of warmer (Holocene Thermal Maximum) and cooler (Neoglacial) conditions. We analysed sediment cores located in different Arctic vegetation biomes (tundra, shrub, forested) in Greenland, Norway and Alaska and used biochemical (algal pigments, stable isotopes) remains to evaluate whether past vegetation shifts were associated with changes in ecosystem carbon processing and biodiversity. When lake catchments were sparsely vegetated and soil vegetation was limited ultra-violet radiation (UVR) screening pigments indicate clear lake waters, scarce dissolved organic carbon/ matter (DOC/M). Moderate vegetation development (birch scrub in Norway; herb tundra in Greenland) appears to enhance delivery of DOM to lakes, and to stimulate algal production which is apparently linked to heterotrophic carbon processing pathways (e.g. algal mixotrophy, nutrient release via the microbial loop). Mature forest cover (in Alaska and Norway) supressed lake autotrophic production, most likely because coloured DOM delivered from catchment vegetation limited light availability. During wetter periods when mires developed lake carbon processing also changed, indicating that hydrological delivery of terrestrial DOM is also important. Therefore, future changes in Arctic vegetation and precipitation patterns are highly likely to alter the way that arctic ecosystems process carbon. Our approach provides an understanding of how ecosystem diversity and carbon processing respond to past climate change and the difficulty of identifying the drivers of state changes in the arctic.

Polycyclic aromatic hydrocarbons (PAHs) in soils and vegetation near an e-waste recycling site in South China: concentration, distribution, source, and risk assessment.

PubMed

Wang, Yan; Tian, Zhongjing; Zhu, Haolin; Cheng, Zhineng; Kang, Meiling; Luo, Chunling; Li, Jun; Zhang, Gan

2012-11-15

This study determined the concentrations of PAHs generated from e-waste recycling activities and their potential impacts on soil, vegetation, and human health. The total PAH concentrations in soils and plants ranged from 127 to 10,600 and 199 to 2420 ng/g, respectively. Samples from an e-waste burning site had higher PAH concentrations than samples from adjacent locations. The PAHs in plants varied with plant species and tissue, and Lactuca sativa L. contained the highest PAHs of all the vegetable species. Various land use types showed different PAH concentrations in soils, with vegetable fields showing higher concentrations than paddy fields. Low molecular weight PAHs, such as phenanthrene, were the predominant congeners in soils, whereas high molecular weight PAHs, such as fluoranthene, pyrene, and benzo[a]anthracene, were enriched in plants relative to soils. Dissimilar PAH profiles in soil and the corresponding vegetation indicated that the uptake of PAHs by plants was selective. A source analysis showed that the contamination by PAHs originated primarily from the open burning of e-waste. The total daily intakes of PAHs and carcinogenic PAHs through vegetables at the e-waste dismantling site were estimated to be 279 and 108 ng/kg/d, respectively, indicating that the consumption of vegetables grown near e-waste recycling sites is risky and should be completely avoided. Copyright © 2012 Elsevier B.V. All rights reserved.

Detection of greenbug infestation on wheat using ground-based radiometry

NASA Astrophysics Data System (ADS)

Yang, Zhiming

Scope of methods of study. The purpose of this greenhouse study was to characterize stress in wheat caused by greenbugs using ground-based radiometry. Experiments were conducted to (a) identify spectral bands and vegetation indices sensitive to greenbug infestation; (b) differentiate stress caused due to greenbugs from water stress; (c) examine the impacts of plant growth stage on detection of greenbug infestation; and (d) compare infestations due to greenbug and Russian wheat aphid. Wheat (variety-TAM 107) was planted (seed spacing 1 in. x 3 in.) in plastic flats with dimension 24 in. x 16 in. x 8.75 in. Fifteen days after sowing, wheat seedlings were infested with greenbugs (biotype-E). Nadir measurement of canopy reflectance started the day after infestation and lasted until most infested plants were dead. Using a 16-band Cropscan radiometer, spectral reflectance data were collected daily (between 13:00--14:00 hours) and 128 vegetation indices were derived in addition to greenbug counts per tiller. Using SAS PROC MIXED, sensitivity of band and vegetation indices was identified based on Threshold Day. Subsequent to Threshold Day there was a consistent significant spectral difference between control and infested plants. Sensitivity of band and vegetation indices was further examined using correlation and relative sensitivity analyses. Findings and conclusions. Results show that it is possible to detect greenbug-induced stress on wheat using hand-held radiometers, such as Cropscan. Band 694 nm and the ratio-based vegetation index (RVI) derived from the band 694 nm and 800 nm were identified as most sensitive to greenbug infestation. Landsat TM bands and their derived vegetation indices also show potential for detecting wheat stress caused by greenbug infestation. Also, RVIs particularly derived using spectral band 694 nm and 800 nm were found useful in differentiating greenbug infestation from water stress. Furthermore, vegetation indices such as Normalized total Pigment to Chlorophyll Index (NPCI) could be used to distinguish greenbug infestation and infestation caused by Russian wheat aphid. Finally, stress was detected in a shorter time interval when wheat plants were infested with greenbugs at two-leaf stage than wheat plants infested at tillering stage. This study demonstrated the utility of adopting remote sensing techniques for detecting greenbug infestation on wheat. Further field-based studies are suggested to apply the technology that has great potential for integrated pest management.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Performance of Vegetation Indices for Wheat Yield Forecasting for Punjab, Pakistan

NASA Astrophysics Data System (ADS)

Dempewolf, J.; Becker-Reshef, I.; Adusei, B.; Barker, B.

2013-12-01

Forecasting wheat yield in major producer countries early in the growing season allows better planning for harvest deficits and surplus with implications for food security, world market transactions, sustaining adequate grain stocks, policy making and other matters. Remote sensing imagery is well suited for yield forecasting over large areas. The Normalized Difference Vegetation Index (NDVI) has been the most-used spectral index derived from remote sensing imagery for assessing crop condition of major crops and forecasting crop yield. Many authors have found that the highest correlation between NDVI and yield of wheat crops occurs at the height of the growing season when NDVI values and photosynthetic activity of the wheat plants are at their relative maximum. At the same time NDVI saturates in very dense and vigorous (healthy, green) canopies such as wheat fields during the seasonal peak and shows significantly reduced sensitivity to further increases in photosynthetic activity. In this study we compare the performance of different vegetation indices derived from space-borne red and near-infrared spectral reflectance measurements for wheat yield forecasting in the Punjab Province, Pakistan. Areas covered by wheat crop each year were determined using a time series of MODIS 8-day composites at 250 m resolution converted to temporal metrics and classified using a bagged decision tree approach, driven by classified multi-temporal Landsat scenes. Within the wheat areas we analyze and compare wheat yield forecasts derived from three different satellite-based vegetation indices at the peak of the growing season. We regressed in turn NDVI, Wide Dynamic Range Vegetation Index (WDRVI) and the Vegetation Condition Index (VCI) from the four years preceding the wheat growing season 2011/12 against reported yield values and applied the regression equations to forecast wheat yield for the 2011/12 season per district for each of 36 Punjab districts. Yield forecasts overall corresponded well with reported values. NDVI-based forecasts showed high correlations of r squared = 0.881 and RMSE 11%. The VCI performed similarly well with r squared = 0.886 and RMSE 11%. WDRVI performed better than either of the other indices with r squared = 0.909 and RMSE 10%, probably due to the increased sensitivity of the index at high values. Wheat yields in Pakistan show on average a slow but steady annual increase but overall are comparatively stable due to the fact that the majority of fields are irrigated. The next steps in this study will be to compare NDVI- with WDRVI-based yield forecasts in other environments dominated by rain-fed agriculture, such as Ukraine, Australia and the United States.

Enhancement of Antioxidant Quality of Green Leafy Vegetables upon Different Cooking Method

PubMed Central

Hossain, Afzal; Khatun, Mst. Afifa; Islam, Mahfuza; Huque, Roksana

2017-01-01

Antioxidant rich green leafy vegetables including garden spinach leaf, water spinach leaf, Indian spinach leaf, and green leaved amaranth were selected to evaluate the effects of water boiling and oil frying on their total phenolic content (TPC), total flavonoid content (TFC), reducing power (RP), and antioxidant capacity. The results revealed that there was a significant increase in TPC, TFC, and RP in all the selected vegetables indicating the effectiveness of the cooking process on the antioxidant potential of leafy vegetables. Both cooking processes enhanced significantly (P<0.05) the radical scavenging ability, especially the oil fried samples showed the highest values. There is a significant reduction in the vitamin C content in all the vegetables due to boiling and frying except in the Indian spinach leaf. However, the present findings suggest that boiling and frying can be used to enhance the antioxidant ability, by increasing the bioaccessibility of health-promoting constituents from the four vegetables investigated in this study. PMID:29043220

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Imbernon, J.; Dedieu, G.; Hautecoeur, O.; Lagouarde, J. P.

1989-01-01

NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRPT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

Effect of combination processing on the microbial, chemical and sensory quality of ready-to-eat (RTE) vegetable pulav

NASA Astrophysics Data System (ADS)

Kumar, R.; George, Johnsy; Rajamanickam, R.; Nataraju, S.; Sabhapathy, S. N.; Bawa, A. S.

2011-12-01

Effect of irradiation in combination with retort processing on the shelf life and safety aspects of an ethnic Indian food product like vegetable pulav was investigated. Gamma irradiation of RTE vegetable pulav was carried out at different dosage rates with 60Co followed by retort processing. The combination processed samples were analysed for microbiological, chemical and sensory characteristics. Microbiological analysis indicated that irradiation in combination with retort processing has significantly reduced the microbial loads whereas the chemical and sensory analysis proved that this combination processing is effective in retaining the properties even after storage for one year at ambient conditions. The results also indicated that a minimum irradiation dosage at 4.0 kGy along with retort processing at an F0 value of 2.0 is needed to achieve the desired shelf life with improved organoleptic qualities.

Vegetative response to water availability on the San Carlos Apache Reservation

USGS Publications Warehouse

Petrakis, Roy; Wu, Zhuoting; McVay, Jason; Middleton, Barry R.; Dye, Dennis G.; Vogel, John M.

2016-01-01

On the San Carlos Apache Reservation in east-central Arizona, U.S.A., vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have significant ecological, cultural, and economic value for the Tribe. This value extends beyond the tribal lands and across the Western United States. Vegetation across the Southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to fluctuating water availability conditions. We used the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Modified Soil Adjusted Vegetation Index II (MSAVI2) to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The study period covered 2002 through 2014 and focused on a region within the San Carlos Apache Reservation. We determined that grassland and woodland had a similar moderate to strong, year-round, positive relationship with precipitation as well as with summer SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple, dominant vegetation types to seasonal and inter-annual water availability. This research demonstrates that multi-temporal remote sensing imagery can be an effective tool for the large scale detection of vegetation response to adverse impacts from climate change and support potential management practices such as increased monitoring and management of drought-affected areas. Different vegetation types displayed various responses to water availability, further highlighting the need for individual management plans for forest and woodland, especially considering the projected drier conditions in the Southwest U.S. and other arid or semi-arid regions around the world.

Performance of different vegetation indices in assessing degradation of community grazing lands in Indian arid zone

NASA Astrophysics Data System (ADS)

Kumar, Suresh; Bastin, Gary; Friedel, Margaret; Narain, Pratap; Saha, D. K.; Ahuja, U. R.; Mathur, B. K.

2006-12-01

Vegetation in arid community grazinglands shows monsoonal growth. Its matching phenology with crops makes its detection difficult during July to September. While crops are harvested during September-October, using satellite data thereafter for the natural vegetation seems most appropriate but by then it turns dry. An index capable of sensing dry vegetation was needed since conventional NDVI is sensitive to greenness of vegetation. Performance of NDVI vis-à-vis another index, PD54, based on cover was therefore compared in assessing degradation of grazinglands. The PD54 was used to isolate anthropogenic impacts from environmental induced degradation by analyzing satellite images from dry and wet seasons. Substantial absence of appreciable vegetation response indicated poor resilience and severe degradation. Five grazinglands in Shergarh tehsil of Jodhpur district in Rajasthan were studied following above approach. Ground radiometric observations were recorded. Satellite data of IRS 1C/1D/P6 with LISS 3 sensor for both pre and post monsoon season were acquired for three contrasting wet-dry season events. These were geometrically registered and radiometrically calibrated to calculate an index of vegetation cover PD54 as well as NDVI. PD54 is a perpendicular vegetation index based on the green and red spectral band width. The PD54 and NDVI calculated from spectro-radiometer were related to vegetation cover measured on ground in permanent plots. This confirmed that PD54 was superior index for estimating cover in arid dry grasslands. These ground vegetation trends in a good rainfall year (2001) with drought year (2002) were related with satellite data for a protected and four unprotected grazinglands. NDVI failed to detect any vegetation in protected areas supporting excellent grass cover which was succinctly brought out by PD54. Successful validation of PD54 in detecting degradation of 13 additional sites confirmed its efficacy. These findings have implication in forage availability assessments, forage forecasting, drought preparedness, pastoralism and transhumance.

Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: A model study

USGS Publications Warehouse

Jiang, J.; DeAngelis, D.L.; Smith, T. J.; Teh, S.Y.; Koh, H. L.

2012-01-01

Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback. ?? 2011 Springer Science+Business Media B.V. (outside the USA).

The Hydrological Regimes Brought by the Three Gorges Project Affected Riparian Vegetation Distribution and Diversity in 2009 and 2010

NASA Astrophysics Data System (ADS)

Miao, Ling-Feng; Liu, Wei-Wei; Yang, Fan

2017-01-01

Post-dam riparian vegetations affected by the new hydrological regimes in the Three Gorges Reservoir (TGR) were investigated in 2009 and 2010, respectively. The investigation in 2009 showed that about 231 vascular plant species belonging to 169 genera of 61 families were distributed in the water-level-fluctuation zone (WLFZ) of the (TGR). Three vegetation types, including Chuanjiang, Gorge, and other vegetation types, were classified efficiently via cluster analysis. Alpha diversity analysis indicated that species richness gradually decreased with decreasing elevation. Beta diversity analysis indicated that high environment heterogeneity was existed between the lower section and the other two sections, and environment homogeneity was also existed between middle section and upper section. Using the analysis of the field growth in the 2009 and 2010 field surveys as bases, we proposed a list of perennial herb species and woody species that may potentially occurred in the WLFZ of the TGR. In addition, we predicted plant community structural changes in the different altitude sections of WLFZ in the future.

Biomethanation of vegetable market waste in an anaerobic baffled reactor: Effect of effluent recirculation and carbon mass balance analysis.

PubMed

Gulhane, Madhuri; Khardenavis, Anshuman A; Karia, Sneha; Pandit, Prabhakar; Kanade, Gajanan S; Lokhande, Satish; Vaidya, Atul N; Purohit, Hemant J

2016-09-01

In the present study, feasibility of biomethanation of vegetable market waste in a 4-chambered anaerobic baffled reactor (ABR) was investigated at 30d hydraulic retention time and organic loading rate of 0.5gVS/L/d for one year. Indicators of process stability viz., butyrate/acetate and propionate/acetate ratios were consistent with phase separation in the different chambers, which remained unaltered even during recirculation of effluent. Chemical oxygen demand (COD) and volatile solids (VS) removal efficiencies were observed to be consistently high (above 90%). Corresponding biogas and methane yields of 0.7-0.8L/g VS added/d and 0.42-52L/g VS added/d respectively were among the highest reported in case of AD of vegetable waste in an ABR. Process efficiency of the ABR for vegetable waste methanation, which is indicated by carbon recovery factor showed that, nearly 96.7% of the input carbon considered for mass balance was accounted for in the product. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relative abundance and lengths of Kendall Warm Springs dace captured from different habitats in a specially designed trap

USGS Publications Warehouse

Gryska, A.D.; Hubert, W.A.; Gerow, K.G.

1998-01-01

A trap was designed to capture endangered Kendall Warm Springs dace Rhinichthys osculus thermalis (a subspecies of speckled dace Rhinichthys osculus) without being destructive to the habitat of the fish in Kendall Warm Springs Creek, Wyoming. Four experiments were conducted to determine differences in catch per unit effort (CPUE) and length frequencies of fish among differing habitat types. The CPUE was highest in channel habitats with current, and one experiment indicated that it was particularly high at vertical interfaces with vegetation. Longer fish were captured in channel habitats away from vegetation than in vegetated areas. The CPUE was significantly greater during the day than at night during one experiment, but no significant differences were observed among the other three experiments. The traps were easy and inexpensive to construct, could be used in a variety of stream habitats, and may have applications in other small streams for sampling small, benthic fishes.

The Importance of Temporal and Spatial Vegetation Structure Information in Biotope Mapping Schemes: A Case Study in Helsingborg, Sweden

NASA Astrophysics Data System (ADS)

Gao, Tian; Qiu, Ling; Hammer, Mårten; Gunnarsson, Allan

2012-02-01

Temporal and spatial vegetation structure has impact on biodiversity qualities. Yet, current schemes of biotope mapping do only to a limited extend incorporate these factors in the mapping. The purpose of this study is to evaluate the application of a modified biotope mapping scheme that includes temporal and spatial vegetation structure. A refined scheme was developed based on a biotope classification, and applied to a green structure system in Helsingborg city in southern Sweden. It includes four parameters of vegetation structure: continuity of forest cover, age of dominant trees, horizontal structure, and vertical structure. The major green structure sites were determined by interpretation of panchromatic aerial photographs assisted with a field survey. A set of biotope maps was constructed on the basis of each level of modified classification. An evaluation of the scheme included two aspects in particular: comparison of species richness between long-continuity and short-continuity forests based on identification of woodland continuity using ancient woodland indicators (AWI) species and related historical documents, and spatial distribution of animals in the green space in relation to vegetation structure. The results indicate that (1) the relationship between forest continuity: according to verification of historical documents, the richness of AWI species was higher in long-continuity forests; Simpson's diversity was significantly different between long- and short-continuity forests; the total species richness and Shannon's diversity were much higher in long-continuity forests shown a very significant difference. (2) The spatial vegetation structure and age of stands influence the richness and abundance of the avian fauna and rabbits, and distance to the nearest tree and shrub was a strong determinant of presence for these animal groups. It is concluded that continuity of forest cover, age of dominant trees, horizontal and vertical structures of vegetation should now be included in urban biotope classifications.

The Effect of Vegetation on Soil Water Infiltration and Retention Capacity by Improving Soil Physiochemical Property in Semi-arid Grassland

NASA Astrophysics Data System (ADS)

A, Y.; Wang, G.

2017-12-01

Water shortage is the main limiting factor for semi-arid grassland development. However, the grassland are gradually degraded represented by species conversion, biomass decrease and ecosystem structure simplification under the influence of human activity. Soil water characteristics such as moisture, infiltration and conductivity are critical variables affecting the interactions between soil parameters and vegetation. In this study, Cover, Height, Shannon-Wiener diversity index, Pielou evenness index and Richness index are served as indexes of vegetation productivity and community structure. And saturated hydraulic conductivity (Ks) and soil moisture content are served as indexes of soil water characters. The interaction between vegetation and soil water is investigated through other soil parameters, such as soil organic matter content at different vertical depths and in different degradation area (e.g., initial, transition and degraded plots). The results show that Ks significantly controlled by soil texture other than soil organic matter content. So the influence of vegetation on Ks through increasing soil organic content (SOM) might be slight. However, soil moisture content (SMC) appeared significantly positive relationship with SOM and silt content and negative relationship with sand content at all depth, significantly. This indicated that capacity of soil water storage was influenced both by soil texture and organic matter. In addition, the highest correlation coefficient of SMC was with SOM at the sub-surficial soil layer (20 40 cm). At the depth of 20 40 cm, the soil water content was relatively steady which slightly influenced by precipitation and evaporation. But it significantly influenced by soil organic matter content which related to vegetation. The correlation coefficient between SOM and SMC at topsoil layer (0 20 cm) was lowest (R2=0.36, p<0.01), which indicated the influence of vegetation on soil water content not only by soil organic matter content but also the other influential factors, such as the root water uptake, precipitation and evaporation.

Automatic summary generating technology of vegetable traceability for information sharing

NASA Astrophysics Data System (ADS)

Zhenxuan, Zhang; Minjing, Peng

2017-06-01

In order to solve problems of excessive data entries and consequent high costs for data collection in vegetable traceablility for farmers in traceability applications, the automatic summary generating technology of vegetable traceability for information sharing was proposed. The proposed technology is an effective way for farmers to share real-time vegetable planting information in social networking platforms to enhance their brands and obtain more customers. In this research, the influencing factors in the vegetable traceablility for customers were analyzed to establish the sub-indicators and target indicators and propose a computing model based on the collected parameter values of the planted vegetables and standard legal systems on food safety. The proposed standard parameter model involves five steps: accessing database, establishing target indicators, establishing sub-indicators, establishing standard reference model and computing scores of indicators. On the basis of establishing and optimizing the standards of food safety and traceability system, this proposed technology could be accepted by more and more farmers and customers.

40 shades of black: regional differences in vegetation response to a changing human influence in the Low Countries during the Dark Ages (AD 300-1000).

NASA Astrophysics Data System (ADS)

Gouw-Bouman, Marjolein T. I. J.; Donders, Timme H.; Hoek, Wim Z.

2016-04-01

During the Dark Ages, which includes the Late Roman Period (LRP, AD 300-500) and the Early Middle Ages (EMA, AD 500-1000), large scale vegetation development in Northwestern Europe is generally characterized by a forest regeneration. This forest redevelopment phase was not uniformous across the Netherlands. A comparison between existing pollen records shows that forest redevelopment started earlier and was more severe in the southern part of the Netherlands than in the northeastern Netherlands. The prevailing view advocates that the forest redevelopment is the result of a diminishing human influence on the landscape due to the collapse of the Roman Empire. Following this view, regional changes in forest regeneration are explained by varying population densities. However, existing climate-records indicate a colder and wetter climate during the Dark Ages and the geomorphological record points to a changing landscape. How and to what extent these climatic and environmental changes contributed to the changes in vegetation development or even to the decline of the Roman Empire is largely unknown. To understand the relative importance of the factors (climate, environment, economy and demography) influencing vegetation development it is important to accurately map regional differences in vegetation both on a regional and extra-regional scale. For an extra-regional overview all available pollen records in the Netherlands from this period are compiled to show differences in amplitude of the vegetation development during the Dark Ages. On a regional scale, vegetation reconstruction maps have been produced reflecting the influence of geological/geomorphological factors.

A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

The relationship between vegetation and climate in the grassland and cropland of the northern US Great Plains was investigated with Normalized Difference Vegetation Index (NDVI) (1989–1993) images derived from the Advanced Very High Resolution Radiometer (AVHRR), and climate data from automated weather stations. The relationship was quantified using a spatial regression technique that adjusts for spatial autocorrelation inherent in these data. Conventional regression techniques used frequently in previous studies are not adequate, because they are based on the assumption of independent observations. Six climate variables during the growing season; precipitation, potential evapotranspiration, daily maximum and minimum air temperature, soil temperature, solar irradiation were regressed on NDVI derived from a 10-km weather station buffer. The regression model identified precipitation and potential evapotranspiration as the most significant climatic variables, indicating that the water balance is the most important factor controlling vegetation condition at an annual timescale. The model indicates that 46% and 24% of variation in NDVI is accounted for by climate in grassland and cropland, respectively, indicating that grassland vegetation has a more pronounced response to climate variation than cropland. Other factors contributing to NDVI variation include environmental factors (soil, groundwater and terrain), human manipulation of crops, and sensor variation.

Variation of Vegetation Ecological Water Consumption and Its Response to Vegetation Coverage Changes in the Rocky Desertification Areas in South China

PubMed Central

Zhou, Jinxing; Guo, Hongyan; Cui, Ming; Liu, Yuguo; Ning, Like; Tang, Fukai

2016-01-01

Over the past several decades, rocky desertification has led to severe ecological problems in karst areas in South China. After a rocky desertification treatment project was completed, the vegetation coverage changed greatly and, consequently, increased the ecology water consumption (approximately equal to the actual evapotranspiration) of the regional vegetation. Thus, it intensified the regional water stresses. This study explored the changes in the actual evapotranspiration (ETa) response to the vegetation coverage changes in the rocky desertification areas in South China based on the precipitation (P), potential evapotranspiration (ETp) and NDVI (the normalized difference vegetation index) datasets. The revised Bagrov model was used to simulate the actual evapotranspiration changes with the supposed increasing NDVI. The results indicated that the average NDVI value was lower when the rocky desertification was more severe. The ETa, evapotranspiration efficiency (ETa/ETp) and potential humidity (P/ETp) generally increased with the increasing NDVI. The sensitivity of the ETa response to vegetation coverage changes varied due to different precipitation conditions and different rocky desertification severities. The ETa was more sensitive under drought conditions. When a drought occurred, the ETa exhibited an average increase of 40~60 mm with the NDVI increasing of 0.1 in the rocky desertification areas. Among the 5 different severity categories of rocky desertification, the ETa values’ responses to NDVI changes were less sensitive in the severe rocky desertification areas but more sensitive in the extremely and potential rocky desertification areas. For example, with the NDVI increasing of 0.025, 0.05, 0.075, and 0.1, the corresponding ETa changes increased by an average of 2.64 mm, 10.62 mm, 19.19 mm, and 27.58 mm, respectively, in severe rocky desertification areas but by 4.94 mm, 14.99 mm, 26.80, and 37.13 mm, respectively, in extremely severe rocky desertification areas. Understanding the vegetation ecological water consumption response to the vegetation coverage changes is essential for the vegetation restoration and water stresses mitigation in rocky desertification areas. PMID:27798642

Variation of Vegetation Ecological Water Consumption and Its Response to Vegetation Coverage Changes in the Rocky Desertification Areas in South China.

PubMed

Wan, Long; Tong, Jing; Zhou, Jinxing; Guo, Hongyan; Cui, Ming; Liu, Yuguo; Ning, Like; Tang, Fukai

2016-01-01

Over the past several decades, rocky desertification has led to severe ecological problems in karst areas in South China. After a rocky desertification treatment project was completed, the vegetation coverage changed greatly and, consequently, increased the ecology water consumption (approximately equal to the actual evapotranspiration) of the regional vegetation. Thus, it intensified the regional water stresses. This study explored the changes in the actual evapotranspiration (ETa) response to the vegetation coverage changes in the rocky desertification areas in South China based on the precipitation (P), potential evapotranspiration (ETp) and NDVI (the normalized difference vegetation index) datasets. The revised Bagrov model was used to simulate the actual evapotranspiration changes with the supposed increasing NDVI. The results indicated that the average NDVI value was lower when the rocky desertification was more severe. The ETa, evapotranspiration efficiency (ETa/ETp) and potential humidity (P/ETp) generally increased with the increasing NDVI. The sensitivity of the ETa response to vegetation coverage changes varied due to different precipitation conditions and different rocky desertification severities. The ETa was more sensitive under drought conditions. When a drought occurred, the ETa exhibited an average increase of 40~60 mm with the NDVI increasing of 0.1 in the rocky desertification areas. Among the 5 different severity categories of rocky desertification, the ETa values' responses to NDVI changes were less sensitive in the severe rocky desertification areas but more sensitive in the extremely and potential rocky desertification areas. For example, with the NDVI increasing of 0.025, 0.05, 0.075, and 0.1, the corresponding ETa changes increased by an average of 2.64 mm, 10.62 mm, 19.19 mm, and 27.58 mm, respectively, in severe rocky desertification areas but by 4.94 mm, 14.99 mm, 26.80, and 37.13 mm, respectively, in extremely severe rocky desertification areas. Understanding the vegetation ecological water consumption response to the vegetation coverage changes is essential for the vegetation restoration and water stresses mitigation in rocky desertification areas.

Vegetation burn severity mapping using Landsat-8 and WorldView-2

USGS Publications Warehouse

Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

2015-01-01

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

NASA Astrophysics Data System (ADS)

Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

2016-08-01

Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

Characterization of Vegetation Change in a Sub-Arctic Mire using Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

DelGreco, J. L.; McArthur, K. J.; Palace, M. W.; Herrick, C.; Garnello, A.; Finnell, D.; McCalley, C. K.; Anderson, S. M.; Varner, R. K.

2015-12-01

Climate change is impacting northern ecosystems through the thawing of the permafrost, which has resulted in changes to plant communities and greenhouse gas emissions, such as carbon dioxide (CO2) and methane (CH4). These greenhouse gases are of concern due to their potential feedbacks which create a warmer climate, thus increasing permafrost thawing. Our study focuses on how vegetation type differs in areas that have been impacted by thawing permafrost at Stordalen Mire located in Abisko, Sweden. To estimate change in vegetation communities, field-based measurements combined with remotely sensed image data was used. 75 randomized square-meter plots were measured for vegetation composition and classified into one of five site-types, each representing a different stage of permafrost degradation. New high-resolution imagery (1 cm) was collected using Unmanned Aerial Vehicles (UAV) providing insight into the spatial patterning, characterizations, and changes of these communities. The UAV imagery was georectified using high precision GPS points collected across the mire. The imagery was then examined using a neural network analysis to estimate cover type across the mire. This 2015 cover type classification was then compared to previous UAV imagery taken on July 2014 to analyze changes in vegetation distribution as an indication of permafrost thaw. Hummock sites represent intact permafrost and have lost 21.5% coverage since 2014, while tall gramminoid sites, which indicate fully thawed sites, have increased coverage by 12.1%. A discriminate function analysis showed that site types can be differentiated based on species composition, thus showing that vegetation differs significantly across the thaw gradient. Using average flux rates of CH4 from each cover type reported previously, the percent of CH4 emitted over the mire was estimated for 2014 and 2015. Comparing both estimates, CH4 emissions increased with a flux change of 5604.5 g CH4/day. Our estimates of vegetation change may be used to parameterize simulation models and create future scenarios of how the vegetation cover will change in response to climate change. Data from this study will also help to explain how the ecology of the subarctic peatlands, now a carbon sink, may be on its way to changing into a source of carbon.

Modelling the interactions between vegetation and climate from the Cretaceous to the Eocene

NASA Astrophysics Data System (ADS)

Loptson, Claire; Lunt, Dan; Francis, Jane

2013-04-01

The climates during the Cretaceous (~144 to 66 Ma) and the early Eocene (~56 to 48 Ma) were much warmer than the present day. Atmospheric CO2 levels for these past climates have a large uncertainty associated with them, but were possibly as high as 2000 to 3000 ppm for the early Eocene (Beerling and Royer, 2011; Lowenstein and Demicco, 2006) and maximum values are thought to range from 800 to 1800 ppm during the Cretaceous (Royer et al., 2012). Current modelling efforts have had great difficulty in replicating the shallow latitudinal temperature gradient indicated by proxy data for these time periods (e.g. Heinemann et al., 2009; Winguth et al., 2010; Shellito et al., 2009). Mechanisms that can result in such a low temperature gradient have not been found (Winguth et al., 2010; Beerling et al., 2011; Sloan and Morrill, 1998), but a contributing factor could be that not all climate feedbacks are included in these models. Vegetation feedbacks have been shown to be especially important (e.g. Otto-Bliesner and Upchurch, 1997; Bonan, 2008) so by including a more accurate representation of vegetation in the climate model, the model-data discrepancies may be reduced. A fully coupled atmosphere-ocean GCM, HadCM3L, coupled to a dynamic global vegetation model (TRIFFID), was used to simulate the climate and the predicted vegetation distributions for and the early Eocene and 12 different time slices representing different ages throughout the Cretaceous at 4x pre-industrial CO2. The only difference in the way these simulations were set up are different boundary conditions that are specific to that time period, e.g. different solar constants and paleogeographies. This allows a direct comparison between the time slices. We present the changes in climate, and therefore vegetation, during the Cretaceous due to changes in these boundary conditions alone, with a focus on Antarctica. Additional Eocene simulations were also carried out with a) fixed globally-uniform vegetation and b) a prescribed vegetation distribution as predicted by the TRIFFID model, but with TRIFFID turned off i.e. the vegetation distribution was fixed, not dynamic. All three Eocene simulations were also run for 2x pre-industrial CO2, allowing the effects of changing CO2 on climate and vegetation to be analysed. We present the effects of different vegetation representations included in a GCM on the early Eocene climate. In addition, climate sensitivity and sensitivity of vegetation to atmospheric CO2 concentration during the early Eocene are investigated. Modelled vegetation types are compared to fossil data to evaluate the performance of TRIFFID for these paleoclimate simulations.

Differences in Perceptions of the Food Environment Between African American Men Who Did and Did Not Consume Recommended Levels of Fruits and Vegetables.

PubMed

Griffith, Derek M; Cornish, Emily K; McKissic, Sydika A; Dean, Donnatesa A L

2016-12-01

African American men have high rates of chronic disease morbidity and mortality associated with their low rates of fruit and vegetable consumption. In an effort to inform tailored behavioral interventions for this demographic, we sought to assess if men with healthier eating practices viewed their environment differently than those who ate less healthy. We segmented participants into high/low healthy eating categories based on the daily fruit and vegetable serving recommendations from the U.S. Department of Agriculture to determine if differences among environmental and social barriers were associated with different healthy eating patterns. We found key differences between men who consumed the recommended amount of fruits and vegetables (five or more servings/day, high healthy eating) and men who did not (low healthy eating). Men who consumed recommended levels of fruits and vegetables found eating healthy to be easy, and they described how they were able to overcome barriers such as the cost of healthy food, their limited knowledge of nutrition guidelines, and their lack of willpower to make healthier food choices. Men with healthier eating practices also identified individuals, plans, and resources they used or could use to help them have healthier eating practices. Conversely, men who were not eating recommended levels of fruits and vegetables also found eating healthy to be easy; however, they identified barriers limiting their access and did not articulate strategies to overcome these perceived barriers. Many of these men also indicated that they did not have social support to help them engage in healthier eating practices. These findings highlight the need to understand how African American men's conceptualization of environmental resources and social supports relate to their eating practices. © 2016 Society for Public Health Education.

Successive monitoring surveys of selected banned and restricted pesticide residues in vegetables from the northwest region of China from 2011 to 2013.

PubMed

Yu, Yan; Hu, Senke; Yang, Yuxuan; Zhao, Xiaodan; Xue, Jianjun; Zhang, Jinghua; Gao, Song; Yang, Aimin

2017-08-02

A wide range of pesticides is applied for crop protection in vegetable cultivation in China. Regulation of pesticide maximum residue limits (MRLs) in vegetables is established but not fully enforced. And pesticide residues in vegetables were not well monitored. This study conducted the monitoring surveys from 2011 to 2013 to investigate the pesticides in vegetables in the northwest region of China. A multi-residue gas chromatography/mass spectrometry method (GC/MS) was used in determination of pesticides in vegetable samples. The χ 2 test was used to compare the concentration of pesticide residues. A total of 32 pesticide residues were detected in 518 samples from 20 types of vegetables in this study. 7.7% of the detected pesticide residues exceeded the MRLs. The percentages of residues that exceeded the MRLs for leafy, melon and fruit, and root vegetables were 11.2%, 5.1%, and 1.6%, respectively. There was no seasonal difference in the proportion of samples that exceeded the MRLs in different vegetables. A total of 84.3% (27/32) pesticides were detected at concentrations that exceeded MRLs. And of the 27 pesticides that exceeded the MRLs, 11 (40.7%) were banned for use in agriculture. The most frequently detected pesticides were Malathion (9.4%), Dichlorvos (8.7%), and Dimethoate (8.1%). The observed high rate of pesticides detected and high incidence of pesticide detection exceeding their MRLs in the commonly consumed vegetables indicated that the Good Agricultural Practices (GAP) may not be well followed. The management of pesticide use and control should be improved. Well-developed training programs should be initiated to improve pesticide application knowledge for farmers.

Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa.

PubMed

Mukwada, Geoffrey; Manatsa, Desmond

2018-05-24

The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.

Optical Sensing of Ecosystem Carbon Fluxes Combining Spectral Reflectance Indices with Solar Induced Fluorescence

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Middleton, E.; Corp, L. A.; Campbell, P. K.; Kustas, W. P.

2014-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations are required to observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. The sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. PRI detects changes in Xanthophyll cycle pigments using reflectance at 531 nm compared to a reference band at 570 nm. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.

Optical Sensing of Ecosystem Carbon Fluxes Combining Spectral Reflectance Indices with Solar Induced Fluorescence

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Corp, L.; Campbell, P. K.; Cook, B. D.; Middleton, E.; Cheng, Y.; Zhang, Q.; Russ, A.; Kustas, W. P.

2013-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations can observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. This sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. PRI detects changes in Xanthophyll cycle pigments using reflectance at 531 nm compared to a reference band at 570 nm. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.

On modelling the relationship between vegetation greenness and water balance and land use change.

PubMed

Berry, Sandra L; Mackey, Brendan

2018-06-13

Here we sought a biologically meaningful, climate variable that captures water-energy availability and is suitable for high resolution (250 m × 250 m) modelling of the fraction of photosynthetically active radiation intercepted by the sunlit canopy (F V ) derived from a 10-year (July 2000 - June 2010) time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized difference vegetation index (NDVI) satellite imagery for Australia. The long-term mean annual evaporation deficit, and mean annual water availability indices all yielded strong linear relationships with mean F V ([Formula: see text], %). We hypothesised whether some of the scatter about the relationships was related to land-use changes that have disrupted the vegetation-climate-soil equilibrium. Using continental-scale spatial data layers of protected area status and vegetation condition classes we repeated our analyses with restricted datasets. [Formula: see text] of intact native vegetation within protected areas was greater than all modified vegetation classes. There was a consistent decline in the slopes of the regression relationships with increasing intensity of woody vegetation clearing and livestock grazing. Where native vegetation has been transformed by land use there was a 25% reduction in predicted [Formula: see text].

Adherence to dietary guidelines for fruit, vegetables and fish among older Dutch adults; the role of education, income and job prestige.

PubMed

Dijkstra, S C; Neter, J E; Brouwer, I A; Huisman, M; Visser, M

2014-01-01

Little is known about socio-economic differences in dietary intake among older adults. In this study we describe self-reported dietary adherence to the fruit, vegetables and fish guidelines among older Dutch adults and investigate the independent associations of three socio-economic status (SES) indicators with adherence to these guidelines. Cross sectional data-analyses. The Longitudinal Aging Study Amsterdam (LASA), the Netherlands. 1057 community dwelling older adults, aged 55-85 years. Fruit, vegetable and fish intake was assessed using a short food frequency questionnaire. We measured SES using self-reported levels of education, household income and occupational prestige. 82.5% of the respondents reported to adhere to the fruit guideline, 65.1% to the vegetables guideline, and 31.7% to the fish guideline. After adjustment for confounders and the other two SES indicators, respondents in the lowest education group adhered less often to the vegetables guideline (OR 0.39 (95% CI 0.22-0.70)) compared to those in the highest education group. Respondents in the lowest income group adhered less often to the fruit (0.44 (95 % CI 0.22-0.91) and fish guideline (OR 0.55 (95% CI 0.33-0.91) compared to those in the highest groups. Occupational prestige was not independently associated with adherence any the guidelines. Self-reported adherence to the fruit, vegetables and fish guidelines among older adults can be improved and particularly in those with a low SES. Education and income have independent and unique contributions to dietary adherence. Future research should investigate potential pathways through which these specific SES indicators influence dietary adherence.

[Study on nutrient and salinity in soil covered with different vegetations in Shuangtaizi estuarine wetlands].

PubMed

Song, Xiao-Lin; Lü, Xian-Guo; Zhang, Zhong-Sheng; Chen, Zhi-Ke; Liu, Zheng-Mao

2011-09-01

Nutrient elements and salinity in soil covered by different vegetations including Phragmites australis (Clay.) Trin., Typha orientalis Presl., Puccinellia distans Parl, and Suaeda salsa in Shuangtaizi estuarine wetlands were investigated to study their distribution characteristics and to reveal the nutrient element variation during the vegetation succession processes. Results indicated that total potassium, total phosphorus and salinity were different significantly in soil between different plant communities while available phosphorus, total nitrogen, available nitrogen, available potassium, total sulfur, iron and soil organic carbon were different insignificantly. Correlation analysis suggested that soil organic carbon were related significantly to total nitrogen, available phosphorus, available potassium, which implied that decomposition of plant litter might be the mail source of soil nitrogen and available nutrient. Salinity was significantly related to total phosphorus and iron in soil. In Shuangtaizi estuarine wetland soil, ratios of carbon to nitrogen (R(C/N)) was in the range of 12.21-26.33 and the average value was 18.21, which was higher than 12.0. It indicated that soil organic carbon in Shuangtaizi estuarine mainly came from land but not ocean and plants contributed the most of soil organic matters. There was no significant difference in R(C/N) between soil from the four plant communities (F = 1.890, p = 0.151). R(C/N) was related significantly to sol salinity (r = 0.346 3, p = 0.035 8) and was increasing with soil salinity.

Use of Normalized Difference Water Index for monitoring live fuel moisture

Treesearch

D.A. Roberts; P.E. Dennison; S.H. Peterson; J. Rechel

2006-01-01

Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were compared for monitoring live fuel moisture in a shrubland ecosystem. Both indices were calculated from 500m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data covering a 33-month period from 2000 to 2002. Both NDVI and NDWI were...

Interaction of dietary antioxidants in vivo: how fruit and vegetables prevent disease?

PubMed

Eastwood, M A

1999-09-01

Epidemiological studies indicate that fruit and vegetables are health-promoting and protective against disease, particularly cardiovascular disease and cancer. Possible plant nutrients providing this protection include antioxidants and dietary fibre. Clinical trials with antioxidant supplements give inconsistent results for protection against lung cancer in smokers, invasive cervical cancer, oesophageal and gastric cancers, colorectal polyps and coronary heart disease. The antioxidants used in trials may be contributing to a more complex system. Antioxidants have differing solubilities which partition across the phases of tissues, cells and macromolecular structures: water-soluble ascorbate, glutathione and urate; lipid-soluble tocopherols and carotenoids, and intermediatory-soluble flavonoids and hydroxycinnamic acids. The health protection provided by fruit and vegetables could arise through an integrated reductive environment delivered by plant antioxidants of differing solubility in each of the tissue, cellular and macromolecular phases.

[Effects of superphosphate addition on NH3 and greenhouse gas emissions during vegetable waste composting].

PubMed

Yang, Yan; Sun, Qin-ping; Li, Ni; Liu, Chun-sheng; Li, Ji-jin; Liu, Ben-sheng; Zou, Guo-yuan

2015-01-01

To study the effects of superphosphate (SP) on the NH, and greenhouse gas emissions, vegetable waste composting was performed for 27 days using 6 different treatments. In addition to the controls, five vegetable waste mixtures (0.77 m3 each) were treated with different amounts of the SP additive, namely, 5%, 10%, 15%, 20% and 25%. The ammonia volatilization loss and greenhouse gas emissions were measured during composting. Results indicated that the SP additive significantly decreased the ammonia volatilization and greenhouse gas emissions during vegetable waste composting. The additive reduced the total NH3 emission by 4.0% to 16.7%. The total greenhouse gas emissions (CO2-eq) of all treatments with SP additives were decreased by 10.2% to 20.8%, as compared with the controls. The NH3 emission during vegetable waste composting had the highest contribution to the greenhouse effect caused by the four different gases. The amount of NH3 (CO2-eq) from each treatment ranged from 59.90 kg . t-1 to 81.58 kg . t-1; NH3(CO2-eq) accounted for 69% to 77% of the total emissions from the four gases. Therefore, SP is a cost-effective phosphorus-based fertilizer that can be used as an additive during vegetable waste composting to reduce the NH3 and greenhouse gas emissions as well as to improve the value of compost as a fertilizer.

Functional diversity, succession, and human-mediated disturbances in raised bog vegetation.

PubMed

Dyderski, Marcin K; Czapiewska, Natalia; Zajdler, Mateusz; Tyborski, Jarosław; Jagodziński, Andrzej M

2016-08-15

Raised and transitional bogs are one of the most threatened types of ecosystem, due to high specialisation of biota, associated with adaptations to severe environmental conditions. The aim of the study was to characterize the relationships between functional diversity (reflecting ecosystem-shaping processes) of raised bog plant communities and successional gradients (expressed as tree dimensions) and to show how impacts of former clear cuts may alter these relationships in two raised bogs in 'Bory Tucholskie' National Park (N Poland). Herbaceous layers of the plant communities were examined by floristic relevés (25m(2)) on systematically established transects. We also assessed patterns of tree ring widths. There were no relationships between vegetation functional diversity components and successional progress: only functional dispersion was negatively, but weakly, correlated with median DBH. Lack of these relationships may be connected with lack of prevalence of habitat filtering and low level of competition over all the successional phases. Former clear cuts, indicated by peaks of tree ring width, influenced the growth of trees in the bogs studied. In the bog with more intensive clear cuts we found more species with higher trophic requirements, which may indicate nutrient influx. However, we did not observe differences in vegetation patterns, functional traits or functional diversity indices between the two bogs studied. We also did not find an influence of clear cut intensity on relationships between functional diversity indices and successional progress. Thus, we found that alteration of the ecosystems studied by neighbourhood clear cuts did not affect the bogs strongly, as the vegetation was resilient to these impacts. Knowledge of vegetation resilience after clear cuts may be crucial for conservation planning in raised bog ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

NDVI-Based analysis on the influence of human activities on vegetation variation on Hainan Island

NASA Astrophysics Data System (ADS)

Luo, Hongxia; Dai, Shengpei; Xie, Zhenghui; Fang, Jihua

2018-02-01

Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we analyzed the predicted NDVI values variation and the influence of human activities on vegetation on Hainan Island during 2001-2015. We investigated the roles of human activities in vegetation variation, particularly from 2002 when implemented the Grain-for-Greenprogram on Hainan Island. The trend analysis, linear regression model and residual analysis were used to analyze the data. The results of the study showed that (1) The predicted vegetation on Hainan Island showed an general upward trend with a linear growth rate of 0.0025/10y (p<0.05) over the past 15 years. The areas where vegetation increasedaccounted for 52.28%, while the areas where vegetation decreased accounted for 47.72%. (2) The residual NDVI values across the region significantly increased, with a growth rate of 0.023/10y.The vegetation increased across 35.95% of Hainan Island, while it decreased in 20.2% of the area as a result of human activities. (3) In general, human activities had played a positive role in the vegetation increase on Hainan Island, and the residual NDVI trend of this region showed positive outcomes for vegetation variation after implementing ecological engineering projects. However, it indicated a growing risk of vegetation degradation in the coastal region of Hainan Island as a result of rapid urbanization, land reclamation.

Temperature responses of carbon monoxide and hydrogen uptake by vegetated and unvegetated volcanic cinders

PubMed Central

King, Caitlin E; King, Gary M

2012-01-01

Ecosystem succession on a large deposit of volcanic cinders emplaced on Kilauea Volcano in 1959 has resulted in a mosaic of closed-canopy forested patches and contiguous unvegetated patches. Unvegetated and unshaded surface cinders (Bare) experience substantial diurnal temperature oscillations ranging from moderate (16 °C) to extreme (55 °C) conditions. The surface material of adjacent vegetated patches (Canopy) experiences much smaller fluctuations (14–25 °C) due to shading. To determine whether surface material from these sites showed adaptations by carbon monoxide (CO) and hydrogen (H2) consumption to changes in ambient temperature regimes accompanying succession, we measured responses of CO and H2 uptake to short-term variations in temperature and long-term incubations at elevated temperature. Based on its broader temperature optimum and lower activation energy, Canopy H2 uptake was less sensitive than Bare H2 uptake to temperature changes. In contrast, Bare and Canopy CO uptake responded similarly to temperature during short-term incubations, indicating no differences in temperature sensitivity. However, during extended incubations at 55 °C, CO uptake increased for Canopy but not Bare material, which indicated that the former was capable of thermal adaptation. H2 uptake for material from both sites was completely inhibited at 55 °C throughout extended incubations. These results indicated that plant development during succession did not elicit differences in short-term temperature responses for Bare and Canopy CO uptake, in spite of previously reported differences in CO oxidizer community composition, and differences in average daily and extreme temperatures. Differences associated with vegetation due to succession did, however, lead to a notable capacity for thermophilic CO uptake by Canopy but not Bare material. PMID:22258097

Temperature responses of carbon monoxide and hydrogen uptake by vegetated and unvegetated volcanic cinders.

PubMed

King, Caitlin E; King, Gary M

2012-08-01

Ecosystem succession on a large deposit of volcanic cinders emplaced on Kilauea Volcano in 1959 has resulted in a mosaic of closed-canopy forested patches and contiguous unvegetated patches. Unvegetated and unshaded surface cinders (Bare) experience substantial diurnal temperature oscillations ranging from moderate (16 °C) to extreme (55 °C) conditions. The surface material of adjacent vegetated patches (Canopy) experiences much smaller fluctuations (14-25 °C) due to shading. To determine whether surface material from these sites showed adaptations by carbon monoxide (CO) and hydrogen (H(2)) consumption to changes in ambient temperature regimes accompanying succession, we measured responses of CO and H(2) uptake to short-term variations in temperature and long-term incubations at elevated temperature. Based on its broader temperature optimum and lower activation energy, Canopy H(2) uptake was less sensitive than Bare H(2) uptake to temperature changes. In contrast, Bare and Canopy CO uptake responded similarly to temperature during short-term incubations, indicating no differences in temperature sensitivity. However, during extended incubations at 55 °C, CO uptake increased for Canopy but not Bare material, which indicated that the former was capable of thermal adaptation. H(2) uptake for material from both sites was completely inhibited at 55 °C throughout extended incubations. These results indicated that plant development during succession did not elicit differences in short-term temperature responses for Bare and Canopy CO uptake, in spite of previously reported differences in CO oxidizer community composition, and differences in average daily and extreme temperatures. Differences associated with vegetation due to succession did, however, lead to a notable capacity for thermophilic CO uptake by Canopy but not Bare material.

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

NASA Technical Reports Server (NTRS)

Gamon, John A.; Huemmrich, K. Fred; Stone, Robert S.; Tweedie, Craig E.

2015-01-01

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile.

PubMed

Glade, Francisco E; Miranda, Marcelo D; Meza, Francisco J; van Leeuwen, Willem J D

2016-12-01

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.

Attribution of trends in global vegetation greenness from 1982 to 2011

NASA Astrophysics Data System (ADS)

Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

2012-12-01

Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring

NASA Astrophysics Data System (ADS)

Peng, D.; Hu, Y.; Li, Z.

2016-05-01

It is important to detect and quantify deforestation to guide strategic decisions regarding environment, socioeconomic development, and climate change. In the present study, we conducted a field experiment to examine spectral reflectance and vegetation index changes in poplar and locust tree foliage with different leaf area indices over the course of three sunny days, following tree removal from the canopy. The spectral reflectance of foliage from harvested trees was measured using an ASD FieldSpec Prospectroradiometer; synchronous meteorological data were also obtained. We found that reflectance in short-wave infrared and red-edge reflectance was more time sensitive after tree removal than reflectance in other spectral regions, and that the normalized difference water index (NDWI) and the red-edge chlorophyll index (CIRE) were the preferred indicators of these changes from several indices evaluated. Synthesized meteorological environments were found to influence water and chlorophyll contents after tree removal, and this subsequently changed the spectral canopy reflectance. Our results indicate the potential for such tree removal to be detected with NDWI or CIRE from the second day of a deforestation event.

Response of alpine vegetation growth dynamics to snow cover phenology on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wang, X.; Wu, C.

2017-12-01

Alpine vegetation plays a crucial role in global energy cycles with snow cover, an essential component of alpine land cover showing high sensitivity to climate change. The Tibetan Plateau (TP) has a typical alpine vegetation ecosystem and is rich of snow resources. With global warming, the snow of the TP has undergone significant changes that will inevitably affect the growth of alpine vegetation, but observed evidence of such interaction is limited. In particular, a comprehensive understanding of the responses of alpine vegetation growth to snow cover variability is still not well characterized on TP region. To investigate this, we calculated three indicators, the start (SOS) and length (LOS) of growing season, and the maximum of normalized difference vegetation index (NDVImax) as proxies of vegetation growth dynamics from the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000-2015. Snow cover duration (SCD) and melt (SCM) dates were also extracted during the same time frame from the combination of MODIS and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data. We found that the snow cover phenology had a strong control on alpine vegetation growth dynamics. Furthermore, the responses of SOS, LOS and NDVImax to snow cover phenology varied among plant functional types, eco-geographical zones, and temperature and precipitation gradients. The alpine steppes showed a much stronger negative correlation between SOS and SCD, and also a more evidently positive relationship between LOS and SCD than other types, indicating a longer SCD would lead to an earlier SOS and longer LOS. Most areas showed positive correlation between SOS and SCM, while a contrary response was also found in the warm but drier areas. Both SCD and SCM showed positive correlations with NDVImax, but the relationship became weaker with the increase of precipitation. Our findings provided strong evidences between vegetation growth and snow cover phenology, and changes in snow cover should be also considered when analyzing alpine vegetation growth dynamics in future.

Assessment of Vegetation Stress Using Reflectance or Fluorescence Measurements

NASA Technical Reports Server (NTRS)

Campbell, P. K. E.; Middleton, E. M.; McMurtrey, J. E.; Corp, L. A.; Chappelle, E. W.

2007-01-01

Current methods for large-scale vegetation monitoring rely on multispectral remote sensing, which has serious limitation for the detection of vegetation stress. To contribute to the establishment of a generalized spectral approach for vegetation stress detection, this study compares the ability of high-spectral resolution reflectance (R) and fluorescence (F) foliar measurements to detect vegetation changes associated with common environmental factors affecting plant growth and productivity. To obtain a spectral dataset from a broad range of species and stress conditions, plant material from three experiments was examined, including (i) corn, nitrogen (N) deficiency/excess; (ii) soybean, elevated carbon dioxide, and ozone levels; and (iii) red maple, augmented ultraviolet irradiation. Fluorescence and R spectra (400-800 nm) were measured on the same foliar samples in conjunction with photosynthetic pigments, carbon, and N content For separation of a wide range of treatment levels, hyperspectral (5-10 nm) R indices were superior compared with F or broadband R indices, with the derivative parameters optimal results. For the detection of changes in vegetation physiology, hyperspectral indices can provide a significant improvement over broadband indices. The relationship of treatment levels to R was linear, whereas that to F was curvilinear. Using reflectance measurements, it was not possible to identify the unstressed vegetation condition, which was accomplished in all three experiments using F indices. Large-scale monitoring of vegetation condition and the detection of vegetation stress could be improved by using hyperspectral R and F information, a possible strategy for future remote sensing missions.

Breeding drought tolerant rice for shallow rainfed ecosystem of eastern India.

PubMed

Swain, Padmini; Raman, Anitha; Singh, S P; Kumar, Arvind

2017-08-01

In shallow rainfed rice agro-ecosystems, drought stress can occur at any growth stage and can cause a significant yield reduction. During recent years, some rice varieties possessing tolerance of reproductive-stage drought stress have recently been developed. Tolerance of vegetative-stage drought stress is also required to improve rice productivity in drought-prone regions. In this study, we evaluated a set of rice breeding lines for their response to a range of different types of vegetative-stage drought stress in order to propose standardized phenotyping protocols for conducting vegetative-stage drought stress screening trials and also to identify genotypes combining tolerance of vegetative- and reproductive-stage drought stress. A soil water potential threshold of -20 kPa during the vegetative stage was identified as the target for effective selection under vegetative stage with grain yield reduction of about 50% compared to irrigated control trials. Genotypes identified as showing high yield under reproductive-stage drought stress were not necessarily the genotypes showing best performance under vegetative-stage drought stress. Genotypes IR72667-16-1-B-B-3, IR78908-126-B-2-B, and IR79970-B-47-1 showed tolerance of both vegetative-stage and reproductive-stage drought stress. For most, the genotypes that were best under vegetative stage drought or even vegetative stage + reproductive stage drought were different from the genotypes that were best under reproductive stage drought. Based on the cultivar superiority measure, IR69515-6-KKN-4-UBN-4-2-1-1-1 and IR78908-126-B-1-B were the stable genotypes (indicated by low P i ) under both irrigated control and severe vegetative stress conditions, genotypes IR83614-203-B and IR78908-80-B-3-B were stable under irrigated control conditions and moderate stress, whereas IR72667-16-1-B-B-3 was stable under both moderate and severe vegetative-stage stress conditions.

Classification and ordination of understory vegetation using multivariate techniques in the Pinus wallichiana forests of Swat Valley, northern Pakistan

NASA Astrophysics Data System (ADS)

Rahman, Inayat Ur; Khan, Nasrullah; Ali, Kishwar

2017-04-01

An understory vegetation survey of the Pinus wallichiana-dominated temperate forests of Swat District was carried out to inspect the structure, composition and ecological associations of the forest vegetation. A quadrat method of sampling was used to record the floristic and phytosociological data necessary for the analysis using 300 quadrats of 10 × 10 m each. Some vegetation parameters viz. frequency and density for trees (overstory vegetation) as well as for the understory vegetation were recorded. The results revealed that in total, 92 species belonging to 77 different genera and 45 families existed in the area. The largest families were Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively. Ward's agglomerative cluster analysis for tree species resulted in three floristically and ecologically distinct community types along different topographic and soil variables. Importance value indices (IVI) were also calculated for understory vegetation and were subjected to ordination techniques, i.e. canonical correspondence analysis (CCA) and detrended correspondence analysis (DCA). DCA bi-plots for stands show that most of the stands were scattered around the centre of the DCA bi-plot, identified by two slightly scattered clusters. DCA for species bi-plot clearly identified three clusters of species revealing three types of understory communities in the study area. Results of the CCA were somewhat different from the DCA showing the impact of environmental variables on the understory species. CCA results reveal that three environmental variables, i.e. altitude, slope and P (mg/kg), have a strong influence on distribution of stands and species. Impact of tree species on the understory vegetation was also tested by CCA which showed that four tree species, i.e. P. wallichiana A.B. Jackson, Juglans regia Linn., Quercus dilatata Lindl. ex Royle and Cedrus deodara (Roxb. ex Lamb.) G. Don, have strong influences on associated understory vegetation. It is therefore concluded that Swat District has various microclimatic zones with suitable environmental variables to support distinct flora.

Monitoring vegetation response to episodic disturbance events by using multitemporal vegetation indices

USGS Publications Warehouse

Steyer, Gregory D.; Couvillion, Brady R.; Barras, John A.

2013-01-01

Normalized Difference Vegetation Index (NDVI) derived from MODerate-resolution Imaging Spectroradiometer (MODIS) satellite imagery and land/water assessments from Landsat Thematic Mapper (TM) imagery were used to quantify the extent and severity of damage and subsequent recovery after Hurricanes Katrina and Rita of 2005 within the vegetation communities of Louisiana's coastal wetlands. Field data on species composition and total live cover were collected from 232 unique plots during multiple time periods to corroborate changes in NDVI values over time. Aprehurricane 5-year baseline time series clearly identified NDVI values by habitat type, suggesting the sensitivity of NDVI to assess and monitor phenological changes in coastal wetland habitats. Monthly data from March 2005 to November 2006 were compared to the baseline average to create a departure from average statistic. Departures suggest that over 33% (4,714 km2) of the prestorm, coastal wetlands experienced a substantial decline in the density and vigor of vegetation by October 2005 (poststorm), mostly in the east and west regions, where landfalls of Hurricanes Katrina and Rita occurred. The percentage of area of persistent vegetation damage due to long-lasting formation of new open water was 91.8% in the east and 81.0% and 29.0% in the central and west regions, respectively. Although below average NDVI values were observed in most marsh communities through November 2006, recovery of vegetation was evident. Results indicated that impacts and recovery from large episodic disturbance events that influence multiple habitat types can be accurately determined using NDVI, especially when integrated with assessments of physical landscape changes and field verifications.

Monitoring vegetation response to episodic disturbance events by using multi-temporal vegetation indices

USGS Publications Warehouse

Steyer, Gregory D.; Couvillion, Brady R.; Barras, John A.

2013-01-01

Normalized Difference Vegetation Index (NDVI) derived from MODerate-resolution Imaging Spectroradiometer (MODIS) satellite imagery and land/water assessments from Landsat Thematic Mapper (TM) imagery were used to quantify the extent and severity of damage and subsequent recovery after Hurricanes Katrina and Rita of 2005 within the vegetation communities of Louisiana's coastal wetlands. Field data on species composition and total live cover were collected from 232 unique plots during multiple time periods to corroborate changes in NDVI values over time. Aprehurricane 5-year baseline time series clearly identified NDVI values by habitat type, suggesting the sensitivity of NDVI to assess and monitor phenological changes in coastal wetland habitats. Monthly data from March 2005 to November 2006 were compared to the baseline average to create a departure from average statistic. Departures suggest that over 33% (4,714 km2) of the prestorm, coastal wetlands experienced a substantial decline in the density and vigor of vegetation by October 2005 (poststorm), mostly in the east and west regions, where landfalls of Hurricanes Katrina and Rita occurred. The percentage of area of persistent vegetation damage due to long-lasting formation of new open water was 91.8% in the east and 81.0% and 29.0% in the central and west regions, respectively. Although below average NDVI values were observed in most marsh communities through November 2006, recovery of vegetation was evident. Results indicated that impacts and recovery from large episodic disturbance events that influence multiple habitat types can be accurately determined using NDVI, especially when integrated with assessments of physical landscape changes and field verifications.

Factors affecting acceptability of an email-based intervention to increase fruit and vegetable consumption.

PubMed

Kothe, Emily J; Mullan, Barbara A

2014-09-30

Fresh Facts is a 30-day email-delivered intervention designed to increase the fruit and vegetable consumption of Australian young adults. This study investigated the extent to which the program was acceptable to members of the target audience and examined the relationships between participant and intervention characteristics, attrition, effectiveness, and acceptability ratings. Young adults were randomised to two levels of message frequency: high-frequency (n = 102), low-frequency (n = 173). Individuals in the high-frequency group received daily emails while individuals in the low-frequency group received an email every 3 days. Individuals in the high-frequency group were more likely to indicate that they received too many emails than individuals in the low-frequency group. No other differences in acceptability were observed. Baseline beliefs about fruit and vegetables were an important predictor of intervention acceptability. In turn, acceptability was associated with a number of indicators of intervention success, including change in fruit and vegetable consumption. The findings highlight the importance of considering the relationship between these intervention and participant factors and acceptability in intervention design and evaluation. Results support the ongoing use of email-based interventions to target fruit and vegetable consumption within young adults. However, the relationships between beliefs about fruit and vegetable consumption and acceptability suggest that this intervention may be differentially effective depending on individual's existing beliefs about fruit and vegetable consumption. As such, there is a pressing need to consider these factors in future research in order to minimize attrition and maximize intervention effectiveness when interventions are implemented outside of a research context.

Designing a generalized soil-adjusted vegetation index (GESAVI)

NASA Astrophysics Data System (ADS)

Gilabert, M. A.; Gonzalez Piqueras, Jose; Garcia-Haro, Joan; Melia, J.

1998-12-01

Operational monitoring of vegetative cover by remote sensing currently involves the utilization of vegetation indices (VIs), most of them being functions of the reflectance in red (R) and near-infrared (NIR) spectral bands. A generalized soil-adjusted vegetation index (GESAVI), theoretically based on a simple vegetation canopy model, is introduced. It is defined in terms of the soil line parameters (A and B) as: GESAVI equals (NIR-BR-A)/(R + Z), where Z is related to the red reflectance at the cross point between the soil line and vegetation isolines. Z can be considered as a soil adjustment coefficient which let this new index be considered as belonging to the SAVI family. In order to analyze the GESAVI sensitivity to soil brightness and soil color, both high resolution reflectance data from two laboratory experiments and data obtained by applying a radiosity model to simulate heterogeneous vegetation canopy scenes were used. VIs (including GESAVI, NDVI, PVI and SAVI family VIs) were computed and their correlation with LAI for the different soil backgrounds was analyzed. Results confirmed the lower sensitivity of GESAVI to soil background in most of the cases, thus becoming the most efficient index. This good index performance results from the fact that the isolines in the NIR-R plane are neither parallel to the soil line (as required by the PVI) nor convergent at the origin (as required by the NDVI) but they converge somewhere between the origin and infinity in the region of negative values of both NIR and R. This convergence point is not necessarily situated on the bisectrix, as required by other SAVI family indices.

Estimating Achievable Accuracy for Global Imaging Spectroscopy Measurement of Non-Photosynthetic Vegetation Cover

NASA Astrophysics Data System (ADS)

Dennison, P. E.; Kokaly, R. F.; Daughtry, C. S. T.; Roberts, D. A.; Thompson, D. R.; Chambers, J. Q.; Nagler, P. L.; Okin, G. S.; Scarth, P.

2016-12-01

Terrestrial vegetation is dynamic, expressing seasonal, annual, and long-term changes in response to climate and disturbance. Phenology and disturbance (e.g. drought, insect attack, and wildfire) can result in a transition from photosynthesizing "green" vegetation to non-photosynthetic vegetation (NPV). NPV cover can include dead and senescent vegetation, plant litter, agricultural residues, and non-photosynthesizing stem tissue. NPV cover is poorly captured by conventional remote sensing vegetation indices, but it is readily separable from substrate cover based on spectral absorption features in the shortwave infrared. We will present past research motivating the need for global NPV measurements, establishing that mapping seasonal NPV cover is critical for improving our understanding of ecosystem function and carbon dynamics. We will also present new research that helps determine a best achievable accuracy for NPV cover estimation. To test the sensitivity of different NPV cover estimation methods, we simulated satellite imaging spectrometer data using field spectra collected over mixtures of NPV, green vegetation, and soil substrate. We incorporated atmospheric transmittance and modeled sensor noise to create simulated spectra with spectral resolutions ranging from 10 to 30 nm. We applied multiple methods of NPV estimation to the simulated spectra, including spectral indices, spectral feature analysis, multiple endmember spectral mixture analysis, and partial least squares regression, and compared the accuracy and bias of each method. These results prescribe sensor characteristics for an imaging spectrometer mission with NPV measurement capabilities, as well as a "Quantified Earth Science Objective" for global measurement of NPV cover. Copyright 2016, all rights reserved.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

NASA Technical Reports Server (NTRS)

Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

2017-01-01

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

Carbon isotopic evidence from paleosols for mixed C 3/C 4 vegetation in the Bogota Basin, Colombia

NASA Astrophysics Data System (ADS)

Mora, Germán; Pratt, Lisa M.

2002-04-01

Pollen reconstructions in the Bogota basin (Colombia) indicate the expansion of tropical high-altitude grassland (paramo) at the expense of Andean forests during glacial intervals. The carbon isotopic composition (δ 13C) of soil organic matter (SOM) can be a useful indicator of changes in vegetation affecting grasslands because it distinguishes between two groups of grasses (C 3 and C 4) adapted to different ecological environments. Values of SOM δ 13C were determined in four weathering profiles containing both modern (Holocene) soils and paleosols formed during the Last Glacial Stage. These profiles are located along an altitudinal transect in the Bogota basin, extending from 2550 to 3100 m. Values of SOM δ 13C in the topsoil horizons reflect those of the native C 3 vegetation that currently dominates the ecosystems in the Colombian Andes. Although C 4 grasses are currently negligible in the basin, elevated SOM δ 13C values indicative of C 4 plants were found in two Holocene soils. Environmental changes or ancient agricultural activities could explain the increased abundance of these plants in the basin during the late Holocene. Isotopic values in the studied paleosols revealed the presence of a mixed C 3/C 4 vegetation in the basin during the Last Glacial Stage, thus indicating the expansion of C 4 grasses. We hypothesized that lowered pCO 2 and possibly reduced rainfall resulted in the colonization of the tropical Andes by lowland C 4 grasses despite of prevailing cooler temperatures.

Hyperspectral remote sensing of the responses of vegetation ecosystems to physical and biological changes of the environment

NASA Astrophysics Data System (ADS)

Krezhova, Dora; Krezhov, Kiril; Maneva, Svetla; Moskova, Irina; Petrov, Nikolay

2016-07-01

Hyperspectral remote sensing technique, based on reflectance measurements acquired in a high number of contiguous spectral bands in the visible and near infrared spectral ranges, was used to detect the influence of some environmental changes to vegetation ecosystems. Adverse physical and biological conditions give rise to morphological, physiological, and biochemical changes in the plants that affect the manner in which they interact with the light. All green vegetation species have unique spectral features, mainly because of the chlorophyll and carotenoid, and other pigments, and water content. Because spectral reflectance is a function of the illumination conditions, tissue optical properties and biochemical content of the plants it may be used to collect information on several important biophysical parameters such as color and the spectral signature of features, vegetation chlorophyll absorption characteristics, vegetation moisture content, etc. Remotely sensed data collected by means of a portable fiber-optics spectrometer in the spectral range 350-1100 nm were used to extract information on the influence of some environmental changes. Stress factors such as enhanced UV-radiation, salinity, viral infections, were applied to some young plants species (potato, tomato, plums). The test data were subjected to different digital image processing techniques. This included statistical (Student's t-criterion), first derivative and cluster analyses and some vegetation indices. Statistical analyses were carried out in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (680-720 nm) and near infrared (720-780 nm). The strong relationship, which was found between the results from the remote sensing technique and some biochemical and serological analyses (stress markers, DAS-ELISA), indicates the importance of hyperspectral reflectance data for conducting, easily and without damage, rapid assessments of plant biophysical variables. Emphasis is put on current capability and future potential of remote sensing for assessment of the plant health and on the optimum spectral regions and vegetation indices for sensing these biophysical variables.

Reprint of: Synthesising the effects of land use on natural and managed landscapes.

PubMed

Thackway, Richard; Specht, Alison

2015-11-15

To properly manage our natural and managed landscapes, and to restore or repair degraded areas, it is important to know the changes that have taken place over time, particularly with respect to land use and its cumulative effect on ecological function. In common with many places in the world, where the industrial revolution resulted in profound changes to land use and management, Australia's landscapes have been transformed in the last 200 years. Initially the VAST (Vegetation Assets, States and Transitions) system was developed to describe and map changes in vegetation over time through a series of condition states or classes; here we describe an enhancement to the VAST method which will enable identification of the factors contributing to those changes in state as a result of changes in management practice. The 'VAST-2' system provides a structure in which to compile, interpret and sequence a range of data about past management practices, their effect on site and vegetation condition. Alongside a systematic chronology of land use and management, a hierarchy of indices is used to build a picture of the condition of the vegetation through time: 22 indicators within ten criteria representing three components of vegetation condition-regenerative capacity, vegetation structure and species composition-are scored using information from a variety of sources. These indicators are assessed relative to a pre-European reference state, either actual or synthetic. Each component is weighted proportionally to its contribution to the whole, determined through expert opinion. These weighted condition components are used to produce an aggregated transformation score for the vegetation. The application of this system to a range of sites selected across Australia's tropical, sub-tropical and temperate bioregions is presented, illustrating the utility of the system. Notably, the method accommodates a range of different types of information to be aggregated. Copyright © 2015 Elsevier B.V. All rights reserved.

Remotely-sensed indicators of N-related biomass allocation in Schoenoplectus acutus

USGS Publications Warehouse

O’Connell, Jessica L.; Byrd, Kristin B.; Kelly, Maggi

2014-01-01

Coastal marshes depend on belowground biomass of roots and rhizomes to contribute to peat and soil organic carbon, accrete soil and alleviate flooding as sea level rises. For nutrient-limited plants, eutrophication has either reduced or stimulated belowground biomass depending on plant biomass allocation response to fertilization. Within a freshwater wetland impoundment receiving minimal sediments, we used experimental plots to explore growth models for a common freshwater macrophyte, Schoenoplectus acutus. We used N-addition and control plots (4 each) to test whether remotely sensed vegetation indices could predict leaf N concentration, root:shoot ratios and belowground biomass of S. acutus. Following 5 months of summer growth, we harvested whole plants, measured leaf N and total plant biomass of all above and belowground vegetation. Prior to harvest, we simulated measurement of plant spectral reflectance over 164 hyperspectral Hyperion satellite bands (350–2500 nm) with a portable spectroradiometer. N-addition did not alter whole plant, but reduced belowground biomass 36% and increased aboveground biomass 71%. We correlated leaf N concentration with known N-related spectral regions using all possible normalized difference (ND), simple band ratio (SR) and first order derivative ND (FDN) and SR (FDS) vegetation indices. FDN1235, 549 was most strongly correlated with leaf N concentration and also was related to belowground biomass, the first demonstration of spectral indices and belowground biomass relationships. While S. acutus exhibited balanced growth (reduced root:shoot ratio with respect to nutrient addition), our methods also might relate N-enrichment to biomass point estimates for plants with isometric root growth. For isometric growth, foliar N indices will scale equivalently with above and belowground biomass. Leaf N vegetation indices should aid in scaling-up field estimates of biomass and assist regional monitoring.

Monitoring post-fire recovery of shrublands in Mediterranean-type ecosystems using MODIS and TM/ETM+ data

NASA Astrophysics Data System (ADS)

Hope, Allen; Albers, Noah; Bart, Ryan

2010-05-01

Wildland fires in Mediterranean-Type Ecosystems (MTEs) are episodic events that dramatically alter land-cover conditions. Monitoring post-fire vegetation recovery is important for land management applications such as the scheduling of prescribed burns, post-fire resource management and soil erosion control. Full recovery of MTE shrublands may take many years and have a prolonged effect on water, energy and carbon fluxes in these ecosystems. Comparative studies of fynbos ecosystems in the Cape Floristic Region of South Africa (Western Cape Region) and chaparral ecosystems of California have demonstrated that there is a considerable degree of convergence in some aspects of post-fire vegetation regeneration and marked differences in other aspects. Since these MTEs have contrasting rainfall and soil nutrient conditions, an obvious question arises as to the similarity or dissimilarity in remotely sensed post-fire recovery pathways of vegetation stands in these two regions and the extent to which fire severity and drought impact the rate of vegetation recovery. Post-fire recovery pathways of chaparral and fynbos vegetation stands were characterized using the normalized difference vegetation index (NDVI) based on TM/ETM+ and MODIS (250 m) data. Procedures based on stands of unburned vegetation (control) were implemented to normalize the NDVI for variations associated with inter-annual differences in rainfall. Only vegetation stands that had not burned for 20 years were examined in this study to eliminate potential effects of variable fire histories on the recovery pathways. Post-fire recovery patterns of vegetation in both regions and across different vegetation types were found to be very similar. Post-fire stand age was the primary control over vegetation recovery and the NDVI returned to pre-fire values within seven to 10 years of the fires. Droughts were shown to cause slight interruptions in recovery rates while fire severity had no discernable effect. Intra-stand variability in the NDVI (pixel-scale) also returned to pre-fire values within the same time frame but increased with water stress associated with droughts. While these studies indicated that the NDVI of fynbos and chaparral stands recovered to pre-fire values within 10 years, it is recognized that other ecosystem characteristics may take considerably longer to recover. Despite the larger pixel size, MODIS data were found to be more suitable for monitoring vegetation post-fire recovery than TM/ETM+ data, requiring considerably less pre-processing and providing substantially more information regarding phenological characteristics of recovery pathways. Future studies will include consideration of fire history in the post-fire recovery characteristics of vegetation in these two MTEs.

Evaluation of a native vegetation masking technique

NASA Technical Reports Server (NTRS)

Kinsler, M. C.

1984-01-01

A crop masking technique based on Ashburn's vegetative index (AVI) was used to evaluate native vegetation as an indicator of crop moisture condition. A mask of the range areas (native vegetation) was generated for each of thirteen Great Plains LANDSAT MSS sample segments. These masks were compared to the digitized ground truth and accuracies were computed. An analysis of the types of errors indicates a consistency in errors among the segments. The mask represents a simple quick-look technique for evaluating vegetative cover.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands

USGS Publications Warehouse

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela L.; Jarchow, Christopher J.; Roberts, Dar A.

2017-01-01

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24 m resolution WorldView-3 and a 0.1 m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure.

A Model-Based Study of Ecohydrological Controls in the Mojave Desert

NASA Astrophysics Data System (ADS)

Ng, G. C.; Bedford, D.; Miller, D. M.

2010-12-01

Desert ecosystems represent extreme conditions near the limits of viability for vegetation. Their dependence on scarce resources make them vulnerable to climate and land use change. Understanding how ecohydrological conditions impact plants in such regions is critical for ecological sustainability. Various relationships have been observed in the field between vegetation growth and meteorology, terrain, and plant physiology. Quantifying the complex interactions of those influences on vegetation dynamics can be facilitated with a physically-based ecohydrological model. To assess ecohydrological controls in the Mojave Desert, we employ the CLM4.0 land-surface model with the Carbon-Nitrogen model component to simulate vegetation dynamics [Olesen et al., 2010]. Using an ecohydrological model with fully prognostic vegetation variables is essential for representing the coupled dynamics between plants and soil moisture. We apply the CLM4.0-CN model to a study basin in the Mojave National Preserve that covers a variety of conditions. Soils range from coarse-textured wash sediments to low-permeability desert pavements. Higher elevations in the basin experience cooler and moister conditions than the lower wash areas. The dominant vegetation types in the basin include the evergreen shrub Larrea tridentata (creosote) and the drought-deciduous shrub Ambrosia dumosa. Simulations are conducted over a 50 year period to investigate both seasonal and interannual dynamics. Sensitivity tests indicate that high temporal resolution rainfall inputs (at least hourly) are important for properly resolving ecohydrological dynamics at the study site. As expected, preliminary results show that both coarser soils and milder climate facilitate vegetation growth in this moisture-limited region. However, results indicate that effects of soil texture variations become subordinate with milder climate. The model also reveals how drought-deciduous and evergreen shrub types respond differently to various conditions. Due to its quick response to sporadic wet episodes, the drought-deciduous Ambrosia thrives under harsher (hotter and drier) climates in simulations. The evergreen Larrea shrub becomes more competitive with more consistent moisture of the relatively milder climates in the basin. Multi-decadal simulations indicate that anomalously wet years can yield a sustained boost in vegetation in following years, especially for Larrea. These model results coincide with many observed vegetation patterns in the field, and they serve to elucidate and quantify the contributing factors that impact desert vegetation.

Relevance of the Sustainable Rangelands Roundtable Criteria and Indicators for Sustainable Rangeland Management to Conditions in Patagonia (Argentina)

Treesearch

Andrés F. Cibils; Gabriel E. Oliva

2006-01-01

Patagonia’s rangelands are similar to those in western United States in terms of climate, topography, and vegetation physiognomy. However, differences in environmental, economic, and societal values do exist between regions. We assessed the usefulness of C&I (Criteria and Indicators) developed in the United States for other countries, and identified indicators not...

Evaluation of last extreme drought events in Amazon basin using remotely sensing data

NASA Astrophysics Data System (ADS)

Panisset, Jéssica S.; Gouveia, Célia M.; Libonati, Renata; Peres, Leonardo; Machado-Silva, Fausto; França, Daniela A.; França, José R. A.

2017-04-01

Amazon basin has experienced several intense droughts among which were highlighted last recent ones in 2005 and 2010. Climate models suggest these events will be even more frequent due to higher concentration of greenhouse gases that are also driven forward by alteration in forest dynamics. Environmental and social impacts demand to identify these intense droughts and the behavior of climate parameters that affect vegetation. This present study also identifies a recent intense drought in Amazon basin during 2015. Meteorological parameters and vegetation indices suggest this event was the most severe already registered in the region. We have used land surface temperature (LST), vegetation indices, rainfall and shortwave radiation from 2000 to 2015 to analyze and compare droughts of 2005, 2010 and 2015. Our results show singularities among the three climate extreme events. The austral winter was the most affected season in 2005 and 2010, but not in 2015 when austral summer presented extreme conditions. Precipitation indicates epicenter of 2005 in west Amazon corroborating with previous studies. In 2010, the west region was strongly affected again together with the northwest and the southeast areas. However, 2015 epicenters were concentrated in the east of the basin. In 2015, shortwave radiation has exceeded the maximum values of 2005 and temperature the maximum value of 2010. Vegetation indices have shown positive and negative anomalies. Despite of heterogenous response of Amazon forest to drought, hybrid vegetation indices using NDVI (Normalized Difference Vegetation Index) and LST highlights the exceptionality of 2015 drought episode that exhibits higher vegetation water stress than the cases of 2010 and 2005. Finally, this work has shown how meteorological parameters influence droughts and the effects on vegetation in Amazon basin. Complexity of climate, ecosystem heterogeneity and high diversity of Amazon forest are response by idiosyncrasies of each drought. All these information improve the predictability of future climate scenarios and their effects in the environment. Research performed was supported by FAPESP/FCT Project Brazilian Fire-Land-Atmosphere System (BrFLAS) (1389/2014 and 2015/01389-4), by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) through a Master grant from PPGM/IGEO/UFRJ (first author), and by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) through grants E-26/201.521/2014; E-26/101.423/2014; E-26/201.221/2015; and E-26/203.174/2016.

Describing socioeconomic gradients in children’s diets – does the socioeconomic indicator used matter?

PubMed Central

2014-01-01

Background Children of low socioeconomic position (SEP) generally have poorer diets than children of high SEP. However there is no consensus on which SEP variable is most indicative of SEP differences in children’s diets. This study investigated associations between diet and various SEP indicators among children aged 9–13 years. Method Families (n = 625) were recruited from 27 Adelaide primary schools in 2010. Children completed semi-quantitative food frequency questionnaires providing intake scores for fruit, vegetables, non-core foods, sweetened drinks, and healthy and unhealthy eating behaviours. Parents reported demographic information by telephone interview. Differences in dietary intake scores were compared across parental education, income, occupation, employment status and home postcode. Results Across most SEP indicators, lower SEP was associated with poorer dietary outcomes, including higher intake of non-core foods and sweetened drinks, and more unhealthy behaviours; and lower intake of fruit and vegetables, and fewer healthy behaviours. The number and type of significant SEP-diet associations differed across SEP indicators and dietary outcomes. Mother’s education appeared most frequently as a predictor of children’s dietary intake, and postcode was the least frequent predictor of children’s dietary intake. Conclusion Socioeconomic gradients in children’s dietary intake varied according to the SEP indicator used, suggesting indicator-specific pathways of influence on children’s dietary intake. Researchers should consider multiple indicators when defining SEP in relation to children’s eating. PMID:24674231

NDVI indicated characteristics of vegetation cover change in China's metropolises over the last three decades.

PubMed

Sun, Jinyu; Wang, Xuhui; Chen, Anping; Ma, Yuecun; Cui, Mengdi; Piao, Shilong

2011-08-01

How urban vegetation was influenced by three decades of intensive urbanization in China is of great interest but rarely studied. In this paper, we used satellite derived Normalized Difference Vegetation Index (NDVI) and socioeconomic data to evaluate effects of urbanization on vegetation cover in China's 117 metropolises over the last three decades. Our results suggest that current urbanization has caused deterioration of urban vegetation across most cities in China, particularly in East China. At the national scale, average urban area NDVI (NDVI(u)) significantly decreased during the last three decades (P < 0.01), and two distinct periods with different trends can be identified, 1982-1990 and 1990-2006. NDVI(u) did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P < 0.01). Different regions also showed difference in the timing of NDVI(u) turning point. The year when NDVI(u) started to decline significantly for Central China and East China was 1987 and 1990, respectively, while NDVI(u) in West China remained relatively constant until 1998. NDVI(u) changes in the Yangtze River Delta and the Pearl River Delta, two regions which has been undergoing the most rapid urbanization in China, also show different characteristics. The Pearl River Delta experienced a rapid decline in NDVI(u) from the early 1980s to the mid-1990s; while in the Yangtze River Delta, NDVI(u) did not decline significantly until the early 1990s. Such different patterns of NDVI(u) changes are closely linked with policy-oriented difference in urbanization dynamics of these regions, which highlights the importance of implementing a sustainable urban development policy.

Influence of rock-soil spectral variation on the assessment of green biomass

NASA Technical Reports Server (NTRS)

Elvidge, C. D.; Lyon, R. J. P.

1985-01-01

A comparison of how n-spaced and ratio-based vegetation indices respond to rock and soil spectral variation is made, using a set of ground-based reflectance spectra and airborne Thematic Mapper imagery of the Virginia Range, NV. The influence of variations in rock-soil brightness on ratio-based vegetation indices is also discussed. It is shown that of all the vegetation indices tested, the perperdicular vegetation index is the most appropriate for use in multispectral imagery of arid and semiarid regions where there is a wide variation in substrate characteristics.

A comparative study of soil water movement under different vegetation covers

NASA Astrophysics Data System (ADS)

FERNANDO, A.; Tanaka, T.

2002-05-01

Vegetation, varying widely floristically, structurally, and in spatial distribution, is a complex phenomenon, delicately adjusted within itself and to its broader environment. To investigate the soil water movement of different vegetation covers, soil physical properties, and pressure head of soil water, have been analysed in a pine forest and adjacent disturbed grassland at the Terrestrial Environmental Research Centre (ERC) of Tsukuba University, Japan. Our results of the soil physical properties showed significant differences under different vegetation. At the forest site, the total porosity was nearly constant, i.e. 81% to 84%, from the ground surface to the depth of 70 cm, and decreased uniformly with the depth to reach 63.2% at 150 cm. At the grassland site, the total porosity was about 70% near the ground surface, however, expeditiously decreased to approximately 62% between the depths of 10 and 40 cm. Below these depths the total porosity increased to a maximum of about 77% between the depths of 50 and 80 cm, then decreased again to 54.9% at 150 cm. The total pressure head indicated that the evapotranspiration zone of the pine forest was 70 cm but was 50 cm in the grassland. KEY WORDS: Natural pine forest, Disturbed grassland, Soil water movement, Soil physical properties, Evaporation effective zone.

[Effects of alien species Robinia pseudoacacia on plant community functional structure in hilly-gully region of Loess Plateau, China.

PubMed

Zhu, Duo Ju; Wen, Zhong Ming; Zhang, Jing; Tao, Yu; Zeng, Hong Wen; Tang, Yang

2018-02-01

To investigate the effects of the introduction of Robinia pseudoacacia on the functional structure of plant communities, we selected paired-plots of R. pseudoacacia communities and native plant communities across different vegetation zones, i.e., steppe zone, forest-steppe zone, forest zone in hilly-gully region of Loess Plateau, China. We measured several functional characteristics and then compared the functional structures of R. pseudoacacia and native plant communities in different vegetation zones. The results showed that the variation of the functional traits across different vegetation zones were consistent in R. pseudoacacia community and native plant community, including leaf carbon concentration, leaf nitrogen concentration, leaf phosphorus concentration, specific leaf area, and leaf tissue density. The leaf carbon concentration, leaf nitrogen concentration, and specific leaf area of the R. pseudoacacia community were significantly higher than those of the native plant community. The trend of change that the functional diversity indices, i.e., FR ic , FE ve , FD iv , FD is , Rao of the R. pseudoacacia community and the native plant community with vegetation zones were different. The introduction of R. pseudoacacia enhanced the plant community functional diversity in the forest zone but reduced community functional diversity in the steppe zone.

Hydrological drivers of wetland vegetational biodiversity patterns within Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Todd, J.; Pumo, D.; Azaele, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of wetland structure. We attempt to link hydrological dynamics with vegetational distribution and species richness across Everglades National Park (ENP) using two publicly available datasets. The first, the Everglades Depth Estimation Network (EDEN),is a water-surface model which determines the median daily measure of water level across a 400mX400m grid over seven years of measurement. The second is a vegetation map and classification system at the 1:15,000 scale which categorizes vegetation within the Everglades into 79 community types. From these data, we have studied the probabilistic structure of the frequency, duration, and depth of hydroperiods. Preliminary results indicate that the percentage of time a location is inundated is a principal structuring variable with individual communities responding differently. For example, sawgrass appears to be more of a generalist community as it is found across a wide range of time inundated percentages while spike rush has a more restricted distribution and favors wetter environments disproportionately more than predicted at random. Further, the diversity of vegetation communities (e.g. a measure of biodiversity) found across a hydrologic variable does not necessarily match the distribution function for that variable on the landscape. For instance, the number of communities does not differ across the percentage of time inundated. Different measures of vegetation biodiversity such as the local number of community types are also studied at different spatial scales with some characteristics, like the slope of the semi-logarithmic relation between rank and occupancy, found to be robust to scale changes. The ENP offers an expansive natural environment in which to study how vegetational dynamics and community composition are affected by hydrologic variables from the small scale (at the individual community level) to the large (biodiversity measures at differing spatial scales).

[Influences of land using patterns on the anti-wind erosion of meadow grassland].

PubMed

Zhou, Yao-Zhi; Wang-Xu; Yang, Gui-Xia; Xin, Xiao-Ping

2008-05-01

In order to analyse the effects of the human disturbances to the ability of anti-wind erosion of the Hulunbuir meadow grassland, the methods of vegetation investigation and the wind tunnel experiment were made to research the changes of vegetation and the abilities of anti-wind erosion of meadow grassland under different using patterns of meadow grassland. The results indicate that, under different grazing intensities of meadow grassland, the critical wind velocity of soil erosion (v) changes with the vegetation cover according to the relation of second power function. Along with the grazing intensities increasing and the vegetation cover reducing, the velocity of soil erosion rapidly increased on the condition of similar wind velocity which is speedier than the critical wind velocity of soil erosion. When the meadow grassland is mildly grazed which the vegetation cover maintains 63%, the velocity of soil erosion is small even there is gale that the wind velocity reach 25 m/s. When the vegetation cover of meadow grassland reduced to less than 35%, the velocity of soil erosion rapidly increased with the vegetation cover's reducing on the condition of the wind velocity is among 20-25 m/s. And owing to the no-tillage cropland of meadow grassland is completely far from the protection of the vegetation, the soil wind erosion quantity achieves 682.1 kg/hm2 in a minute when the wind velocity is 25 m/s, which approaches the average formation quantity of soil (1 000 kg/hm2) in a year.

Common ways Americans are incorporating fruits and vegetables into their diet: intake patterns by meal, source and form, National Health and Nutrition Examination Survey 2007-2010.

PubMed

Moore, Latetia V; Hamner, Heather C; Kim, Sonia A; Dalenius, Karen

2016-10-01

We explored how Americans aged ≥2 years who consumed the recommended amount of fruits and vegetables on a given day incorporated fruits and vegetables into their diet compared with those who did not consume recommended amounts. We used 1 d of dietary recall data from the National Health and Nutrition Examination Survey (NHANES) 2007-2010 to examine cross-sectional differences in mean intakes of fruits and vegetables in cup-equivalents by meal, source and form between the two groups. USA. NHANES 2007-2010 participants aged ≥2 years (n 17 571) with 1 d of reliable 24 h recall data. On a given day, the proportions of fruits and vegetables consumed at different meals were similar between those who consumed recommended amounts and those who did not. Among adults, 59-64 % of their intake of fruits was consumed at breakfast or as a snack and almost 90 % came from retail outlets regardless of whether they consumed the recommended amount or not. Adults who consumed the recommended amount of fruits ate more fruits in raw form and with no additions than those who did not. Among children and adults, 52-57 % of vegetables were consumed at dinner by both groups. Retail outlets were the main source of vegetables consumed (60-68 %). Our findings indicate that habits of when, where and how consumers eat fruits and vegetables might not need to change but increasing the amount consumed would help those not currently meeting the recommendation.

Soil indicators to assess the effectiveness of restoration strategies in dryland ecosystems

NASA Astrophysics Data System (ADS)

Costantini, E. A. C.; Branquinho, C.; Nunes, A.; Schwilch, G.; Stavi, I.; Valdecantos, A.; Zucca, C.

2015-12-01

Soil indicators may be used for assessing both land suitability for restoration and the effectiveness of restoration strategies in restoring ecosystem functioning and services. In this review paper, several soil indicators, which can be used to assess the effectiveness of restoration strategies in dryland ecosystems at different spatial and temporal scales, are discussed. The selected indicators represent the different viewpoints of pedology, ecology, hydrology, and land management. The recovery of soil capacity to provide ecosystem services is primarily obtained by increasing soil rooting depth and volume, and augmenting water accessibility for vegetation. Soil characteristics can be used either as indicators of suitability, that is, inherently slow-changing soil qualities, or as indicators for modifications, namely dynamic, thus "manageable" soil qualities. Soil organic matter forms, as well as biochemistry, micro- and meso-biology, are among the most utilized dynamic indicators. On broader territorial scales, the Landscape Function Analysis uses a functional approach, where the effectiveness of restoration strategies is assessed by combining the analysis of spatial pattern of vegetation with qualitative soil indicators. For more holistic and comprehensive projects, effective strategies to combat desertification should integrate soil indicators with biophysical and socio-economic evaluation and include participatory approaches. The integrated assessment protocol of Sustainable Land Management developed by the World Overview of Conservation Approaches and Technologies network is thoroughly discussed. Two overall outcomes stem from the review: (i) the success of restoration projects relies on a proper understanding of their ecology, namely the relationships between soil, plants, hydrology, climate, and land management at different scales, which is particularly complex due to the heterogeneous pattern of ecosystems functioning in drylands, and (ii) the selection of the most suitable soil indicators follows a clear identification of the different and sometimes competing ecosystem services that the project is aimed at restoring.

Concepts for Sensor Data Fusion to Detect Vegetation Stress and Implications on Ecosystem Health Following Hurricane Katrina

DTIC Science & Technology

2008-09-01

Description NDVI Narrow-band Normalized Difference Vegetation Index (can check all possible two-band combinations, and determine best band combinations...were calculated for each site. The band indices were: • NDVI (Hyperion bands 45 & 33) (Figure 2) • NDWI (Hyperion bands 51 & 109) • PRI (Hyperion...between categories for these groups. NDVI and NDWI were very close to achiev- ing a significant result, and were still particularly good at separating two

Canopy Modeling of Aquatic Vegetation: Construction of Submerged Vegetation Index

NASA Astrophysics Data System (ADS)

Ma, Z.; Zhou, G.

2018-04-01

The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.

Hazardous impact and translocation of vanadium (V) species from soil to different vegetables and grasses grown in the vicinity of thermal power plant.

PubMed

Khan, Sumaira; Kazi, Tasneem Gul; Kolachi, Nida Fatima; Baig, Jameel Ahmed; Afridi, Hassan Imran; Shah, Abdul Qadir; Kumar, Sham; Shah, Faheem

2011-06-15

The distribution of vanadium (V) species in soil (test soil), vegetables and grasses, collected from the vicinity of a thermal power plant has been studied. For comparison purpose soil (control soil), same vegetable and grass samples were collected from agricultural land devoid of any industrial area. A simple and efficient ultrasonic assisted extraction method has been developed for the extraction of V(5+) species from soil, vegetable and grass samples using Na(2)CO(3) in the range of 0.1-0.5 mol/L. For comparison purpose same sub samples were also extracted by conventional heating method. The total and V species were determined by electrothermal atomic absorption spectrometry using different modifiers. The validity of V(5+) and V(4+) determination had been confirmed by the spike recovery and total amount of V by the analysis of CRM 1570 (spinach leave) and sub samples of agricultural soil. The concentration of total V was found in the range of 90-215 and 11.4-42.3 μg/g in test and control soil samples, respectively. The contents of V(5+) and total V in vegetables and grasses grown around the thermal power plant were found in the range of 2.9-5.25 and 8.74-14.9 μg/g, respectively, which were significantly higher than those values obtained from vegetables and fodders grown in non exposed agricultural site (P<0.01). Statistical evaluations indicate that the sum of concentrations of V(5+) and V(4+) species was not significantly different from total concentration of V in same sub samples of vegetable, grass and soil of both origins, at 95% level of confidence. Copyright © 2011 Elsevier B.V. All rights reserved.

Peat drainage conditions assessment in Scotland

NASA Astrophysics Data System (ADS)

Poggio, Laura; Artz, Rebekka; Donaldson-Selby, Gillian; Aitkenhead, Matt; Donnelly, David; Gimona, Alessandro

2017-04-01

Large areas of Scotland are covered in peat, providing an important sink of carbon but also a notable source of emission where peatlands are not in good condition. However, despite data from designated sites that peat degradation is common, a detailed spatial assessment of the condition of most peatlands across the whole of Scotland is missing. An assessment of peatland drainage was carried out at >600 random sampling locations with an expert-based estimation of presence or absence of drainage ditches within a 500 metre block using 25 cm resolution aerial imagery. The resulting dataset was modelled using a scorpan-kriging approach, in particular using Generalised Additive Models for the description of the trend. Remote sensing images from different sensors (i.e. MODIS, Landsat and Sentinel 1 and 2) were used. In particular we used indices describing vegetation greenness (Enhanced Vegetation Index), water availability (Normalised Water Difference index), Land Surface Temperature and vegetation productivity. When considering MODIS indices we used time series and phenological summaries. The model provides also uncertainty of the estimations. The derived dataset can then be used in the decision making process for the selection of sites for restoration, emissions estimation and accounting.

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Differentiate responses of soil structure to natural vegetation and artificial plantation in landslide hazard region of the West Qinling Mountains, China

NASA Astrophysics Data System (ADS)

Wang, X.; Huang, Z.; Zhao, Y.; Hong, M.

2017-12-01

Natural vegetation and artificial plantation are the most important measures for ecological restoration in soil erosion and landslide hazard-prone regions of China. Previous studies have demonstrated that both measures can significantly change the soil structure and decrease soil and water erosion. Few reports have compared the effects of the two contrasting measures on mechanical and hydrological properties and further tested the differentiate responses of soil structure. In the study areas, two vegetation restoration measures-natural vegetation restoration (NVR) and artificial plantation restoration (APR) compared with control site, with similar topographical and geological backgrounds were selected to investigate the different effects on soil structure based on eight-year ecological restoration projects. The results showed that the surface vegetation played an important role in releasing soil erosion and enhance soil structure stability through change the soil aggregates (SA) and total soil porosity (TSP). The SA<0.25mm content in NVR (36.13%) was higher than that in APR (32.14%). The study indicated that SA and TSP were the principal components (PCs) related to soil structure variation. Soil organic carbon, soil water retention, clay and vegetation biomass were more strongly correlated with the PCs in NVR than those in APR. The study indicated that NVR was more beneficial for soil structure stability than APR. These findings will provide a theoretical basis for the decisions around reasonable land use for ecological restoration and conservation in geological hazard-prone regions.

Characterization of extreme years in Central Europe between 2000 and 2016 according to specific vegetation characteristics based on Earth Observatory data

NASA Astrophysics Data System (ADS)

Kern, Anikó; Marjanović, Hrvoje; Barcza, Zoltán

2017-04-01

Extreme weather events frequently occur in Central Europe, affecting the state of the vegetation in large areas. Droughts and heat-waves affect all plant functional types, but the response of the vegetation is not uniform and depends on other parameters, plant strategies and the antecedent meteorological conditions as well. Meteorologists struggle with the definition of extreme events and selection of years that can be considered as extreme in terms of meteorological conditions due to the large variability of the meteorological parameters both in time and space. One way to overcome this problem is the definition of extreme weather based on its observed effect on plant state. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Leaf Area Index (LAI), the Fraction of Photosynthetically Active Radiation (FPAR) and the Gross Primary Production (GPP) are different measures of the land vegetation derived from remote sensing data, providing information about the plant state, but it is less known how weather anomalies affect these measures. We used the vegetation related official products created from the measurements of the MODerate resolution Imaging Spectroradiometer (MODIS) on board satellite Terra to select and characterize the extreme years in Central European countries during the 2000-2016 time period. The applied Collection-6 MOD13 NDVI/EVI, MOD15 LAI/FPAR and MOD17 GPP datasets have 500 m × 500 m spatial resolution covering the region of the Carpathian-Basin. After quality and noise filtering (and temporal interpolation in case of MOD13) 8-day anomaly values were derived to investigate the different years. The freely available FORESEE meteorological database was used to study climate variability in the region. Daily precipitation and maximum/minimum temperature fields at 1/12° × 1/12° grid were resampled to the 8-day temporal and 500 m × 500 m spatial resolution of the MODIS products. To discriminate the different behavior of the various plant functional types MODIS (MCD12) and CORINE (CLC2012) land cover datasets were applied and handled together. Based on the determination of the reliable pixels with different plant types the response of broadleaf forests, coniferous forests, grasslands and croplands were discriminated and investigated. Characteristic time periods were selected based on the remote sensing data to define anomalies, and then the meteorological data were used to define critical time periods within the year that has the strongest effect on the observed anomalies. Similarities/dissimilarities between the behaviors of the different remotely sensed measures are also studied to elucidate the consistency of the indices. The results indicate that the diverse remote sensing indices typically co-vary but reveal strong plant functional type dependency. The study suggest that the selection of extreme years based on annual data is not the best choice, as shorter time periods within the years explain the anomalies to a higher degree than annual data. The results can be used to select anomalous years outside of the satellite era as well. Keywords: Remote sensing, meteorology; extreme years; MODIS, NDVI; EVI; LAI; FPAR; GPP; phenology

Near ground level sensing for spatial analysis of vegetation

NASA Technical Reports Server (NTRS)

Sauer, Tom; Rasure, John; Gage, Charlie

1991-01-01

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

Effects of land use pattern on soil water in revegetation watersheds in semi-arid Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Lei; Chen, Liding; Wei, Wei

2017-04-01

Soil water stored below rainfall infiltration depth is a reliable water resource for plant growth in arid and semi-arid regions. For decreasing serious soil erosion, large-scale human-introduced vegetation restoration was initiated in Chinese Loess Plateau in late 1990s. However, these activities may result in excessive water consumption and soil water deficit if no appropriate scientific guidance were offered. This in turn impacts the regional ecological restoration and sustainable management of water resources. In this study, soil water content data in depth of 0-5 m was obtained by long-term field observation and geostatistical method in 6 small watersheds covered with different land use pattern. Profile characteristics and spatial-temporal patterns of soil water were compared between different land use types, hillslopes, and watersheds. The results showed that: (1) Introduced vegetation consumed excessive amount of water when compared with native grassland and farmland, and induced temporally stable soil desiccation in depth of 0-5 m. The introduced vegetation decreased soil water content to levels lower than the reference value representing no human impact in all soil layers. (2) The analysis of differences in soil water at hillslope and watershed scales indicated that land use determined the spatial and temporal variability of soil water. Soil water at watershed scale increased with the increasing area of farmland, and decreased with increasing percentage of introduced vegetation. Land use structure determined the soil water condition and land use pattern determined the spatial-temporal variability of soil water at watershed scale. (3) Large-scale revegetation with introduced vegetation diminished the spatial heterogeneity of soil water at different scales. Land use pattern adjustment could be used to improve the water resources management and maintain the sustainability of vegetation restoration.

Green Infrastructure Increases Biogeochemical Responsiveness, Vegetation Growth and Decreases Runoff in a Semi-Arid City, Tucson, AZ, USA

NASA Astrophysics Data System (ADS)

Meixner, T.; Papuga, S. A.; Luketich, A. M.; Rockhill, T.; Gallo, E. L.; Anderson, J.; Salgado, L.; Pope, K.; Gupta, N.; Korgaonkar, Y.; Guertin, D. P.

2017-12-01

Green Infrastructure (GI) is often viewed as a mechanism to minimize the effects of urbanization on hydrology, water quality, and other ecosystem services (including the urban heat island). Quantifying the effects of GI requires field measurements of the dimensions of biogeochemical, ecosystem, and hydrologic function that we expect GI to impact. Here we investigated the effect of GI features in Tucson, Arizona which has a low intensity winter precipitation regime and a high intensity summer regime. We focused on understanding the effect of GI on soil hydraulic and biogeochemical properties as well as the effect on vegetation and canopy temperature. Our results demonstrate profound changes in biogeochemical and hydrologic properties and vegetation growth between GI systems and nearby control sites. In terms of hydrologic properties GI soils had increased water holding capacity and hydraulic conductivity. GI soils also have higher total carbon, total nitrogen, and organic matter in general than control soils. Furthermore, we tested the sampled soils (control and GI) for differences in biogeochemical response upon wetting. GI soils had larger respiration responses indicating greater biogeochemical activity overall. Long-term Lidar surveys were used to investigate the differential canopy growth of GI systems versus control sites. The results of this analysis indicate that while a significant amount of time is needed to observe differences in canopy growth GI features due increase tree size and thus likely impact street scale ambient temperatures. Additionally monitoring of transpiration, soil moisture, and canopy temperature demonstrates that GI features increase vegetation growth and transpiration and reduce canopy temperatures. These biogeochemical and ecohydrologic results indicate that GI can increase the biogeochemical processing of soils and increase tree growth and thus reduce urban ambient temperatures.

Angiosperm n-alkane distribution patterns and the geologic record of C4 grassland evolution

NASA Astrophysics Data System (ADS)

Henderson, A.; Graham, H. V.; Patzkowsky, M.; Fox, D. L.; Freeman, K. H.

2012-12-01

n-Alkane average chain-length (ACL) patterns vary regionally with community composition and climate. To clarify the influence of phylogenetic and community patterns, we compiled and analyzed a global database of published n-alkane abundance for n-C27 to C35 homologs in modern plant specimens (n=205). ACL for waxes in C4 non-woody plants are longer than for woody plants, suggesting ACL can serve as an indicator of the three-dimensional structure of local vegetation. Further, these findings suggest compound-specific isotopic data for longer alkane homologs (C31, C33, C35) will proportionately represent non-woody vegetation and isotope measurements of C29 are more representative of woody vegetation. Thus, the combination of ACL and carbon isotope compositions should allow us to disentangle C3 woody, C3 non-woody, and C4 non-woody signals in terrestrial paleorecords. Application of this approach to the geologic record of Miocene C4 grassland expansion in the US Great Plains and the Siwaliks in Pakistan illustrate two very different transition scenarios. Alkane-specific isotopic data indicate C4 grasslands appeared 2.5 Ma in the Great Plains and 6.5 Ma in the Siwaliks, and ACL analysis indicates that this transition involved the replacement of woody vegetation in the US and the replacement of C3 grasses in Pakistan. Our analysis illustrates that, consistent with differences in the timing of C4 grassland, the drivers of change were likely not the same in these regions. Oxygen isotope records suggest that the more recent transition in the Great Plains was associated with climate cooling and possibly changes in disturbance regimes and that the transition in the Siwaliks was likely associated with warming and drying.

Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity

NASA Astrophysics Data System (ADS)

Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego

2015-04-01

Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity over the last two decades. The co-variability of a range of climate oscillation indices and newly-derived records of fluorescence and vegetation optical depth is analyzed using a statistical framework based on correlations, bootstrapping and Empirical Orthogonal Functions (EOFs). Results will enable us to characterize regional hotspots where particular climatic oscillations control vegetation productivity, as well as allowing us to underpin the climatic variables behind this control.

Extraction and determination of arsenic species in leafy vegetables: Method development and application.

PubMed

Ma, Li; Yang, Zhaoguang; Kong, Qian; Wang, Lin

2017-02-15

Extraction of arsenic (As) species in leafy vegetables was investigated by different combinations of methods and extractants. The extracted As species were separated and determined by HPLC-ICP-MS method. The microwave assisted method using 1% HNO3 as the extractant exhibited satisfactory efficiency (>90%) at 90°C for 1.5h. The proposed method was applied for extracting As species from real leafy vegetables. Thirteen cultivars of leafy vegetables were collected and analyzed. The predominant species in all the investigated vegetable samples were As(III) and As(V). Moreover, both As(III) and As(V) concentrations were positive significant (p<0.01) correlated with total As (tAs) concentration. However, the percentage of As(V) reduced with tAs concentration increasing probably due to the conversion and transformation of As(V) to As(III) after uptake. The hazard quotient results indicated no particular risk to 94.6% of local consumers. Considerably carcinogenic risk by consumption of the leafy vegetables was observed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hyperspectral remote sensing for advanced detection of early blight (Alternaria solani) disease in potato (Solanum tuberosum) plants

NASA Astrophysics Data System (ADS)

Atherton, Daniel

Early detection of disease and insect infestation within crops and precise application of pesticides can help reduce potential production losses, reduce environmental risk, and reduce the cost of farming. The goal of this study was the advanced detection of early blight (Alternaria solani) in potato (Solanum tuberosum) plants using hyperspectral remote sensing data captured with a handheld spectroradiometer. Hyperspectral reflectance spectra were captured 10 times over five weeks from plants grown to the vegetative and tuber bulking growth stages. The spectra were analyzed using principal component analysis (PCA), spectral change (ratio) analysis, partial least squares (PLS), cluster analysis, and vegetative indices. PCA successfully distinguished more heavily diseased plants from healthy and minimally diseased plants using two principal components. Spectral change (ratio) analysis provided wavelengths (490-510, 640, 665-670, 690, 740-750, and 935 nm) most sensitive to early blight infection followed by ANOVA results indicating a highly significant difference (p < 0.0001) between disease rating group means. In the majority of the experiments, comparisons of diseased plants with healthy plants using Fisher's LSD revealed more heavily diseased plants were significantly different from healthy plants. PLS analysis demonstrated the feasibility of detecting early blight infected plants, finding four optimal factors for raw spectra with the predictor variation explained ranging from 93.4% to 94.6% and the response variation explained ranging from 42.7% to 64.7%. Cluster analysis successfully distinguished healthy plants from all diseased plants except for the most mildly diseased plants, showing clustering analysis was an effective method for detection of early blight. Analysis of the reflectance spectra using the simple ratio (SR) and the normalized difference vegetative index (NDVI) was effective at differentiating all diseased plants from healthy plants, except for the most mildly diseased plants. Of the analysis methods attempted, cluster analysis and vegetative indices were the most promising. The results show the potential of hyperspectral remote sensing for the detection of early blight in potato plants.

Synthesis, reactivity and application studies for different biolubricants

PubMed Central

2014-01-01

Vegetable oils have different unique properties owing to their unique chemical structure. Vegetable oils have a greater ability to lubricate and have higher viscosity indices. Therefore, they are being more closely examined as base oil for biolubricants and functional fluids. In spite of their many advantages, vegetable oils suffer from two major drawbacks of inadequate oxidative stability and poor low-temperature properties, which hinder their utilization as biolubricant base oils. Transforming alkene groups in fatty acids to other stable functional groups could improve the oxidative stability, whereas reducing structural uniformity of the oil by attaching alkyl side chains could improve the low-temperature performance. In that light, the epoxidation of unsaturated fatty acids is very interesting as it can provide diverse side chains arising from the mono- or di-epoxidation of the unsaturated fatty acid. Oxirane ring opening by an acid-catalyzed reaction with a suitable reagent provides interesting polyfunctional compounds. PMID:24612780

Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment

NASA Astrophysics Data System (ADS)

Götze, Christian; Jung, András; Merbach, Ines; Wennrich, Rainer; Gläßer, Cornelia

2010-06-01

Floodplain ecosystems are affected by flood dynamics, nutrient supply as well as anthropogenic activities. Heavy metal pollution poses a serious environmental challenge. Pollution transfer from the soil to vegetation is still present at the central location of Elbe River, Germany. The goal of this study was to assess and separate the current heavy metal contamination of the floodplain ecosystem, using spectrometric field and laboratory measurements. A standardized pot experiment with floodplain vegetation in differently contaminated soils provided the basis for the measurements. The dominant plant types of the floodplains are: Urtica dioica, Phalaris arundinacea and Alopecurus pratensis, these were also chemically analysed. Various vegetation indices and methods were used to estimate the red edge position, to normalise the spectral curve of the vegetation and to investigate the potential of different methods for separating plant stress in floodplain vegetation. The main task was to compare spectral bands during phenological phases to find a method to detect heavy metal stress in plants. A multi-level algorithm for the curve parameterisation was developed. Chemo-analytical and ecophysiological parameters of plants were considered in the results and correlated with spectral data. The results of this study show the influence of heavy metals on the spectral characteristics of the focal plants. The developed method (depth CR1730) showed significant relationship between the plants and the contamination.

Influence of vegetation on water isotope partitioning across different northern headwater catchments

NASA Astrophysics Data System (ADS)

Gabor, R. S.; Tetzlaff, D.; Buttle, J. M.; Carey, S. K.; Laudon, H.; Mitchell, C. P. J.; McNamara, J. P.; Soulsby, C.

2014-12-01

The hydrology of high latitude catchments is sensitive to small changes in temperature, and likely to be impacted by changes in climate. Vegetation water usage can play a large role in catchment hydrologic pathways, affecting how water is stored, released, and partitioned within a landscape. Thus a better understanding of how vegetation impacts water partitioning in northern catchments can help us understand how climate change will impact high-latitude hydrology. As part of the VeWa project, five catchments were chosen between 44oN and 64oN in Europe and North America, to compare the role of vegetation in the movement of water across northern landscapes. These catchments vary in aspect as well as extent of snowpack and their vegetative landscapes include heather moorland, coniferous and deciduous forests, mixed grass, and tundra landscapes. Importantly, all the catchments have records of stable isotopes in different waters of the system. An initial comparison of the water isotopes in these catchments demonstrates variation between the catchments, with the lower latitude sites showing more fractionation suggestive of evapotranspiration. While all catchments show a depletion of heavy isotopes in the spring, the depletion is most evident in catchments with a heavier snowpack. The vegetative growing season during the summer months shows the greatest impact of evapotranspiration on isotopes, indicating that an increased summer in a warmer climate would likely alter water partitioning and storage dynamics in these regions.

A system to evaluate fire impacts from simulated fire behavior in Mediterranean areas of Central Chile.

PubMed

Castillo, Miguel E; Molina, Juan R; Rodríguez Y Silva, Francisco; García-Chevesich, Pablo; Garfias, Roberto

2017-02-01

Wildfires constitute the greatest economic disruption to Mediterranean ecosystems, from a socio-economic and ecological perspective (Molina et al., 2014). This study proposes to classify fire intensity levels based on potential fire behavior in different types of Mediterranean vegetation types, using two geographical scales. The study considered >4 thousand wildfires over a period of 25years, identifying fire behavior on each event, based on simulations using "KITRAL", a model developed in Chile in 1993 and currently used in the entire country. Fire intensity values allowed results to be classified into six fire effects categories (levels), each of them with field indicators linking energy values with damage related to burned vegetation and wildland urban interface zone. These indicators also facilitated a preliminary assessment of wildfire impact on different Mediterranean land uses and, are therefore, a useful tool to prioritize future interventions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Lary, David J.; Vrieling, Anton; Stathakis, Demetris; Mussa, Hamse

2008-01-01

The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

Arbuscular mycorrhizal fungi associated with vegetation and soil parameters under rest grazing management in a desert steppe ecosystem.

PubMed

Bai, Gegenbaoleer; Bao, Yuying; Du, Guoxin; Qi, Yunlong

2013-05-01

The impact of rest grazing on arbuscular mycorrhizal fungi (AMF) and the interactions of AMF with vegetation and soil parameters under rest grazing condition were investigated between spring and late summer in a desert steppe ecosystem with different grazing managements (rest grazing with different lengths of resting period, banned or continuous grazing) in Inner Mongolia, China. AMF diversity and colonization, vegetation biomass, soil properties and soil phosphatase activity were examined. In rest grazing areas of 60 days, AMF spore number and diversity index at a 0-10 cm soil depth as well as vesicular and hyphal colonization rates were higher compared with other grazing treatments. In addition, soil organic matter and total N contents were highest and soil alkaline phosphatase was most active under 60-day rest grazing. In August and September, these areas also had the highest amount of aboveground vegetation. The results indicated that resting grazing for an appropriate period of time in spring has a positive effect on AMF sporulation, colonization and diversity, and that under rest grazing conditions, AMF parameters are positively correlated with some soil characteristics.

[Variation characteristics and influencing factors of actual evapotranspiration under various vegetation types: A case study in the Huaihe River Basin, China.

PubMed

Wu, Rong Jun; Xing, Xiao Yong

2016-06-01

The actual evapotranspiration was modelled utilizing the boreal ecosystem productivity simulator (BEPS) in Huaihe River Basin from 2001 to 2012. In the meantime, the quantitative analyses of the spatial-temporal variations of actual evapotranspiration characteristics and its influencing factors under different vegetation types were conducted. The results showed that annual evapotranspiration gradually decreased from southeast to northwest, tended to increase annually, and the monthly change for the average annual evapotranspiration was double-peak curve. The differences of evapotranspiration among vegetation types showed that the farmland was the largest contributor for the evapotranspiration of Huaihe Basin. The annual actual evapotranspiration of the mixed forest per unit area was the largest, and that of the bare ground per unit area was the smallest. The changed average annual evapotranspiration per unit area for various vegetation types indicated an increased tendency other than the bare ground, with a most significant increase trend for the evergreen broadleaf forest. The thermodynamic factors (such as average temperature) were the dominant factors affecting the actual evapotranspiration in the Huaihe Basin, followed by radiation and moisture factors.

Using ground observations of a digital camera in the VIS-NIR range for quantifying the phenology of Mediterranean woody species

NASA Astrophysics Data System (ADS)

Weil, Gilad; Lensky, Itamar M.; Levin, Noam

2017-10-01

The spectral reflectance of most plant species is quite similar, and thus the feasibility of identifying most plant species based on single date multispectral data is very low. Seasonal phenological patterns of plant species may enable to face the challenge of using remote sensing for mapping plant species at the individual level. We used a consumer-grade digital camera with near infra-red capabilities in order to extract and quantify vegetation phenological information in four East Mediterranean sites. After illumination corrections and other noise reduction steps, the phenological patterns of 1839 individuals representing 12 common species were analyzed, including evergreen trees, winter deciduous trees, semi-deciduous summer shrubs and annual herbaceous patches. Five vegetation indices were used to describe the phenology: relative green and red (green/red chromatic coordinate), excess green (ExG), normalized difference vegetation index (NDVI) and green-red vegetation index (GRVI). We found significant differences between the phenology of the various species, and defined the main phenological groups using agglomerative hierarchical clustering. Differences between species and sites regarding the start of season (SOS), maximum of season (MOS) and end of season (EOS) were displayed in detail, using ExG values, as this index was found to have the lowest percentage of outliers. An additional visible band spectral index (relative red) was found as useful for characterizing seasonal phenology, and had the lowest correlation with the other four vegetation indices, which are more sensitive to greenness. We used a linear mixed model in order to evaluate the influences of various factors on the phenology, and found that unlike the significant effect of species and individuals on SOS, MOS and EOS, the sites' location did not have a direct significant effect on the timing of phenological events. In conclusion, the relative advantage of the proposed methodology is the exploitation of representative temporal information that is collected with accessible and simple devices, for the subsequent determination of optimal temporal acquisition of images by overhead sensors, for vegetation mapping over larger areas.

Co-composting of vegetable wastes and carton: Effect of carton composition and parameter variations.

PubMed

Rawoteea, Soonita Anjeena; Mudhoo, Ackmez; Kumar, Sunil

2017-03-01

The aim of the study was to investigate the effects of carton in the composting process of mixed vegetable wastes using an experimental composter of capacity 80L. Three different mixes were set-up (Mixes 1, 2 and 3) which consisted of vegetable wastes, 2.0kg paper and bulking agents, vegetable wastes, 1.5kg carton and bulking agents, vegetable wastes, 4.5kg carton and bulking agents, respectively. Temperature evolution, pH trends, moisture levels, respiration rates, percentage volatile solids and electrical conductivity were monitored for a period of 50days. The system remained under thermophilic conditions for a very short period due to the small size of the reactor. The three mixes did not exceed a temperature of 55°C, where sanitization takes place by the destruction of pathogens. The highest peak of CO 2 evolution was observed in Mix 2 indicating that maximum microbial degradation took place in that mix. Copyright © 2016. Published by Elsevier Ltd.

Above Ground Carbon Stock Estimates of Mangrove Forest Using Worldview-2 Imagery in Teluk Benoa, Bali

NASA Astrophysics Data System (ADS)

Candra, E. D.; Hartono; Wicaksono, P.

2016-11-01

Mangrove forests have a role as an absorbent and a carbon sink to a reduction CO2 in the atmosphere. Based on the previous studies found that mangrove forests have the ability to sequestering carbon through photosynthesis and carbon burial of sediment effectively. The value and distribution of carbon stock are important to understand through remote sensing technology. In this study, will estimate the carbon stock using WorldView-2 imagery with and without distinction mangrove species. Worldview-2 is a high resolution image with 2 meters spatial resolution and eight spectral bands. Worldview-2 potential to estimate carbon stock in detail. Vegetation indices such as DVI (Difference Vegetation Index), EVI (Enhanced Vegetation Index), and MRE-SR (Modified Red Edge-Simple Ratio) and field data were modeled to determine the best vegetation indices to estimate carbon stocks. Carbon stock estimated by allometric equation approach specific to each species of mangrove. Worldview-2 imagery to map mangrove species with an accuracy of 80.95%. Total carbon stock estimation results in the study area of 35.349,87 tons of dominant species Rhizophora apiculata, Rhizophora mucronata and Sonneratia alba.

A Five-Year Analysis of MODIS NDVI and NDWI for Rangeland Drought Assessment: Preliminary Results

NASA Astrophysics Data System (ADS)

Gu, Y.; Brown, J. F.; Verdin, J. P.; Wardlow, B.

2006-12-01

Drought is one of the most costly natural disasters in the United States. Traditionally, drought monitoring has been based on weather station observations, which lack the continuous spatial coverage needed to adequately characterize and monitor detailed spatial patterns of drought conditions. Satellite remote sensing observations can provide a synoptic view of the land and provide a spatial context for measuring drought. A common satellite-based index, the normalized difference vegetation index (NDVI) has a 30-year history of use for vegetation condition monitoring. NDVI is calculated from the visible red and near infrared channels and measures the changes in chlorophyll absorption and reflection in the spongy mesophyll of the vegetation canopy that are reflected in these respective bands. The normalized difference water index (NDWI) is another index, derived from the near-infrared and short wave infrared channels, and reflects changes in both the water content and spongy mesophyll in the vegetation canopy. As a result, the NDWI is influenced by both desiccation and wilting in the vegetation canopy and may be a more sensitive indicator than the NDVI for large- area drought monitoring. The objective of this study was to process and evaluate a 5-year history of 500-meter NDVI and NDWI data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument and to investigate methods for measuring and monitoring drought in rangeland over the southern plains of the United States. This initial study included: (1) the development of a climatological database for MODIS NDVI and NDWI, (2) a study of the relationship between the NDVI, NDWI, and drought condition over rangeland, (3) the development of a method to provide threshold NDVI/NDWI values under drought conditions based on the 5-year NDVI/NDWI/drought condition analysis, and (4) the investigation of additional vegetation drought information provided by the NDWI versus the NDVI in a 5-year comparison of the two indices. The MODIS data were obtained from the Land Processes Distributed Active Archive System. Results show strong relationships among NDVI, NDWI, and drought analyzed over grasslands in the Flint Hills region of Kansas and Oklahoma. During the summer months, the average NDVI and NDWI values were consistently lower (NDVI<0.5 and NDWI<0.3) for the tallgrass prairie under drought conditions than under normal climate conditions (NDVI>0.6 and NDWI>0.4). The distinctions between drought conditions and normal climate conditions are based on the historic U.S. Drought Monitor maps and the historic Palmer index data. To take advantage of information contained in both indices, we calculated the difference between NDVI and NDWI (NDVI-NDWI). The difference between NDVI and NDWI slightly increases during the summer drought condition. Based on these analyses, the NDWI appears to be more sensitive than NDVI to drought conditions. The results of statistical analysis of the relationships among these indices will be presented in the poster.

Effects of Canada goose herbivory on the tidal freshwater wetlands in Anacostia Park, 2009-2011

USGS Publications Warehouse

Krafft, Cairn C.; Hatfield, Jeffrey S.; Hammerschlag, Richard S.

2013-01-01

Herbivory has played a major role in dictating vegetation abundance and species composition at Kingman Marsh in Anacostia Park, Washington, D.C., since restoration of this tidal freshwater wetland was initiated in 2000. The diverse and robust vegetative cover that developed in the first year post-reconstruction experienced significant decimation in the second year, after the protective fencing was removed, and remained suppressed throughout the five-year study period. In June 2009 a herbivory study was initiated to document the impacts of herbivory by resident and nonmigratory Canada geese (Branta canadensis) to vegetation at Kingman Marsh. Sixteen modules consisting of paired fenced plots and unfenced control plots were constructed. Eight of the modules were installed in vegetated portions of the restoration site that had been protected over time by pre-existing fencing, while the remaining eight modules were placed in portions of the site that had not been protected over time and were basically unvegetated at the start of the experiment. Exclosure fencing was sufficiently elevated from the substrate level to allow access to other herbivores such as fish and turtles, while hopefully excluding mature Canada geese. The study was designed with an initial exclosure elevation of 20 cm. This elevation was chosen based on the literature, as adequate to exclude mature Canada geese, while maximizing access to other herbivores such as fish and turtles. Repeated measures analysis of variance (ANOVA) was used to analyze the differences between paired fenced and unfenced control plots for a number of variables including total vegetative cover. Differences in total vegetative cover were not statistically significant for the baseline data collected in June 2009. By contrast, two months after the old protective fencing was removed from the initially-vegetated areas to allow Canada geese access to the unfenced control plots, total vegetative cover had declined dramatically in the initially-vegetated unfenced control plots, and differences between paired fenced and unfenced control plots were statistically significant. These differences have remained steady and significant throughout the remainder of these first three years of the study. Total vegetative cover has followed a somewhat different path in the initially-unvegetated modules, where cover in the fenced plots did not significantly exceed cover in the unfenced control plots until the August 2010 sampling event. In spite of the slow start in the initially-unvegetated modules, differences between paired fenced plots and unfenced control plots have remained significant and even increased significantly over time. This indicates that total vegetative cover in the initially-unvegetated fenced plots and unfenced control plots is continuing to diverge over time as vegetation increases in the protected plots compared to the basically unvegetated unfenced control plots. Total vegetative cover has been composed almost entirely of native species during the first three years of the study, with cover by exotics averaging less than 1% during each sampling event. Species richness did not differ significantly between fenced plots and unfenced control plots during 2009, the first year of the study. Since August 2010, species richness has remained significantly greater in the fenced plots than in the unfenced control plots. These differences have remained relatively steady over time for both the initially-vegetated and initially unvegetated modules. During the study it became apparent that our elevated fence plots were more accessible to mature geese than we had expected. Even after lowering the exclosure fencing to 15 cm in 2010 and 10 cm in 2011, we documented geese inside exclosures in both years. Nonetheless the data indicate that even at 10 cm, we have limited the numbers of mature geese entering the fenced plots, rather than totally preventing their access through low spots in the uneven substrate surface. At an exclosure elevation of 10 cm and with a soft, mucky substrate, we are assuming that non-goose herbivores such as fish and turtles still have free access to the fenced plots. Annual wildrice (Zizania aquatica), known from previous studies to be especially palatable to Canada geese, has seen the greatest impact from partial access to the fenced plots by mature geese, moving from an overwhelming dominant in the initially-vegetated plots to a minor presence there by August 2011. Interestingly, pickerelweed (Pontederia cordata), also known to be highly palatable to Canada geese, has so far shown only minor herbivory in the fenced plots. By August 2011, pickerelweed had actually increased to significantly greater cover levels in the fenced plots compared to the unfenced control plots. In conclusion, the first three years of data document that vegetation exposed to full herbivory by resident and nonmigratory Canada geese for three years in the unfenced control plots showed significantly lower total vegetative cover and species richness compared to the vegetation in the fenced plots, which experienced reduced herbivory by resident and nonmigratory Canada geese. These effects were documented for modules located in both initially-vegetated and initially-unvegetated habitats.

Vertical and Horizontal Vegetation Structure across Natural and Modified Habitat Types at Mount Kilimanjaro.

PubMed

Rutten, Gemma; Ensslin, Andreas; Hemp, Andreas; Fischer, Markus

2015-01-01

In most habitats, vegetation provides the main structure of the environment. This complexity can facilitate biodiversity and ecosystem services. Therefore, measures of vegetation structure can serve as indicators in ecosystem management. However, many structural measures are laborious and require expert knowledge. Here, we used consistent and convenient measures to assess vegetation structure over an exceptionally broad elevation gradient of 866-4550 m above sea level at Mount Kilimanjaro, Tanzania. Additionally, we compared (human)-modified habitats, including maize fields, traditionally managed home gardens, grasslands, commercial coffee farms and logged and burned forests with natural habitats along this elevation gradient. We distinguished vertical and horizontal vegetation structure to account for habitat complexity and heterogeneity. Vertical vegetation structure (assessed as number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) displayed a unimodal elevation pattern, peaking at intermediate elevations in montane forests, whereas horizontal structure (assessed as coefficient of variation of number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) was lowest at intermediate altitudes. Overall, vertical structure was consistently lower in modified than in natural habitat types, whereas horizontal structure was inconsistently different in modified than in natural habitat types, depending on the specific structural measure and habitat type. Our study shows how vertical and horizontal vegetation structure can be assessed efficiently in various habitat types in tropical mountain regions, and we suggest to apply this as a tool for informing future biodiversity and ecosystem service studies.

Analysis of land cover/use changes using Landsat 5 TM data and indices.

PubMed

Ettehadi Osgouei, Paria; Kaya, Sinasi

2017-04-01

Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

Determining the K coefficient to leaf area index estimations in a tropical dry forest

NASA Astrophysics Data System (ADS)

Magalhães, Sarah Freitas; Calvo-Rodriguez, Sofia; do Espírito Santo, Mário Marcos; Sánchez Azofeifa, Gerardo Arturo

2018-03-01

Vegetation indices are useful tools to remotely estimate several important parameters related to ecosystem functioning. However, improving and validating estimations for a wide range of vegetation types are necessary. In this study, we provide a methodology for the estimation of the leaf area index (LAI) in a tropical dry forest (TDF) using the light diffusion through the canopy as a function of the successional stage. For this purpose, we estimated the K coefficient, a parameter that relates the normalized difference vegetation index (NDVI) to LAI, based on photosynthetically active radiation (PAR) and solar radiation. The study was conducted in the Mata Seca State Park, in southeastern Brazil, from 2012 to 2013. We defined four successional stages (very early, early, intermediate, and late) and established one optical phenology tower at one plot of 20 × 20 m per stage. Towers measured the incoming and reflected solar radiation and PAR for NDVI calculation. For each plot, we established 24 points for LAI sampling through hemispherical photographs. Because leaf cover is highly seasonal in TDFs, we determined ΔK (leaf growth phase) and K max (leaf maturity phase). We detected a strong correlation between NDVI and LAI, which is necessary for a reliable determination of the K coefficient. Both NDVI and LAI varied significantly between successional stages, indicating sensitivity to structural changes in forest regeneration. Furthermore, the K values differed between successional stages and correlated significantly with other environmental variables such as air temperature and humidity, fraction of absorbed PAR, and soil moisture. Thus, we established a model based on spectral properties of the vegetation coupled with biophysical characteristics in a TDF that makes possible to estimate LAI from NDVI values. The application of the K coefficient can improve remote estimations of forest primary productivity and gases and energy exchanges between vegetation and atmosphere. This model can be applied to distinguish different successional stages of TDFs, supporting environmental monitoring and conservation policies towards this biome.

Global meta-analysis of leaf area index in wetlands indicates uncertainties in understanding of their ecosystem function

NASA Astrophysics Data System (ADS)

Dronova, I.; Taddeo, S.; Foster, K.

2017-12-01

Projecting ecosystem responses to global change relies on the accurate understanding of properties governing their functions in different environments. An important variable in models of ecosystem function is canopy leaf area index (LAI; leaf area per unit ground area) declared as one of the Essential Climate Variables in the Global Climate Observing System and extensively measured in terrestrial landscapes. However, wetlands have been largely under-represented in these efforts, which globally limits understanding of their contribution to carbon sequestration, climate regulation and resilience to natural and anthropogenic disturbances. This study provides a global synthesis of >350 wetland-specific LAI observations from 182 studies and compares LAI among wetland ecosystem and vegetation types, biomes and measurement approaches. Results indicate that most wetland types and even individual locations show a substantial local dispersion of LAI values (average coefficient of variation 65%) due to heterogeneity of environmental properties and vegetation composition. Such variation indicates that mean LAI values may not sufficiently represent complex wetland environments, and the use of this index in ecosystem function models needs to incorporate within-site variation in canopy properties. Mean LAI did not significantly differ between direct and indirect measurement methods on a pooled global sample; however, within some of the specific biomes and wetland types significant contrasts between these approaches were detected. These contrasts highlight unique aspects of wetland vegetation physiology and canopy structure affecting measurement principles that need to be considered in generalizing canopy properties in ecosystem models. Finally, efforts to assess wetland LAI using remote sensing strongly indicate the promise of this technology for cost-effective regional-scale modeling of canopy properties similar to terrestrial systems. However, such efforts urgently require more rigorous corrections for three-dimensional contributions of non-canopy material and non-vegetated surfaces to wetland canopy reflectance.

Mineral composition of non-conventional leafy vegetables.

PubMed

Barminas, J T; Charles, M; Emmanuel, D

1998-01-01

Six non-conventional leafy vegetables consumed largely by the rural populace of Nigeria were analyzed for mineral composition. Mineral contents appeared to be dependent on the type of vegetables. Amaranthus spinosus and Adansonia digitata leaves contained the highest level of iron (38.4 mg/100 g and 30.6 mg/100 g dw, respectively). These values are low compared to those for common Nigerian vegetables but higher than those for other food sources. All the vegetables contained high levels of calcium compared to common vegetables, thus they could be a rich source of this mineral. Microelement content of the leaves varied appreciably. Zinc content was highest in Moringa oleifera, Adansonia digitata and Cassia tora leaves (25.5 mg/100 g, 22.4 mg/100 g and 20.9 mg/100 g dw, respectively) while the manganese content was comparatively higher in Colocasia esculenta. The concentrations of the mineral elements in the vegetables per serving portion are presented and these values indicate that the local vegetables could be valuable and important contributors in the diets of the rural and urban people of Nigeria. The mean daily intake of P, Mg, Ca, Fe, Cu and Zn were lower than their recommended dietary allowances (RDAs). However, the manganese daily intake was found not to differ significantly (p = 0.05) from the RDA value.

Multivariate ordination identifies vegetation types associated with spider conservation in brassica crops

PubMed Central

Saqib, Hafiz Sohaib Ahmed; You, Minsheng

2017-01-01

Conservation biological control emphasizes natural and other non-crop vegetation as a source of natural enemies to focal crops. There is an unmet need for better methods to identify the types of vegetation that are optimal to support specific natural enemies that may colonize the crops. Here we explore the commonality of the spider assemblage—considering abundance and diversity (H)—in brassica crops with that of adjacent non-crop and non-brassica crop vegetation. We employ spatial-based multivariate ordination approaches, hierarchical clustering and spatial eigenvector analysis. The small-scale mixed cropping and high disturbance frequency of southern Chinese vegetation farming offered a setting to test the role of alternate vegetation for spider conservation. Our findings indicate that spider families differ markedly in occurrence with respect to vegetation type. Grassy field margins, non-crop vegetation, taro and sweetpotato harbour spider morphospecies and functional groups that are also present in brassica crops. In contrast, pumpkin and litchi contain spiders not found in brassicas, and so may have little benefit for conservation biological control services for brassicas. Our findings also illustrate the utility of advanced statistical approaches for identifying spatial relationships between natural enemies and the land uses most likely to offer alternative habitats for conservation biological control efforts that generates testable hypotheses for future studies. PMID:29085741

Associations of parenting styles, parental feeding practices and child characteristics with young children's fruit and vegetable consumption.

PubMed

Vereecken, Carine; Rovner, Alisha; Maes, Lea

2010-12-01

The purpose of this study was to investigate the role of parent and child characteristics in explaining children's fruit and vegetable intakes. In 2008, parents of preschoolers (mean age 3.5 years) from 56 schools in Belgium-Flanders completed questionnaires including a parent and child fruit and vegetable food frequency questionnaire, general parenting styles (laxness, overreactivity and positive interactions), specific food parenting practices (child-centered and parent-centered feeding practices) and children's characteristics (children's shyness, emotionality, stubbornness, activity, sociability, and negative reactions to food). Multiple linear regression analyses (n = 755) indicated a significant positive association between children's fruit and vegetable intake and parent's intake and a negative association with children's negative reactions to food. No general parenting style dimension or child personality characteristic explained differences in children's fruit and vegetable intakes. Child-centered feeding practices were positively related to children's fruit and vegetable intakes, while parent-centered feeding practices were negatively related to children's vegetable intakes. In order to try to increase children's fruit and vegetable consumption, parents should be guided to improve their own diet and to use child-centered parenting practices and strategies known to decrease negative reactions to food. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Polish Study on the Influence of Food Neophobia in Children (10–12 Years Old) on the Intake of Vegetables and Fruits

PubMed Central

Guzek, Dominika; Głąbska, Dominika; Lange, Ewa; Jezewska-Zychowicz, Marzena

2017-01-01

Adhering to the recommended intake of fruits and vegetables is an important habit that should be inculcated in children, whereas food neophobia is indicated as one of the most important factors creating food preferences that may interfere. The aim of the presented study was to analyze the association between the food neophobia level and the intake of fruits and vegetables in children aged 10–12 years. The study was conducted among a group of 163 children (78 girls and 85 boys). The assessment of the food neophobia level was based on the Food Neophobia Scale (FNS) questionnaire and the assessment of the fruit and vegetable intake was based on the food frequency questionnaire. A negative correlation between the food neophobia level and the vegetable intake was observed both for girls (p = 0.032; R = −0.2432) and for boys (p = 0.004; R = −0.3071), whereas for girls differences in vegetable intake were observed also between various food neophobia categories (p = 0.0144). It may be concluded that children with higher food neophobia level are characterized by lower vegetable intake than children with lower food neophobia level. For fruits and juices of fruits and vegetables, associations with food neophobia level were not observed. PMID:28574424

Analyzing the non-stationary space relationship of a city's degree of vegetation and social economic conditions in Shanghai, China using OLS and GWR models

NASA Astrophysics Data System (ADS)

Wang, Kejing; Zhang, Yuan; An, Youzhi; Jing, Zhuoxin; Wang, Chao

2013-09-01

With the fast urbanization process, how does the vegetation environment change in one of the most economically developed metropolis, Shanghai in East China? To answer this question, there is a pressing demand to explore the non-stationary relationship between socio-economic conditions and vegetation across Shanghai. In this study, environmental data on vegetation cover, the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery in 2003 were integrated with socio-economic data to reflect the city's vegetative conditions at the census block group level. To explore regional variations in the relationship of vegetation and socio-economic conditions, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to characterize mean NDVI against three independent socio-economic variables, an urban land use ratio, Gross Domestic Product (GDP) and population density. The study results show that a considerable distinctive spatial variation exists in the relationship for each model. The GWR model has superior effects and higher precision than the OLS model at the census block group scale. So, it is more suitable to account for local effects and geographical variations. This study also indicates that unreasonable excessive urbanization, together with non-sustainable economic development, has a negative influence of vegetation vigor for some neighborhoods in Shanghai.

A Polish Study on the Influence of Food Neophobia in Children (10-12 Years Old) on the Intake of Vegetables and Fruits.

PubMed

Guzek, Dominika; Głąbska, Dominika; Lange, Ewa; Jezewska-Zychowicz, Marzena

2017-06-02

Adhering to the recommended intake of fruits and vegetables is an important habit that should be inculcated in children, whereas food neophobia is indicated as one of the most important factors creating food preferences that may interfere. The aim of the presented study was to analyze the association between the food neophobia level and the intake of fruits and vegetables in children aged 10-12 years. The study was conducted among a group of 163 children (78 girls and 85 boys). The assessment of the food neophobia level was based on the Food Neophobia Scale (FNS) questionnaire and the assessment of the fruit and vegetable intake was based on the food frequency questionnaire. A negative correlation between the food neophobia level and the vegetable intake was observed both for girls ( p = 0.032; R = -0.2432) and for boys ( p = 0.004; R = -0.3071), whereas for girls differences in vegetable intake were observed also between various food neophobia categories ( p = 0.0144). It may be concluded that children with higher food neophobia level are characterized by lower vegetable intake than children with lower food neophobia level. For fruits and juices of fruits and vegetables, associations with food neophobia level were not observed.

On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

2015-04-01

Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbanceInternational Journal of Applied Earth Observation and Geoinformation 26 441-446 Lanorte A, M Danese, R Lasaponara, B Murgante 2014 Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis International Journal of Applied Earth Observation and Geoinformation 20, 42-51 Tuia D, F Ratle, R Lasaponara, L Telesca, M Kanevski 2008 Scan statistics analysis of forest fire clusters Communications in Nonlinear Science and Numerical Simulation 13 (8), 1689-1694 Telesca L, R Lasaponara 2006 Pre and post fire behavioral trends revealed in satellite NDVI time series Geophysical Research Letters 33 (14) Lasaponara R 2005 Intercomparison of AVHRR based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy International Journal of Remote Sensing 26 (5), 853-870

On the terminology of the spectral vegetation index (NIR – SWIR)/(NIR + SWIR)

USGS Publications Warehouse

Ji, Lel; Zhang, Li; Wylie, Bruce K.; Rover, Jennifer R.

2011-01-01

The spectral vegetation index (ρNIR – ρSWIR)/(ρNIR + ρSWIR), where ρNIR and ρSWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI), and normalized burn ratio (NBR), etc. After reviewing each term’s definition, associated sensors, and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2–1.3 µm, 1.55–1.75 µm, or 2.05–2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term’s popularity, and the “rule of priority” in scientific nomenclature, NDWI, NDII, and NBR, each corresponding to the three SWIR regions, are more preferable terms.

Remote sensing of aquatic vegetation distribution in Taihu Lake using an improved classification tree with modified thresholds.

PubMed

Zhao, Dehua; Jiang, Hao; Yang, Tangwu; Cai, Ying; Xu, Delin; An, Shuqing

2012-03-01

Classification trees (CT) have been used successfully in the past to classify aquatic vegetation from spectral indices (SI) obtained from remotely-sensed images. However, applying CT models developed for certain image dates to other time periods within the same year or among different years can reduce the classification accuracy. In this study, we developed CT models with modified thresholds using extreme SI values (CT(m)) to improve the stability of the models when applying them to different time periods. A total of 903 ground-truth samples were obtained in September of 2009 and 2010 and classified as emergent, floating-leaf, or submerged vegetation or other cover types. Classification trees were developed for 2009 (Model-09) and 2010 (Model-10) using field samples and a combination of two images from winter and summer. Overall accuracies of these models were 92.8% and 94.9%, respectively, which confirmed the ability of CT analysis to map aquatic vegetation in Taihu Lake. However, Model-10 had only 58.9-71.6% classification accuracy and 31.1-58.3% agreement (i.e., pixels classified the same in the two maps) for aquatic vegetation when it was applied to image pairs from both a different time period in 2010 and a similar time period in 2009. We developed a method to estimate the effects of extrinsic (EF) and intrinsic (IF) factors on model uncertainty using Modis images. Results indicated that 71.1% of the instability in classification between time periods was due to EF, which might include changes in atmospheric conditions, sun-view angle and water quality. The remainder was due to IF, such as phenological and growth status differences between time periods. The modified version of Model-10 (i.e. CT(m)) performed better than traditional CT with different image dates. When applied to 2009 images, the CT(m) version of Model-10 had very similar thresholds and performance as Model-09, with overall accuracies of 92.8% and 90.5% for Model-09 and the CT(m) version of Model-10, respectively. CT(m) decreased the variability related to EF and IF and thereby improved the applicability of the models to different time periods. In both practice and theory, our results suggested that CT(m) was more stable than traditional CT models and could be used to map aquatic vegetation in time periods other than the one for which the model was developed. Copyright © 2011 Elsevier Ltd. All rights reserved.

AN APPROACH TO ASSESSING THE CONDITION OF RIPARIAN PLANT COMMUNITIES IN THE JOHN DAY AND DESCHUTES RIVER BASINS OF EASTERN OREGON

EPA Science Inventory

Riparian vegetation represents unique plant communities and provides a variety of ecosystem services that influence in-stream condition. This research develops methods and indicators for evaluating vegetation condition. A key indicator of riparian vegetation condition is the deg...

Assessment of the environmental effects of mining using SPOT-Vegetation NDVI

NASA Astrophysics Data System (ADS)

Tote, C.; Swinnen, E.; Goossens, M.; Reusen, I.; Delalieux, S.

2012-04-01

Within the ImpactMin project, funded by the Framework Programme 7 of the European Commission, new methods for the environmental impact monitoring of mining operations are being developed. The objective of this study is to analyze the impact of mining on soil properties through assessment of the vegetation status using time series analysis of low resolution Normalized Difference Vegetation Index (NDVI) images derived from SPOT-Vegetation. The study focuses on the surroundings of mining areas in the Orenburg region in the Russian Urals. Karabash has been a centre for mining and metal production for well over 3000 years, and environmental impact of (historical) mining in the area is extremely severe. The area was characterized as an 'ecological disaster zone', based on chemical analysis of soil samples in the area [1]. The mining activities were intensified in the early to mid-20th century, but the old smelter was modernized in the 1990s. A time series of 10-daily NDVI images from SPOT-Vegetation (S10 April/1998-December/2010 at 1km2 resolution, http://www.vgt.vito.be/) is analyzed. Different land cover types clearly show different phenology. To remove seasonal vegetation changes and thus to facilitate the interpretation through the historical record, a Standardized Difference Vegetation Index (SDVI) was calculated for each pixel and for each record of the time series. The first results of trend analyses indicate a strong recovery of open forests in the Karabash region in the last decade. To what extent this can be related to reduced mining impact or climate factors, still needs to be assessed. Further research will also focus on the spatial heterogeneity of phenological parameters, in relation to distance to and wind direction of the smelters and soil properties. [1] V. Nestersnko, "Urban associations of elements- environmental pollutants in Karabash city (Chelyabinsk oblast) as a reflection of ore-chemical descriptions of mineral raw material", Proceedings of the Chelyabinsk Scientific Center, vol. 3, pp. 58-62, 2006.

Impacts of hydroelectric dams on alluvial riparian plant communities in Eastern Brazilian Amazonian.

PubMed

Ferreira, Leandro Valle; Cunha, Denise A; Chaves, Priscilla P; Matos, Darley C L; Parolin, Pia

2013-09-01

The major rivers of the Amazon River basin and their biota are threatened by the planned construction of large hydroelectric dams that are expected to have strong impacts on floodplain plant communities. The present study presents forest inventories from three floodplain sites colonized by alluvial riparian vegetation in the Tapajós, Xingu and Tocantins River basins in eastern Amazonian. Results indicate that tree species of the highly specialized alluvial riparian vegetation are clearly distinct among the three river basins, although they are not very distinct from each other and environmental constraints are very similar. With only 6 of 74 species occurring in all three inventories, most tree and shrub species are restricted to only one of the rivers, indicating a high degree of local distribution. Different species occupy similar environmental niches, making these fragile riparian formations highly valuable. Conservation plans must consider species complementarily when decisions are made on where to place floodplain forest conservation units to avoid the irreversible loss of unique alluvial riparian vegetation biodiversity.

Assessment of air pollution impacts on vegetation in South Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botha, A.T.

1989-01-01

Field surveys and biomonitoring network experiments were conducted in selected areas in South Africa to assess possible air pollution damage to vegetation. During field surveys, atmospheric fluoride was identified as an important pollutant that damaged vegetation in residential areas north of Cape Town. Gaseous air pollutants, including acid deposition and acidic mist, probably play a major role in the development of characteristic air pollution injury symptoms observed on pine trees in the Eastern Transvaal area. The impact of urban air pollution in the Cape Town area was evaluated by exposing bio-indicator plants in a network of eight biomonitoring network stationsmore » from June 1985 to May 1988. Sensitive Freesia and Gladiolus cultivars were used to biomonitor atmospheric fluoride, while a green bean cultivar was used as a biomonitor of atmospheric sulfur dioxide and ozone. At one location, bio-indicator plants were simultaneously exposed in a biomonitoring network station, open-top chambers, as well as in open plots. The responses of plants grown under these different conditions were compared.« less

Leaf area index retrieval using Hyperion EO-1 data-based vegetation indices in Himalayan forest system

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Singh, Sarnam

2016-04-01

Present Study is being taken to retrieve Leaf Area Indexn(LAI) in Himalayan forest system using vegetation indices developed from Hyperion EO-1 hyperspectral data. Hemispherical photograph were captured in the month of March and April, 2012 at 40 locations, covering moist tropical Sal forest, subtropical Bauhinia and pine forest and temperate Oak forest and analysed using an open source GLA software. LAI in the study region was ranging in between 0.076 m2/m2 to 6.00 m2/m2. These LAI values were used to develop spectral models with the FLAASH corrected Hyperion measurements.Normalized difference vegetation index (NDVI) was used taking spectral reflectance values of all the possible combinations of 170 atmospherically corrected channels. The R2 was ranging from lowest 0.0 to highest 0.837 for the band combinations of spectral region 640 nm and 670 nm. The spectral model obtained was, spectral reflectance (y) = 0.02x LAI(x) - 0.0407.

Post-fire Vegetation Regeneration Dynamics to Topography and Burn Severity in two contrasting ecosystems: the Case of the Montane Cordillera Ecozones of Western Canada & that of a Typical Mediterranean site in Greece

NASA Astrophysics Data System (ADS)

Ireland, Gareth; Petropoulos, George P.; Kalivas, Dionissios; Griffirths, Hywel M.; Louka, Panagiota

2015-04-01

Altering land cover dynamics is currently regarded as the single most important variable of global change affecting ecological systems. Wildfires are an integral part of many terrestrial ecosystems and are considered to dramatically affect land cover dynamics at a variety of spatial and temporal scales. In this context, knowledge of the spatio-temporal distribution of post-fire vegetation recovery dynamics is of key importance. In this study, we explore the relationships between vegetation recovery dynamics to topography and burn severity for two different ecosystems using a chronosequence of Landsat TM data images analysis. One of our experimental sites is the Okanagan Mountain Park, located in the Montane Cordillera Ecozones of western Canada at which a fire occurred in 2003. The other is Mt. Parnitha, located in Greece, representing a typical Mediterranean setting. The spatio-temporal patterns of regrowth for 8 years following the fire events were quantified based on the analysis of 2 widely used indices, the Normalized Difference Vegetation Index (NDVI) and the Regeneration Index (RI). Burn severity was derived from the differenced Normalized Burn Ratio (dNBR) index computed from the Landsat TM images. Topographical information for the studied area was obtained from the ASTER global operational product. Relationships of vegetation regrowth to both topography and burn severity was quantified using a series of additional statistical metrics. In overall, results indicated noticeable differences in the recovery rates of both ecosystems to the pre-fire patterns. Re-growth rates appeared to be somewhat higher in north-facing slopes in comparison to south facing ones for both experimental sites, in common with other similar studies in different ecosystems. Lastly, areas of lower burn severity exhibited a higher recovery rate compared to areas of high severity burns. Results are presented in detail and an explanation of the main observation trends is also attempted to be provided. To our knowledge, this study is one of the few attempting to explore the relationships between post-fire vegetation regrowth and topography or burn severity, particularly so in such a comparative and systematic manner between two contrasting ecosystem types. It corroborates the significance of EO technology as a successful and cost-effective solution in providing information related to post-fire regeneration assessment. Keywords: post-fire vegetation regeneration, topography, burn severity, Landsat, remote sensing, Cordillera Ecozones, Canada, Mt. Parnitha, Greece

Information extraction with object based support vector machines and vegetation indices

NASA Astrophysics Data System (ADS)

Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

2016-07-01

Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

Spatial variation in below ground carbon cycling in a pristine peatland, driven by present and past vegetation

NASA Astrophysics Data System (ADS)

Mathijssen, Paul; Knorr, Klaus-Holger; Gałka, Mariusz; Borken, Werner

2017-04-01

Peat carbon cycling is controlled by both large scale factors, such as climate and hydrological setting, and small scale factors, such as microtopography, vegetation, litter quality, and rooting depth. These small scale factors commonly vary within peatlands, causing variation in the carbon balance at different locations within the same site. Understanding the relationship between small scale carbon cycling and vegetation helps us to assess the variation of carbon dynamics of peatlands, because vegetation composition acts as an integrator of factors such as microtopography, hydrology, and nutrient level. Variation in vegetation illustrates spatial variation of these underlying factors. Furthermore, the presence of certain plant species affects carbon cycling directly through litter quality or aeration through root tissues. In order to understand these within-site variations in terms of carbon cycling, we investigated carbon accumulation, decomposition, and biogeochemistry of pore waters along a transect of peat cores with changing vegetation and water levels in an ombrotrophic peatland in southern Patagonia. The transect ran from a Sphagnum magellanicum dominated spot with relatively high water table, to intermediately wet spots with mixed Sphagnum/shrubs vegetation, or dominated by Cyperaceae, eventually to a more elevated and drier spot dominated by cushion plants (mainly Astelia pumila). There were large differences in peat accumulation rates and peat densities, with faster peat growth and lower densities under Sphagnum, but overall carbon accumulation rates were quite similar in the various microenvironments. At most plots C/N ratios decreased with depth, concurrent with increasing humification index derived from FT-IR spectra. But under cushion plants this relation was opposite: more humification with depth, but also C/N ratios increases. This reflected the differing source material at depth under the cushion plants, and that the cushion plant peat layers were formed on top of Sphagnum peat. The divergent source material throughout a peat core makes it difficult to use C/N ratios to indicate peat decomposition rates. Although the low peat density and higher C/N ratios indicate that overall carbon turnover is slow at Sphagnum plots, pore water methane concentrations were elevated. At cushion plant plots, however, higher redox potentials exist until greater depths due to aerenchymous roots, inhibiting methane production and release. Our results demonstrate that large variation exists within pristine bogs, in terms of decomposition patterns, organic matter quality, and carbon turnover pathways, corresponding to variation in surface moisture levels and vegetation. Furthermore, variation in carbon cycling properties are maintained in buried peat layers and reflect more the organic material of that layer, than the current surface carbon dynamics.

Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

2017-12-01

The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks, RNVCF shows significant overestimation in summer, perhaps due to RNVCF ignores the growing characteristics of vegetation (mainly grass) in these two regions. Our results demonstrate that VCF schemes have significant influence on LSM performance, and indicate that it is important to consider vegetation growing characteristics in VCF schemes for different LCs.

Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak

USGS Publications Warehouse

Carlson, Amanda R.; Sibold, Jason S.; Assal, Timothy J.; Negrón, José F.

2017-01-01

Spruce beetle (Dendroctonus rufipennis) outbreaks are rapidly spreading throughout subalpine forests of the Rocky Mountains, raising concerns that altered fuel structures may increase the ecological severity of wildfires. Although many recent studies have found no conclusive link between beetle outbreaks and increased fire size or canopy mortality, few studies have addressed whether these combined disturbances produce compounded effects on short-term vegetation recovery. We tested for an effect of spruce beetle outbreak severity on vegetation recovery in the West Fork Complex fire in southwestern Colorado, USA, where much of the burn area had been affected by severe spruce beetle outbreaks in the decade prior to the fire. Vegetation recovery was assessed using the Landsat-derived Normalized Difference Vegetation Index (NDVI) two years after the fire, which occurred in 2013. Beetle outbreak severity, defined as the basal area of beetle-killed trees within Landsat pixels, was estimated using vegetation index differences (dVIs) derived from pre-outbreak and post-outbreak Landsat images. Of the seven dVIs tested, the change in Normalized Difference Moisture Index (dNDMI) was most strongly correlated with field measurements of beetle-killed basal area (R2 = 0.66). dNDMI was included as an explanatory variable in sequential autoregressive (SAR) models of NDVI2015. Models also included pre-disturbance NDVI, topography, and weather conditions at the time of burning as covariates. SAR results showed a significant correlation between NDVI2015 and dNDMI, with more severe spruce beetle outbreaks corresponding to reduced post-fire vegetation cover. The correlation was stronger for models which were limited to locations in the red stage of outbreak (outbreak ≤ 5 years old at the time of fire) than for models of gray-stage locations (outbreak > 5 years old at the time of fire). These results indicate that vegetation recovery processes may be negatively impacted by severe spruce beetle outbreaks occurring within a decade of stand-replacing wildfire.

Are vegetated areas of mangroves attractive to juvenile and small fish? The case of Dongzhaigang Bay, Hainan Island, China

NASA Astrophysics Data System (ADS)

Wang, Mao; Huang, Zhenyuan; Shi, Fushan; Wang, Wenqing

2009-11-01

Well-developed aerial roots of mangroves make it difficult to study how fish utilize the mangrove forest as a habitat. In the present study, we compared the differences in fish assemblages in three major types of habitats of mangrove estuary (vegetated area, treeless mudflat, and creek) of a mangrove bay in Hainan Island, China, at different seasons during two consecutive years. Three types of gears, centipede net, gill net and cast net, were used in the different habitats of mangrove estuary and sampling efficiencies among gears were evaluated. Centipede nets were used in all the three types of habitats and cast nets and gill nets in treeless mudflats and creeks. Fish assemblages were dependent on gears used. Centipede net could efficiently catch fish occurring both inside and outside of vegetated areas efficiently. A total of 115 fish species in 51 families were collected. In terms of numbers of species per family, Gobiidae was the most diverse (17 species), followed by Mugilidae (5 species). Almost all of the fish were juvenile or small fish and few predators were recorded, implying low predation pressure in the bay. ANOVA analysis showed that significant seasonal and spatial variation existed in species richness, abundance, and biomass, which were less in the vegetated areas than those of treeless mudflats and creeks. The attraction of vegetated areas to fish was less than that of creeks and mudflats. Many species were specific to a particular habitat type, 4 species occurring exclusively in the creeks, 45 species occurring exclusively in the treeless mudflats, and 5 species occurring exclusively in the vegetated areas. The results indicated that mangrove estuaries were potentially attractive habitats for juvenile and small fish, but this attraction was accomplished by a connection of vegetated areas, treeless mudflats and creeks, not only by vegetated areas.

Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak

PubMed Central

Carlson, Amanda R.; Sibold, Jason S.; Assal, Timothy J.; Negrón, Jose F.

2017-01-01

Spruce beetle (Dendroctonus rufipennis) outbreaks are rapidly spreading throughout subalpine forests of the Rocky Mountains, raising concerns that altered fuel structures may increase the ecological severity of wildfires. Although many recent studies have found no conclusive link between beetle outbreaks and increased fire size or canopy mortality, few studies have addressed whether these combined disturbances produce compounded effects on short-term vegetation recovery. We tested for an effect of spruce beetle outbreak severity on vegetation recovery in the West Fork Complex fire in southwestern Colorado, USA, where much of the burn area had been affected by severe spruce beetle outbreaks in the decade prior to the fire. Vegetation recovery was assessed using the Landsat-derived Normalized Difference Vegetation Index (NDVI) two years after the fire, which occurred in 2013. Beetle outbreak severity, defined as the basal area of beetle-killed trees within Landsat pixels, was estimated using vegetation index differences (dVIs) derived from pre-outbreak and post-outbreak Landsat images. Of the seven dVIs tested, the change in Normalized Difference Moisture Index (dNDMI) was most strongly correlated with field measurements of beetle-killed basal area (R2 = 0.66). dNDMI was included as an explanatory variable in sequential autoregressive (SAR) models of NDVI2015. Models also included pre-disturbance NDVI, topography, and weather conditions at the time of burning as covariates. SAR results showed a significant correlation between NDVI2015 and dNDMI, with more severe spruce beetle outbreaks corresponding to reduced post-fire vegetation cover. The correlation was stronger for models which were limited to locations in the red stage of outbreak (outbreak ≤ 5 years old at the time of fire) than for models of gray-stage locations (outbreak > 5 years old at the time of fire). These results indicate that vegetation recovery processes may be negatively impacted by severe spruce beetle outbreaks occurring within a decade of stand-replacing wildfire. PMID:28777802

InfoSequia: the first operational remote sensing-based Drought Monitoring System of Spain

NASA Astrophysics Data System (ADS)

Contreras, Sergio; Hunink, Johannes E.

2016-04-01

We present a satellite-based Drought Monitoring System that provides weekly updates of maps and bulletins with vegetation drought indices over the Iberian Peninsula. The web portal InfoSequía (http://infosequia.es) aims to complement the current Spanish Drought Monitoring System which relies on a hydrological drought index computed at the basin level using data on river flows and water stored in reservoirs. Drought indices computed by InfoSequia are derived from satellite data provided by MODIS sensors (TERRA and AQUA satellites), and report the relative anomaly observed in the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and in an additive combination of both. Similar to the U.S. Drought Monitoring System by NOAA, the indices include the Vegetation Condition Index (VCI, relative NDVI anomaly), the Temperature Condition Index (TCI, relative LST anomaly) and the Vegetation Health Index (VHI, relative NDVI-LST anomaly). Relative anomalies are codified into four warning levels, and all of them are provided for short periods of time (8-day windows), or longer periods (e.g. 1 year) in order to capture the cumulative effects of droughts in the state variables. Additionally, InfoSequia quantifies the seasonal trajectories of the cumulative deviation of the observed NDVI in relation with the averaged seasonal trajectory observed over a reference period. Through the weekly bulletins, the Drought Monitoring System InfoSequia aims to provide practical information to stakeholders on the sensitivity and resilience of native ecosystems and rainfed agrosystems during drought periods. Also, the remote sensed indices can be used as drought impact indicator to evaluate the skill of seasonal agricultural drought forecasting systems. InfoSequia is partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant.

The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

NASA Astrophysics Data System (ADS)

Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

2016-06-01

Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower relationship to vegetation indices. Total amount of aboveground biomass was identified as the most important factor influencing the values of vegetation indices. Based on the results can be assumed that UAV and satellite monitoring provide reliable information about crop parameters for site specific crop management. The main difference of their utilization is coming from their specification and technical limits. Satellite survey can be used for periodic monitoring of crops as the indicator of their spatial heterogeneity within fields, but with low resolution (30 m per pixel for OLI). On the other hand UAV represents a special campaign aimed on the mapping of high-detailed spatial inputs for site specific crop management and variable rate application of fertilizers.

Effects of Different Regeneration Scenarios and Fertilizer Treatments on Soil Microbial Ecology in Reclaimed Opencast Mining Areas on the Loess Plateau, China

PubMed Central

Li, Junjian; Zheng, Yuanming; Yan, Junxia; Li, Hongjian; Wang, Xiang; He, Jizheng; Ding, Guangwei

2013-01-01

The soil microbial community in reclaimed mining areas is fundamental to vegetative establishment. However, how this community responds to different regeneration scenarios and fertilizer treatments is poorly understood. This research evaluated plant and soil microbial communities from different regeneration scenarios and different fertilizer treatments. Regeneration scenarios significantly influenced soil bacterial, archaeal, and fungal rDNA abundance. The ratios of fungi to bacteria or archaea were increased with fertilizer application. The diversity of both plants and microbes was lowest in Lotus corniculatus grasslands. Regeneration scenario, fertilizer treatment, and their interaction influenced soil microbial richness, diversity and evenness indices. Labile carbon pool 2 was a significant factor affected plant and microbe communities in July, suggesting that plants and microbes may be competing for nutrients. The higher ratios of positive to negative association were found in soil bacteria and total microbe than in archaea and fungi. Stronger clustering of microbial communities from the same regeneration scenario indicated that the vegetative composition of regeneration site may have a greater influence on soil microbial communities than fertilizer treatment. PMID:23658819

A Study on Spectral Signature Analysis of Wetland Vegetation Based on Ground Imaging Spectrum Data

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Liu, Hua; Ju, Hongbo; Zhang, Huaiqing; You, Jia; Li, Weina

2017-10-01

The objective of this study was to verify the application of imaging spectrometer in wetland vegetation remote sensing monitoring, based on analysis of wetland vegetation spectral features. Spectral information of Carex vegetation spectral data under different water environment was collected bySOC710VP and ASD FieldSpec 3; Meanwhile, the chlorophyll contents of wheat leaves were tested in the lab. A total 9 typical vegetation indices were calculated by using two instruments’ data which were spectral values from 400nm to 1000 nm. Then features between the same vegetation indices and soil water contents for two applications were analyzed and compared. The results showed that there were same spectrum curve trends of Carex vegetation (soil moisture content of 51%, 32%, 14% and three regional comparative analysis)reflectance between SOC710VP and ASD FieldSpec 3, including the two reflectance peak of 550nm and 730 nm, two reflectance valley of 690 nm and 970nm, and continuous near infrared reflectance platform. However, The two also have a very clear distinction: (1) The reflection spectra of SOC710VP leaves of Carex Carex leaf spectra in the three soil moisture environment values are greater than ASD FieldSpec 3 collected value; (2) The SOC710VP reflectivity curve does not have the smooth curve of the original spectrum measured by the ASD FieldSpec 3, the amplitude of fluctuation is bigger, and it is more obvious in the near infrared band. It is concluded that SOC710VP spectral data are reliable, with the image features, spectral curve features reliable. It has great potential in the research of hyperspectral remote sensing technology in the development of wetland near earth, remote sensing monitoring of wetland resources.

Predicting landslide vegetation in patches on landscape gradients in Puerto Rico

USGS Publications Warehouse

Myster, R.W.; Thomlinson, J.R.; Larsen, M.C.

1997-01-01

We explored the predictive value of common landscape characteristics for landslide vegetative stages in the Luquillo Experimental Forest of Puerto Rico using four different analyses. Maximum likelihood logistic regression showed that aspect, age, and substrate type could be used to predict vegetative structural stage. In addition it showed that the structural complexity of the vegetation was greater in landslides (1) facing the southeast (away from the dominant wind direction of recent hurricanes), (2) that were older, and (3) that had volcaniclastic rather than dioritic substrate. Multiple regression indicated that both elevation and age could be used to predict the current vegetation, and that vegetation complexity was greater both at lower elevation and in older landslides. Pearson product-moment correlation coefficients showed that (1) the presence of volcaniclastic substrate in landslides was negatively correlated with aspect, age, and elevation, (2) that road association and age were positively correlated, and (3) that slope was negatively correlated with area. Finally, principal components analysis showed that landslides were differentiated on axes defined primarily by age, aspect class, and elevation in the positive direction, and by volcaniclastic substrate in the negative direction. Because several statistical techniques indicated that age, aspect, elevation, and substrate were important in determining vegetation complexity on landslides, we conclude that landslide succession is influenced by variation in these landscape traits. In particular, we would expect to find more successional development on landslides which are older, face away from hurricane winds, are at lower elevation, and are on volcaniclastic substrate. Finally, our results lead into a hierarchical conceptual model of succession on landscapes where the biota respond first to either gradients or disturbance depending on their relative severity, and then to more local biotic mechanisms such as dispersal, predation and competition.

Quantification of inorganic arsenic exposure and cancer risk via consumption of vegetables in southern selected districts of Pakistan.

PubMed

Rehman, Zahir Ur; Khan, Sardar; Qin, Kun; Brusseau, Mark L; Shah, Mohammad Tahir; Din, Islamud

2016-04-15

Human exposures to arsenic (As) through different pathways (dietary and non-dietary) are considered to be one of the primary worldwide environmental health risks to humans. This study was conducted to investigate the presence of As in soil and vegetable samples collected from agricultural lands located in selected southern districts of Khyber Pakhtunkhwa (KPK) Province, Pakistan. We examined the concentrations of total arsenic (TAs), organic species of As such as monomethylarsonic acid (MMA) and dimethylarsonic acid (DMA), and inorganic species including arsenite (AsIII) and arsenate (AsV) in both soil and vegetables. The data were used to determine several parameters to evaluate human health risk, including bioconcentration factor (BCF) from soil to plant, average daily intake (ADI), health risk index (HRI), incremental lifetime cancer risk (ILTCR), and hazard quotient (HQ). The total As concentration in soil samples of the five districts ranged from 3.0-3.9mgkg(-1), exhibiting minimal variations from site to site. The mean As concentration in edible portions of vegetable samples ranged from 0.03-1.38mgkg(-1). It was observed that As concentrations in 75% of the vegetable samples exceeded the safe maximum allowable limit (0.1mgkg(-1)) set by WHO/FAO. The highest value of ADI for As was measured for Momordica charantia, while the lowest was for Allium chinense. The results of this study revealed minimal health risk (HI<1) associated with consumption of vegetables for the local inhabitants. The ILTCR values for inorganic As indicated a minimal potential cancer risk through ingestion of vegetables. In addition, the HQ values for total As were <1, indicating minimal non-cancer risk. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantification of inorganic arsenic exposure and cancer risk via consumption of vegetables in southern selected districts of Pakistan

PubMed Central

Rehman, Zahir Ur; Khan, Sardar; Qin, Kun; Brusseau, Mark L; Shah, Mohammad Tahir; Din, Islamud

2016-01-01

Human exposures to arsenic (As) through different pathways (dietary and non-dietary) are considered to be one of the primary worldwide environmental health risks to humans. This study was conducted to investigate the presence of As in soil and vegetable samples collected from agricultural lands located in selected southern districts of Khyber Pakhtunkhwa (KPK) Province, Pakistan. We examined the concentrations of total arsenic (TAs), organic species of As such as monomethylarsonic acid (MMA) and dimethylarsonic acid (DMA), and inorganic species including arsenite (AsIII) and arsenate (AsV) in both soil and vegetable. The data were used to determine several parameters to evaluate human health risk, including bioconcentration factor (BCF) from soil to plant, average daily intake (ADI), health risk index (HRI), incremental lifetime cancer risk (ILTCR), and hazard quotient (HQ). The total As concentration in soil samples of the five districts ranged from 3.0-3.9 mg kg−1, exhibiting minimal variations from site to site. The mean As concentration in edible portions of vegetable samples ranged from 0.03-1.38 mg kg−1. It was observed that As concentrations in 75% of the vegetable samples exceeded the safe maximum allowable limit (0.1 mg kg−1) set by WHO/FAO. The highest value of ADI for As was measured for M. charantia, while the lowest was for A. chinense. The results of this study revealed minimal health risk (HI <1) associated with consumption of vegetables for the local inhabitants. The ILTCR values for inorganic As indicated a minimal potential cancer risk through ingestion of vegetables. In addition, the HQ values for total As were <1, indicating minimal non-cancer risk. PMID:26820935

Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors.

NASA Astrophysics Data System (ADS)

Alonso, C.; Benito, R. M.; Tarquis, A. M.

2012-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI. The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Scaling analysis and modeling techniques are increasingly understood to be the result of nonlinear dynamic mechanisms repeating scale after scale from large to small scales leading to non-classical resolution dependencies. In the remote sensing framework the main characteristic of sensors images is the high local variability in their values. This variability is a consequence of the increase in spatial and radiometric resolution that implies an increase in complexity that it is necessary to characterize. Fractal and multifractal techniques has been proven to be useful to extract such complexities from remote sensing images and will applied in this study to see the scaling behavior for each sensor in generalized fractal dimensions. The studied area is located in the provinces of Caceres and Salamanca (east of Iberia Peninsula) with an extension of 32 x 32 km2. The altitude in the area varies from 1,560 to 320 m, comprising natural vegetation in the mountain area (forest and bushes) and agricultural crops in the valleys. Scaling analysis were applied to Landsat-5 and MODIS TERRA to the normalized derived vegetation index (NDVI) on the same region with one day of difference, 13 and 12 of July 2003 respectively. From these images the area of interest was selected obtaining 1024 x 1024 pixels for Landsat image and 128 x 128 pixels for MODIS image. This implies that the resolution for MODIS is 250x250 m. and for Landsat is 30x30 m. From the reflectance data obtained from NIR and RED bands, NDVI was calculated for each image focusing this study on 0.2 to 0.5 ranges of values. Once that both NDVI fields were obtained several fractal dimensions were estimated in each one segmenting the values in 0.20-0.25, 0.25-0.30 and so on to rich 0.45-0.50. In all the scaling analysis the scale size length was expressed in meters, and not in pixels, to make the comparison between both sensors possible. Results are discussed. Acknowledgements This work has been supported by the Spanish MEC under Projects No. AGL2010-21501/AGR, MTM2009-14621 and i-MATH No. CSD2006-00032

Hurricane Katrina

Atmospheric Science Data Center

2014-05-15

... camera. Such a display causes water bodies and inundated soil to appear in blue and purple hues, and highly vegetated areas to appear ... MISR's oblique cameras, indicating the presence of inundated soil throughout the floodplain. Note that clouds appear in a different spot for ...

Indicators: Lakeshore Habitat/Riparian Vegetative Cover

EPA Pesticide Factsheets

Riparian and lakeshore vegetative cover consist of the vegetation corridor alongside streams, rivers, and lakes. Vegetative cover refers to overhanging or submerged tree limbs, shrubs, and other plants growing along the shore of the waterbody.

Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran).

PubMed

Motlagh, Mohadeseh Ghanbari; Kafaky, Sasan Babaie; Mataji, Asadollah; Akhavan, Reza

2018-05-21

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.

Anopheles species associations in Southeast Asia: indicator species and environmental influences.

PubMed

Obsomer, Valérie; Dufrene, Marc; Defourny, Pierre; Coosemans, Marc

2013-05-04

Southeast Asia presents a high diversity of Anopheles. Environmental requirements differ for each species and should be clarified because of their influence on malaria transmission potential. Monitoring projects collect vast quantities of entomological data over the whole region and could bring valuable information to malaria control staff but collections are not always standardized and are thus difficult to analyze. In this context studying species associations and their relation to the environment offer some opportunities as they are less subject to sampling error than individual species. Using asymmetrical similarity coefficients, indirect clustering and the search of indicator species, this paper identified species associations. Environmental influences were then analysed through canonical and discriminant analysis using climatic and topographic data, land cover in a 3 km buffer around villages and vegetation indices. Six groups of sites characterized the structure of the species assemblage. Temperature, rainfall and vegetation factors all play a role. Four out of the six groups of sites based on species similarities could be discriminated using environmental information only. Vegetation indices derived from satellite imagery proved very valuable with one variable explaining more variance of the species dataset than any other variable. The analysis could be improved by integrating seasonality in the sampling and collecting at least 4 consecutive days.

Vegetation index anomaly response to varying lengths of drought across vegetation and climatic gradients in Hawaii

NASA Astrophysics Data System (ADS)

Lucas, M.; Miura, T.; Trauernicht, C.; Frazier, A. G.

2017-12-01

A drought which results in prolonged and extended deficit in naturally available water supply and creates multiple stresses across ecosystems is classified as an ecological drought. Detecting and understanding the dynamics and response of such droughts in tropical systems, specifically across various vegetation and climatic gradients is fairly undetermined, yet increasingly important for better understandings of the ecological effects of drought. To understanding the link between what lengths and intensities of known meteorological drought triggers detectable ecological vegetation responses, a landscape scale regression analysis evaluating the response (slope) and relationship strength (R-squared) of several cumulative SPI (standard precipitation index) lengths(1, 3, 6, 12, 18, 24, 36, 48, and 60 month), to various satellite derived monthly vegetation indices anomalies (NDVI, EVI, EVI2, and LSWI) was performed across a matrix of dominant vegetation covers (grassland, shrubland, and forest) and climatic moisture zones (arid, dry, mesic, and wet). The nine different SPI lags across these climactic and vegetation gradients was suggest that stronger relationships and steeper slopes were found in dryer climates (across all vegetation covers) and finer vegetation types (across all moisture zones). Overall NDVI, EVI and EVI2 showed the best utility in these dryer climatic zones across all vegetation types. Within arid and dry areas "best" fits showed increasing lengths of cumulative SPI were with increasing vegetation coarseness respectively. Overall these findings suggest that rainfall driven drought may have a stronger impact on the ecological condition of vegetation in water limited systems with finer vegetation types ecologically responding more rapidly to meteorological drought events than coarser woody vegetation systems. These results suggest that previously and newly documented trends of decreasing rainfall and increasing drought in Hawaiian drylands may have drastic and lasting impacts on these unique ecosystems.

Pest damage assessment in fruits and vegetables using thermal imaging

NASA Astrophysics Data System (ADS)

Vadakkapattu Canthadai, Badrinath; Muthuraju, M. Esakki; Pachava, Vengalrao; Sengupta, Dipankar

2015-05-01

In some fruits and vegetables, it is difficult to visually identify the ones which are pest infested. This particular aspect is important for quarantine and commercial operations. In this article, we propose to present the results of a novel technique using thermal imaging camera to detect the nature and extent of pest damage in fruits and vegetables, besides indicating the level of maturity and often the presence of the pest. Our key idea relies on the fact that there is a difference in the heat capacity of normal and damaged ones and also observed the change in surface temperature over time that is slower in damaged ones. This paper presents the concept of non-destructive evaluation using thermal imaging technique for identifying pest damage levels of fruits and vegetables based on investigations carried out on random samples collected from a local market.

Vegetation Health and Productivity Indicators for Sustained National Climate Assessments

NASA Astrophysics Data System (ADS)

Jones, M. O.; Running, S. W.

2014-12-01

The National Climate Assessment process is developing a system of physical, ecological, and societal indicators that communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness for the purpose of informing both decision makers and the public. Implementing a 14 year record of Gross and Net Primary Productivity (GPP/NPP) derived from the NASA EOS MODIS satellite sensor we demonstrate how these products can serve as Ecosystem Productivity and Vegetation Health National Climate Indicators for implementation in sustained National Climate Assessments. The NPP product combines MODIS vegetation data with daily global meteorology to calculate annual growth of all plant material at 1 sq. km resolution. NPP anomalies identify regions with above or below average plant growth that may result from climate fluctuations and can inform carbon source/sink dynamics, agricultural and forestry yield measures, and response to wildfire or drought conditions. The GPP product provides a high temporal resolution (8-day) metric of vegetation growth which can be used to monitor short-term vegetation response to extreme events and implemented to derive vegetation phenology metrics; growing season start, end, and length, which can elucidate land cover and regionally specific vegetation responses to a changing climate. The high spatial resolution GPP and NPP indicators can also inform and clarify responses seen from other proposed Pilot Indicators such as forest growth/productivity, land cover, crop production, and phenology. The GPP and NPP data are in continuous production and will be sustained into the future with the next generation satellite missions. The long-term Ecosystem Productivity and Vegetation Health Indicators are ideal for use in sustained National Climate Assessments, providing regionally specific responses to a changing climate and complete coverage at the national scale.

Effect of Climate Change on Vegetation Phenology of Different Land Cover Types on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cheng, M.; Jin, J.

2017-12-01

Vegetation phenology is one of the most sensitive bio-indicators of climate change, and it has received increasing interests in the context of global warming. As one of the most sensitive areas to global change, the Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of its unique vegetation composition, climate features and low-level human disturbance. Although some studies have aroused wide controversies about the actual plant phenology patterns in the Tibetan Plateau, yet the reasons remain unclear. In particular, the phenology characteristics of sparse herbaceous or sparse shrub and evergreen forest that are mostly located in the northwest and southeast of the Tibetan Plateau remain less studied. In this study, the spatio-temporal patterns of the start (SOS), end (EOS) and length (LOS) of the vegetation growing season for six vegetation types in the Tibetan Plateau, including evergreen broadleaf forests, evergreen coniferous forests, evergreen shrub, meadow, steppe and sparse herbaceous or sparse shrub, were quantified from 1982 to 2014 using NOAA/AVHRR NDVI data set at a spatial resolution of 0.05°×0.05° and 7-day intervals using NDVI relative change rate threshold and sixth order polynomial fit models. Assisted with the monthly precipitation and temperature data, the relative effects of changing climates on the variability of phenology were also examined. Diverse phenological changes were observed for different land cover types, with an advancing start of growing season (SOS), delaying end of growing season (EOS) and increasing length of growing season (LOS) in the eastern Tibetan Plateau where meadow was the dominant vegetation type, but with the opposite changes in the steppe and sparse herbaceous or sparse shrub regions which are mostly located in the northwestern and western edges of the Tibetan Plateau. Correlation analysis indicated that sufficient preseason precipitation may delay the SOS of evergreen forests in the southeastern Plateau and advance the SOS of steppe and sparse herbaceous or sparse shrub in relatively arid areas, while the advance of SOS in meadow areas could be related to higher preseason temperature.

[Comparative characteristics of the isotopic D/H composition and antioxidant activity of freshly squeezed juices from fruits and vegetables grown in different geographical regions].

PubMed

Bykov, M I; Dzhimak, S S; Basov, A A; Arcybasheva, O M; Shashkov, D; Baryshev, M G

2015-01-01

Data presented in this paper reflect changes in antioxidant activity, the content of prooxidant factors and deuterium concentration in freshly squeezed juices from fruits and vegetables grown in different climatic regions (10 samples of juices from wholesale and retail trade network of 8 kinds of vegetables and fruits, 28 manufacturers from 14 countries). Determination of the concentration of deuterium was performed using a nuclear magnetic resonance spectrometer. Total antioxidant activity of fresh juices was determined amperometrically after dilution in 2.2 mM H3PO4 in a ratio of 1:100. Prooxidant performance was evaluated by a maximum and area of flash of chemiluminescence induced by the introduction of 0.3% hydrogen peroxide. It was found that the antioxidant activity of fresh juice from fruits and vegetables grown within the same climatic region can differ by several times. In this case, most of the fruits and vegetables of russian producers were not inferior, than antioxidant activity of the fresh juices from the same plant products grown abroad. It should be noted that the indicators of the antioxidant activity of fresh juice from Russian pears exceeded this indicator of all fresh juices from pears, imported from Argentina, South Africa and the United States of America by 21.1, 30.4 and 32.7%, respectively. In assessing the prooxidant properties of fresh juices should be noted the almost complete absence of factors with prooxidant nature only in 36% of the studied fresh juices, whose maximum performance and area of flash of chemiluminescence were less than 0.1%, including a pear and apple juices from the russian production. It should be noted that the area of chemiluminescence of the juice from potatoes, grown in Russia, was at 103.1 and 115.2% lower than in juice obtained respectively from potatoes produced in Israel and Egypt (p<0.05), indicating a higher safety of consumption of potatoes produced in Russia. When studying--the isotopic D/H composition of fresh juices it was found that the highest deuterium content was in the juice from the pears, imported from Argentina (deltaD = -72% per hundred), while the lowest concentration of deuterium was observed in the juice from the Egyptian potatoes (delta = -358% per hundred). In general, significantly lower deuterium content was determined in fresh juices made from potatoes and cabbage grown in different countries, in comparison with other fresh juices from fruits and vegetables. The smallest range of differences in the isotopic D/H was composed in freshjuices from tomato, pomegranate and oranges of Turkish manufacturers (deuterium concentration ranged in them from -221 to -214% per hundred), that can be used to confirm the geographical origin of fruits and vegetables grown in Turkey. The data reflecting the antioxidant activity, the content of prooxidant factors and deuterium concentration in the juices, allow us to recommend the latter as additional criteria when assessing the quality of food products.

Developing Remote Sensing Methodology to Characterize Savanna Vegetation Structure and Composition for Rangeland Monitoring and Conservation Applications

NASA Astrophysics Data System (ADS)

Tsalyuk, M.; Kelly, M.; Getz, W.

2012-12-01

Rangeland ecosystems cover more than fifty percent of earth's land surface, host considerable biodiversity and provide vital ecosystem services. However, rangelands around the world face degradation due to climate change, land use change and overgrazing. Human-driven changes to fire and grazing regimes enhance degradation processes. The purpose of this research is to develop a remote sensing methodology to characterize the structure and composition of savanna vegetation, in order to improve the ability of conservation managers to monitor and address such degradation processes. Our study site, Etosha National Park, is a 22,270 km^2 semi-arid savanna located in north-central Namibia. Fencing and provision of artificial water sources for wildlife have changed the natural grazing patterns, which has caused bush encroachment and vegetation degradation across the park. We used MODIS and Landsat ETM+ 7 satellite imagery to map the vegetation type, dominant species, density, cover and biomass of herbaceous and woody vegetation in Etosha. We used imagery for 2007-2012 together with extensive field sampling, both in the wet and the dry seasons. At each sampling point, we identified the dominant species and measured the density, canopy size, height and diameter of the trees and shrubs. At only 31% of the sampling points, the identified vegetation type matched the class assigned at the 1996 classification. This may indicate significant habitat modifications in Etosha. We used two parallel analytical approaches to correlate between radiometric and field data. First, we show that traditional supervised classification identifies well five classes: bare soil, grassland, steppe, shrub savanna and tree savanna. We then refined this classification to enable us to identify the species composition in an area utilizing the phenological differences in timing and duration of greenness of the dominant tree and shrub species in Etosha. Specifically, using multi-date images we were able to identify additional six sub-classes based on the dominant species in each class: Colophospermum mopane woodland, Colophospermum mopane shrubland, Cataphractes alexandri woodland, Acacia nebrownii shrubland, mixed Combretum species woodland and Terminalia prunioides woodland. Second, we used quantitative methods to relate satellite-based vegetation indices to the biometric properties measured on the ground. We found a correlation among measured height, diameter and canopy cover of woody vegetation and used this to improve the correlation between cover and Normalized Difference Vegetation Index (NDVI). We showed that the Soil Adjusted Total Vegetation Index (SATVI) and Normalized Difference Water Index (NDWI) were related to both greenness and density at a site. In order to measure grass biomass in the field, we calibrated Disc Pasture Mater by clipping, weighing and drying grass in 1m^2 plots, in the dry and wet seasons, with resulting R^2 of 0.87 and 0.83, respectively. MODIS-derived leaf area index (LAI) data was best correlated with dry grass biomass. We used these correlations to produce detailed maps of each vegetation parameter for the whole park. These maps will provide a baseline to employ historical imagery to better understand the effects of the park's management and changing grazing pressure on vegetation structure.

Vegetation-Associated Impacts on Arctic Tundra Bacterial and Microeukaryotic Communities

PubMed Central

Shi, Yu; Xiang, Xingjia; Shen, Congcong; Neufeld, Josh D.; Walker, Virginia K.

2014-01-01

The Arctic is experiencing rapid vegetation changes, such as shrub and tree line expansion, due to climate warming, as well as increased wetland variability due to hydrological changes associated with permafrost thawing. These changes are of global concern because changes in vegetation may increase tundra soil biogeochemical processes that would significantly enhance atmospheric CO2 concentrations. Predicting the latter will at least partly depend on knowing the structure, functional activities, and distributions of soil microbes among the vegetation types across Arctic landscapes. Here we investigated the bacterial and microeukaryotic community structures in soils from the four principal low Arctic tundra vegetation types: wet sedge, birch hummock, tall birch, and dry heath. Sequencing of rRNA gene fragments indicated that the wet sedge and tall birch communities differed significantly from each other and from those associated with the other two dominant vegetation types. Distinct microbial communities were associated with soil pH, ammonium concentration, carbon/nitrogen (C/N) ratio, and moisture content. In soils with similar moisture contents and pHs (excluding wet sedge), bacterial, fungal, and total eukaryotic communities were correlated with the ammonium concentration, dissolved organic nitrogen (DON) content, and C/N ratio. Operational taxonomic unit (OTU) richness, Faith's phylogenetic diversity, and the Shannon species-level index (H′) were generally lower in the tall birch soil than in soil from the other vegetation types, with pH being strongly correlated with bacterial richness and Faith's phylogenetic diversity. Together, these results suggest that Arctic soil feedback responses to climate change will be vegetation specific not just because of distinctive substrates and environmental characteristics but also, potentially, because of inherent differences in microbial community structure. PMID:25362064

Vegetation-associated impacts on arctic tundra bacterial and microeukaryotic communities.

PubMed

Shi, Yu; Xiang, Xingjia; Shen, Congcong; Chu, Haiyan; Neufeld, Josh D; Walker, Virginia K; Grogan, Paul

2015-01-01

The Arctic is experiencing rapid vegetation changes, such as shrub and tree line expansion, due to climate warming, as well as increased wetland variability due to hydrological changes associated with permafrost thawing. These changes are of global concern because changes in vegetation may increase tundra soil biogeochemical processes that would significantly enhance atmospheric CO2 concentrations. Predicting the latter will at least partly depend on knowing the structure, functional activities, and distributions of soil microbes among the vegetation types across Arctic landscapes. Here we investigated the bacterial and microeukaryotic community structures in soils from the four principal low Arctic tundra vegetation types: wet sedge, birch hummock, tall birch, and dry heath. Sequencing of rRNA gene fragments indicated that the wet sedge and tall birch communities differed significantly from each other and from those associated with the other two dominant vegetation types. Distinct microbial communities were associated with soil pH, ammonium concentration, carbon/nitrogen (C/N) ratio, and moisture content. In soils with similar moisture contents and pHs (excluding wet sedge), bacterial, fungal, and total eukaryotic communities were correlated with the ammonium concentration, dissolved organic nitrogen (DON) content, and C/N ratio. Operational taxonomic unit (OTU) richness, Faith's phylogenetic diversity, and the Shannon species-level index (H') were generally lower in the tall birch soil than in soil from the other vegetation types, with pH being strongly correlated with bacterial richness and Faith's phylogenetic diversity. Together, these results suggest that Arctic soil feedback responses to climate change will be vegetation specific not just because of distinctive substrates and environmental characteristics but also, potentially, because of inherent differences in microbial community structure. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Early vegetational changes on a forested wetland constructed for mitigation

USGS Publications Warehouse

Perry, M.C.; Osenton, P.C.; Sibrel, C.B.

1997-01-01

Changes in vegetation were studied on 15 acres of a 35 acre forested wetland created as a mitigation site in Anne Arundel County, Maryland during 1994-96. Meter-square sampling on four different hydrologic elevations determined that grasses initially dominated the area, but decreased from 59 percent in 1994 to 51 percent in 1995 and 30 percent in 1996. Herbaceous non-grass plants (forbs) increased from 19 percent to 56 percent in the three-year period. Area with no plant cover decreased from 21 percent in 1994 to 11 percent in 1995, and 10 percent in 1996. Woody plants comprised 2 percent of the cover in 1994, increased to 4 percent in 1995, and remained at 4 percent in 1996. The increase of woody plants was mainly from natural regeneration (pioneer) plants. Monitoring of the transplanted trees and shrubs indicated 35 percent mortality and little growth of surviving plants. The pioneer woody plant forming most of the cover was black willow (Salix nigra). Differences in the vegetation were observed among the four elevations, although no differences were observed for the major vegetation classes between plots that were planted and those that were not planted with woody plants. Dominant grass species was redtop (Agrostis stolonifera), which comprised 51 percent of the cover in 1994 and 42 percent cover in 1995 and 23 percent in 1996. Other species that were common were bush clover (Lespedeza cuneata), Japanese clover (Lespedeza striata) and flat pea (Lathyrus sylvestris). All four of these dominant species were part of the original seed mixtures that were seeded on the site. A total of 134 species of plants was recorded on the site indicating a fairly diverse community for a newly established habitat.

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

USGS Publications Warehouse

Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

2016-01-01

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

The effects of a 25% discount on fruits and vegetables: results of a randomized trial in a three-dimensional web-based supermarket

PubMed Central

2012-01-01

Background Lowering the price of fruit and vegetables is a promising strategy in stimulating the purchase of those foods. However, the true effects of this strategy are not well studied and it is unclear how the money saved is spent. The aim of this study is to examine the effects of a 25% discount on fruits and vegetables on food purchases in a supermarket environment. Methods A randomized controlled trial with two research conditions was conducted: a control condition with regular prices (n = 52) and an experimental condition with a 25% discount on fruits and vegetables (n = 63). The experiment was carried out using a three-dimensional web-based supermarket, which is a software application in the image of a real supermarket. Data were collected in 2010 in the Netherlands. Participants received a fixed budget and were asked to buy weekly household groceries at the web-based supermarket. Differences in fruit and vegetable purchases, differences in expenditures in other food categories and differences in total calories were analyzed using independent samples t-tests and multiple linear regression models accounting for potential effect modifiers and confounders. Results The purchased amount of fruit plus vegetables was significantly higher in the experimental condition compared to the control condition (Δ984 g per household per week, p = .03) after appropriate adjustments. This corresponds to a 25% difference compared to the control group. Both groups had similar expenditures in unhealthier food categories, including desserts, soda, crisps, candy and chocolate. Furthermore, both groups purchased an equal number of food items and an equal amount of calories, indicating that participants in the discount condition did not spend the money they saved from the discounts on other foods than fruits and vegetables. Conclusion A 25% discount on fruits and vegetables was effective in stimulating purchases of those products and did neither lead to higher expenditures in unhealthier food categories nor to higher total calories purchased. Future studies in real supermarkets need to confirm these findings. PMID:22316357

The effects of a 25% discount on fruits and vegetables: results of a randomized trial in a three-dimensional web-based supermarket.

PubMed

Waterlander, Wilma E; Steenhuis, Ingrid H M; de Boer, Michiel R; Schuit, Albertine J; Seidell, Jacob C

2012-02-08

Lowering the price of fruit and vegetables is a promising strategy in stimulating the purchase of those foods. However, the true effects of this strategy are not well studied and it is unclear how the money saved is spent. The aim of this study is to examine the effects of a 25% discount on fruits and vegetables on food purchases in a supermarket environment. A randomized controlled trial with two research conditions was conducted: a control condition with regular prices (n = 52) and an experimental condition with a 25% discount on fruits and vegetables (n = 63). The experiment was carried out using a three-dimensional web-based supermarket, which is a software application in the image of a real supermarket. Data were collected in 2010 in the Netherlands. Participants received a fixed budget and were asked to buy weekly household groceries at the web-based supermarket. Differences in fruit and vegetable purchases, differences in expenditures in other food categories and differences in total calories were analyzed using independent samples t-tests and multiple linear regression models accounting for potential effect modifiers and confounders. The purchased amount of fruit plus vegetables was significantly higher in the experimental condition compared to the control condition (Δ984 g per household per week, p = .03) after appropriate adjustments. This corresponds to a 25% difference compared to the control group. Both groups had similar expenditures in unhealthier food categories, including desserts, soda, crisps, candy and chocolate. Furthermore, both groups purchased an equal number of food items and an equal amount of calories, indicating that participants in the discount condition did not spend the money they saved from the discounts on other foods than fruits and vegetables. A 25% discount on fruits and vegetables was effective in stimulating purchases of those products and did neither lead to higher expenditures in unhealthier food categories nor to higher total calories purchased. Future studies in real supermarkets need to confirm these findings.

Does the consumption of fruits and vegetables differ between Eastern and Western European populations? Systematic review of cross-national studies.

PubMed

Stefler, Denes; Bobak, Martin

2015-01-01

Difference in fruit and vegetable consumption has been suggested as a possible reason for the large gap in cardiovascular disease (CVD) mortality rates between Eastern and Western European populations. However, individual-level dietary data which allow direct comparison across the two regions are rare. In this systematic review we aimed to answer the question whether cross-national studies with comparable individual-level dietary data reveal any systematic differences in fruit and vegetable consumption between populations in Central and Eastern Europe (CEE) and the Former Soviet Union (FSU) compared to Western Europe (WE). Studies were identified by electronic search of MEDLINE, EMBASE and Web of Science databases from inception to September 2014, and hand search. Studies which reported data on fruit, vegetable consumption or carotene and vitamin C intake or tissue concentrations of adult participants from both CEE/FSU and WE countries were considered for inclusion. Quality of the included studies was assessed by a modified STROBE statement. Power calculation was performed to determine the statistical significance of the comparison results. Twenty-two studies fulfilled the inclusion criteria. Fruit consumption was found to be consistently lower in CEE/FSU participants compared to Western Europeans. Results on vegetable intake were less unambiguous. Antioxidant studies indicated lower concentration of beta-carotene in CEE/FSU subjects, but the results for vitamin C were not consistent. This systematic review suggests that populations in CEE and FSU consume less fruit than Western Europeans. The difference in the consumption of fruit may contribute to the CVD gap between the two regions.

Vegetation dynamics in Bishrampur collieries of northern Chhattisgarh, India: eco-restoration and management perspectives.

PubMed

Kumar, A; Jhariya, M K; Yadav, D K; Banerjee, A

2017-08-01

Phytosociological study in and around reclaimed coal mine site is an essential requirement for judging restoration impact on a disturbed site. Various studies have been aimed towards assessing the impact of different restoration practices on coal mine wastelands. Plantation scheme in a scientific way is the most suitable approach in this context. During the present investigation, an effort have been made to assess the vegetation dynamics through structure, composition, diversity, and forest floor biomass analysis in and around Bishrampur collieries, Sarguja division, northern Chhattisgarh, India. We have tried to develop strategies for eco-restoration and habitat management of the concerned study sites. Four sites were randomly selected in different directions of the study area. We classified the vegetation community of the study sites into various strata on the basis of height. Two hundred forty quadrats were laid down in various directions of the study area to quantify vegetation under different strata. During our investigation, we found eight different tree species representing four families in the different study sites. The density of the various tree species ranged between 40 and 160 individuals ha -1 . The density of sapling, seedling, shrub, and herb ranged between 740 and 1620; 2000 and 6000; 1200 and 2000; and 484,000 and 612,000 individuals ha -1 , respectively, in different directions. The diversity indices of the tree reflected highest Shannon index value of 1.91. Simpsons index ranged between 0.28 and 0.50, species richness ranged between 0.27 and 0.61, equitability up to 1.44, and Beta diversity ranged between 2.00 and 4.00. Total forest floor biomass ranged between 4.20 and 5.65 t/ha among the study sites. Highest forest floor biomass occurred in the south direction and lowest at east direction. Total forest floor biomass declined by 6.19% in west, 13.10% in north, and 25.66% in east direction, respectively. The mining activities resulted significant damage to natural vegetation and its dynamics. The study indicated that Acacia mangium, Cassia siamea, and Dalbergia sissoo can be recommended for effective eco-restoration of the concerned sites due to cosmopolitan distribution, high regeneration potential, as well as existence in the form of various girth classes with stable population structure.

Integrated study of biomass index in La Herreria (Sierra de Guadarrama)

NASA Astrophysics Data System (ADS)

Hernandez Díaz-Ambrona, Carlos G.

2016-04-01

Drought severity has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. There have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). The'biomass index', based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in several countries for pasture and forage crops for some years (Rao, 2010; Escribano-Rodriguez et al., 2014). NDVI generally provides a broad overview of the vegetation condition and spatial vegetation distribution in a region. Vegetative drought is closely related with weather impacts. However, in NDVI, the weather component gets subdued by the strong ecological component. Another vegetation index is Vegetation Condition Index (VCI) that separates the short-term weather-related NDVI fluctuations from the long-term ecosystem changes (Kogan, 1990). Therefore, while NDVI shows seasonal vegetation dynamics, VCI rescales vegetation dynamics between 0 and 100 to reflect relative changes in the vegetation condition from extremely bad to optimal (Kogan et al., 2003). In this work a pasture area at La Herreria (Sierra de Guadarrama, Spain) has been delimited. Then, NDVI historical data are reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. From the closest meteorological station (Santolaria-Canales, 2015) records of weekly precipitation, temperature and evapotranspiration from 2001 till 2012 were obtained. Standard Precipitation Index (SPI), Crop Moisture Index (CMI) (Palmer, 1968) and Evapotranspiration-Precipitation Ratio (EPR) are calculated in an attempt to relate them to several vegetation indexes: NDVI, VCI and NDVI Change Ratio to Median (RMNDVI). The results are discussed in the context of pasture index insurance. References Escribano Rodriguez, J.Agustín, Carlos Gregorio Hernández Díaz-Ambrona and Ana María Tarquis Alfonso. Selection of vegetation indices to estimate pasture production in Dehesas. PASTOS, 44(2), 6-18, 2014. Kogan, F. N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int. J. Remote Sensing, 11(8), pp. 1405-1419. Kogan, F. N., Gitelson, A., Edige, Z., Spivak, l., and Lebed, L., 2003. AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation State and Productivity: Calibration and Validation. Photogrammetric Engineering & Remote Sensing, 69(8), pp. 899-906. Niemeyer, S., 2008. New drought indices. First Int. Conf. on Drought Management: Scientific and Technological Innovations, Zaragoza, Spain, Joint Research Centre of the European Commission. Palmer, W.C., 1968. Keeping track of crop moisture conditions, nationwide: The new Crop Moisture Index. Weatherwise 21, 156-161. Rao, K.N. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Santolaria-Canales, Edmundo and the GuMNet Consortium Team (2015). GuMNet - Guadarrama Monitoring Network. Installation and set up of a high altitude monitoring network, north of Madrid. Spain. Geophysical Research Abstracts, 17, EGU2015-13989-2 Web: http://www.ucm.es/gumnet/

Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield.

PubMed

Rime, Thomas; Hartmann, Martin; Brunner, Ivano; Widmer, Franco; Zeyer, Josef; Frey, Beat

2015-03-01

Spatial patterns of microbial communities have been extensively surveyed in well-developed soils, but few studies investigated the vertical distribution of micro-organisms in newly developed soils after glacier retreat. We used 454-pyrosequencing to assess whether bacterial and fungal community structures differed between stages of soil development (SSD) characterized by an increasing vegetation cover from barren (vegetation cover: 0%/age: 10 years), sparsely vegetated (13%/60 years), transient (60%/80 years) to vegetated (95%/110 years) and depths (surface, 5 and 20 cm) along the Damma glacier forefield (Switzerland). The SSD significantly influenced the bacterial and fungal communities. Based on indicator species analyses, metabolically versatile bacteria (e.g. Geobacter) and psychrophilic yeasts (e.g. Mrakia) characterized the barren soils. Vegetated soils with higher C, N and root biomass consisted of bacteria able to degrade complex organic compounds (e.g. Candidatus Solibacter), lignocellulolytic Ascomycota (e.g. Geoglossum) and ectomycorrhizal Basidiomycota (e.g. Laccaria). Soil depth only influenced bacterial and fungal communities in barren and sparsely vegetated soils. These changes were partly due to more silt and higher soil moisture in the surface. In both soil ages, the surface was characterized by OTUs affiliated to Phormidium and Sphingobacteriales. In lower depths, however, bacterial and fungal communities differed between SSD. Lower depths of sparsely vegetated soils consisted of OTUs affiliated to Acidobacteria and Geoglossum, whereas depths of barren soils were characterized by OTUs related to Gemmatimonadetes. Overall, plant establishment drives the soil microbiota along the successional gradient but does not influence the vertical distribution of microbiota in recently deglaciated soils. © 2014 John Wiley & Sons Ltd.

Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

NASA Astrophysics Data System (ADS)

Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

2002-12-01

We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

Spectral reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting

USGS Publications Warehouse

Zhang, J.-H.; Zhou, Z.-M.; Wang, P.-J.; Yao, F.-M.; Yang, L.

2011-01-01

The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area. The result showed that for a pure snow spectrum, the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1030 nm wavelength. Compared with fresh snow, the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300~1300, 1700~1800 and 2200~2300 nm, the lowest was from the compacted snow and frozen ice. For the vegetation and snow mixed spectral characteristics, it was indicated that the spectral reflectance increased for the snow-covered land types(including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350~1300 nm. However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic. In the end, based on the spectrum analysis of snow, vegetation, and mixed snow/vegetation pixels, the mixed spectral fitting equations were established, and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones(correlation coefficient R2=0.9509).

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands.

PubMed

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J; Roberts, Dar A

2017-04-15

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24m resolution WorldView-3 and a 0.1m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure. Copyright © 2017 Elsevier B.V. All rights reserved.

Understanding the yield gap in wheat production

USDA-ARS?s Scientific Manuscript database

Remote sensing has been used to assess various components of agricultural systems for several decades. Utilization of different wavebands in various combinations to form vegetative indices have been used to estimate ground cover, biomass, leaf chlorophyll content, light interception, leaf area index...

Dynamics of gene expression during development and expansion of vegetative stem internodes of bioenergy sorghum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kebrom, Tesfamichael H.; McKinley, Brian; Mullet, John E.

Bioenergy sorghum accumulates 75% of shoot biomass in stem internodes. Grass stem internodes are formed during vegetative growth and elongate in response to developmental and environmental signals. To identify genes and molecular mechanisms that modulate the extent of internode growth, we conducted microscopic and transcriptomic analyses of four successive sub-apical vegetative internodes representing different stages of internode development of the bioenergy sorghum genotype R.07020. Stem internodes of sorghum genotype R.07020 are formed during the vegetative phase and their length is enhanced by environmental signals such as shade and floral induction in short days. During vegetative growth, the first visible andmore » youngest sub-apical internode was ~0.7 cm in length, whereas the fourth fully expanded internode was ~5 cm in length. Microscopic analyses revealed that all internode tissue types including pith parenchyma and vascular bundles are present in the four successive internodes. Growth in the first two sub-apical internodes occurred primarily through an increase in cell number consistent with expression of genes involved in the cell cycle and DNA replication. Growth of the 3rd internode was associated with an increase in cell length and growth cessation in the 4th internode was associated with up-regulation of genes involved in secondary cell wall deposition. The expression of genes involved in hormone metabolism and signaling indicates that GA, BR, and CK activity decreased while ethylene, ABA, and JA increased in the 3rd/4th internodes. While the level of auxin appears to be increasing as indicated by the up-regulation of ARFs, down-regulation of TIR during development indicates that auxin signaling is also modified. The expression patterns of transcription factors are closely associated with their role during the development of the vegetative internodes. Microscopic and transcriptome analyses of four successive sub-apical internodes characterized the developmental progression of vegetative stem internodes from initiation through full elongation in the sorghum genotype R.07020. Transcriptome profiling indicates that dynamic variation in the levels and action of GA, CK, IAA, BR, ethylene, ABA, and JA modulate gene expression and growth during internode growth and development. Thus, this study provides detailed microscopic and transcriptomic data useful for identifying genes and molecular pathways regulating internode elongation in response to various developmental and environmental signals.« less

Dynamics of gene expression during development and expansion of vegetative stem internodes of bioenergy sorghum

DOE PAGES

Kebrom, Tesfamichael H.; McKinley, Brian; Mullet, John E.

2017-06-21

Bioenergy sorghum accumulates 75% of shoot biomass in stem internodes. Grass stem internodes are formed during vegetative growth and elongate in response to developmental and environmental signals. To identify genes and molecular mechanisms that modulate the extent of internode growth, we conducted microscopic and transcriptomic analyses of four successive sub-apical vegetative internodes representing different stages of internode development of the bioenergy sorghum genotype R.07020. Stem internodes of sorghum genotype R.07020 are formed during the vegetative phase and their length is enhanced by environmental signals such as shade and floral induction in short days. During vegetative growth, the first visible andmore » youngest sub-apical internode was ~0.7 cm in length, whereas the fourth fully expanded internode was ~5 cm in length. Microscopic analyses revealed that all internode tissue types including pith parenchyma and vascular bundles are present in the four successive internodes. Growth in the first two sub-apical internodes occurred primarily through an increase in cell number consistent with expression of genes involved in the cell cycle and DNA replication. Growth of the 3rd internode was associated with an increase in cell length and growth cessation in the 4th internode was associated with up-regulation of genes involved in secondary cell wall deposition. The expression of genes involved in hormone metabolism and signaling indicates that GA, BR, and CK activity decreased while ethylene, ABA, and JA increased in the 3rd/4th internodes. While the level of auxin appears to be increasing as indicated by the up-regulation of ARFs, down-regulation of TIR during development indicates that auxin signaling is also modified. The expression patterns of transcription factors are closely associated with their role during the development of the vegetative internodes. Microscopic and transcriptome analyses of four successive sub-apical internodes characterized the developmental progression of vegetative stem internodes from initiation through full elongation in the sorghum genotype R.07020. Transcriptome profiling indicates that dynamic variation in the levels and action of GA, CK, IAA, BR, ethylene, ABA, and JA modulate gene expression and growth during internode growth and development. Thus, this study provides detailed microscopic and transcriptomic data useful for identifying genes and molecular pathways regulating internode elongation in response to various developmental and environmental signals.« less

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

Dynamics of riparian plant communities, a new integrative ecohydrological modelling approach

NASA Astrophysics Data System (ADS)

García-Arias, Alicia; Francés, Félix

2015-04-01

The Riparian Vegetation Dynamic Model (RVDM) integrates the impacts of the hydrological extremes on the vegetation, the vegetation evolution and the competition between different vegetation classes. Considering a daily time step and a detailed spatial resolution, RVDM allows the analysis of the dynamic vegetation distribution in riverine areas during a simulated period. The riparian vegetation wellbeing and distribution are considered to be conditioned by the river hydrodynamics in RVDM. Using biomass loss functions, the stress caused by hydrological extreme events is translated into changes on the distribution of the vegetation. These extreme events are considered as removal and asphyxia associated to floods, and wilt related to droughts. The variables considered to determine the impacts are water shear stress, water table elevation and the soil moisture, respectively. RVDM includes the modelling of the natural evolution of the vegetation. The potential recruitment in bared areas, the plant growth and the succession/retrogression between plant categories are included in the model conceptualization. The recruitment takes place when seeds presence, germination and seedlings establishment overcome, so it depends on the plant reproductive period and the environmental conditions. Light use efficiency determines the vegetation growth in terms of biomass production while the soil moisture limits this biomass production and the successional evolution. Finally, the competition modelling considers the advantages between successional patterns under the specific soil moisture conditions of each unit area. Several meteorological, morphological, hydrological and hydraulic inputs are required. In addition, an initial vegetation condition is required for RVDM to start the simulation period. The model results on new vegetation maps that are considered as new inputs in the next model step. Following this approach the model simulates iteratively al the processes day by day. This model represents an improvement respect to previous models in the way of understanding the riparian dynamics. Currently, RVDM has been already implemented in a Mediterranean semi-arid river reach and a sensitivity analysis to analyze the influence of the different vegetation parameters has been performed. The good results obtained indicate that the model is suitable for scenarios analysis and for environmental flows establishment.

Detecting forest canopy change due to insect activity using Landsat MSS

NASA Technical Reports Server (NTRS)

Nelson, R. F.

1983-01-01

Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

[Individual characteristics of correction of the cosmonauts' vegetative status with a method of adaptive biofeedback

NASA Technical Reports Server (NTRS)

Kornilova, L. N.; Cowings, P.; Arlashchenko, N. I.; Korneev, D. Iu; Sagalovich, S. V.; Sarantseva, A. V.; Toscano, W.; Kozlovskaia, I. B.

2003-01-01

The ability of 4 cosmonauts to voluntarily control their physiological parameters during the standing test was evaluated following a series of the adaptive feedback (AF) training sessions. Vegetative status of the cosmonauts during voluntary "relaxation" and "straining" was different when compared with its indices determined before these sessions. In addition, there was a considerable individual variability in the intensity and direction of the AF effects, and the range of parameters responding to AF. It was GCR which was the easiest one for the AF control.

Vegetation of prairie potholes, North Dakota, in relation to quality of water and other environmental factors

USGS Publications Warehouse

Stewart, R.E.; Kantrud, H.A.

1972-01-01

Measurements of specific conductance provide an adequate indication of the average salinity of surface waters in natural ponds and lakes of the northern .prairie region. Yearly and seasonal variations in specific conductance were much greater in brackish and subsaline wetlands than in fresh-water areas. The principal vegetational types. Land-use practices of varying brackish to saline wetlands were sulfates and chlorides of sodium and magnesium. In less saline waters, carbonate and bicarbonate salts of calcium and potassium were of greater importance, but as salinity increased, the proportion of these compounds decreased rapidly.A major environmental factor controlling the establishment of marsh and aquatic vegetation is the permanence of surface water. Permanence is a measure of the extent to which surface water persists at a given site. Varying degrees of water permanence during the growing season led to the establishment of distinct vegetational types, which were differentiated primarily on the 'basis of community structure or life form of the dominant vegetation.Salinity of surface waters was closely correlated with differences in species composition of plant communities found in the principal vegetational types. Land-use practices of varying degrees of intensity also had a secondary influence on species composition. Since an unstable water chemistry is characteristic of most prairie ponds and lakes, it is more reliable to use the plant communities as indicators of average salinity than to use single measurements of specific conductance.Characteristic species of wetland vegetational types occupied the central deeper parts of pond and lake basins or occurred as concentric peripheral bands. The wetland vegetational types are wetland low-prairie, wet-meadow, shallow-marsh emergent, deep-marsh emergent, fen emergent, submerged and floating, natural drawdown, cropland drawdown, and cropland tillage vegetation. Combinations of species (plant associations) within these vegetational types were placed in one of six salinity categories designated as fresh, slightly brackish, moderately brackish, brackish, subsaline, and saline. Salt tolerance apparently varied greatly among the various marsh and aquatic plants since the num'ber of species represented in moderately brackish to saline communities decreased markedly with increased salinity of the surface water environment.

Late Glacial Tropical Savannas in Sundaland Inferred From Stable Carbon Isotope Records of Cave Guano

NASA Astrophysics Data System (ADS)

Wurster, C. M.; Bird, M. I.; Bull, I.; Dungait, J.; Bryant, C. L.; Ertunç, T.; Hunt, C.; Lewis, H. A.; Paz, V.

2008-12-01

During the Last Glacial Period (LGP), reduced global sea level exposed the continental shelf south of Thailand to Sumatra, Java, and Borneo to form the contiguous continent of Sundaland. However, the type and extent of vegetation that existed on much of this exposed landmass during the LGP remains speculative. Extensive bird and bat guano deposits in caves throughout this region span beyond 40,000 yr BP, and contain a wealth of untapped stratigraphic palaeoenvironmental information. Stable carbon isotope ratios of insectivorous bird and bat guano contain a reliable record of the animal's diet and, through non-specific insect predation, reflect the relative abundance of major physiological pathways in plants. Various physiological pathways of carbon fixation in plants yield differing stable carbon isotope ratios. Stable carbon isotope values of C3 plants are lower than C4 vegetation due to different enzymatic discriminations of the heavy isotope through the carbon fixing pathways. In tropical locales, grasses nearly always follow the C4 photosynthetic pathway, whereas tropical rainforest uses C3 photosynthesis, providing a proxy for vegetation and therefore climate change in the past. Here we discuss four guano stable-isotope records, based on insect cuticle and n-alkane analysis, supplemented by pollen analysis. All sites suggest a C3 dominated ecosystem for the Holocene, consistent with the wet tropical forest vegetation present at all locations. Two sites from Palawan Island, Philippines, record stable carbon isotope values of guano that document a drastic change from C3 (forest) to C4 (savanna) dominated ecosystems during the Last Glacial Maximum (LGM). A third location, at Niah Great Cave, Malaysia, indicates C3-dominant vegetation throughout the record, but does display variation in stable carbon isotope values likely linked to humidity changes. A fourth location, Batu Caves in Peninsular Malaysia, also indicates open vegetation during the LGM. Vegetation models disagree as to the nature of vegetation during the LGM in Sundaland, but our results suggest major contraction of forest area with significant implications for carbon storage during the LGM and also for understanding the development of modern biogeographic and genetic patterns in the region. Additional cave guano sites will provide further constraints on the nature of environmental change in the region over the last glacial cycle.

Vegetation optical depth measured by microwave radiometry as an indicator of tree mortality risk

NASA Astrophysics Data System (ADS)

Rao, K.; Anderegg, W.; Sala, A.; Martínez-Vilalta, J.; Konings, A. G.

2017-12-01

Increased drought-related tree mortality has been observed across several regions in recent years. Vast spatial extent and high temporal variability makes field monitoring of tree mortality cumbersome and expensive. With global coverage and high temporal revisit, satellite remote sensing offers an unprecedented tool to monitor terrestrial ecosystems and identify areas at risk of large drought-driven tree mortality events. To date, studies that use remote sensing data to monitor tree mortality have focused on external climatic thresholds such as temperature and evapotranspiration. However, this approach fails to consider internal water stress in vegetation - which can vary across trees even for similar climatic conditions due to differences in hydraulic behavior, soil type, etc - and may therefore be a poor basis for measuring mortality events. There is a consensus that xylem hydraulic failure often precedes drought-induced mortality, suggesting depleted canopy water content shortly before onset of mortality. Observations of vegetation optical depth (VOD) derived from passive microwave are proportional to canopy water content. In this study, we propose to use variations in VOD as an indicator of potential tree mortality. Since VOD accounts for intrinsic water stress undergone by vegetation, it is expected to be more accurate than external climatic stress indicators. Analysis of tree mortality events in California, USA observed by airborne detection shows a consistent relationship between mortality and the proposed VOD metric. Although this approach is limited by the kilometer-scale resolution of passive microwave radiometry, our results nevertheless demonstrate that microwave-derived estimates of vegetation water content can be used to study drought-driven tree mortality, and may be a valuable tool for mortality predictions if they can be combined with higher-resolution variables.

Investigating carbon dynamics in Siberian peat bogs using molecular-level analyses

NASA Astrophysics Data System (ADS)

Kaiser, K.; Benner, R. H.

2013-12-01

Total hydrolysable carbohydrates, and lignin and cutin acid compounds were analyzed in peat cores collected 56.8 N (SIB04), 58.4 N (SIB06), 63.8 N (G137) and 66.5 N (E113) in the Western Siberian Lowland to investigate vegetation, chemical compositions and the stage of decomposition. Sphagnum mosses dominated peatland vegetation in all four cores. High-resolution molecular analyses revealed rapid vegetation changes on timescales of 50-200 years in the southern cores Sib4 and Sib6. Syringyl and vanillyl (S/V) ratios and cutin acids indicated these vegetation changes were due to varying inputs of angiosperm and gymnosperm and root material. In the G137 and E113 cores lichens briefly replaced sphagnum mosses and vascular plants. Molecular decomposition indicators used in this study tracked the decomposition of different organic constituents of peat organic matter. The carbohydrate decomposition index was sensitive to the polysaccharide component of all peat-forming plants, whereas acid/aldehyde ratios of S and V phenols (Ac/AlS,V) followed the lignin component of vascular plants. Low carbohydrate decomposition indices in peat layers corresponded well with elevated (Ad/Al)S,V ratios. This suggested both classes of biochemicals were simultaneously decomposed, and decomposition processes were associated with extensive total mass loss in these ombrotrophic systems. Selective decomposition or transformation of lignin was observed in the permafrost-influenced northern cores G137 and E113. Both cores exhibited the highest (Ad/Al)S,V ratios, almost four-fold higher than measured in peat-forming plants. The extent of decomposition in the four peat cores did not uniformly increase with age, but showed episodic extensive decomposition events. Variable decomposition events independent of climatic conditions and vegetation shifts highlight the complexity of peatland dynamics.

FLUXNET to MODIS: Connecting the dots to capture heterogenious biosphere metabolism

NASA Astrophysics Data System (ADS)

Woods, K. D.; Schwalm, C.; Huntzinger, D. N.; Massey, R.; Poulter, B.; Kolb, T.

2015-12-01

Eddy co-variance flux towers provide our most widely distributed network of direct observations for land-atmosphere carbon exchange. Carbon flux sensitivity analysis is a method that uses in situ networks to understand how ecosystems respond to changes in climatic variables. Flux towers concurrently observe key ecosystem metabolic processes (e..g. gross primary productivity) and micrometeorological variation, but only over small footprints. Remotely sensed vegetation indices from MODIS offer continuous observations of the vegetated land surface, but are less direct, as they are based on light use efficiency algorithms, and not on the ground observations. The marriage of these two data products offers an opportunity to validate remotely sensed indices with in situ observations and translate information derived from tower sites to globally gridded products. Here we provide correlations between Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and MODIS gross primary production with FLUXNET derived estimates of gross primary production, respiration and net ecosystem exchange. We demonstrate remotely sensed vegetation products which have been transformed to gridded estimates of terrestrial biosphere metabolism on a regional-to-global scale. We demonstrate anomalies in gross primary production, respiration, and net ecosystem exchange as predicted by both MODIS-carbon flux sensitivities and meteorological driver-carbon flux sensitivities. We apply these sensitivities to recent extreme climatic events and demonstrate both our ability to capture changes in biosphere metabolism, and differences in the calculation of carbon flux anomalies based on method. The quantification of co-variation in these two methods of observation is important as it informs both how remotely sensed vegetation indices are correlated with on the ground tower observations, and with what certainty we can expand these observations and relationships.

Terrestrial Plant Biomarkers Preserved in Cariaco Basin Sediments: Records of Abrupt Tropical Vegetation Response to Rapid Climate Changes

NASA Astrophysics Data System (ADS)

Hughen, K. A.; Eglinton, T. I.; Makou, M.; Xu, L.; Sylva, S.

2004-12-01

Organic-rich sediments from the anoxic Cariaco Basin, Venezuela, preserve high concentrations of biomarkers for reconstruction of terrestrial environmental conditions. Molecular-level investigations of organic compounds provide a valuable tool for extracting terrestrial signals from these annually laminated marine sediments. Differences in hydrogen isotopic fractionation between C16-18 and C24-30 n-alkanoic acids suggest a marine source for the shorter chain lengths and a terrestrial source for the longer chains. Records of carbon and hydrogen isotopes, as well as average carbon chain length (ACL), from long-chain n-alkanoic acids parallel millennial-scale changes in vegetation and climate between the late Glacial and Preboreal periods, 15,000 to 10,000 years ago. Data from all terrestrial chain lengths were combined to produce single δ D and δ 13C indices through deglaciation, exhibiting enrichment during the late Glacial and Younger Dryas and depletion during the Bolling-Allerod and Preboreal periods. δ D reflects the hydrogen isotopic composition of environmental water used for plant growth, combined with evaporative enrichment within leaf spaces, and as such may act as a proxy for local aridity. Leaf wax δ 13C, which is a proxy for C3 versus C4 metabolic pathways, indicates that C3 plants predominated in the Cariaco watershed during warm/wet Bolling-Allerod and Holocene periods, and C4 plant biomass proliferated during cool/dry Glacial and Younger Dryas intervals. Coupled carbon and hydrogen isotopic measurements together clearly distinguish deglacial climatic periods as wetter with C3 vegetation versus drier with C4 vegetation. High resolution biomarker records reveal the rapidity of vegetation changes in northern South America during the last deglaciation. The leaf wax data reveal that local vegetation biomass, although not necessarily entire assemblages, shifted between arid grassland and wetter forest taxa on timescales of decades. Comparison of ACL versus δ 13C for Cariaco Basin and NW African leaf waxes indicate that biomarkers reflect real changes in local South American vegetation and not contamination from long-distance transport during cold windy climates. The precise temporal relationship between tropical vegetation shifts and climate changes is measured by direct comparison of terrestrial vegetation and climate proxies from the same core. Abrupt deglacial climate shifts in tropical and high-latitude North Atlantic regions were synchronous, whereas changes in tropical vegetation consistently lagged climate shifts by several decades.

Modeling Above-Ground Biomass Across Multiple Circum-Arctic Tundra Sites Using High Spatial Resolution Remote Sensing

NASA Astrophysics Data System (ADS)

Räsänen, Aleksi; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo

2017-04-01

Biomass is one of the central bio-geophysical variables in Earth observation for tracking plant productivity, and flow of carbon, nutrients, and water. Most of the satellite based biomass mapping exercises in Arctic environments have been performed by using rather coarse spatial resolution data, e.g. Landsat and AVHRR which have spatial resolutions of 30 m and >1 km, respectively. While the coarse resolution images have high temporal resolution, they are incapable of capturing the fragmented nature of tundra environment and fine-scale changes in vegetation and carbon exchange patterns. Very high spatial resolution (VHSR, spatial resolution 0.5-2 m) satellite images have the potential to detect environmental variables with an ecologically sound spatial resolution. The usage of VHSR images has, nevertheless, been modest so far in biomass modeling in the Arctic. Our objectives were to use VHSR for predicting above ground biomass in tundra landscapes, evaluate whether a common predictive model can be applied across circum-Arctic tundra and peatland sites having different types of vegetation, and produce knowledge on distribution of plant functional types (PFT) in these sites. Such model development is dependent on ground-based surveys of vegetation with the same spatial resolution and extent with the VHSR images. In this study, we conducted ground-based surveys of vegetation composition and biomass in four different arctic tundra or peatland areas located in Russia, Canada, and Finland. First, we sorted species into PFTs and developed PFT-specific models to predict biomass on the basis of non-destructive measurements (cover, height). Second, we predicted overall biomass on landscape scale by combinations of single bands and vegetation indices of very high resolution satellite images (QuickBird or WorldView-2 images of the eight sites). We compared area-specific empirical regression models and common models that were applied across all sites. We found that NDVI was usually the highest scoring spectral indices in explaining biomass distribution with good explanatory power. Furthermore, models which had more than one explanatory variable had higher explanatory power than models with a single index. The dissimilarity between common and site-specific model estimates was, however, high and data indicates that variation in vegetation properties and its impact on spectral reflectance needs to be acknowledged. Our work produced knowledge on above-ground biomass distribution and contribution of PFTs across circum-Arctic low-growth landscapes and will contribute to developing space-borne vegetation monitoring schemes utilizing VHSR satellite images.

Vegetation indicators of transformation in the urban forest ecosystems of "Kuzminki-Lyublino" Park

NASA Astrophysics Data System (ADS)

Buyvolova, Anna; Trifonova, Tatiana; Bykova, Elena

2017-04-01

Forest ecosystems in the city are at the same time a component of its natural environment and part of urban developmental planning. It imposes upon urban forests a large functional load, both environmental (formation of environment, air purification, noise pollution reducing, etc.) and social (recreational, educational) which defines the special attitude to their management and study. It is not a simple task to preserve maximum accessibility to the forest ecosystems of the large metropolises with a minimum of change. The urban forest vegetates in naturally formed soil, it has all the elements of a morphological structure (canopy layers), represented by natural species of the zonal vegetation. Sometimes it is impossible for a specialist to distinguish between an urban forest and a rural one. However, the urban forests are changing, being under the threat of various negative influences of the city, of which pollution is arguably the most significant. This article presents some indicators of structural changes to the plant communities, which is a response of forest ecosystems to an anthropogenic impact. It is shown that the indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The assessment of the impact of the urban environment on the state of vegetation in the "Kuzminki-Lyublino" Natural-Historical Park was conducted in two key areas least affected by anthropogenic impacts under different plant communities represented by complex pine and birch forests and in similar forest types in the Prioksko-Terrasny Biosphere Reserve. The selection of pine forests as a model is due to the fact that, according to some scientists, pine (Pinus Sylvestris L.), a very ductile and widespread species, is a sensitive indicator of anthropogenic burden, responding to the impact of defoliation and needles discoloration, and survives even at fairly high levels of pollution. The vegetation cover is one of the most dynamic components of the ecosystem and under the conditions of urban existence it is subject to transformation. The indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The further study of plant communities with a view to identifying indicators of transformation in urban environmental conditions will help for the early detection of reversible changes in the ecosystems of urban forests and the development of rational urban forest care technologies.

Marital transitions and associated changes in fruit and vegetable intake: Findings from the population-based prospective EPIC-Norfolk cohort, UK

PubMed Central

Vinther, Johan L.; Conklin, Annalijn I.; Wareham, Nicholas J.; Monsivais, Pablo

2016-01-01

Background Diet is critical to health and social relationships are an important determinant of diet. We report the association between transitions in marital status and healthy eating behaviours in a UK population. Methods Longitudinal study of middle-age and older adults 39−78y (n = 11 577) in EPIC-Norfolk, a population-based cohort, who completed food frequency questionnaires in 1993–97 and 1998–2002. Multivariable linear regression analyses assessed gender-specific associations between five categories of marital transitions and changes in quantity (g/d), and variety (no/month) of fruits or vegetables. Results In 3.6 years of follow-up and relative to men who stayed married, widowed men showed significant declines (mean difference, 95% CI) in all four indicators of healthy eating including fruit quantity (−47.7, −80.6 to −14.9 g/d), fruit variety (−0.6, −1.1 to −0.2 no/month), vegetable quantity (−27.7, −50.5 to −4.9 g/d), and vegetable variety (−1.6, −2.2 to −0.9 no/month). Men who were separated or divorced or who remained single also showed significant declines in three of the indicators. Among women, only those who became separated/divorced or stayed single showed declines in one indicator, vegetable variety. Conclusion Unhealthy changes to diet accompanying divorce, separation and becoming widowed may be more common among men than women. Moreover, deterioration in fruit and vegetable intakes was more apparent for variety rather than quantity consumed. Programmes to promote healthy eating among older adults need to recognise these social determinants of diet and consider prioritising people who live alone and in particular men who have recently left relationships or who have been widowed. PMID:27082023

Evaluating the utility of vegetation indices to monitoring forests in South America, Western & Central Africa, and Southeast Asia

NASA Astrophysics Data System (ADS)

Cherrington, E. A.; Vincent, G.; Barbier, N.; Pélissier, R.; Sabatier, D.; Berger, U.

2017-12-01

In recent years, there has been controversy regarding applying vegetation indices (VIs) for monitoring tropical forests because of data artefacts related to sun-sensor geometry issues. One means of addressing the issue is comparing the VI variation of tropical forests in similar latitudes. That is, if intra-annual variation in VIs is not driven by real structural and biological changes in the vegetation, then one would expect that forests on the same latitudes should display similar patterns of VI variation. Data from multiple vegetation indices (from MODIS and SPOT VEGETATION) were analyzed over three ten degree by ten degree tiles covering the Guianas, western-central Africa, and northern Borneo in Southeast Asia. In addition to comparing the intra-annual trends across the three regions, the trends were also compared with intra-annual patterns of temporal variation, to see if these explained the VI variation. Those analyses showed that not only did the VI variation across the three regions differ significantly, but the patterns in VI variation for at least two of the three regions were largely correlated with intra-annual variation in environmental factors such as rainfall or light availability. For the Guianas, the pattern of VI variation was largely correlated with the variation in solar radiation, while for western-central Africa, the pattern of variation was more correlated to the variation in rainfall. In contrast, for northern Borneo, the pattern of VI variation did not correlate well with either variation in solar elevation or with intra-annual variation in environmental factors. Firstly, the data would seem to suggest that the patterns of variation in VI data for tropical forests are not strongly biased by artefacts related to sun-sensor geometry effects. More importantly, however, the results also suggest that the phenological of forests in both the Guianas and in western-central Africa are governed by different environmental regimes. That is to say, the forests in the Guianas appear to be light-limited, whereas in contrast, the forests in western-central Africa appear to be moisture-limited. This research suggests that vegetation index data - when corrected for artefacts related to bi-directional effects - can indeed be used to study patterns of temporal variation of forests in the tropics.

Rainbow trout can discriminate between feeds with different oil sources.

PubMed

Geurden, I; Cuvier, A; Gondouin, E; Olsen, R E; Ruohonen, K; Kaushik, S; Boujard, T

2005-06-02

The purpose of present two-choice trials was to examine the capacity of groups of juvenile rainbow trout to differentiate between two isolipidic diets containing distinct oils and to detect an eventual preference. The choice was offered by means of two self-feeders per tank. One feeder distributed a standard diet with fish oil (FO), the other a diet containing vegetable oil, either rich in linolenic acid (linseed oil, LO), linoleic acid (sunflower oil, SO), or oleic acid (rapeseed oil, RO). Each 15-day preference test was preceded by a 15-day adaptation period during which both feeders distributed the same diet. The tests were followed by a 10- to 15-day validation period in order to confirm that feeder solicitations were steered by the characteristics of the diets. Preferences were expressed as relative changes in feed demands for a specific feeder. Averaged over all groups, the preference tests demonstrated the capacity of rainbow trout to discriminate between a diet with FO and a diet containing vegetable oil, and indicated a general preference for the diet with FO over the other diets irrespective of whether they received the diet with fish oil (Experiment 1) or with vegetable oil (Experiment 2) prior to the preference test. The tests also indicated a difference in the extent of relative avoidance of each of the three vegetable oil diets. Diet LO was the most avoided, as indicated by the 37-39% decrease in demands for the feeder with diet LO (P<0.05). Diet RO was the best accepted, causing a decrease in feed demands of only 15-17% (P>0.05). The avoidance of diet SO at the end of the preference test was 30% (P>0.05) after an initially higher avoidance of 43% (P<0.05). It is believed that the metabolic consequences of the excess of linolenic or linoleic acid negatively affected the feed acceptances of diets LO and SO. Further work is needed to elucidate a possible interference of differences in palatability. In all groups, the lower demands for the vegetable oil diets were compensated by increased demands for diet FO. Hence, changes in diet selection had no effect on total feed or energy intakes, measured as the sum of both selections.

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method

USGS Publications Warehouse

Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis

2017-01-01

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant density, height, and to a certain degree, diameter. Wave dissipation is mostly dependent on the variation in plant density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance for future observational and modeling work to optimize efforts and reduce exploration of parameter space.

Vertical and Horizontal Vegetation Structure across Natural and Modified Habitat Types at Mount Kilimanjaro

PubMed Central

Rutten, Gemma; Ensslin, Andreas; Hemp, Andreas; Fischer, Markus

2015-01-01

In most habitats, vegetation provides the main structure of the environment. This complexity can facilitate biodiversity and ecosystem services. Therefore, measures of vegetation structure can serve as indicators in ecosystem management. However, many structural measures are laborious and require expert knowledge. Here, we used consistent and convenient measures to assess vegetation structure over an exceptionally broad elevation gradient of 866–4550m above sea level at Mount Kilimanjaro, Tanzania. Additionally, we compared (human)-modified habitats, including maize fields, traditionally managed home gardens, grasslands, commercial coffee farms and logged and burned forests with natural habitats along this elevation gradient. We distinguished vertical and horizontal vegetation structure to account for habitat complexity and heterogeneity. Vertical vegetation structure (assessed as number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) displayed a unimodal elevation pattern, peaking at intermediate elevations in montane forests, whereas horizontal structure (assessed as coefficient of variation of number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) was lowest at intermediate altitudes. Overall, vertical structure was consistently lower in modified than in natural habitat types, whereas horizontal structure was inconsistently different in modified than in natural habitat types, depending on the specific structural measure and habitat type. Our study shows how vertical and horizontal vegetation structure can be assessed efficiently in various habitat types in tropical mountain regions, and we suggest to apply this as a tool for informing future biodiversity and ecosystem service studies. PMID:26406985

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data

NASA Astrophysics Data System (ADS)

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.; Yin, Yunhe; Kumar, Jitendra; Ma, Chun; Xu, Xiaofeng

2017-09-01

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. We compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62). However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S-10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1-0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.

Role of climate variables and spectral indices in characterizing ecosystem water use efficiency of flood irrigated citrus orchards

NASA Astrophysics Data System (ADS)

Peddinti, S. R.; Sanaga, S.; Rodda, S. R.

2017-12-01

Exchange of carbon and water fluxes between vegetation and atmosphere play a crucial role in the metabolism of terrestrial ecosystems. These exchanges are coupled through a key ecosystem characteristic called water use efficiency (WUE): the ratio between carbon assimilation (proxy to photosynthesis) to water loss (proxy to consumptive use). Globally, India ranks fourth in mandarin orange (Citrus reticulata) production, but ranks 64th in orange crop yield. The dichotomy between crop production and yield can be attributed to erratic rainfall and improper management practices. This research aims at analysing the diurnal and seasonal dynamics of WUE, and their dominant controls for the citrus orchards of central India. Eddy covariance (EC) technique was used to estimate evapotranspiration (ET) and gross primary product (GPP) fluxes in a flood irrigated, matured, healthy citrus orchard for one crop cycle. Seasonal variations in ET and GPP were observed to be strongly influenced by leaf phonological parameters and less by climate variables. Landsat-8 images were used to extrapolate and scale-up the in situ fluxes to characterize the ecosystem WUE. Overall, Landsat-8 has reasonably captured ET, GPP, and WUE dynamics at the flux tower location (R2 ≥0.86). Spatiotemporal patterns of ET, GPP, and WUE fluxes reveals that the heterogeneity is gradually increasing from flowering to development stage. A number of vegetation, soil, and biophysical indices derived from Landsat-8 were then correlated with WUE estimates, to see if these indices either in solitary or in combination can explain WUE dynamics of citrus orchards. Results conclude that, spatial patterns in WUE are strongly correlated with enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and soil adjusted vegetation index (SAVI). Spectral indices derived WUE estimates were further used to develop sustainable agricultural management practices applicable to the region.

Ground Field-Based Hyperspectral Imaging: A Preliminary Study to Assess the Potential of Established Vegetation Indices to Infer Variation in Water-Use Efficiency.

NASA Astrophysics Data System (ADS)

Pelech, E. A.; McGrath, J.; Pederson, T.; Bernacchi, C.

2017-12-01

Increases in the global average temperature will consequently induce a higher occurrence of severe environmental conditions such as drought on arable land. To mitigate these threats, crops for fuel and food must be bred for higher water-use efficiencies (WUE). Defining genomic variation through high-throughput phenotypic analysis in field conditions has the potential to relieve the major bottleneck in linking desirable genetic traits to the associated phenotypic response. This can subsequently enable breeders to create new agricultural germplasm that supports the need for higher water-use efficient crops. From satellites to field-based aerial and ground sensors, the reflectance properties of vegetation measured by hyperspectral imaging is becoming a rapid high-throughput phenotyping technique. A variety of physiological traits can be inferred by regression analysis with leaf reflectance which is controlled by the properties and abundance of water, carbon, nitrogen and pigments. Although, given that the current established vegetation indices are designed to accentuate these properties from spectral reflectance, it becomes a challenge to infer relative measurements of WUE at a crop canopy scale without ground-truth data collection. This study aims to correlate established biomass and canopy-water-content indices with ground-truth data. Five bioenergy sorghum genotypes (Sorghum bicolor L. Moench) that have differences in WUE and wild-type Tobacco (Nicotiana tabacum var. Samsun) under irrigated and rainfed field conditions were examined. A linear regression analysis was conducted to determine if variation in canopy water content and biomass, driven by natural genotypic and artificial treatment influences, can be inferred using established vegetation indices. The results from this study will elucidate the ability of ground field-based hyperspectral imaging to assess variation in water content, biomass and water-use efficiency. This can lead to improved opportunities to select ideal genotypes for an increasing water-limited environment and to help parameterize and validate terrestrial vegetation models that require a better representation of genetic variation within crop species.

Linking chlorophyll fluorescence, hyperspectral reflectance and plant physiological responses to detect stress using the photochemical reflectance index (PRI) (Invited)

NASA Astrophysics Data System (ADS)

Naumann, J. C.; Young, D.; Anderson, J.

2009-12-01

The concept of using vegetation as sentinels to indicate natural or anthropogenic stress is not new and could potentially provide an ideal mechanism for large-scale detection. Advances in fluorescence spectroscopy and reflectance-derived fluorescence have made possible earlier detection of stress in plants, especially before changes in chlorophyll content are visible. Our studies have been used to fuse leaf fluorescence and reflectance characteristics to remotely sense and rapidly detect vegetation stress and terrain characteristics. Laboratory studies have indicated that light-adapted fluorescence (ΔF/F‧m) measurements have been successful in all experiments at detecting stress from flooding, salinity, drought, herbicide and TNT contamination prior to visible signs of damage. ΔF/F‧m was related to plant physiological status in natural stress conditions, as seen in the relationships with stomatal conductance and photosynthesis The photochemical reflectance index (PRI) and other reflectance ratios were effective at tracking changes in ΔF/F‧m at the leaf and canopy-level scales. At the landscape-level, chlorophyll fluorescence and airborne reflectance imagery were used to evaluate spatial variations in stress in the dominant shrub on a barrier island, Myrica cerifera, during a severe drought and compared to an extremely wet year. Measurements of relative water content and the water band index (WBI970) indicated that water stress did not vary across the island. In contrast, there were significant differences in tissue chlorides across sites. Using PRI we were able to detect salinity stress across the landscape. PRI did not differ between wet and dry years. There was a positive relationship between PRI and ΔF/F‧m for M. cerifera (r2 = 0.79). The normalized difference vegetation index (NDVI), the chlorophyll index (CI) and WBI970 were higher during the wet summer but varied little across the island. PRI was not significantly related to NDVI, suggesting that the indices are spatially independent. For anthropogenic stress, M. cerifera plants were exposed to a range of TNT concentrations. Several reflectance indices revealed stress prior to changes in chlorophyll concentration, while other optical indices did not change that would be indicative of natural stress. Field studies of M. cerifera at Duck Pier, NC, an old Navy bombing range, indicated numerous reflectance indices were able to detect stress likely due to explosives contamination. Our results suggest that hyperspectral indices may be used for early identification of stress, especially in environments where direct variations in stressors are typical and vegetation structure and landscape features are relatively simple. PRI may be used for early identification of salt stress that may lead to changes in plant distributions at the landscape level as a result of rising sea-level and increased storm intensity from global climate change. Other derived indices may be useful for separating natural and anthropogenic stress at multiple spatial scales.

Soil-plant-microbial relations in hydrothermally altered soils of Northern California

USGS Publications Warehouse

Blecker, S.W.; Stillings, L.L.; DeCrappeo, N.M.; Ippolito, J.A.

2014-01-01

Soils developed on relict hydrothermally altered soils throughout the Western USA present unique opportunities to study the role of geology on above and belowground biotic activity and composition. Soil and vegetation samples were taken at three unaltered andesite and three hydrothermally altered (acid-sulfate) sites located in and around Lassen VolcanicNational Park in northeastern California. In addition, three different types of disturbed areas (clearcut, thinned, and pipeline) were sampled in acid-sulfate altered sites. Soils were sampled (0–15 cm) in mid-summer 2010 from both under-canopy and between-canopy areas within each of the sites. Soils were analyzed for numerous physical and chemical properties along with soil enzyme assays, C and N mineralization potential, microbial biomass-C and C-substrate utilization. Field vegetation measurements consisted of canopy cover by life form (tree, shrub, forb, and grass), tree and shrub density, and above-ground net primary productivity of the understory. Overall, parameters at the clearcut sites were more similar to the unaltered sites, while parameters at the thinned and pipeline sites were more similar to the altered sites. We employed principal components analysis (PCA) to develop two soil quality indices (SQI) to help quantify the differences among the sites: one based on the correlation between soil parameters and canopy cover, and the second based on six sub-indices. Soil quality indices developed in these systems could provide a means for monitoring and identifying key relations between the vegetation, soils, and microorganisms.

[Variation of satellite-based spring vegetation phenology and the relationship with climate in the Northern Hemisphere over 1982 to 2009.

PubMed

Cong, Nan; Shen, Miao Gen

2016-09-01

In-depth understanding the variation of vegetation spring phenology is important and nece-ssary for estimation and prediction of ecosystem response to climate change. Satellite-based estimation is one of the important methods for detecting the vegetation spring phenology in Northern Hemisphere. However, there are still many uncertainties among different remote sensing models. In this study, we employed NDVI satellite product from 1982 to 2009 to estimate vegetation green-up onset dates in spring across Northern Hemisphere, and further analyzed the phenology spatio-temporal variation and the relationship with climate. Results showed that spatial mean spring phenology significantly advanced by (4.0±0.8) days during this period in the Northern Hemisphere, while spring phenology advanced much faster in Eurasia (0.22±0.04 d·a -1 ) than in North America (0.03±0.02 d·a -1 ). Moreover, phenology of different vegetation types changed inconstantly during the period. All five methods consistently indicated that grassland significantly advanced, while forests didn't advance robustly among methods. In addition, the interannual change of spring phenology was mainly driven by spring temperature. The spring phenology advanced (3.2±0.5) days with 1 ℃ increase in temperature. On the contrary, we did not find significant relationship between vegetation spring phenology and spring accumulative precipitation across the Northern Hemisphere (P>0.05) in this study.

Quality of Vegetables Based on Total Phenolic Concentration Is Lower in More Rural Consumer Food Environments in a Rural American State.

PubMed

Ahmed, Selena; Byker Shanks, Carmen

2017-08-17

While daily consumption of fruits and vegetables (FVs) is widely recognized to be associated with supporting nutrition and health, disparities exist in consumer food environments regarding access to high-quality produce based on location. The purpose of this study was to evaluate FV quality using total phenolic (TP) scores (a phytochemical measure for health-promoting attributes, flavor, appearance, and shelf-life) in consumer food environments along a rural to urban continuum in the rural state of Montana, United States. Significant differences were found in the means of the FV TP scores ( p < 0.0001) and vegetable TP scores ( p < 0.0001) on the basis of rurality, while no significant difference was found for fruit TP scores by rurality ( p < 0.2158). Specifically, FV TP scores and vegetable TP scores were highest for the least rural stores and lowest for the most rural stores. Results indicate an access gap to high-quality vegetables in more rural and more health-disparate consumer food environments of Montana compared to urban food environments. Findings highlight that food and nutrition interventions should aim to increase vegetable quality in rural consumer food environments in the state of Montana towards enhancing dietary quality and food choices. Future studies are called for that examine TP scores of a wide range of FVs in diverse food environments globally. Studies are further needed that examine linkages between FV quality, food choices, diets, and health outcomes towards enhancing food environments for public health.