Assessment of post forest fire reclamation in Algarve, Portugal

NASA Astrophysics Data System (ADS)

Andrade, Rita; Panagopoulos, Thomas; Guerrero, Carlos; Martins, Fernando; Zdruli, Pandi; Ladisa, Gaetano

2014-05-01

Fire is a common phenomenon in Mediterranean landscapes and it plays a crucial role in its transformations, making the determination of its impact on the ecosystem essential for land management. During summer of 2012, a wildfire took place in Algarve, Portugal, on an area mainly covered by sclerophyllous vegetation (39.44%, 10080ha), broad-leaved forest (20.80%, 5300ha), agriculture land with significant areas of natural vegetation (17.40%, 4400ha) and transitional woodlands-shrubs (16.17%, 4100ha). The objective of the study was to determine fire severity in order to plan post-fire treatments and to aid vegetation recovery and land reclamation. Satellite imagery was used to estimate burn severity by detecting physical and ecological changes in the landscape caused by fire. Differenced Normalized Burn Ratio (DNBR) was used to measure burn severity with pre and post fire data of four Landsat images acquired in October 2011, February and August 2012 and April 2013. The initial and extended differenced normalized burn ratio (DiNBR and DeNBR) were calculated. The calculated burned area of 24291 ha was 552ha lower than the map data determined with field reports. The 19.5% of that area was burned with high severity, 45% with moderate severity and 28.3% with low severity. Comparing fire severity and regrowth with land use, it is shown in DiNBR that the most severely burned areas were predominantly sclerophyllous vegetation (37.6%) and broad-leaved forests (31.1%). From the DeNRB it was found that the reestablishment of vegetation was slower in mixed forests and higher in sclerophyllous vegetation and in land with significant areas of natural vegetation. Faster recovery was calculated for the land uses of sclerophyllous vegetation (46.7%) and significant regrowth in areas of natural vegetation and lands occupied by agriculture (25.4%). Next steps of the study are field validation and crossing with erosion risk maps before to take land reclamation decisions.

Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper

NASA Astrophysics Data System (ADS)

Renza, Diego; Martinez, Estibaliz; Molina, Iñigo; Ballesteros L., Dora M.

2017-04-01

This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load.

Landsat-Based Detection and Severity Analysis of Burned Sugarcane Plots in Tarlac, Philippines Using Differenced Normalized Burn Ratio (dNBR)

NASA Astrophysics Data System (ADS)

Baloloy, A. B.; Blanco, A. C.; Gana, B. S.; Sta. Ana, R. C.; Olalia, L. C.

2016-09-01

The Philippines has a booming sugarcane industry contributing about PHP 70 billion annually to the local economy through raw sugar, molasses and bioethanol production (SRA, 2012). Sugarcane planters adapt different farm practices in cultivating sugarcane, one of which is cane burning to eliminate unwanted plant material and facilitate easier harvest. Information on burned sugarcane extent is significant in yield estimation models to calculate total sugar lost during harvest. Pre-harvest burning can lessen sucrose by 2.7% - 5% of the potential yield (Gomez, et al 2006; Hiranyavasit, 2016). This study employs a method for detecting burn sugarcane area and determining burn severity through Differenced Normalized Burn Ratio (dNBR) using Landsat 8 Images acquired during the late milling season in Tarlac, Philippines. Total burned area was computed per burn severity based on pre-fire and post-fire images. Results show that 75.38% of the total sugarcane fields in Tarlac were burned with post-fire regrowth; 16.61% were recently burned; and only 8.01% were unburned. The monthly dNBR for February to March generated the largest area with low severity burn (1,436 ha) and high severity burn (31.14 ha) due to pre-harvest burning. Post-fire regrowth is highest in April to May when previously burned areas were already replanted with sugarcane. The maximum dNBR of the entire late milling season (February to May) recorded larger extent of areas with high and low post-fire regrowth compared to areas with low, moderate and high burn severity. Normalized Difference Vegetation Index (NDVI) was used to analyse vegetation dynamics between the burn severity classes. Significant positive correlation, rho = 0.99, was observed between dNBR and dNDVI at 5% level (p = 0.004). An accuracy of 89.03% was calculated for the Landsat-derived NBR validated using actual mill data for crop year 2015-2016.

Mapping burned areas and burn severity patterns across the Mediterranean region

NASA Astrophysics Data System (ADS)

Kalogeropoulos, Christos; Amatulli, Giuseppe; Kempeneers, Pieter; Sedano, Fernando; San Miguel-Ayanz, Jesus; Camia, Andrea

2010-05-01

The Mediterranean region is highly susceptible to wildfires. On average, about 60,000 fires take place in this region every year, burning on average half a million hectares of forests and natural vegetation. Wildfires cause environmental degradation and affect the lives of thousands of people in the region. In order to minimize the consequences of these catastrophic events, fire managers and national authorities need to have in their disposal accurate and updated spatial information concerning the size of the burned area as well as the burn severity patterns. Mapping burned areas and burn severity patterns is necessary to effectively support the decision-making process in what concerns strategic (long-term) planning with the definition of post-fire actions at European and national scales. Although a comprehensive archive of burnt areas exists at the European Forest Fire Information System, the analysis of the severity of the areas affected by forest fires in the region is not yet available. Fire severity is influenced by many variables, including fuel type, topography and meteorological conditions before and during the fire. The analysis of fire severity is essential to determine the socio-economic impact of forest fires, to assess fire impacts, and to determine the need of post-fire rehabilitation measures. Moreover, fire severity is linked to forest fire emissions and determines the rate of recovery of the vegetation after the fire. Satellite imagery can give important insights about the conditions of the live fuel moisture content and can be used to assess changes on vegetation structure and vitality after forest fires. Fire events occurred in Greece, Portugal and Spain during the fire season of 2009 were recorded and analyzed in a GIS environment. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI) and the Normalized Burn Ratio (NBR) were calculated from 8-days composites MODIS/TERRA imagery from March to October 2009. In addition, subtracting a post-fire from a pre-fire image derived index produces a measure of absolute change of the vegetation condition, like the differenced Normalized Burn Ratio index (dNBR). The aim of this study was the assessment of fire severity across diverse ecological and environmental conditions in the Mediterranean region. The specific objectives were: • The analysis of the correlation between the fire severity and local site conditions, including topography, fuel type, land use, land cover. • The analysis of the correlation between fire severity and fire danger conditions during the fire, as estimated by the European Forest Fire Information System. • Assessing the performance of several vegetation indices derived from MODIS imagery in estimating fire severity. • Assessing the permanence of the burnt signal for large fires as an estimate of fire severity.

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

Arctic Browning: vegetation damage and implications for carbon balance.

NASA Astrophysics Data System (ADS)

Treharne, Rachael; Bjerke, Jarle; Emberson, Lisa; Tømmervik, Hans; Phoenix, Gareth

2016-04-01

'Arctic browning' is the loss of biomass and canopy in Arctic ecosystems. This process is often driven by climatic and biological extreme events - notably extreme winter warm periods, winter frost-drought and severe outbreaks of defoliating insects. Evidence suggests that browning is becoming increasingly frequent and severe at the pan-arctic scale, a view supported by observations from more intensely observed regions, with major and unprecedented vegetation damage reported at landscape (>1000km2) and regional (Nordic Arctic Region) scales in recent years. Critically, the damage caused by these extreme events is in direct opposition to 'Arctic greening', the well-established increase in productivity and shrub abundance observed at high latitudes in response to long-term warming. This opposition creates uncertainty as to future anticipated vegetation change in the Arctic, with implications for Arctic carbon balance. As high latitude ecosystems store around twice as much carbon as the atmosphere, and vegetation impacts are key to determining rates of loss or gain of ecosystem carbon stocks, Arctic browning has the potential to influence the role of these ecosystems in global climate. There is therefore a clear need for a quantitative understanding of the impacts of browning events on key ecosystem carbon fluxes. To address this, field sites were chosen in central and northern Norway and in Svalbard, in areas known to have been affected by either climatic extremes or insect outbreak and subsequent browning in the past four years. Sites were chosen along a latitudinal gradient to capture both conditions already causing vegetation browning throughout the Norwegian Arctic, and conditions currently common at lower latitudes which are likely to become more damaging further North as climate change progresses. At each site the response of Net Ecosystem CO2 Exchange to light was measured using a LiCor LI6400 Portable Photosynthesis system and a custom vegetation chamber with artificial shading. These data allowed the impact of browning on plot-level Gross Primary Productivity (GPP), Net Ecosystem Exchange and ecosystem respiration to be calculated. Substantial site-level impacts were identified, with heavily damaged vegetation converted from a net CO2 sink to a net source. Plot-level spectral data were then used to establish a relationship between Leaf Area Index (LAI), as predicted from Normalised Differenced Vegetation Index (NDVI), and GPP. This builds on work demonstrating that NDVI-derived LAI can explain up to 80% of variation in GPP in healthy vegetation. Confirmation that this relationship holds true in browned vegetation validates its use for estimating browning impacts on Arctic carbon balance using remotely sensed data.

Trend time-series modeling and forecasting with neural networks.

PubMed

Qi, Min; Zhang, G Peter

2008-05-01

Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.

Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data

NASA Astrophysics Data System (ADS)

Mei, Alessandro; Manzo, Ciro; Fontinovo, Giuliano; Bassani, Cristiana; Allegrini, Alessia; Petracchini, Francesco

2016-10-01

The Lampedusa Island displays important socio-economic criticalities related to an intensive touristic activity, which implies an increase in electricity consumption and waste production. An adequate island conversion to a more environmental, sustainable community needs to be faced by the local Management Plans establishment. For this purpose, several thematic datasets have to be produced and evaluated. Socio-economic and bio-ecological components as well as land cover/use assessment are some of the main topics to be managed within the Decision Support Systems. Considering the lack of Land Cover (LC) and vegetation change detection maps in Lampedusa Island (Italy), this paper focuses on the retrieval of these topics by remote sensing techniques. The analysis was carried out by Landsat 5 TM and Landsat 8 OLI multispectral images from 1984 to 2014 in order to obtain spatial and temporal information of changes occurred in the island. Firstly, imagery was co-registered and atmospherically corrected; secondly, it was then classified for land cover and vegetation distribution analysis with the use of QGIS and Saga GIS open source softwares. The Maximum Likelihood Classifier (MLC) was used for LC maps production, while the Normalized Difference Vegetation Index (NDVI) was used for vegetation examination and distribution. Topographic maps, historical aerial photos, ortophotos and field data are merged in the GIS for accuracy assessment. Finally, change detection of MLC and NDVI are provided respectively by Post-Classification Comparison (PCC) and Image Differencing (ID). The provided information, combined with local socio-economic parameters, is essential for the improvement of environmental sustainability of anthropogenic activities in Lampedusa.

Evaluation of linear spectral unmixing and deltaNBR for predicting post-fire recovery in a North American ponderosa pine forest

Treesearch

A. M. S. Smith; L. B. Lenilte; A. T. Hudak; P. Morgan

2007-01-01

The Differenced Normalized Burn Ratio (deltaNBR) is widely used to map post-fire effects in North America from multispectral satellite imagery, but has not been rigorously validated across the great diversity in vegetation types. The importance of these maps to fire rehabilitation crews highlights the need for continued assessment of alternative remote sensing...

Impact of India's watershed development programs on biomass productivity

NASA Astrophysics Data System (ADS)

Bhalla, R. S.; Devi Prasad, K. V.; Pelkey, Neil W.

2013-03-01

Watershed development (WSD) is an important and expensive rural development initiative in India. Proponents of the approach contend that treating watersheds will increase agricultural and overall biomass productivity, which in turn will reduce rural poverty. We used satellite-measured normalized differenced vegetation index as a proxy for land productivity to test this crucial contention. We compared microwatersheds that had received funding and completed watershed restoration with adjacent untreated microwatersheds in the same region. As the criteria used can influence results, we analyzed microwatersheds grouped by catchment, state, ecological region, and biogeographical zones for analysis. We also analyzed pre treatment and posttreatment changes for the same watersheds in those schemes. Our findings show that WSD has not resulted in a significant increase in productivity in treated microwatersheds at any grouping, when compared to adjacent untreated microwatershed or the same microwatershed prior to treatment. We conclude that the well-intentioned people-centric WSD efforts may be inhibited by failing to adequately address the basic geomorphology and hydraulic condition of the catchment areas at all scales.

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.

Monitoring of reforestation on burnt areas in Western Russia using Landsat time series

NASA Astrophysics Data System (ADS)

Vorobev, Oleg; Kurbanov, Eldar

2017-04-01

Forest fires are main disturbance factor for the natural ecosystems, especially in boreal forests. Monitoring for the dynamic of forest cover regeneration in the post-fire period of ecosystem recovery is crucial to both estimation of forest stands and forest management. In this study, on the example of burnt areas of 2010 wildfires in Republic Mari El of Russian Federation we estimated post-fire dynamic of different classes of vegetation cover between 2011-2016 years with the use of time series Landsat satellite images. To validate the newly obtained thematic maps we used 80 test sites with independent field data, as well Canopus-B images of high spatial resolution. For the analysis of the satellite images we referred to Normalized Differenced Vegetation Index (NDVI) and Tasseled Cap transformation. The research revealed that at the post-fire period the area of thematic classes "Reforestation of the middle and low density" has maximum cover (44%) on the investigated burnt area. On the burnt areas of 2010 there is ongoing active process of grass overgrowing (up to 20%), also there are thematic classes of deadwood (15%) and open spaces (10%). The results indicate that there is mostly natural regeneration of tree species pattern corresponding to the pre-fire condition. Forest plantations cover only 2% of the overall burnt area. By the 2016 year the NDVI parameters of young vegetation cover were recovered to the pre-fire level as well. The overall unsupervised classification accuracy of more than 70% shows high degree of agreement between the thematic map and the ground truth data. The research results can be applied for the long term succession monitoring and management plan development for the reforestation activities on the lands disturbed by fire.

Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Molthan, Andrew L.; Schultz, Lori A.; McGrath, Kevin M.; Burks, Jason E.

2015-01-01

The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as for hail damage swath identification. Initial validation of the automated algorithm is based upon Storm Prediction Center storm reports but also the National Severe Storm Laboratory (NSSL) Maximum Estimated Size Hail (MESH) product. Opportunities for future work are also shown, with focus on expansion of this algorithm with pixel-based image classification techniques for tracking surface changes as a result of severe weather.

Modeling of multi-strata forest fire severity using Landsat TM data

Treesearch

Q. Meng; R.K. Meentemeyer

2011-01-01

Most of fire severity studies use field measures of composite burn index (CBI) to represent forest fire severity and fit the relationships between CBI and Landsat imagery derived differenced normalized burn ratio (dNBR) to predict and map fire severity at unsampled locations. However, less attention has been paid on the multi-strata forest fire severity, which...

An Analysis Framework Using Satellite Remote Sensing to Understand Landscape Patterns of High Severity Burns from Wildfires in Coastal Woodlands of California and Italy

NASA Astrophysics Data System (ADS)

Potter, C. S.

2016-12-01

The central California coastal landscape has a history of frequent large wildfires that have threatened or destroyed many residential structures at the wildland interface. This study starts with the largest wildfires on the Central Coast over the past 30 years and analyzes the fraction and landscape patterns of high severity burned (HBS) areas from the Landsat-based Monitoring Trends in Burn Severity (MTBS) data base as a function of weather conditions and topographic variations. Results indicate that maximum temperatures at the time of fire and the previous 12 months of rainfall explained a significant portion of the variation in total area burned and the fraction of HBS area. Average patch size and aggregation metrics of HBS areas were included in the analysis framework. Within each burned area, the Landsat (30-meter resolution) differenced Normalized Burn Ratio (dNBR), a continuous index of vegetation burn severity, was correlated against slope, aspect, and elevation to better understand landscape level-controls over HBS patches. The Landsat dNBR analysis framework is being extended next to the island of Sardinia, Italy for a comparison of Mediterranean climates and wildfire patterns since the mid-1980s.

1984–2010 trends in fire burn severity and area for the conterminous US

USGS Publications Warehouse

Picotte, Joshua J.; Peterson, Birgit E.; Meier, Gretchen; Howard, Stephen M.

2016-01-01

Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed across the conterminous US (CONUS) and mapped by MTBS. Yearly mean burn severity values (weighted by area), maximum burn severity metric values, mean area of burn, maximum burn area and total burn area were evaluated within 27 US National Vegetation Classification macrogroups. Time series assessments of burned area and severity were performed using Mann–Kendall tests. Burned area and severity varied by vegetation classification, but most vegetation groups showed no detectable change during the 1984–2010 period. Of the 27 analysed vegetation groups, trend analysis revealed burned area increased in eight, and burn severity has increased in seven. This study suggests that burned area and severity, as measured by the severity metric based on dNBR or RdNBR, have not changed substantially for most vegetation groups evaluated within CONUS.

a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

NASA Astrophysics Data System (ADS)

Dehnavi, S.; Maghsoudi, Y.

2015-12-01

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

Relating fire-caused change in forest structure to remotely sensed estimates of fire severity

Treesearch

Jamie M. Lydersen; Brandon M. Collins; Jay D. Miller; Danny L. Fry; Scott L. Stephens

2016-01-01

Fire severity maps are an important tool for understanding fire effects on a landscape. The relative differenced normalized burn ratio (RdNBR) is a commonly used severity index in California forests, and is typically divided into four categories: unchanged, low, moderate, and high. RdNBR is often calculated twice--from images collected the year of the fire (initial...

Observations of Typhoon Center by Using Satellite-derived Normalized Difference Convection Index

NASA Astrophysics Data System (ADS)

Liu, Chung-Chih; Chen, Chun-Hsu

2015-04-01

A technique involving differencing water vapor and infrared window channel brightness temperature values to identify and quantify intense convection in tropical cyclones using bispectral geostationary satellite imagery was proposed by Olander and Velden (2009). Rouse et al. (1974) calculated a normalized ratio of the near infrared and red bands and proposed an index called the normalized difference vegetation index. It was then used in many fields such as estimations of vegetation biomass, leaf area, the proportion of absorbed photosynthetically active radiation, etc. The present study used the spectral features of the IR1 and WV channels of the satellite to define a new index, the brightness temperature of the infrared window channel minus the brightness temperature of the water vapor channel divided by the brightness temperature of the infrared window channel plus the brightness temperature of the water vapor channel. The values obtained by this formula are called the Normalized Difference Convection Index (NDCI) values. The NDCI value is between -1 and 1. The NDCI value at WV = 0K is the highest, 1; while that at IR1 = 0K is the lowest, -1. In cases of a clear sky or atmosphere with thin cloud and dry air, NDCI values should be larger than 0. In cases of a convective cloud system, NDCI values should be lower than 0. In addition, the newly defined NDCI does show significant difference from simple difference of IR1-WV. For example, the NDCI value is -0.0017 at IR1=299K and WV=300K, while the NDCI value is -0.0033 at IR1=149K and WV=150K. The two times difference of NDCI values shows the features of clouds with NDCI value -0.0017 are quite different from those with NDCI value -0.0033. The former may be low level clouds, but the latter may be deep convections. However, the simple difference of IR1-WV cannot be used to distinguish the difference. The NDCI was applied to determine the centers of Typhoon Longwang (2005). The results showed that the two-dimensional NDCI analysis helped to identify positions of overshooting areas. In addition, because the NDCI values near a typhoon eye were rather significant, if a typhoon eye was formed, the NDCI cross-section analysis could help to confirm its position. When the center of a typhoon was covered by the high Anvils and Cirrus Layers, it could still be found qualitatively through the two-dimensional analysis. Keywords:Typhoon, Satellite imagery, Normalized Difference Convection Index

Normalized burn ratios link fire severity with patterns of avian occurrence

USGS Publications Warehouse

Rose, Eli T.; Simons, Theodore R.; Klein, Rob; McKerrow, Alexa

2016-01-01

ContextRemotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.ObjectivesWe evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.MethodsWe identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.ResultsAgreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.ConclusionsDNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

A fully redundant double difference algorithm for obtaining minimum variance estimates from GPS observations

NASA Technical Reports Server (NTRS)

Melbourne, William G.

1986-01-01

In double differencing a regression system obtained from concurrent Global Positioning System (GPS) observation sequences, one either undersamples the system to avoid introducing colored measurement statistics, or one fully samples the system incurring the resulting non-diagonal covariance matrix for the differenced measurement errors. A suboptimal estimation result will be obtained in the undersampling case and will also be obtained in the fully sampled case unless the color noise statistics are taken into account. The latter approach requires a least squares weighting matrix derived from inversion of a non-diagonal covariance matrix for the differenced measurement errors instead of inversion of the customary diagonal one associated with white noise processes. Presented is the so-called fully redundant double differencing algorithm for generating a weighted double differenced regression system that yields equivalent estimation results, but features for certain cases a diagonal weighting matrix even though the differenced measurement error statistics are highly colored.

Applying Lidar and High-Resolution Multispectral Imagery for Improved Quantification and Mapping of Tundra Vegetation Structure and Distribution in the Alaskan Arctic

NASA Astrophysics Data System (ADS)

Greaves, Heather E.

Climate change is disproportionately affecting high northern latitudes, and the extreme temperatures, remoteness, and sheer size of the Arctic tundra biome have always posed challenges that make application of remote sensing technology especially appropriate. Advances in high-resolution remote sensing continually improve our ability to measure characteristics of tundra vegetation communities, which have been difficult to characterize previously due to their low stature and their distribution in complex, heterogeneous patches across large landscapes. In this work, I apply terrestrial lidar, airborne lidar, and high-resolution airborne multispectral imagery to estimate tundra vegetation characteristics for a research area near Toolik Lake, Alaska. Initially, I explored methods for estimating shrub biomass from terrestrial lidar point clouds, finding that a canopy-volume based algorithm performed best. Although shrub biomass estimates derived from airborne lidar data were less accurate than those from terrestrial lidar data, algorithm parameters used to derive biomass estimates were similar for both datasets. Additionally, I found that airborne lidar-based shrub biomass estimates were just as accurate whether calibrated against terrestrial lidar data or harvested shrub biomass--suggesting that terrestrial lidar potentially could replace destructive biomass harvest. Along with smoothed Normalized Differenced Vegetation Index (NDVI) derived from airborne imagery, airborne lidar-derived canopy volume was an important predictor in a Random Forest model trained to estimate shrub biomass across the 12.5 km2 covered by our lidar and imagery data. The resulting 0.80 m resolution shrub biomass maps should provide important benchmarks for change detection in the Toolik area, especially as deciduous shrubs continue to expand in tundra regions. Finally, I applied 33 lidar- and imagery-derived predictor layers in a validated Random Forest modeling approach to map vegetation community distribution at 20 cm resolution across the data collection area, creating maps that will enable validation of coarser maps, as well as study of fine-scale ecological processes in the area. These projects have pushed the limits of what can be accomplished for vegetation mapping using airborne remote sensing in a challenging but important region; it is my hope that the methods explored here will illuminate potential paths forward as landscapes and technologies inevitably continue to change.

Reducing numerical diffusion for incompressible flow calculations

NASA Technical Reports Server (NTRS)

Claus, R. W.; Neely, G. M.; Syed, S. A.

1984-01-01

A number of approaches for improving the accuracy of incompressible, steady-state flow calculations are examined. Two improved differencing schemes, Quadratic Upstream Interpolation for Convective Kinematics (QUICK) and Skew-Upwind Differencing (SUD), are applied to the convective terms in the Navier-Stokes equations and compared with results obtained using hybrid differencing. In a number of test calculations, it is illustrated that no single scheme exhibits superior performance for all flow situations. However, both SUD and QUICK are shown to be generally more accurate than hybrid differencing.

Post-fire ecosystem recovery trajectories along burn severity gradients

NASA Astrophysics Data System (ADS)

Newingham, B. A.; Hudak, A. T.; Bright, B. C.; Smith, A. G.; Henareh Khalyani, A.

2017-12-01

Burn severity is a term used to describe the longer-term, second-order effects of fire on ecosystems. Plant communities are assumed to recover more slowly at higher burn severities; however, this likely depends on plant community type and climate. We assessed vegetation recovery approximately a decade post-fire across North American forests (moist mixed conifer, dry mixed conifer, ponderosa pine) and shrublands (mountain big sagebrush and Wyoming big sagebrush) distributed across climate and burn severity gradients. We assessed vegetation recovery across these ecosystems as indicated by the differenced Normalized Burn Ratio derived from 1984-2016 Landsat time series imagery (LandTrendr). Additionally, we used field vegetation measurements to examine local topographic controls on burn severity and post-fire vegetation recovery. Ecosystem responses were related to climate predictors derived from downscaled 1993-2011 climate normals. We hypothesized that drier and hotter ecosystems would take longer to recover. We also predicted areas with higher burn severity to have slower recovery. We found post-fire recovery to be strongly predicted by precipitation with the slowest recovery in shrublands and ponderosa pine forest, the driest vegetation types considered. We conclude that climate and burn severity interact to determine ecosystem recovery trajectories after fire, with burn severity having larger influence in the short term, and climate having larger influence in the long term.

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.

The computation of dynamic fractional difference parameter for S&P500 index

NASA Astrophysics Data System (ADS)

Pei, Tan Pei; Cheong, Chin Wen; Galagedera, Don U. A.

2015-10-01

This study evaluates the time-varying long memory behaviors of the S&P500 volatility index using dynamic fractional difference parameters. Time-varying fractional difference parameter shows the dynamic of long memory in volatility series for the pre and post subprime mortgage crisis triggered by U.S. The results find an increasing trend in the S&P500 long memory volatility for the pre-crisis period. However, the onset of Lehman Brothers event reduces the predictability of volatility series following by a slight fluctuation of the factional differencing parameters. After that, the U.S. financial market becomes more informationally efficient and follows a non-stationary random process.

Determination of mangrove change in Matang Mangrove Forest using multi temporal satellite imageries

NASA Astrophysics Data System (ADS)

Ibrahim, N. A.; Mustapha, M. A.; Lihan, T.; Ghaffar, M. A.

2013-11-01

Mangrove protects shorelines from damaging storm and hurricane winds, waves, and floods. Mangroves also help prevent erosion by stabilizing sediments with their tangled root systems. They maintain water quality and clarity, filtering pollutants and trapping sediments originating from land. However, mangrove has been reported to be threatened by land conversion for other activities. In this study, land use and land cover changes in Matang Mangrove Forest during the past 18 years (1993 to 2011) were determined using multi-temporal satellite imageries by Landsat TM and RapidEye. In this study, classification of land use and land cover approach was performed using the maximum likelihood classifier (MCL) method along with vegetation index differencing (NDVI) technique. Data obtained was evaluated through Kappa coefficient calculation for accuracy and results revealed that the classification accuracy was 81.25% with Kappa Statistics of 0.78. The results indicated changes in mangrove forest area to water body with 2,490.6 ha, aquaculture with 890.7 ha, horticulture with 1,646.1 ha, palm oil areas with 1,959.2 ha, dry land forest with 2,906.7 ha and urban settlement area with 224.1 ha. Combinations of these approaches were useful for change detection and for indication of the nature of these changes.

Method and apparatus for rate integration supplement for attitude referencing with quaternion differencing

NASA Technical Reports Server (NTRS)

Rodden, John James (Inventor); Price, Xenophon (Inventor); Carrou, Stephane (Inventor); Stevens, Homer Darling (Inventor)

2002-01-01

A control system for providing attitude control in spacecraft. The control system comprising a primary attitude reference system, a secondary attitude reference system, and a hyper-complex number differencing system. The hyper-complex number differencing system is connectable to the primary attitude reference system and the secondary attitude reference system.

Performance of differenced range data types in Voyager navigation

NASA Technical Reports Server (NTRS)

Taylor, T. H.; Campbell, J. K.; Jacobson, R. A.; Moultrie, B.; Nichols, R. A., Jr.; Riedel, J. E.

1982-01-01

Voyager radio navigation made use of a differenced rage data type for both Saturn encounters because of the low declination singularity of Doppler data. Nearly simultaneous two-way range from two-station baselines was explicitly differenced to produce this data type. Concurrently, a differential VLBI data type (DDOR), utilizing doubly differenced quasar-spacecraft delays, with potentially higher precision was demonstrated. Performance of these data types is investigated on the Jupiter-to-Saturn leg of Voyager 2. The statistics of performance are presented in terms of actual data noise comparisons and sample orbit estimates. Use of DDOR as a primary data type for navigation to Uranus is discussed.

Performance of differenced range data types in Voyager navigation

NASA Technical Reports Server (NTRS)

Taylor, T. H.; Campbell, J. K.; Jacobson, R. A.; Moultrie, B.; Nichols, R. A., Jr.; Riedel, J. E.

1982-01-01

Voyager radio navigation made use of differenced range data type for both Saturn encounters because of the low declination singularity of Doppler data. Nearly simultaneous two-way range from two-station baselines was explicitly differenced to produce this data type. Concurrently, a differential VLBI data type (DDOR), utilizing doubly differenced quasar-spacecraft delays, with potentially higher precision was demonstrated. Performance of these data types is investigated on the Jupiter to Saturn leg of Voyager 2. The statistics of performance are presented in terms of actual data noise comparisons and sample orbit estimates. Use of DDOR as a primary data type for navigation to Uranus is discussed.

Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions

NASA Astrophysics Data System (ADS)

Xie, Qiaoyun; Huang, Wenjiang; Dash, Jadunandan; Song, Xiaoyu; Huang, Linsheng; Zhao, Jinling; Wang, Renhong

2015-12-01

Leaf area index (LAI) is an important indicator for monitoring crop growth conditions and forecasting grain yield. Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques. Spectral vegetation indices, mathematical combination of reflectance bands, are widely used for LAI estimation due to their computational simplicity and their applications ranged from the leaf scale to the entire globe. However, in many cases, their applicability is limited to specific vegetation types or local conditions due to species specific nature of the relationship used to transfer the vegetation indices to LAI. The overall objective of this study is to investigate the most suitable vegetation index for estimating winter wheat LAI under eight different types of fertilizer and irrigation conditions. Regression models were used to estimate LAI using hyperspectral reflectance data from the Pushbroom Hyperspectral Imager (PHI) and in-situ measurements. Our results showed that, among six vegetation indices investigated, the modified soil-adjusted vegetation index (MSAVI) and the normalized difference vegetation index (NDVI) exhibited strong and significant relationships with LAI, and thus were sensitive across different nitrogen and water treatments. The modified triangular vegetation index (MTVI2) confirmed its potential on crop LAI estimation, although second to MSAVI and NDVI in our study. The enhanced vegetation index (EVI) showed moderate performance. However, the ratio vegetation index (RVI) and the modified simple ratio index (MSR) predicted the least accurate estimations of LAI, exposing the simple band ratio index's weakness under different treatment conditions. The results support the use of vegetation indices for a quick and effective LAI mapping procedure that is suitable for winter wheat under different management practices.

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.

Comparison of two satellite imaging platforms for evaluating quasi-circular vegetation patch in the Yellow River Delta, China

NASA Astrophysics Data System (ADS)

Liu, Qingsheng; Liang, Li; Liu, Gaohuan; Huang, Chong

2017-09-01

Vegetation often exists as patch in arid and semi-arid region throughout the world. Vegetation patch can be effectively monitored by remote sensing images. However, not all satellite platforms are suitable to study quasi-circular vegetation patch. This study compares fine (GF-1) and coarse (CBERS-04) resolution platforms, specifically focusing on the quasicircular vegetation patches in the Yellow River Delta (YRD), China. Vegetation patch features (area, shape) were extracted from GF-1 and CBERS-04 imagery using unsupervised classifier (K-Means) and object-oriented approach (Example-based feature extraction with SVM classifier) in order to analyze vegetation patterns. These features were then compared using vector overlay and differencing, and the Root Mean Squared Error (RMSE) was used to determine if the mapped vegetation patches were significantly different. Regardless of K-Means or Example-based feature extraction with SVM classification, it was found that the area of quasi-circular vegetation patches from visual interpretation from QuickBird image (ground truth data) was greater than that from both of GF-1 and CBERS-04, and the number of patches detected from GF-1 data was more than that of CBERS-04 image. It was seen that without expert's experience and professional training on object-oriented approach, K-Means was better than example-based feature extraction with SVM for detecting the patch. It indicated that CBERS-04 could be used to detect the patch with area of more than 300 m2, but GF-1 data was a sufficient source for patch detection in the YRD. However, in the future, finer resolution platforms such as Worldview are needed to gain more detailed insight on patch structures and components and formation mechanism.

Estimating sources of Valley Fever pathogen propagation in southern Arizona: A remote sensing approach

NASA Astrophysics Data System (ADS)

Pianalto, Frederick S.

Coccidioidomycosis (Valley Fever) is an environmentally-mediated respiratory disease caused by the inhalation of airborne spores from the fungi Coccidioides spp. The fungi reside in arid and semi-arid soils of the Americas. The disease has increased epidemically in Arizona and other areas within the last two decades. Despite this increase, the ecology of the fungi remains obscure, and environmental antecedents of the disease are largely unstudied. Two sources of soil disturbance, hypothesized to affect soil ecology and initiate spore dissemination, are investigated. Nocturnal desert rodents interact substantially with the soil substrate. Rodents are hypothesized to act as a reservoir of coccidioidomycosis, a mediator of soil properties, and a disseminator of fungal spores. Rodent distributions are poorly mapped for the study area. We build automated multi-linear regression models and decision tree models for ten rodent species using rodent trapping data from the Organ Pipe Cactus National Monument (ORPI) in southwest Arizona with a combination of surface temperature, a vegetation index and its texture, and a suite of topographic rasters. Surface temperature, derived from Landsat TM thermal images, is the most widely selected predictive variable in both automated methods. Construction-related soil disturbance (e.g. road construction, trenching, land stripping, and earthmoving) is a significant source of fugitive dust, which decreases air quality and may carry soil pathogens. Annual differencing of Landsat Thematic Mapper (TM) mid-infrared images is used to create change images, and thresholded change areas are associated with coordinates of local dust inspections. The output metric identifies source areas of soil disturbance, and it estimates the annual amount of dust-producing surface area for eastern Pima County spanning 1994 through 2009. Spatially explicit construction-related soil disturbance and rodent abundance data are compared with coccidioidomycosis incidence data using rank order correlation and regression methods. Construction-related soil disturbance correlates strongly with annual county-wide incidence. It also correlates with Tucson periphery incidence aggregated to zip codes. Abundance values for the desert pocket mouse (Chaetodipus penicillatus), derived from a soil-adjusted vegetation index, aspect (northing) and thermal radiance, correlate with total study period incidence aggregated to zip code.

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.

Area of vegetation loss: a new index of campsite impact

Treesearch

David N. Cole

1989-01-01

Expressions of the amount of vegetation lost on campsites should reflect both the proportion of vegetation lost and the area1 extent of vegetation loss. A new index-area of vegetation loss-incorporates these two elements by multiplying campsite area by absolute vegetation loss. Guidelines on how to take the measurements needed to calculate this index are provided...

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

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Thurman, S. W.

1992-01-01

An approximate six-parameter analytic model for Earth-based differenced range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 microrad, and angular rate precision on the order of 10 to 25(10)(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wide band and narrow band (delta)VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 /microrad, and angular rate precisions of 0.5 to 1.0(10)(exp -12) rad/sec.

Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies

DTIC Science & Technology

2011-01-01

sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI ), tend to saturate at...little or no improvement over NDVI . Furthermore, indirect ground-sampling techniques often used to evaluate the potential of vegetation indices also...landscapes makes remote sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI

Performance Analysis of Several GPS/Galileo Precise Point Positioning Models

PubMed Central

Afifi, Akram; El-Rabbany, Ahmed

2015-01-01

This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada’s GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference. PMID:26102495

Performance Analysis of Several GPS/Galileo Precise Point Positioning Models.

PubMed

Afifi, Akram; El-Rabbany, Ahmed

2015-06-19

This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada's GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

Orbit determination performances using single- and double-differenced methods: SAC-C and KOMPSAT-2

NASA Astrophysics Data System (ADS)

Hwang, Yoola; Lee, Byoung-Sun; Kim, Haedong; Kim, Jaehoon

2011-01-01

In this paper, Global Positioning System-based (GPS) Orbit Determination (OD) for the KOrea-Multi-Purpose-SATellite (KOMPSAT)-2 using single- and double-differenced methods is studied. The requirement of KOMPSAT-2 orbit accuracy is to allow 1 m positioning error to generate 1-m panchromatic images. KOMPSAT-2 OD is computed using real on-board GPS data. However, the local time of the KOMPSAT-2 GPS receiver is not synchronized with the zero fractional seconds of the GPS time internally, and it continuously drifts according to the pseudorange epochs. In order to resolve this problem, an OD based on single-differenced GPS data from the KOMPSAT-2 uses the tagged time of the GPS receiver, and the accuracy of the OD result is assessed using the overlapping orbit solution between two adjacent days. The clock error of the GPS satellites in the KOMPSAT-2 single-differenced method is corrected using International GNSS Service (IGS) clock information at 5-min intervals. KOMPSAT-2 OD using both double- and single-differenced methods satisfies the requirement of 1-m accuracy in overlapping three dimensional orbit solutions. The results of the SAC-C OD compared with JPL’s POE (Precise Orbit Ephemeris) are also illustrated to demonstrate the implementation of the single- and double-differenced methods using a satellite that has independent orbit information available for validation.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1990-01-01

A process is disclosed for x ray registration and differencing which results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

Digital Data Registration and Differencing Compression System

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1996-01-01

A process for X-ray registration and differencing results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic X-ray digital images.

Deep Learning of Post-Wildfire Vegetation Loss using Bitemporal Synthetic Aperture Radar Images

NASA Astrophysics Data System (ADS)

Chen, Z.; Glasscoe, M. T.; Parker, J. W.

2017-12-01

Wildfire events followed by heavy precipitation have been proven causally related to breakouts of mudflow or debris flow, which, can demand rapid evacuation and threaten residential communities and civil infrastructure. For example, in the case of the city of Glendora, California, it was first afflicted by a severe wildfire in 1968 and then the flooding caused mudslides and debris flow in 1969 killed 34 people. Therefore, burn area or vegetation loss mapping due to wildfire is critical to agencies for preparing for secondary hazards, particularly flooding and flooding induced mudflow. However, rapid post-wildfire mapping of vegetation loss mapping is not readily obtained by regular remote sensing methods, e.g. various optical methods, due to the presence of smoke, haze, and rainy/cloudy conditions that often follow a wildfire event. In this paper, we will introduce and develop a deep learning-based framework that uses Synthetic Aperture Radar images collected prior to and after a wildfire event. A convolutional neural network (CNN) approach will be used that replaces traditional principle component analysis (PCA) based differencing for non-supervised change feature extraction. Using a small sample of human-labeled burned vegetation, normal vegetation, and urban built-up pixels, we will compare the performance of deep learning and PCA-based feature extraction. The 2014 Coby Fire event, which affected the downstream city of Glendora, was used to evaluate the proposed framework. The NASA's UAVSAR data (https://uavsar.jpl.nasa.gov/) will be utilized for mapping the vegetation damage due to the Coby Fire event.

Effectiveness of Vegetation Index Transformation for Land Use Identifying and Mapping in the Area of Oil palm Plantation based on SPOT-6 Imagery (Case Study: PT.Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu)

NASA Astrophysics Data System (ADS)

Setyowati, H. A.; S, S. H. Murti B.; Sukentyas, E. S.

2016-11-01

The reflection of land surface, atmosphere and vegetation conditions affect the reflectance value of the object is recorded on remote sensing image so that it can affect the outcome of information extraction from remote sensing imagery one multispectral classification. This study aims to assess the ability of the transformation of generic vegetation index (Wide Dynamic Range Vegetation Index), the vegetation index transformation that is capable reducing the influence of the atmosphere (Atmospherically Resistant Vegetation Index), and the transformation of vegetation index that is capable of reducing the influence of the background soil (Second Modified Soil Adjusted Vegetation Index) for the identification and mapping of land use in the oil palm plantation area based on SPOT-6 archived on June 13, 2013 from LAPAN. The study area selected oil palm plantations PT. Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu, Riau Province. The method is using the transformation of the vegetation index ARVI, MSAVI2, and WDRVI. Sample selection method used was stratified random sampling. The test method used mapping accuracy of the confusion matrix. The results showed that the best transformation of the vegetation index for the identification and mapping of land use in the plantation area is ARVI transformation with a total of accuracy is 96%. Accuracy of mapping land use settlements 100%, replanting 82.35%, 81.25% young oil palm, old oil palm 99.46%, 100% bush, body of water 100%, and 100% bare-soil.

Monitoring change in mountainous dry-heath vegetation at a regional scale using multitemporal Landsat TM data.

PubMed

Nordberg, Maj-Liz; Evertson, Joakim

2003-12-01

Vegetation cover-change analysis requires selection of an appropriate set of variables for measuring and characterizing change. Satellite sensors like Landsat TM offer the advantages of wide spatial coverage while providing land-cover information. This facilitates the monitoring of surface processes. This study discusses change detection in mountainous dry-heath communities in Jämtland County, Sweden, using satellite data. Landsat-5 TM and Landsat-7 ETM+ data from 1984, 1994 and 2000, respectively, were used. Different change detection methods were compared after the images had been radiometrically normalized, georeferenced and corrected for topographic effects. For detection of the classes change--no change the NDVI image differencing method was the most accurate with an overall accuracy of 94% (K = 0.87). Additional change information was extracted from an alternative method called NDVI regression analysis and vegetation change in 3 categories within mountainous dry-heath communities were detected. By applying a fuzzy set thresholding technique the overall accuracy was improved from of 65% (K = 0.45) to 74% (K = 0.59). The methods used generate a change product showing the location of changed areas in sensitive mountainous heath communities, and it also indicates the extent of the change (high, moderate and unchanged vegetation cover decrease). A total of 17% of the dry and extremely dry-heath vegetation within the study area has changed between 1984 and 2000. On average 4% of the studied heath communities have been classified as high change, i.e. have experienced "high vegetation cover decrease" during the period. The results show that the low alpine zone of the southern part of the study area shows the highest amount of "high vegetation cover decrease". The results also show that the main change occurred between 1994 and 2000.

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...

Study of vegetation cover distribution using DVI, PVI, WDVI indices with 2D-space plot

NASA Astrophysics Data System (ADS)

Naji, Taghreed A. H.

2018-05-01

The present work aims to study the effect of using vegetation indices technique on image segmentation for subdividing an image into the homogeneous regions. Three of these vegetation indices technique has been adopted (i.e. Difference Vegetation-Index (DVI), Perpendicular Vegetation Index (PVI) and Weighted Difference Vegetation Index (WDVI)) for detecting and monitoring vegetation distribution and healthiness. Image binarization method being followed the implementation of the indices to isolating the vegetation areas from the image background. The separated agriculture regions from other land use regions and their percentages are presented for two years (2001 and 2002) of the (ETM+) scenes. The counted areas resulted from 2D-space plot technique and the separated vegetated areas resulted from the using of the vegetation indices are also presented. The separated agriculture regions from the implementation of the DVI-index have proved better than other used indices. Because it showed better coincident approximately with 2D-space plot segmentation.

Interferometric observations of an artificial satellite.

PubMed

Preston, R A; Ergas, R; Hinteregger, H F; Knight, C A; Robertson, D S; Shapiro, I I; Whitney, A R; Rogers, A E; Clark, T A

1972-10-27

Very-long-baseline interferometric observations of radio signals from the TACSAT synchronous satellite, even though extending over only 7 hours, have enabled an excellent orbit to be deduced. Precision in differenced delay and delay-rate measurements reached 0.15 nanosecond ( approximately 5 centimeters in equivalent differenced distance) and 0.05 picosecond per second ( approximately 0.002 centimeter per second in equivalent differenced velocity), respectively. The results from this initial three-station experiment demonstrate the feasibility of using the method for accurate satellite tracking and for geodesy. Comparisons are made with other techniques.

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.

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.

ESTCP Pilot Project Wide Area Assessment for Munitions Response

DTIC Science & Technology

2008-07-01

Data A broadband normalized difference vegetation index ( NDVI ) was computed from the high- resolution spectral data to provide a detection of canopy...chlorophyll content. The NDVI strongly correlates with the green yucca, cactus, juniper, and other SAR-responsive vegetation species on the site...Vegetation Index. NDVI is broadband normalized difference vegetation index computed from high resolution spectral data using (RED-NIR) / (RED +NIR) to

Soil-vegetation correlations in the Connecticut River floodplain of Western Massachusetts

USGS Publications Warehouse

Veneman, Peter L.M.; Tiner, Ralph W.

1990-01-01

As part of a national study analyzing the relation between hydric soils and wetland vegetation, the vegetation associated with a series of known soils was sampled along the Connecticut River floodplain in Massachusetts. Weighted average and index average (presence/absence) values were calculated for vegetation using wetland ecological index values from the National List of Plant Species that Occur in Wetlands developed by the U.S. Fish and Wildlife Service and procedures developed by T. R. Wentworth and G. P. Johnson at North Carolina State University. Good correspondence between soils and vegetation was recorded with two exceptions. Two typically nonhydric soils were determined to be hydric based on vegetation analyses. Examination of the groundwater hydrology of these two soils confirmed their hydric nature. The authors suggested that one of these soils may need to be redefined and they also suggested that the assigned index values for a few species of vegetation should be reexamined. However, in general the index average values of vegetation based on published wetland index values corresponded with the hydric and nonhydric nature of soils.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Pump-probe differencing technique for cavity-enhanced, noise-canceling saturation laser spectroscopy.

PubMed

de Vine, Glenn; McClelland, David E; Gray, Malcolm B; Close, John D

2005-05-15

We present an experimental technique that permits mechanical-noise-free, cavity-enhanced frequency measurements of an atomic transition and its hyperfine structure. We employ the 532-nm frequency-doubled output from a Nd:YAG laser and an iodine vapor cell. The cell is placed in a folded ring cavity (FRC) with counterpropagating pump and probe beams. The FRC is locked with the Pound-Drever-Hall technique. Mechanical noise is rejected by differencing the pump and probe signals. In addition, this differenced error signal provides a sensitive measure of differential nonlinearity within the FRC.

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Thurman, S. W.

1992-01-01

An approximate six-parameter analytic model for Earth-based differential range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 micro-rad, and angular rate precision on the order of 10 to 25 x 10(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wideband and narrowband (delta) VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 micro-rad, and angular rate precisions of 0.5 to 1.0 x 10(exp -12) rad/sec.

Phenology Analysis of Forest Vegetation to Environmental Variables during - and Post-Monsoon Seasons in Western Himalayan Region of India

NASA Astrophysics Data System (ADS)

Khare, S.; Latifi, H.; Ghosh, K.

2016-06-01

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVIchange) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVIchange values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVIchange between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous forests could be explained.

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.

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/

[Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

PubMed

Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

2011-02-01

Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural vegetation showed the strongest correlation with drought index. There existed definite correlations among the climatic factors. If the correlations among the climatic factors were ignored, the significant level of the correlations between NDVI and climatic factors would be somewhat reduced.

Towards the Mitigation of Correlation Effects in the Analysis of Hyperspectral Imagery with Extensions to Robust Parameter Design

DTIC Science & Technology

2012-08-01

Difference Vegetation Index ( NDVI ) ..................................... 15  2.3  Methodology...Atmospheric Compensation ........................................................................ 31  3.2.3.1  Normalized Difference Vegetation Index ( NDVI ...anomaly detection algorithms are contrasted and implemented, and explains the use of the Normalized Difference Vegetation Index ( NDVI ) in post

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

Space Monitoring of urban sprawl

NASA Astrophysics Data System (ADS)

Nole, G.; Lanorte, A.; Murgante, B.; Lasaponara, R.

2012-04-01

Space Monitoring of urban sprawl Gabriele Nolè (1,2), Antonio Lanorte (1), , Beniamino Murgante (2) and Rosa Lasaponara (1) , (1,2) Institute of Methodologies for Environmental Analysis, National Research Council, Italy (2) Laboratory of Urban and Territorial Systems, University of Basilicata, During the last few decades, in many regions throughout the world abandonment of agricultural land has induced a high concentration of people in densely populated urban areas. The deep social, economic and environmental changes have caused strong and extensive land cover changes. This is regarded as a pressing issue that calls for a clear understanding of the ongoing trends and future urban expansion. The main issue of great importance in modelling urban growth includes spatial and temporal dynamics, scale dynamics, man-induced land use changes. Although urban growth is perceived as necessary for a sustainable economy, uncontrolled or sprawling urban growth can cause various problems, such as, the loss of open space, landscape alteration, environmental pollution, traffic congestion, infrastructure pressure, and other social and economical issues. To face these drawbacks, a continuous monitoring of the urban growth evolution in terms of type and extent of changes over time are essential for supporting planners and decision makers in future urban planning. A critical point for the understanding and monitoring urban expansion processes is the availability of both (i) time-series data set and (ii) updated information relating to the current urban spatial structure a to define and locate the evolution trends. In such a context, an effective contribution can be offered by satellite remote sensing technologies, which are able to provide both historical data archive and up-to-date imagery. Satellite technologies represent a cost-effective mean for obtaining useful data that can be easily and systematically updated for the whole globe. Nowadays medium resolution satellite images, such as Landsat TM or ASTER can be downloaded free of charge from the NASA web site. The use of satellite imagery along with robust data analysis techniques can be used for the monitoring and planning purposes as these enable the reporting of ongoing trends of urban growth at a detailed level. Nevertheless, the exploitation of satellite Earth Observation in the field of the urban growth monitoring is a relatively new tool, although during the last three decades great efforts have been addressed to the application of remote sensing in detecting land use and land cover changes using a number of data analyses, such as: (i) Spectral enhancement based on vegetation index differencing, principal component analysis, Image differencing and visual interpretation and/or classification, (ii) post-classification change differencing and a combination of image enhancement and post-classification comparison, (iii) mixture analysis, (iv) artificial neural networks, (v) landscape metrics (patchiness and map density) and (vi) the integration of geographical information system and remote sensing data. In this paper a comparison of the methods listed before is carried out using satellite time series made up of Landsat MSS, TM, ETM+ASTER for some test areas selected in South of Italy and Cairo in order to extract and quantify urban sprawl and its spatial and temporal feature patterns.

Evaluating channel morphologic changes and bed-material transport using airborne lidar, upper Colorado River, Rocky Mountain National Park, Colorado

NASA Astrophysics Data System (ADS)

Mangano, Joseph F.

A debris flow associated with the 2003 breach of Grand Ditch in Rocky Mountain National Park, Colorado provided an opportunity to determine controls on channel geomorphic responses following a large sedimentation event. Due to the remote site location and high spatial and temporal variability of processes controlling channel response, repeat airborne lidar surveys in 2004 and 2012 were used to capture conditions along the upper Colorado River and tributary Lulu Creek i) one year following the initial debris flow, and ii) following two bankfull flows (2009 and 2010) and a record-breaking long duration, high intensity snowmelt runoff season (2011). Locations and volumes of aggradation and degradation were determined using lidar differencing. Channel and valley metrics measured from the lidar surveys included water surface slope, valley slope, changes in bankfull width, sinuosity, braiding index, channel migration, valley confinement, height above the water surface along the floodplain, and longitudinal profiles. Reaches of aggradation and degradation along the upper Colorado River are influenced by valley confinement and local controls. Aggradational reaches occurred predominantly in locations where the valley was unconfined and valley slope remained constant through the length of the reach. Channel avulsions, migration, and changes in sinuosity were common in all unconfined reaches, whether aggradational or degradational. Bankfull width in both aggradational and degradational reaches showed greater changes closer to the sediment source, with the magnitude of change decreasing downstream. Local variations in channel morphology, site specific channel conditions, and the distance from the sediment source influence the balance of transport supply and capacity and, therefore, locations of aggradation, degradation, and associated morphologic changes. Additionally, a complex response initially seen in repeat cross-sections is broadly supported by lidar differencing, although the differencing captures only the net change over eight years and not annual changes. Lidar differencing shows great promise because it reveals vertical and horizontal trends in morphologic changes at a high resolution over a large area. Repeat lidar surveys were also used to create a sediment budget along the upper Colorado River by means of the morphologic inverse method. In addition to the geomorphic changes detected by lidar, several levels of attrition of the weak clasts within debris flow sediment were applied to the sediment budget to reduce gaps in expected inputs and outputs. Bed-material estimates using the morphologic inverse method were greater than field-measured transport estimates, but the two were within an order of magnitude. Field measurements and observations are critical for robust interpretation of the lidar-based analyses because applying lidar differencing without field control may not identify local controls on valley and channel geometry and sediment characteristics. The final sediment budget helps define variability in bed-material transport and constrain transport rates through the site, which will be beneficial for restoration planning. The morphologic inverse method approach using repeat lidar surveys appears promising, especially if lidar resolution is similar between sequential surveys.

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...

Basic research for the Earth dynamics program

NASA Technical Reports Server (NTRS)

1981-01-01

The technique of range differencing with Lageos ranges to obtain more accurate estimates of baseline lengths and polar motion variation was studied. Differencing quasi simultaneous range observations eliminate a great deal of orbital biases. Progress is reported on the definition and maintenance of a conventional terrestrial reference system.

RESULTS FROM KINEROS STREAM CHANNEL ELEMENTS MODEL OUTPUT THROUGH AGWA DIFFERENCING 1973 AND 1997 NALC LANDCOVER DATA

EPA Science Inventory

Results from differencing KINEROS model output through AGWA for Sierra Vista subwatershed. Percent change between 1973 and 1997 is presented for all KINEROS output values (and some derived from the KINEROS output by AGWA) for the stream channels.

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.

Monitoring Drought at Continental Scales Using Thermal Remote Sensing of Evapotranspiration (Invited)

NASA Astrophysics Data System (ADS)

Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.

2009-12-01

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for assessing standard meteorologically-based drought indicators, and may be more robust in regions with limited monitoring networks. In this study, monthly maps of ESI anomalies for 2000-2008 are compared to standard drought indices and to drought classifications in the U.S. Drought Monitor. The ESI shows better skill in ranking drought severity than do precipitation-based indices composited over comparable time intervals. The thermal remote sensing inputs to ALEXI detect drought conditions even under the dense forest cover along the East Coast of the United States, where microwave soil moisture retrievals typically lose sensitivity. On the other hand, microwave observations are not constrained by cloud cover and provide better temporal continuity, but typically at significantly lower spatial resolution. A merged TIR-microwave moisture anomaly product may have potential for optimizing both spatial and temporal coverage in continental-scale drought monitoring.

CINDA-3G: Improved Numerical Differencing Analyzer Program for Third-Generation Computers

NASA Technical Reports Server (NTRS)

Gaski, J. D.; Lewis, D. R.; Thompson, L. R.

1970-01-01

The goal of this work was to develop a new and versatile program to supplement or replace the original Chrysler Improved Numerical Differencing Analyzer (CINDA) thermal analyzer program in order to take advantage of the improved systems software and machine speeds of the third-generation computers.

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.

Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

NASA Astrophysics Data System (ADS)

Cheong, Chin Wen

2008-02-01

This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

Comparison of the New LEAF Area INDEX (LAI 3G) with the Kazahstan-Wide LEAF Area INDEX DATA SET (GGRS-LAI) over Central ASIA

NASA Astrophysics Data System (ADS)

Kappas, M.; Propastin, P.; Degener, J.; Renchin, T.

2014-12-01

Long-term global data sets of Leaf Area Index (LAI) are important for monitoring global vegetation dynamics. LAI indicating phenological development of vegetation is an important state variable for modeling land surface processes. The comparison of long-term data sets is based on two recently available data sets both derived from AVHRR time series. The LAI 3g data set introduced by Zaichun Zhu et al. (2013) is developed from the new improved third generation Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) and best-quality MODIS LAI data. The second long-term data set is based on the 8 km spatial resolution GIMMS-AVHRR data (GGRS-data set by Propastin et al. 2012). The GGRS-LAI product uses a three-dimensional physical radiative transfer model which establishes relationship between LAI, vegetation fractional cover and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. The model incorporates a number of site/region specific parameters, including the vegetation architecture variables such as leaf angle distribution, clumping index, and light extinction coefficient. For the application of the model to Kazakhstan, the vegetation architecture variables were computed at the local (pixel) level based on extensive field surveys of the biophysical properties of vegetation in representative grassland areas of Kazakhstan. The comparison of both long-term data sets will be used to interpret their quality for scientific research in other disciplines. References:Propastin, P., Kappas, M. (2012). Retrieval of coarse-resolution leaf area index over the Republic of Kazakhstan using NOAA AVHRR satellite data and ground measurements," Remote Sensing, vol. 4, no. 1, pp. 220-246. Zaichun Zhu, Jian Bi, Yaozhong Pan, Sangram Ganguly, Alessandro Anav, Liang Xu, Arindam Samanta, Shilong Piao, Ramakrishna R. Nemani and Ranga B. Myneni (2013). Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011. Remote Sens. 2013, 5, 927-948; doi:10.3390/rs5020927

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1992-01-01

A process for x ray registration and differencing results in more efficient compression is discussed. Differencing of registered modeled subject image with a modeled reference image forms a differential image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three dimensional model, which three dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

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.

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Shen, Sunhung; Leptoukh, Gregory G.; Gerasimov, Irina

2012-01-01

Vegetation growth depends on local climate. Significant anthropogenic land cover and land use change activities over Asia have changed vegetation distribution as well. On the other hand, vegetation is one of the important land surface variables that influence the Asian Monsoon variability through controlling atmospheric energy and water vapor conditions. In this presentation, the mean and variations of vegetation index of last decade at regional scale resolution (5km and higher) from MODIS have been analyzed. Results indicate that the vegetation index has been reduced significantly during last decade over fast urbanization areas in east China, such as Yangtze River Delta, where local surface temperatures were increased significantly in term of urban heat Island. The relationship between vegetation Index and climate (surface temperature, precipitation) over a grassland in northern Asia and over a woody savannas in southeast Asia are studied. In supporting Monsoon Asian Integrated Regional Study (MAIRS) program, the data in this study have been integrated into Giovanni, the online visualization and analysis system at NASA GES DISC. Most images in this presentation are generated from Giovanni system.

Assessment of Tibetan grassland degeneration via landscape analysis

NASA Astrophysics Data System (ADS)

Sun, Jian; Hou, Ge; Ma, Baibing; Zang, Wenqian

2017-04-01

Desertification as one of the most severity social-economic-environmental issues has been extensive researched, and the assessments of desertification can be implemented accurately and efficiently based on the landscape indicators of vegetation coverage. Consequently, we explored the relationships of the degeneration index of the grassland with climate factors (temperature and precipitation), and human disturbance factors (livestock quantity and animal husbandry output value) via a landscape assessment approach across Tibet. The results showed that the vegetation coverage presented an increase tendency in the central region of Tibet, but the adverse phenomenon was observed in the northwest region. Meanwhile, the correlation of vegetation coverage with precipitation presented as positive effect in most region of Tibet except some regions of the alpine steppe, and the positive correlation of vegetation coverage with temperature also was observed in the less northwest region of Tibet. In addition, we found that the livestock quantity play a key roles in regulating vegetation coverage of the central region. Furthermore, the landscape indexes [number of patches (NP), patch density (PD), contagion index (CONTAG), landscape shape index (LSI), aggregation index (AI)] of grasslands were analyzed, the results exposed that vegetation coverage (1%-20%) has the positive influences on CONTAG and AI, but negative affects LSI, PD and NP. Morreover, there are opposite correlations among vegetation coverage and landscape indexes when vegetation coverage is 21%-40%. We concluded that overgrazing is the main reason of grassland degradation in Tibet, especially the number of livestock aggravates the landscape fragmentation. The results highlighted the alpine grassland management in future.

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre

2014-05-01

Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as the water shortage can be sensed several weeks before the vegetation dryness occures. Keywords: SMOS, microwave, level 4, soil moisture, drought, precipitation, hydrological model, vegetation index

Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

NASA Astrophysics Data System (ADS)

Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

2017-04-01

The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already operational SNPP VIIRS Green Vegetation Fraction (GVF) global gridded 4km resolution. The ultimate goal is a global consistent set of global gridded land products at 1-km resolution to enable consistent use of the products in the full suite of global and regional NCEP land models. The new JPSS vegetation products system is scheduled to transition to operations in the fall of 2017.

Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.

1988-01-01

Weekly AVHRR Normalized Difference Vegetation Index (NDVI) values for 1983-1984 for seven sites of diverse climate in North America were correlated with results of an ecosystem simulation model of a hypothetical forest stand for the corresponding period at each site. The tendency of raw NDVI data to overpredict photosynthesis and transpiration on water limited sites was shown to be partially corrected by using an aridity index of annual radiation/annual precipitation. The results suggest that estimates of vegetation productivity using the global vegetation index are only accurate as annual integrations, unless unsubsampled local area coverage NDVI data can be tested against forest photosynthesis, transpiration and aboveground net primary production data measured at shorter time intervals.

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

Analysis of the spatial-temporal change and impact factors of the vegetation index in Yulin of China: the effect of forest conservation and grain for green

NASA Astrophysics Data System (ADS)

Liu, D.; Luan, J.; Lin, M.; Huang, Q.

2017-12-01

Since 1999, China began the Grain for Green program to conserve the forest in the north of China. After 17 years, the vegetation in the north has changed. Vegetation index is an important method to study the regional vegetation change. This study is based on MODIS/Terra NDVI remote sensing data, and analyzes the spatial-temporal changes and the impact factors of the NDVI in August from 2000 to 2016 at pixel scale in Yulin City of Shaanxi Province in China. The results showed that, on about 96.44% of the region in the Yulin city, vegetation index increased, and the area with increasing NDVI between 0-0.02/a accounts for 93.63% of Yulin city. The area with significant increasing trend accounts for 80.72%. The complex linear regression analysis showed that, the meteorological factors play a positive role in the growth and evolution of vegetation, and human activities also make the vegetation index become more uniform. The area, where the human activities restrain the growth and evolution of the vegetation, is 45.04% of the Yulin area. It is mainly distributed in Fugu County which located in the north of Yulin, and most areas of southern and western parts of Yulin. The area where human activities promote the increase of the vegetation index, accounted for 54.96% of the Yulin area, which indicated that on more than half of the region, human activities have played a positive role in the growth of vegetation. In these areas, the effect of forest conservation, and grain for green (i.e. returning farmland to forests, and returning pasturage to natural grassland) is better.

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

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.

[Remote sensing detection of vegetation health status after ecological restoration in soil and water loss region].

PubMed

Hu, Xiu Juan; Xu, Han Qiu; Guo, Yan Bin; Zhang, Bo Bo

2017-01-01

This paper proposed a vegetation health index (VHI) to rapidly monitor and assess vegetation health status in soil and water loss region based on remote sensing techniques and WorldView-2 imagery. VHI was constructed by three factors, i.e., the normalized mountain vegetation index, the nitrogen reflectance index and the reflectance of the yellow band, through the principal component transformation, in order to avoid the deviation induced by subjective method of weighted summation. The Hetian Basin of Changting County in Fujian Province, China, was taken as a test area to assess the vegetation health status in soil and water loss region using VHI. The results showed that the VHI could detect vegetation health status with a total accuracy of 91%. The vegetation of Hetian Basin in good, moderate and poor health status accounted for 10.1%, 49.2% and 40.7%, respectively. The vegetation of the study area was still under an unhealthy status because the soil was poor and the growth of newly planted vegetation was not good in the soil and water loss region.

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.

Application of non-coherent Doppler data types for deep space navigation

NASA Technical Reports Server (NTRS)

Bhaskaran, Shyam

1995-01-01

Recent improvements in computational capability and Deep Space Network technology have renewed interest in examining the possibility of using one-way Doppler data alone to navigate interplanetary spacecraft. The one-way data can be formulated as the standard differenced-count Doppler or as phase measurements, and the data can be received at a single station or differenced if obtained simultaneously at two stations. A covariance analysis is performed which analyzes the accuracy obtainable by combinations of one-way Doppler data and compared with similar results using standard two-way Doppler and range. The sample interplanetary trajectory used was that of the Mars Pathfinder mission to Mars. It is shown that differenced one-way data is capable of determining the angular position of the spacecraft to fairly high accuracy, but has relatively poor sensitivity to the range. When combined with single station data, the position dispersions are roughly an order of magnitude larger in range and comparable in angular position as compared to dispersions obtained with standard data two-way types. It was also found that the phase formulation is less sensitive to data weight variations and data coverage than the differenced-count Doppler formulation.

The application of noncoherent Doppler data types for Deep Space Navigation

NASA Technical Reports Server (NTRS)

Bhaskaran, S.

1995-01-01

Recent improvements in computational capability and DSN technology have renewed interest in examining the possibility of using one-way Doppler data alone to navigate interplanetary spacecraft. The one-way data can be formulated as the standard differenced-count Doppler or as phase measurements, and the data can be received at a single station or differenced if obtained simultaneously at two stations. A covariance analysis, which analyzes the accuracy obtainable by combinations of one-way Doppler data, is performed and compared with similar results using standard two-way Doppler and range. The sample interplanetary trajectory used was that of the Mars Pathfinder mission to Mars. It is shown that differenced one-way data are capable of determining the angular position of the spacecraft to fairly high accuracy, but have relatively poor sensitivity to the range. When combined with single-station data, the position dispersions are roughly an order of magnitude larger in range and comparable in angular position as compared to dispersions obtained with standard two-way data types. It was also found that the phase formulation is less sensitive to data weight variations and data coverage than the differenced-count Doppler formulation.

An Assessment of Normalized Difference Skin Index Robustness in Aquatic Environments

DTIC Science & Technology

2014-03-27

Index NDSI Normalized Difference Skin Index NDVI Normalized Difference Vegetation Index NIR Near-Infrared SAR Search and Rescue SERG Sensors... Vegetation and water-bearing objects with high scatter tend to have NDSI values similar to human skin , potentially causing false positives in certain...AN ASSESSMENT OF NORMALIZED DIFFERENCE SKIN INDEX ROBUSTNESS IN AQUATIC ENVIRONMENTS THESIS Alice W. Chan, First Lieutenant, USAF AFIT-ENG-14-M-17

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

NASA Technical Reports Server (NTRS)

Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

1989-01-01

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

Satellite assessment of early-season forecasts for vegetation conditions of grazing allotments in Nevada, United States

USDA-ARS?s Scientific Manuscript database

Fifteen years of enhanced vegetation index data from the MODIS sensor are examined in conjunction with precipitation and the Palmer drought severity index to assess how well growing season conditions for vegetation within grazing allotments of Nevada can be predicted at different times of the year. ...

Finite difference methods for reducing numerical diffusion in TEACH-type calculations. [Teaching Elliptic Axisymmetric Characteristics Heuristically

NASA Technical Reports Server (NTRS)

Syed, S. A.; Chiappetta, L. M.

1985-01-01

A methodological evaluation for two-finite differencing schemes for computer-aided gas turbine design is presented. The two computational schemes include; a Bounded Skewed Finite Differencing Scheme (BSUDS); and a Quadratic Upwind Differencing Scheme (QSDS). In the evaluation, the derivations of the schemes were incorporated into two-dimensional and three-dimensional versions of the Teaching Axisymmetric Characteristics Heuristically (TEACH) computer code. Assessments were made according to performance criteria for the solution of problems of turbulent, laminar, and coannular turbulent flow. The specific performance criteria used in the evaluation were simplicity, accuracy, and computational economy. It is found that the BSUDS scheme performed better with respect to the criteria than the QUDS. Some of the reasons for the more successful performance BSUDS are discussed.

Path length differencing and energy conservation of the S[sub N] Boltzmann/Spencer-Lewis equation

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

Filippone, W.L.; Monahan, S.P.

It is shown that the S[sub N] Boltzmann/Spencer-Lewis equations conserve energy locally if and only if they satisfy particle balance and diamond differencing is used in path length. In contrast, the spatial differencing schemes have no bearing on the energy balance. Energy is conserved globally if it is conserved locally and the multigroup cross sections are energy conserving. Although the coupled electron-photon cross sections generated by CEPXS conserve particles and charge, they do not precisely conserve energy. It is demonstrated that these cross sections can be adjusted such that particles, charge, and energy are conserved. Finally, since a conventional negativemore » flux fixup destroys energy balance when applied to path legend, a modified fixup scheme that does not is presented.« less

Non-oscillatory central differencing for hyperbolic conservation laws

NASA Technical Reports Server (NTRS)

Nessyahu, Haim; Tadmor, Eitan

1988-01-01

Many of the recently developed high resolution schemes for hyperbolic conservation laws are based on upwind differencing. The building block for these schemes is the averaging of an appropriate Godunov solver; its time consuming part involves the field-by-field decomposition which is required in order to identify the direction of the wind. Instead, the use of the more robust Lax-Friedrichs (LxF) solver is proposed. The main advantage is simplicity: no Riemann problems are solved and hence field-by-field decompositions are avoided. The main disadvantage is the excessive numerical viscosity typical to the LxF solver. This is compensated for by using high-resolution MUSCL-type interpolants. Numerical experiments show that the quality of results obtained by such convenient central differencing is comparable with those of the upwind schemes.

White vegetables: glycemia and satiety.

PubMed

Anderson, G Harvey; Soeandy, Chesarahmia Dojo; Smith, Christopher E

2013-05-01

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance.

A Rapidly Prototyped Vegetation Dryness Index Developed for Wildfire Risk Assessment at Stennis Space Center

NASA Technical Reports Server (NTRS)

Ross, Kenton; Graham, William D.; Prados, Donald; Spruce, Joseph

2006-01-01

A remote sensing index was developed to allow improved monitoring of vegetation dryness conditions on a regional basis. This remote sensing index was rapidly prototyped at Stennis Space Center in response to drought conditions in the local area in spring 2006.

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.

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.

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

Adjusting Spectral Indices for Spectral Response Function Differences of Very High Spatial Resolution Sensors Simulated from Field Spectra

PubMed Central

Cundill, Sharon L.; van der Werff, Harald M. A.; van der Meijde, Mark

2015-01-01

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices’ values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important. PMID:25781511

Analyzing Hydro-Geomorphic Responses in Post-Fire Stream Channels with Terrestrial LiDAR

NASA Astrophysics Data System (ADS)

Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

2015-12-01

Wildfires have potential to significantly alter soil properties and vegetation within watersheds. These alterations often contribute to accelerated erosion, runoff, and sediment transport in stream channels and hillslopes. This research applies repeated Terrestrial Laser Scanning (TLS) Light Detection and Ranging (LiDAR) to stream reaches within the Pike National Forest in Colorado following the 2012 Waldo Canyon Fire. These scans allow investigation of the relationship between sediment delivery and environmental characteristics such as precipitation, soil burn severity, and vegetation. Post-fire LiDAR images provide high resolution information of stream channel changes in eight reaches for three years (2012-2014). All images are processed with RiSCAN PRO to remove vegetation and triangulated and smoothed to create a Digital Elevation Model (DEM) with 0.1 m resolution. Study reaches with two or more successive DEM images are compared using a differencing method to estimate the volume of sediment erosion and deposition. Preliminary analysis of four channel reaches within Williams Canyon and Camp Creek yielded erosion estimates between 0.035 and 0.618 m3 per unit area. Deposition was estimated as 0.365 to 1.67 m3 per unit area. Reaches that experienced higher soil burn severity or larger rainfall events produced the greatest geomorphic changes. Results from LiDAR analyses can be incorporated into post-fire hydrologic models to improve estimates of runoff and sediment yield. These models will, in turn, provide guidance for water resources management and downstream hazards mitigation.

Postfire soil burn severity mapping with hyperspectral image unmixing

USGS Publications Warehouse

Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events

USDA-ARS?s Scientific Manuscript database

Drought poses significant water and food security concerns in many parts of the world and can lead to negative agricultural, economic, and environmental impacts. The Vegetation Drought Response Index (VegDRI) approach has the flexibility to be adapted for other regions of the world using the climate...

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

USGS Publications Warehouse

Kim, Jin-Woo; Lu, Zhong; Jones, John W.; Shum, C.K.; Lee, Hyongki; Jia, Yuanyuan

2014-01-01

The Florida Everglades plays a significant role in controlling floods, improving water quality, supporting ecosystems, and maintaining biodiversity in south Florida. Adaptive restoration and management of the Everglades requires the best information possible regarding wetland hydrology. We developed a new and innovative approach to quantify spatial and temporal variations in wetland water levels within the Everglades, Florida. We observed high correlations between water level measured at in situ gages and L-band SAR backscatter coefficients in the freshwater marsh, though C-band SAR backscatter has no close relationship with water level. Here we illustrate the complementarity of SAR backscatter coefficient differencing and interferometry (InSAR) for improved estimation of high spatial resolution water level variations in the Everglades. This technique has a certain limitation in applying to swamp forests with dense vegetation cover, but we conclude that this new method is promising in future applications to wetland hydrology research.

Integrating reconstructed scatterometer and advanced very high resolution radiometer data for tropical forest inventory

NASA Astrophysics Data System (ADS)

Hardin, Perry J.; Long, David G.

1995-11-01

A scientific effort is currently underway to assess tropical forest degradation and its potential impact on Earth's climate. Because of the large continental regions involved, Advanced Very High Resolution Radiometer (AVHRR) imagery and its derivative vegetation index products with resolutions between 1 and 12 km are typically used to inventory the Earth's equatorial vegetation. Archival AVHRR imagery is also used to obtain a temporal baseline of historical forest extent. Recently however, 50-km Seasat-A Scatterometer (SASS) Ku-band imagery (acquired in 1978) has been reconstructed to approximately equals 4-km resolution, making it a supplement to AVHRR imagery for historical vegetation assessment. In order to test the utility of reconstructed Ku-band scatterometer imagery for this purpose, seasonal AVHRR vegetation index and SASS images of identical resolutions were constructed. Using the imagery, discrimination experiments involving 18 vegetation categories were conducted for a central South America study area. The results of these experiments indicate that AVHRR vegetation- index images are slightly superior to reconstructed SASS images for differentiating between equatorial vegetation classes when used alone. However, combining the scatterometer imagery with the vegetation-index images provides discrimination superior to any other combination of the data sets. Using the two data sets together, 90.3% of the test data could be correctly classified into broad classes of equatorial forest, degraded woodland/forest, woodland/savanna, and caatinga.

Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-density Cypress Forest.

PubMed

Matsushita, Bunkei; Yang, Wei; Chen, Jin; Onda, Yuyichi; Qiu, Guoyu

2007-11-05

Vegetation indices play an important role in monitoring variations in vegetation.The Enhanced Vegetation Index (EVI) proposed by the MODIS Land Discipline Groupand the Normalized Difference Vegetation Index (NDVI) are both global-based vegetationindices aimed at providing consistent spatial and temporal information regarding globalvegetation. However, many environmental factors such as atmospheric conditions and soilbackground may produce errors in these indices. The topographic effect is another veryimportant factor, especially when the indices are used in areas of rough terrain. In thispaper, we theoretically analyzed differences in the topographic effect on the EVI and theNDVI based on a non-Lambertian model and two airborne-based images acquired from amountainous area covered by high-density Japanese cypress plantation were used as a casestudy. The results indicate that the soil adjustment factor "L" in the EVI makes it moresensitive to topographic conditions than is the NDVI. Based on these results, we stronglyrecommend that the topographic effect should be removed in the reflectance data beforethe EVI was calculated-as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI)-when these indices are used in the area of rough terrain, where the topographic effect on the vegetation indices having only a band ratio format (e.g., the NDVI) can usually be ignored.

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

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.

Comparison of Topographic Effects between the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI)

NASA Astrophysics Data System (ADS)

Matsushita, B.; Yang, W.; Chen, J.; Onda, Y.

2007-12-01

Vegetation indices play an important role in monitoring variations in vegetation. The Enhanced Vegetation Index (EVI) proposed by the MODIS Land Discipline Group and the Normalized Difference Vegetation Index (NDVI) are both global-based vegetation indices aimed at providing consistent spatial and temporal information regarding global vegetation. However, many environmental factors such as atmospheric conditions and soil background may produce errors in these indices. The topographic effect is another very important factor, especially when the indices are used in areas of rough terrain. In this paper, we analyzed differences in the topographic effect between the EVI and the NDVI based on a non-Lambertian model and using two airborne-based images with a spatial resolution of 1.5m acquired from a mountainous area covered by a homogeneous Japanese cypress plantation. The results indicate that the soil adjustment factor "L" in the EVI makes it more sensitive to topographic conditions than is the NDVI. Based on these results, we strongly recommend that the topographic effect be removed from the EVI--as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI)--when these indices are used in conjunction with a high spatial resolution image of an area of rough terrain, where the topographic effect on the vegetarian indices having only a band ratio format (e.g., the NDVI) can usually be ignored.

[Effects of green space vegetation canopy pattern on the microclimate in residential quarters of Shenzhen City].

PubMed

Li, Ying-Han; Wang, Jun-Jian; Chen, Xue; Sun, Jian-Lin; Zeng, Hui

2011-02-01

Based on field survey and landscape pattern analysis, this paper studied the effects of green space vegetation canopy on the microclimate in three typical residential quarters in Shenzhen City. In each of the residential quarters, 22-26 points were chosen for meteorological observation; and around each of the observation points, a 20 m x 20 m quadrat was installed, with each quadrat divided into two different patches, one covered by vegetation canopy and the another no-covered. The patch density index (D(p)) and contagion index (CONTAG) in each quadrat were calculated to analyze the relationships between vegetation canopy pattern index and microclimate in each point. The results showed that the green space vegetation canopy pattern in Shenzhen had significant regulation effect on temperature and humidity. The cooling effect was mainly from the shading effect of vegetation, and also, correlated with vegetation quantity. The increase in the CONTAG of bare surface had obvious negative effects on the regulation effect of vegetation on microclimate. The regulation capability of green space vegetation on the temperature and humidity in residential quarters mainly came from tall arbor species.

Higher-order differencing method with a multigrid approach for the solution of the incompressible flow equations at high Reynolds numbers

NASA Astrophysics Data System (ADS)

Tzanos, Constantine P.

1992-10-01

A higher-order differencing scheme (Tzanos, 1990) is used in conjunction with a multigrid approach to obtain accurate solutions of the Navier-Stokes convection-diffusion equations at high Re numbers. Flow in a square cavity with a moving lid is used as a test problem. a multigrid approach based on the additive correction method (Settari and Aziz) and an iterative incomplete lower and upper solver demonstrated good performance for the whole range of Re number under consideration (from 1000 to 10,000) and for both uniform and nonuniform grids. It is concluded that the combination of the higher-order differencing scheme with a multigrid approach proved to be an effective technique for giving accurate solutions of the Navier-Stokes equations at high Re numbers.

Hydrologic and Geomorphic Changes Resulting from the Onset of Episodic Glacial Lake Outburst Floods: Colonia River, Chile

NASA Astrophysics Data System (ADS)

Jacquet, J.; McCoy, S. W.; McGrath, D.; Nimick, D.; Friesen, B.; Fahey, M. J.; Leidich, J.; Okuinghttons, J.

2015-12-01

The Colonia river system, draining the eastern edge of the Northern Patagonia Icefield, Chile, has experienced a dramatic shift in flow regime from one characterized by seasonal discharge variability to one dominated by episodic glacial lake outburst floods (GLOFs). We use multi-temporal visible satellite images, high-resolution digital elevation models (DEMs) derived from stereo image pairs, and in situ observations to quantify sediment and water fluxes out of the dammed glacial lake, Lago Cachet Dos (LC2), as well as the concomitant downstream environmental change. GLOFs initiated in April 2008 and have since occurred, on average, two to three times a year. Differencing concurrent gage measurements made on the Baker River upstream and downstream of the confluence with the Colonia river finds peak GLOF discharges of ~ 3,000 m3s-1, which is ~ 4 times the median discharge of the Baker River and over 20 times the median discharge of the Colonia river. During each GLOF, ~ 200,000,000 m3 of water evacuates from the LC2, resulting in erosion of valley-fill sediments and the delta on the upstream end of LC2. Differencing DEMs between April 2008 and February 2014 revealed that ~ 2.5 x 107 m3 of sediment was eroded. Multi-temporal DEM differencing shows that erosion rates were highest initially, with > 20 vertical m of sediment removed between 2008 and 2012, and generally less than 5 m between 2012 and 2014. The downstream Colonia River Sandur also experienced geomorphic changes due to GLOFs. Using Landsat imagery to calculate the normalized difference water index (NDWI), we demonstrate that the Colonia River was in a stable configuration between 1984 and 2008. At the onset of GLOFs in April 2008, a change in channel location began and continued with each subsequent GLOF. Quantification of sediment and water fluxes due to GLOFs in the Colonia river valley provides insight on the geomorphic and environmental changes in river systems experiencing dramatic shifts in flow regime.

Remote sensing sensitivity to fire severity and fire recovery

USGS Publications Warehouse

Key, C.H.

2005-01-01

The paper examines fundamental ways that geospatial data on fire severity and recovery are influenced by conditions of the remote sensing. Remote sensing sensitivities are spatial, temporal and radiometric in origin. Those discussed include spatial resolution, the sampling time of year, and time since fire. For standard reference, sensitivities are demonstrated with examples drawn from an archive of burn assessments based on one radiometric index, the differenced Normalized Burn Ratio. Resolution determines the aggregation of fire effects within a pixel (alpha variation), hence defining the detected ecological response, and controlling the ability to determine patchiness and spatial distribution of responses throughout a burn (beta variation). As resolution decreases, alpha variation increases, extracting beta variation from the complexity of the whole burn. Seasonal timing impacts the radiometric quality of data in terms of transmittance, sun angle, and potential for enhanced contrast between responses within burns. Remote sensing sensitivity can degrade during many fire seasons when snow, incomplete burning, hazy conditions, low sun angles, or extended drought are common. Time since fire (lag timing) most notably shapes severity detection through the first-order fire effects evident in survivorship and delayed mortality that emerge by the growth period after fire. The former effects appear overly severe at first, but diminish, as burned vegetation remains viable. Conversely, the latter signals vegetation that appears healthy at first, but is damaged by heat to the extent that it soon dies. Both responses can lead to either over- or under-estimating severity, respectively, depending on fire behavior and pre-fire composition unique to each burned area. Based on implications of such sensitivities, three sampling intervals for short-term burn severity are identified; rapid, initial, and extended assessment, sampled within ca. two weeks, two months, and depending on the ecotype, from three months to one year after fire, respectively. Jointly, remote sensing conditions and the way burns are studied yield different tendencies for data quality and information content that impact the objectives and hypotheses that can be studied. Such considerations can be commonly overlooked, but need to be incorporated especially in comparative studies, and to build long-term reference databases on fire severity and recovery.

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

White Vegetables: Glycemia and Satiety12

PubMed Central

Anderson, G. Harvey; Soeandy, Chesarahmia Dojo; Smith, Christopher E.

2013-01-01

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance. PMID:23674805

Gender-related asymmetric brain vasomotor response to color stimulation: a functional transcranial Doppler spectroscopy study.

PubMed

Njemanze, Philip C

2010-11-30

The present study was designed to examine the effects of color stimulation on cerebral blood mean flow velocity (MFV) in men and women. The study included 16 (8 men and 8 women) right-handed healthy subjects. The MFV was recorded simultaneously in both right and left middle cerebral arteries in Dark and white Light conditions, and during color (Blue, Yellow and Red) stimulations, and was analyzed using functional transcranial Doppler spectroscopy (fTCDS) technique. Color processing occurred within cortico-subcortical circuits. In men, wavelength-differencing of Yellow/Blue pairs occurred within the right hemisphere by processes of cortical long-term depression (CLTD) and subcortical long-term potentiation (SLTP). Conversely, in women, frequency-differencing of Blue/Yellow pairs occurred within the left hemisphere by processes of cortical long-term potentiation (CLTP) and subcortical long-term depression (SLTD). In both genders, there was luminance effect in the left hemisphere, while in men it was along an axis opposite (orthogonal) to that of chromatic effect, in women, it was parallel. Gender-related differences in color processing demonstrated a right hemisphere cognitive style for wavelength-differencing in men, and a left hemisphere cognitive style for frequency-differencing in women. There are potential applications of fTCDS technique, for stroke rehabilitation and monitoring of drug effects.

Comparison of North and South American biomes from AVHRR observations

NASA Technical Reports Server (NTRS)

Goward, Samuel N.; Dye, Dennis; Kerber, Arlene; Kalb, Virginia

1987-01-01

Previous analysis of the North American continent with AVHRR-derived vegetation index measurements showed a strong relation between known patterns of vegetation seasonality, productivity and the spectral vegetation index measurements. This study extends that analysis to South America to evaluate the degree to which these findings extend to tropical regions. The results show that the spectral vegetation index measurements provide a general indicator of vegetation activity across the major biomes of the Western Hemisphere of the earth, including tropical regions. The satellite-observed patterns are strongly related to the known climatology of the continents and may offer a means to improve understanding of global bioclimatology. For example, South America is shown to have a longer growing season with much earlier spring green-up than North America. The time integral of the measurements, computed from 12 composited monthly values, produces a value that is related to published net primary productivity data. However, limited net primary production data does not allow complete evaluation of satellite-observed contrasts between North and South American biomes. These results suggest that satellite-derived spectral vegetation index measurements are of great potential value in improving knowledge of the earth's biosphere.

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.

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.

Analysis of Differences in Phenology Extracted from the Enhanced Vegetation Index and the Leaf Area Index

PubMed Central

Wang, Cong; Li, Jing; Wu, Shanlong; Xia, Chuanfu

2017-01-01

Remote-sensing phenology detection can compensate for deficiencies in field observations and has the advantage of capturing the continuous expression of phenology on a large scale. However, there is some variability in the results of remote-sensing phenology detection derived from different vegetation parameters in satellite time-series data. Since the enhanced vegetation index (EVI) and the leaf area index (LAI) are the most widely used vegetation parameters for remote-sensing phenology extraction, this paper aims to assess the differences in phenological information extracted from EVI and LAI time series and to explore whether either index performs well for all vegetation types on a large scale. To this end, a GLASS (Global Land Surface Satellite Product)-LAI-based phenology product (GLP) was generated using the same algorithm as the MODIS (Moderate Resolution Imaging Spectroradiometer)-EVI phenology product (MLCD) over China from 2001 to 2012. The two phenology products were compared in China for different vegetation types and evaluated using ground observations. The results show that the ratio of missing data is 8.3% for the GLP, which is less than the 22.8% for the MLCD. The differences between the GLP and the MLCD become stronger as the latitude decreases, which also vary among different vegetation types. The start of the growing season (SOS) of the GLP is earlier than that of the MLCD in most vegetation types, and the end of the growing season (EOS) of the GLP is generally later than that of the MLCD. Based on ground observations, it can be suggested that the GLP performs better than the MLCD in evergreen needleleaved forests and croplands, while the MLCD performs better than the GLP in shrublands and grasslands. PMID:28867773

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

PubMed

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

USDA-ARS?s Scientific Manuscript database

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and funct...

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.

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.

Vegetation diversity protects against childhood asthma: results from a large New Zealand birth cohort

Treesearch

Geoffrey H. Donovan; Demetrios Gatziolis; Ian Longley; Jeroen Douwes

2018-01-01

We assessed the association between the natural environment and asthma in 49,956 New Zealand children born in 1998 and followed up until 2016 using routinely collected data. Children who lived in greener areas, as measured by the normalized difference vegetation index, were less likely to be asthmatic: a 1 s.d. increase in normalized difference vegetation index was...

Mapping Collective Identity: Territories and Boundaries of Human Terrain

DTIC Science & Technology

2011-06-10

Line MAP-HT Mapping the Human Terrain NDVI Normalized Difference Vegetation Index NGA National Geospatial-Intelligence Agency xi OBIA Object-Based...The Normalized Difference Vegetation Index ( NDVI ) uses the red band to represent the low reflectance from vegetation and the expanded near infrared...spectrum to provide greater delineation of agricultural areas. This layer highlights different fields, crops, and their boundaries. NDVI layers are

Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

USGS Publications Warehouse

Wilson, Natalie R.; Norman, Laura

2018-01-01

Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

MACH2: A Two-Dimensional Magnetohydrodynamic Simulation Code for Complex Experimental Configurations.

DTIC Science & Technology

1987-09-01

Eulerian or Lagrangian flow problems, use of real equations of state and transport properties from the Los Alamos National Laboratory SESAME package...permissible problem geometries; time differencing; and spatial discretization, centering, and differ- encing of MACH2. /. I." - Magnetohydrodynamics...R-A & Y7 24 9 5.2 THE IDEAL COORDINATE SYSTEM DTIC TAB 13 24 5.3 THE MATERIAL DERIVATIVE Uannounoed 0 26 Justifloatlo- 6. TIME DIFFERENCING 31 6.1

Steganography algorithm multi pixel value differencing (MPVD) to increase message capacity and data security

NASA Astrophysics Data System (ADS)

Rojali, Siahaan, Ida Sri Rejeki; Soewito, Benfano

2017-08-01

Steganography is the art and science of hiding the secret messages so the existence of the message cannot be detected by human senses. The data concealment is using the Multi Pixel Value Differencing (MPVD) algorithm, utilizing the difference from each pixel. The development was done by using six interval tables. The objective of this algorithm is to enhance the message capacity and to maintain the data security.

TLE uncertainty estimation using robust weighted differencing

NASA Astrophysics Data System (ADS)

Geul, Jacco; Mooij, Erwin; Noomen, Ron

2017-05-01

Accurate knowledge of satellite orbit errors is essential for many types of analyses. Unfortunately, for two-line elements (TLEs) this is not available. This paper presents a weighted differencing method using robust least-squares regression for estimating many important error characteristics. The method is applied to both classic and enhanced TLEs, compared to previous implementations, and validated using Global Positioning System (GPS) solutions for the GOCE satellite in Low-Earth Orbit (LEO), prior to its re-entry. The method is found to be more accurate than previous TLE differencing efforts in estimating initial uncertainty, as well as error growth. The method also proves more reliable and requires no data filtering (such as outlier removal). Sensitivity analysis shows a strong relationship between argument of latitude and covariance (standard deviations and correlations), which the method is able to approximate. Overall, the method proves accurate, computationally fast, and robust, and is applicable to any object in the satellite catalogue (SATCAT).

Study of Wetland Ecosystem Vegetation Using Satellite Data

NASA Astrophysics Data System (ADS)

Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

2017-12-01

The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

Multiscaling of vegetative indexes from remote sensing images obtained at different spatial resolutions

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zuñiga, Ignacio; Benito, Rosa M.

2017-04-01

Vegetation indexes, such as Normalized Difference Vegetation Index (NDVI) and enhanced Vegetation index (EVI), can been used to estimate root zone soil moisture through high resolution remote sensing images. These indexes are based in red (R), near infrared (NIR) and blue (B) wavelengths data. In this work we have studied the scaling properties of both vegetation indexes analyzing the information contained in two satellite data: Landsat-7 and Ikonos. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends possible data archives from present time to over several decades back. For this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. To study the influence of the spatial resolution the vegetation indexes map estimated with Ikonos-2 coded in 8 bits, with a resolution of 4m, have been compared through a multifractal analysis with the ones obtained with Lansat-7 8 bits, of 30 m. resolution, on the same area of study. The scaling behaviour of NDVI and EVI presents several differences that will be discussed based on the multifractal parameters extracted from the analysis. REFERENCES Alonso, C., Tarquis, A. M., Benito, R. M. and Zuñiga, I. Correlation scaling properties between soil moisture and vegetation indices. Geophysical Research Abstracts, 11, EGU2009-13932, 2009. Alonso, C., Tarquis, A. M. and Benito, R. M. Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors. Geophysical Research Abstracts, 14, EGU2012-14342, 2012. Escribano Rodriguez, J., Alonso, C., Tarquis, A.M., Benito, R.M. and Hernandez Diaz-Ambrona, C. Comparison of NDVI fields obtained from different remote sensors. Geophysical Research Abstracts,15, EGU2013-14153, 2013. Lovejoy, S., Tarquis, A., Gaonac'h, H. and Schertzer, D. Single and multiscale remote sensing techniques, multifractals and MODIS derived vegetation and soil moisture, Vadose Zone J., 7, 533-546, 2008. Renosh, P. R., Schmitt, F. G., and Loisel, H.: Scaling analysis of ocean surface turbulent heterogeneities from satellite remote sensing: use of 2D structure functions. PLoS ONE, 10, e0126975, 2015. Tarquis, A.M., Platonov, A., Matulka, A., Grau, J., Sekula, E., Diez, M. and Redondo J. M. Application of multifractal analysis to the study of SAR features and oil spills on the ocean surface. Nonlin. Processes Geophys., 21, 439-450, 2014.

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.

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.

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

Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator)

1984-01-01

The effect different wetland plant canopies have upon observed reflectance in Thematic Mapper bands is studied. The three major vegetation canopy types (broadleaf, gramineous and leafless) produce unique spectral responses for a similar quantity of live biomass. The spectral biomass estimate of a broadleaf canopy is most similar to the harvest biomass estimate when a broadleaf canopy radiance model is used. All major wetland vegetation species can be identified through TM imagery. Simple regression models are developed equating the vegetation index and the infrared index with biomass. The spectral radiance index largely agreed with harvest biomass estimates.

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.

Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

PubMed

Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

2012-06-01

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

a Proposed New Vegetation Index, the Total Ratio Vegetation Index (trvi), for Arid and Semi-Arid Regions

NASA Astrophysics Data System (ADS)

Fadaei, H.; Suzuki, R.; Sakai, T.; Torii, K.

2012-07-01

Vegetation indices that provide important key to predict amount vegetation in forest such as percentage vegetation cover, aboveground biomass, and leaf-area index. Arid and semi-arid areas are not exempt of this rule. Arid and semi-arid areas of northeast Iran cover about 3.4 million ha and are populated by two main tree species, the broadleaf Pistacia vera (pistachio) and the conifer Juniperus excelsa ssp. polycarpos (Persian juniper). Natural stands of pistachio in Iran are not only environmentally important but also genetically essential as seed sources for pistachio production in orchards. We investigated the relationships between tree density and vegetation indices in the arid and semi-arid regions in the northeast of Iran by analysing Advanced Land Observing Satellite (ALOS) data PRISM is a panchromatic radiometer with a 2.5 m spatial resolution at nadir, and has one band with a wavelength of 0.52-0.77 μm (JAXA EORC). AVNIR-2 is a visible and near infrared radiometer for observing land and coastal zones with a 10 m spatial resolution at nadir, and has four multispectral bands: blue (0.42-0.50 μm), green (0.52-0.60 μm), red (0.61-0.69 μm), and near infrared (0.76-0.89 μm) (JAXA EORC). In this study, we estimated various vegetation indices using maximum filtering algorithm (5×5) and examined. This study carried out of juniper forests and natural pistachio stand using Advanced Land Observing Satellite (ALOS) and field inventories. Have been compared linear regression model of vegetation indices and proposed new vegetation index for arid and semi-arid regions. Also, we estimated the densities of juniper forests and natural pistachio stands using remote sensing to help in the sustainable management and production of pistachio in Iran. We present a new vegetation index for arid and semi-arid regions with sparse forest cover, the Total Ratio Vegetation Index (TRVI), and we investigate the relationship of the new index to tree density by analysing data from the Advanced Land Observing Satellite (ALOS) using 5×5 maximum filtering algorithms. The results for pistachio forest showed the coefficient regression of NDVI, SAVI, MSAVI, OSAVI, and TRVI were (R2= 0.68, 0.67, 0.68, 0.68, and 0.71) respectively. The results for juniper forest showed the coefficient regression of NDVI, SAVI, MSAVI, OSAVI, and TRVI were (R2= 0.51, 0.52, 0.51, 0.52, and 0.56) respectively. I hope this research can provide decision of managers to helping sustainable management for arid and semi-arid regions in Iran.

Combination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity

NASA Astrophysics Data System (ADS)

Quintano, C.; Fernández-Manso, A.; Fernández-Manso, O.

2018-02-01

Nowadays Earth observation satellites, in particular Landsat, provide a valuable help to forest managers in post-fire operations; being the base of post-fire damage maps that enable to analyze fire impacts and to develop vegetation recovery plans. Sentinel-2A MultiSpectral Instrument (MSI) records data in similar spectral wavelengths that Landsat 8 Operational Land Imager (OLI), and has higher spatial and temporal resolutions. This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire (around 8000 ha) located in Sierra de Gata (central-western Spain) on 6-11 August 2015. 1) burn severity maps based exclusively on Landsat data; specifically, on differenced Normalized Burn Ratio (dNBR) and on its relative versions (Relative dNBR, RdNBR, and Relativized Burn Ratio, RBR) and 2) burn severity maps based on the same indexes but combining pre-fire data from Landsat 8 OLI with post-fire data from Sentinel-2A MSI data. Combination of both Landsat and Sentinel-2 data might reduce the time elapsed since forest fire to the availability of an initial fire damage map. Interpretation of ortho-photograph Pléiades 1 B data (1:10,000) provided us the ground reference data to measure the accuracy of both burn severity maps. Results showed that Landsat based burn severity maps presented an adequate assessment of the damage grade (κ statistic = 0.80) and its spatial distribution in wildfire emergency response. Further using both Landsat and Sentinel-2 MSI data the accuracy of burn severity maps, though slightly lower (κ statistic = 0.70) showed an adequate level for be used by forest managers.

[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.

Environmental Humidity Regulates Effects of Experimental Warming on Vegetation Index and Biomass Production in an Alpine Meadow of the Northern Tibet

PubMed Central

Fu, Gang; Shen, Zhen Xi

2016-01-01

Uncertainty about responses of vegetation index, aboveground biomass (AGB) and gross primary production (GPP) limits our ability to predict how climatic warming will influence plant growth in alpine regions. A field warming experiment was conducted in an alpine meadow at a low (4313 m), mid- (4513 m) and high elevation (4693 m) in the Northern Tibet since May 2010. Growing season vapor pressure deficit (VPD), soil temperature (Ts) and air temperature (Ta) decreased with increasing elevation, while growing season precipitation, soil moisture (SM), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), AGB and GPP increased with increasing elevation. The growing season Ta, Ts and VPD in 2015 was greater than that in 2014, while the growing season precipitation, SM, NDVI, SAVI, AGB and GPP in 2015 was lower than that in 2014, respectively. Compared to the mean air temperature and precipitation during the growing season in 1963–2015, it was a warmer and wetter year in 2014 and a warmer and drier year in 2015. Experimental warming increased growing season Ts, Ta,VPD, but decreased growing season SM in 2014–2015 at all the three elevations. Experimental warming only reduced growing season NDVI, SAVI, AGB and GPP at the low elevation in 2015. Growing season NDVI, SAVI, AGB and GPP increased with increasing SM and precipitation, but decreased with increasing VPD, indicating vegetation index and biomass production increased with environmental humidity. The VPD explained more variation of growing season NDVI, SAVI, AGB and GPP compared to Ts, Ta and SM at all the three elevations. Therefore, environmental humidity regulated the effect of experimental warming on vegetation index and biomass production in alpine meadows on the Tibetan Plateau. PMID:27798690

Metrics for determining hydrophytic vegetation in wetland delineation: a clarification on the prevalence index

Treesearch

Diane De Steven

2015-01-01

A recent publication and an article in Wetland Science & Practice (Lichvar and Gillrich 2014b, 2014a) discuss two metrics for determining if vegetation is hydrophytic for purposes of U.S. wetland delineations, the Prevalence Index (PI) and a proposed Hydrophytic Cover Index (HCI). Based on Wentworth et al. (1988), the PI is a weighted average of ordinal scores (1-5...

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)

HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

PubMed

Salimon, Cleber; Anderson, Liana

2017-05-22

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

[Correlationships between the coverage of vegetation and the quality of groundwater in the lower reaches of the Tarim River].

PubMed

Chen, Yong-jin; Chen, Ya-ning; Liu, Jia-zhen

2010-03-01

The variations vegetation coverage is the result of conjunct effects of inner and outer energy of the earth, however, the human activity always makes the coverage of vegetation change a lot. Based on the monitoring data of chemistry of groundwater and the coverage of vegetation from 2002 to 2007 in the lower reaches of Tarim River, relations between vegetation coverage and groundwater chemistry were studied. It is found that vegetation coverage at Sector A was more than 80%, and decreased from sector to sector, the coverage of Sector I was less than 10%. At the same sector, samples near to water source owned high coverage index, and samples far away from the river had low coverage index. The variations of pH in groundwater expressed similar regulation to vegetation coverage, that is, Sectors near the water source had higher pH index comparing than those far away. Regression between groundwater quality and vegetation coverage disclosed that the coverage of Populus euphratica climbed up along with increase of pH in groundwater, change of Tamarix ramosissima coverage expressed an opposite trend to the Populus euphratica with the same environmental factors. This phenomenon can interpret spatial distribution of Populus euphratica and Tamarix ramosissima in lower reaches of the Tarim River.

Vegetation shifts observed in arctic tundra 17 years after fire

USGS Publications Warehouse

Barrett, Kirsten; Rocha, Adrian V.; van de Weg, Martine Janet; Shaver, Gaius

2012-01-01

With anticipated climate change, tundra fires are expected to occur more frequently in the future, but data on the long-term effects of fire on tundra vegetation composition are scarce. This study addresses changes in vegetation structure that have persisted for 17 years after a tundra fire on the North Slope of Alaska. Fire-related shifts in vegetation composition were assessed from remote-sensing imagery and ground observations of the burn scar and an adjacent control site. Early-season remotely sensed imagery from the burn scar exhibits a low vegetation index compared with the control site, whereas the late-season signal is slightly higher. The range and maximum vegetation index are greater in the burn scar, although the mean annual values do not differ among the sites. Ground observations revealed a greater abundance of moss in the unburned site, which may account for the high early growing season normalized difference vegetation index (NDVI) anomaly relative to the burn. The abundance of graminoid species and an absence of Betula nana in the post-fire tundra sites may also be responsible for the spectral differences observed in the remotely sensed imagery. The partial replacement of tundra by graminoid-dominated ecosystems has been predicted by the ALFRESCO model of disturbance, climate and vegetation succession.

Computer program documentation for the pasture/range condition assessment processor

NASA Technical Reports Server (NTRS)

Mcintyre, K. S.; Miller, T. G. (Principal Investigator)

1982-01-01

The processor which drives for the RANGE software allows the user to analyze LANDSAT data containing pasture and rangeland. Analysis includes mapping, generating statistics, calculating vegetative indexes, and plotting vegetative indexes. Routines for using the processor are given. A flow diagram is included.

Normalized difference vegetation index (NDVI) variation among cultivars and environments

USDA-ARS?s Scientific Manuscript database

Although Nitrogen (N) is an essential nutrient for crop production, large preplant applications of fertilizer N can result in off-field loss that causes environmental concerns. Canopy reflectance is being investigated for use in variable rate (VR) N management. Normalized difference vegetation index...

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.

Using Panchromatic Imagery in Place of Multispectral Imagery for Kelp Detection in Water

DTIC Science & Technology

2010-01-01

Normalized Difference Vegetation Index ( NDVI ). In broadband panchromatic imagery, the kelp appears brighter than the water because of the strong...response of vegetation in the NIR, and can be reliably detected by means of a simple threshold; overall brightness is generally proportional to the NDVI ...Index ( NDVI ). In broadband panchromatic imagery, the kelp appears brighter than the water because of the strong response of vegetation in the NIR, and

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.

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts

PubMed Central

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0–4, 0–9 and 0–6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively. Overall, vegetation greenness declines during the 2005 and 2010 extreme droughts were adversely influenced by precipitation, radiation and temperature; this study provides evidence of the influence of multiple climatic factors on vegetation during the 2005 and 2010 Amazon droughts. PMID:28426691

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts.

PubMed

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0-4, 0-9 and 0-6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively. Overall, vegetation greenness declines during the 2005 and 2010 extreme droughts were adversely influenced by precipitation, radiation and temperature; this study provides evidence of the influence of multiple climatic factors on vegetation during the 2005 and 2010 Amazon droughts.

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.

Sensitivity analysis of the Commonly Used Drought Indices on the different land use Types - Case Study over Turkey

NASA Astrophysics Data System (ADS)

Ersoy, E. N.; Hüsami Afşar, M.; Bulut, B.; Onen, A.; Yilmaz, M. T.

2017-12-01

Droughts are climatic phenomenon that may impact large and small regions alike for long or short time periods and influence society in terms of industrial, agricultural, domestic and many more aspects. The characteristics of the droughts are commonly investigated using indices like Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). On the other hand, these indices may not necessarily yield similar performance over different vegetation types. The aim is to analyze the sensitivity of drought indices (SPI, SPEI, PDSI) to vegetation types over different climatic regions in Turkey. Here the magnitude of the drought severity is measured using MODIS NDVI data, while the vegetation type (e.g., non-irrigated arable lands, vineyards, fruit trees and berry plantations, olive groves, pastures, land principally occupied by agriculture) information is obtained using CORINE land cover classification. This study has compared the drought characteristics and vegetation conditions on different land use types using remotely sensed datasets (e.g., CORINE land use data, MODIS NDVI), and commonly used drought indices between 2000 and 2016 using gauge based precipitation and temperature measurements.

A study of pressure-based methodology for resonant flows in non-linear combustion instabilities

NASA Technical Reports Server (NTRS)

Yang, H. Q.; Pindera, M. Z.; Przekwas, A. J.; Tucker, K.

1992-01-01

This paper presents a systematic assessment of a large variety of spatial and temporal differencing schemes on nonstaggered grids by the pressure-based methods for the problems of fast transient flows. The observation from the present study is that for steady state flow problems, pressure-based methods can be very competitive with the density-based methods. For transient flow problems, pressure-based methods utilizing the same differencing scheme are less accurate, even though the wave speeds are correctly predicted.

[Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

PubMed

Xu, Han-qiu; Zhang, Tie-jun

2011-07-01

The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

Limited Area Coverage/High Resolution Picture Transmission (LAC/HRPT) data vegetative index calculation processor user's manual

NASA Technical Reports Server (NTRS)

Obrien, S. O. (Principal Investigator)

1980-01-01

The program, LACVIN, calculates vegetative indexes numbers on limited area coverage/high resolution picture transmission data for selected IJ grid sections. The IJ grid sections were previously extracted from the full resolution data tapes and stored on disk files.

Stability of spatial distributions of stink bugs, boll injury, and NDVI in cotton

USDA-ARS?s Scientific Manuscript database

A two-year study was conducted to determine the degree of aggregation of thrips, stink bugs, and aphids in cotton, Gossypium hirsutum L., and their spatial association with soil apparent electrical conductivity (ECa), a multispectral vegetation index (Normalized Difference Vegetation Index [NDVI]), ...

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

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.

NDVI to Detect Sugarcane Aphid Injury to Grain Sorghum.

PubMed

Elliott, N C; Backoulou, G F; Brewer, M J; Giles, K L

2015-06-01

Multispectral remote sensing has potential to provide quick and inexpensive information on sugarcane aphid, Melanaphis sacchari (Zehntner), pest status in sorghum fields. We describe a study conducted to determine if injury caused by sugarcane aphid to sorghum plants in fields of grain sorghum could be detected using multispectral remote sensing from a fixed wing aircraft. A study was conducted in commercial grain sorghum fields in the Texas Gulf Coast region in June 2014. Twenty-six commercial grain sorghum fields were selected and rated for the level of injury to sorghum plants in the field caused by sugarcane aphid. Plant growth stage ranged from 5.0 (watery ripe) to 7.0 (hard dough) among fields; and plant injury rating from sugarcane aphid ranged from 1.0 (little or no injury) to 4.0 (>40% of plants displaying injury) among fields. The normalized differenced vegetation index (NDVI) is calculated from light reflectance in the red and near-infrared wavelength bands in multispectral imagery and is a common index of plant stress. High NDVI indicates low levels of stress and low NDVI indicates high stress. NDVI ranged from -0.07 to 0.26 among fields. The correlation between NDVI and plant injury rating was negative and significant, as was the correlation between NDVI and plant growth stage. The negative correlation of NDVI with injury rating indicated that plant stress increased with increasing plant injury. Reduced NDVI with increasing plant growth probably resulted from reduced photosynthetic activity in more mature plants. The correlation between plant injury rating and plant growth stage was positive and significant indicating that plant injury from sugarcane aphid increased as plants matured. The partial correlation of NDVI with plant injury rating was negative and significant indicating that NDVI decreased with increasing plant injury after adjusting for its association with plant growth stage. We demonstrated that remotely sensed imagery acquired from grain sorghum fields using an airborne multi-spectral imaging system was sensitive to injury to sorghum plants caused by sugarcane aphid. Published by Oxford University Press on behalf of Entomological Society of America 2015. This work is written by US Government employees and is in the public domain in the US.

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.

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).

Non-Lambertian effects on remote sensing of surface reflectance and vegetation index

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kaufman, Y. J.

1986-01-01

This paper discusses the effects of non-Lambertian reflection from a homogeneous surface on remote sensing of the surface reflectance and vegetation index from a satellite. Remote measurement of the surface characteristics is perturbed by atmospheric scattering of sun light. This scattering tends to smooth the angular dependence of non-Lambertian surface reflectances, an effect that is not present in the case of Lambertian surfaces. This effect is calculated to test the validity of a Lambertian assumption used in remote sensing. For the three types of vegetations considered in this study, the assumption of Lambertian surface can be used satisfactorily in the derivation of surface reflectance from remotely measured radiance for a view angle outside the backscattering region. Within the backscattering region, however, the use of the assumption can result in a considerable error in the derived surface reflectance. Accuracy also deteriorates with increasing solar zenith angle. The angular distribution of the surface reflectance derived from remote measurements is smoother than that at the surface. The effect of surface non-Lambertianity on remote sensing of vegetation index is very weak. Since the effect is similiar in the visible and near infrared part of the solar spectrum for the vegetations treated in this study, it is canceled in deriving the vegetation index. The effect of the diffuse skylight on surface reflectance measurements at ground level is also discussed.

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 use of LANDSAT digital data to detect and monitor vegetation water deficiencies. [South Dakota

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1977-01-01

A technique devised using a vector transformation of LANDSAT digital data to indicate when vegetation is undergoing moisture stress is described. A relation established between the remote sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index) is discussed.

How does spatial and temporal resolution of vegetation index impact crop yield estimation?

USDA-ARS?s Scientific Manuscript database

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing data have long been used in crop yield estimation for decades. The process-based approach uses light use efficiency model to estimate crop yield. Vegetation index (VI) ...

Monitoring vegetation cover in the postfire in Tavira - São Brás de Alportel (southern Portugal)

NASA Astrophysics Data System (ADS)

Ramos-Simões, Nuno A.; Granja-Martins, Fernando M.; Neto-Paixão, Helena M.; Jordán, Antonio; Zavala, Lorena M.

2014-05-01

1. INTRODUCTION Often, restoration of areas affected by fire faces lack of knowledge of how ecosystems respond to the action of fire. Depending on environmental conditions, structure and diversity of the vegetation or the severity of the fire, burnt systems can provide responses ranging from spontaneous recovery in a relatively short time to onset of severe degradation processes. For this reason, it is necessary to monitor the evolution of post-burned in the fire, in order to plan effective strategies for restoring systems and soil erosion control. In order to assess soil erosion risk, this research aims to is to analyse the evolution of vegetation cover in a Mediterranean burnt forest soil, using vegetation indexes derived from Landsat-7 (Thematic Mapper sensor-TM) and Landsat-8 (Operation Land Imager sensor, OLI). 2. METHODS This study was carried out in a forest area affected by a wildfire by 18-22 July 2012. The study area is located within the coordinates 37o 9' - 37o 21' N and 7o 40' - 7o 53' W, including part of the municipalities of Tavira and São Brás de Alportel (southern Portugal). The relief in the studied area has an irregular topography. Soils are shallow and develop mainly metamorphic rocks (as slates or quartzite) and igneous rocks, which produce acidic and nutrient-poor soils, poorly developed in depth. The wildfire was one of the most important fires in Portugal during the recent years, and affected more than 24000 ha. Vegetation is dominated by cork oak (Quercus suber) ,holm oaks (Quercus ilex), strawberry tree (Arbutus unedo) and sclerophyllous vegetation (mostly formed by Quercus coccifera and Rosmarinus officinalis). These species are adapted to acidic-poor soils and show a great capability of resprouting and germination after fire. The study area is poorly developed, with cork and timber harvesting and other forest products or tourism as main economic activities. The area shows a highly fragmented urban fabric with the sparse infrastructures. In recent years, migration processes have further aggravated the economic situation in this region. Landsat 7 and Landsat 8 images were used for this study (April 2012, December 2012, March 2013 and November 2013). Images were corrected for the scattering effect by extraction of black objects for near infrared bands and correction by linear regression for the red bands. Several vegetation indexes were used, such as, vegetation ratio, NDVI, the perpendicular vegetation index with assessment of distance to soil, PVI, WDVI, PVI3, and vegetation indexes based on orthogonal transformation of bands (Tasselled Cap) and principal component analysis (PCA). After studying the correlations between indexes by PCA, the Tasselled Cap-green index was selected as the most accurate one. Presence/absence of vegetation and land use were monitored to select the best parameter to study the evolution of vegetation. The evolution of the vegetation was compared with the CORINE Land Cover map (2006) and validated in field visits in January 2014. 3. RESULTS For the study area, results show a positive evolution of vegetation in the burned area during the months following to burning. Recovery of natural-native vegetation is more intense than anthropic vegetation types, with sclerophyllous vegetation showing the most intense evolution after burning.

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

Vegetable behavioral tool demonstrates validity with MyPlate vegetable cups and carotenoid and inflammatory biomarkers.

PubMed

Townsend, Marilyn S; Shilts, Mical K; Styne, Dennis M; Drake, Christiana; Lanoue, Louise; Woodhouse, Leslie; Allen, Lindsay H

2016-12-01

Young children are not meeting recommendations for vegetable intake. Our objective is to provide evidence of validity and reliability for a pictorial vegetable behavioral assessment for use by federally funded community nutrition programs. Parent/child pairs (n=133) from Head Start and the Special Supplemental Nutrition Program for Women, Infants and Children [WIC] provided parent-administered vegetable tools, three child 24-hour diet recalls, child blood sample and measured heights/weights. The 10-item Focus on Veggies scale, with an alpha of .83 and a stability reliability coefficient of .74, was positively related to vegetables in cup equivalents [p≤.05]; dietary intakes of folate, vitamin C, β-carotene, potassium and magnesium [p≤.05-.01]; and soluble fiber [p≤.001]. The child vegetable scores were related to the parent's mediators [p≤.00001] and vegetable behaviors [p≤.00001]. Children's plasma inflammatory markers were negatively related to the 10 item scale [p≤.05] and are indicators of the child's health status. The positive relationship between the serum carotenoid index and a sub-scale of child vegetable behaviors offered additional support for criterion validity [p≤.05]. Finally, the inverse relationship of BMI-for-age percentile one year post baseline and a sub-scale of child vegetable behaviors supported the predictive validity [p≤.05]. Focus on Veggies, a simple assessment tool, can inform practitioners about the child's health status. A child with a high score, shows a healthful profile with a lower inflammation index, higher carotenoid index, lower BMI and higher vegetable intake. In conclusion, validity of Focus on Veggies has been demonstrated using vegetable cup equivalents and micronutrient intakes, anthropometry and blood biomarkers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Riparian vegetation as an indicator of riparian condition: Detecting departures from historic condition across the North American West.

PubMed

Macfarlane, William W; Gilbert, Jordan T; Jensen, Martha L; Gilbert, Joshua D; Hough-Snee, Nate; McHugh, Peter A; Wheaton, Joseph M; Bennett, Stephen N

2017-11-01

Floodplain riparian ecosystems support unique vegetation communities and high biodiversity relative to terrestrial landscapes. Accordingly, estimating riparian ecosystem health across landscapes is critical for sustainable river management. However, methods that identify local riparian vegetation condition, an effective proxy for riparian health, have not been applied across broad, regional extents. Here we present an index to assess reach-scale (500 m segment) riparian vegetation condition across entire drainage networks within large, physiographically-diverse regions. We estimated riparian vegetation condition for 53,250 km of perennial streams and rivers, 25,685 km in Utah, and 27,565 km in twelve watersheds of the interior Columbia River Basin (CRB), USA. We used nationally available, existing land cover classification derived from 30 m Landsat imagery (LANDFIRE EVT) and a modeled estimate of pre-European settlement land cover (LANDFIRE BpS). The index characterizes riparian vegetation condition as the ratio of existing native riparian vegetation cover to pre-European settlement riparian vegetation cover at a given reach. Roughly 62% of Utah and 48% of CRB watersheds showed significant (>33%) to large (>66%) departure from historic condition. Riparian vegetation change was predominantly caused by human land-use impacts (development and agriculture), or vegetation change (native riparian to invasive or upland vegetation types) that likely resulted from flow and disturbance regime alteration. Through comparisons to ground-based classification results, we estimate the existing vegetation component of the index to be 85% accurate. Our assessments yielded riparian condition maps that will help resource managers better prioritize sites and treatments for reach-scale conservation and restoration activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

PubMed

Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

2006-08-01

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer. [North America

NASA Technical Reports Server (NTRS)

Goward, S. N.; Tucker, C. J.; Dye, D. G.

1985-01-01

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the advanced very high resolution radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. Significant information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

[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.

Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography

PubMed Central

Zhao, Dehua; Xie, Dong; Zhou, Hengjie; Jiang, Hao; An, Shuqing

2012-01-01

Non-destructive estimation using digital cameras is a common approach for estimating leaf area index (LAI) of terrestrial vegetation. However, no attempt has been made so far to develop non-destructive approaches to LAI estimation for aquatic vegetation. Using the submerged plant species Potamogeton malainus, the objective of this study was to determine whether the gap fraction derived from vertical photographs could be used to estimate LAI of aquatic vegetation. Our results suggested that upward-oriented photographs taken from beneath the water surface were more suitable for distinguishing vegetation from other objects than were downward-oriented photographs taken from above the water surface. Exposure settings had a substantial influence on the identification of vegetation in upward-oriented photographs. Automatic exposure performed nearly as well as the optimal trial exposure, making it a good choice for operational convenience. Similar to terrestrial vegetation, our results suggested that photographs taken for the purpose of distinguishing gap fraction in aquatic vegetation should be taken under diffuse light conditions. Significant logarithmic relationships were observed between the vertical gap fraction derived from upward-oriented photographs and plant area index (PAI) and LAI derived from destructive harvesting. The model we developed to depict the relationship between PAI and gap fraction was similar to the modified theoretical Poisson model, with coefficients of 1.82 and 1.90 for our model and the theoretical model, respectively. This suggests that vertical upward-oriented photographs taken from below the water surface are a feasible alternative to destructive harvesting for estimating PAI and LAI for the submerged aquatic plant Potamogeton malainus. PMID:23226557

Urban green land cover changes and their relation to climatic variables in an anthropogenically impacted area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Dida, Adrian I.

2017-10-01

Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.

The use of Landsat digital data to detect and monitor vegetation water deficiencies

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1977-01-01

In the Large Area Crop Inventory Experiment a technique was devised using a vector transformation of Landsat digital data to indicate when vegetation is undergoing moisture stress. A relation was established between the remote-sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index).

Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

USDA-ARS?s Scientific Manuscript database

Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

Dietary Patterns and Body Mass Index in Children with Autism and Typically Developing Children

ERIC Educational Resources Information Center

Evans, E. Whitney; Must, Aviva; Anderson, Sarah E.; Curtin, Carol; Scampini, Renee; Maslin, Melissa; Bandini, Linda

2012-01-01

To determine whether dietary patterns (juice and sweetened non-dairy beverages, fruits, vegetables, fruits and vegetables, snack foods, and kid's meals) and associations between dietary patterns and body mass index (BMI) differed between 53 children with autism spectrum disorders (ASD) and 58 typically developing children, ages 3-11, multivariate…

Vegetation Structure of Ebony Leaf Monkey (Trachypithecus auratus) Habitat in Kecubung Ulolanang Nature Preservation Central Java-Indonesia

NASA Astrophysics Data System (ADS)

Ervina, Rahmawati; Wasiq, Hidayat Jafron

2018-02-01

Kecubung Ulolanang Nature Preservation is ebony leaf monkey's habitats in Central Java Indonesia. Continuously degradation of their population is caused by illegal hunting and habitat degradation that made this species being vulnerable. Habitat conservation is one of important aspects to prevent them from extinction. The purpose of this research was to analyze the vegetation's structure and composition, which was potentially, becomes habitat and food source for the monkeys. Data collected using purposive sampling with line transect method of four different level of vegetation. Data analysis used Important Value Index and Diversity Index. There were 43 species of vegetation at seedling stage, 18 species at sapling stage, 8 species at poles stage and 27 species at trees stage. Species that had the highest important value index at seedling was Stenochlaena palustri , at the sapling was Gnetum gnemon, at pole was Swietenia mahagoni and at tree was Tectona grandis . Species of trees those were potentially to become habitat (food source) for ebony leaf monkey were T. grandis, Dipterocarpus gracilis, Quercus sundaica and Ficus superba. The highest diversity index was at seedling gwoth stage.

[Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

PubMed

Wang, Li-Wen; Wei, Ya-Xing

2013-10-01

Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

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.

Assessment of ASTER data for forest inventory in Canary Islands

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Arbelo, Manuel; Hernandez-Leal, Pedro A.; González-Calvo, Alejandro; Labrador Garcia, Mauricio

To understand and evaluate the forest structural attributes, forest inventories are conducted, which are costly and lengthy in time. Since the last 10-15 years there has been examining the possibility of using remote sensing data, to save costs and cheapen the process. One of the aims of SATELMAC, a project PCT-MAC 2007-2013 co-financing with FEDER funds, is to automate the forest inventory in Canary Islands using satellite images. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to estimate forest structure of the endemic vegetal specie, Pinus canariensis, located on the island of Tenerife (Spain). The forest structural attributes analyzed have been volume, basal area, stem per hectare and tree height. ASTER is an imaging instrument flying on Terra, a satellite launched in December 1999 as part of NASA's Earth Observing System. ASTER data were used because it have relatively high spatial resolution in the three visible and near-infrared bands (15 m) and in the six spectral bands (30 m) in the shortwave-IR region. To identify the vegetation index that is most suitable to use, about specific forest structural attributes in our study area, we assess the ability of different spectral indices: Normalized Difference Vegetation Index, Transformed Soil Adjusted Vegetation Index, Modified Soil adjusted Vegetation Index, Perpendicular Vegetation Index and Reduced Simple Ratio. The information provided by the ASTER data has been supplemented by the Third National Forest Inventory (III NFI) and field data. The results are analyzed statistically in order to see the degree of correlation (R2) and the mean square error (RMSE) of the values studied.

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.

Lifting the Green Veil: A Fresh Look at Synoptic Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Vina, A.; Gitelson, A. A.

2003-12-01

Observing the dynamics of the vegetated land surface synoptically from spaceborne sensors plays a key role in understanding the global water, carbon, and nitrogen cycles, land cover and land use change, and biodiversity mapping. For the past three decades the study of global and regional vegetation dynamics has relied on satellite observations of the distinctive spectral contrast between red and near infrared reflectance exhibited by photosynthetically active green vegetation. It has long been recognized, however, that the spectral vegetation index with the widest currency-the Normalized Difference Vegetation Index (NDVI)-suffers a rapid decrease of sensitivity even at moderate Leaf Area Index (LAI) values of 2 to 4, as are commonly encountered in croplands and woodlands. This decrease in NDVI sensitivity casts a green veil over the land surface that obscures vegetation dynamics across vast areas during much of the growing season. This veil has important consequences for monitoring vegetation dynamics, developing land surface climatologies, and detecting significant changes. A straightforward modification of the NDVI, developed to increase its sensitivity under higher green biomass conditions, was applied to a standard, widely available AVHRR NDVI dataset for the conterminous US. The new Wide Dynamic Range Vegetation Index (WDRVI) exhibited increases in sensitivity between 30%-50% for Omernik Level III ecoregions dominated by woodlands, croplands, and grasslands. Ecoregions with lower aboveground net primary production, such as aridlands and semi-arid grasslands, showed no increase in sensitivity of the WDRVI over the NDVI. This powerful, new but simple approach creates an opportunity for a fresh look at the satellite data record. Further, it offers the possibility for significant improvements in the retrievals of canopy variables for carbon and nitrogen models, more accurate land surface characterizations for numerical weather prediction models, more sensitive analyses of land cover / land use change, and improvements in habitat mapping for biodiversity management.

A consistent spatial differencing scheme for the transonic full-potential equation in three dimensions

NASA Technical Reports Server (NTRS)

Thomas, S. D.; Holst, T. L.

1985-01-01

A full-potential steady transonic wing flow solver has been modified so that freestream density and residual are captured in regions of constant velocity. This numerically precise freestream consistency is obtained by slightly altering the differencing scheme without affecting the implicit solution algorithm. The changes chiefly affect the fifteen metrics per grid point, which are computed once and stored. With this new method, the outer boundary condition is captured accurately, and the smoothness of the solution is especially improved near regions of grid discontinuity.

Upwind differencing and LU factorization for chemical non-equilibrium Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun

1992-01-01

By means of either the Roe or the Van Leer flux-splittings for inviscid terms, in conjunction with central differencing for viscous terms in the explicit operator and the Steger-Warming splitting and lower-upper approximate factorization for the implicit operator, the present, robust upwind method for solving the chemical nonequilibrium Navier-Stokes equations yields formulas for finite-volume discretization in general coordinates. Numerical tests in the illustrative cases of a hypersonic blunt body, a ramped duct, divergent nozzle flows, and shock wave/boundary layer interactions, establish the method's efficiency.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

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.

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.

Remote Sensing of Evapotranspiration and Carbon Uptake at Harvard Forest

NASA Technical Reports Server (NTRS)

Min, Qilong; Lin, Bing

2005-01-01

A land surface vegetation index, defined as the difference of microwave land surface emissivity at 19 and 37 GHz, was calculated for a heavily forested area in north central Massachusetts. The microwave emissivity difference vegetation index (EDVI) was estimated from satellite SSM/I measurements at the defined wavelengths and used to estimate land surface turbulent fluxes. Narrowband visible and infrared measurements and broadband solar radiation observations were used in the EDVI retrievals and turbulent flux estimations. The EDVI values represent physical properties of crown vegetation such as vegetation water content of crown canopies. The collocated land surface turbulent and radiative fluxes were empirically linked together by the EDVI values. The EDVI values are statistically sensitive to evapotranspiration fractions (EF) with a correlation coefficient (R) greater than 0.79 under all-sky conditions. For clear skies, EDVI estimates exhibit a stronger relationship with EF than normalized difference vegetation index (NDVI). Furthermore, the products of EDVI and input energy (solar and photosynthetically-active radiation) are statistically significantly correlated to evapotranspiration (R=0.95) and CO2 uptake flux (R=0.74), respectively.

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.

Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

NASA Astrophysics Data System (ADS)

Guzinski, R.; Anderson, M. C.; Kustas, W. P.; Nieto, H.; Sandholt, I.

2013-07-01

The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.

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.

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.

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.

Monitoring grasshopper and locust habitats in Sahelian Africa using GIS and remote sensing technology

USGS Publications Warehouse

Tappan, G. Gray; Moore, Donald G.; Knauseberger, Walter I.

1991-01-01

Development programmes in Sahelian Africa are beginning to use geographic information system (GIS) technology. One of the GIS and remote sensing programmes introduced to the region in the late 1980s was the use of seasonal vegetation maps made from satellite data to support grasshopper and locust control. Following serious outbreaks of these pests in 1987, the programme addressed a critical need, by national and international crop protection organizations, to monitor site-specific dynamic vegetation conditions associated with grasshopper and locust breeding. The primary products used in assessing vegetation conditions were vegetation index (greenness) image maps derived from National Oceanic and Atmospheric Administration satellite imagery. Vegetation index data were integrated in a GIS with digital cartographic data of individual Sahelian countries. These near-real-time image maps were used regularly in 10 countries for locating potential grasshopper and locust habitats. The programme to monitor vegetation conditions is currently being institutionalized in the Sahel.

Mapping wildfire danger at regional scale with an index model integrating coarse spatial resolution remote sensing data

NASA Astrophysics Data System (ADS)

ChéRet, VéRonique; Denux, Jean Philippe

2007-06-01

Wildfires are a prevalent natural hazard in the south of France. Planners need a permanent fire danger assessment valid for several years over a territory as large and heterogeneous as Midi-Pyrénées region. To this end, we developed an expert knowledge-based index model adapted to the specific features of the study area. The fire danger depends on two complementary elements: spatial occurrence and fire intensity. Among the GIS layers identified as input variables for modeling, vegetation fire susceptibility is one of the most influent. However, the main difficulty at this scale is the scarcity or the lack of exhaustiveness of the data. In this respect, remote sensing imagery is capable of providing relevant information. We proposed to calculate an annual relative greenness index (annual RGRE) that reflects vegetation dryness in summer. We processed times series of Normalized Difference Vegetation Index (NDVI) from SPOT-VEGETATION images over the last six available years (1998 to 2003). The first step was to verify that these images characterize vegetation types and highlight intraannual and interannual response variability. It is then possible to identify phenological stages corresponding to the maximum NDVI (and therefore to maximum photosynthetic activity) during the growing season, the minimum NDVI at the end of the growing season and the minimum NDVI during winter period. These phenology metrics ground the annual RGRE calculation. Values obtained for each observation year show significant correlation (r2 = 0.70) with the De Martonne aridity index calculated for the same period. A synthesis of yearly index was integrated in the model as a variable that expresses fire susceptibility.

[The new method monitoring crop water content based on NIR-Red spectrum feature space].

PubMed

Cheng, Xiao-juan; Xu, Xin-gang; Chen, Tian-en; Yang, Gui-jun; Li, Zhen-hai

2014-06-01

Moisture content is an important index of crop water stress condition, timely and effective monitoring of crop water content is of great significance for evaluating crop water deficit balance and guiding agriculture irrigation. The present paper was trying to build a new crop water index for winter wheat vegetation water content based on NIR-Red spectral space. Firstly, canopy spectrums of winter wheat with narrow-band were resampled according to relative spectral response function of HJ-CCD and ZY-3. Then, a new index (PWI) was set up to estimate vegetation water content of winter wheat by improveing PDI (perpendicular drought index) and PVI (perpendicular vegetation index) based on NIR-Red spectral feature space. The results showed that the relationship between PWI and VWC (vegetation water content) was stable based on simulation of wide-band multispectral data HJ-CCD and ZY-3 with R2 being 0.684 and 0.683, respectively. And then VWC was estimated by using PWI with the R2 and RMSE being 0.764 and 0.764, 3.837% and 3.840%, respectively. The results indicated that PWI has certain feasibility to estimate crop water content. At the same time, it provides a new method for monitoring crop water content using remote sensing data HJ-CCD and ZY-3.

Discrete return lidar-based prediction of leaf area index in two conifer forests

Treesearch

Jennifer L. R. Jensen; Karen S. Humes; Lee A. Vierling; Andrew T. Hudak

2008-01-01

Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical...

Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

PubMed

Cheng, Zhan-Hong; Zhang, Jin-Tun

2005-09-01

The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

Satellite Vegetation Index Data as a Tool to Forecast Population Dynamics of Medically Important Mosquitoes at Military Installations in the Continental United States

DTIC Science & Technology

2008-07-01

for the two installations. We obtained monthly North American normalized differ- ence vegetation index ( NDVI ) satellite climate data sets for 1981-2005...from the Goddard Space Flight Center."*-" The NDVI measures the greenness of the earth, capturing in one index the combined effects of temperature...humidity, insola- tion, elevation, soils, land use. and precipitation on vegeta- tion. There is an almost-linear relationship between NDVI values and

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

Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

2005-10-01

The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

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.

One-dimensional transient radiative transfer by lattice Boltzmann method.

PubMed

Zhang, Yong; Yi, Hongliang; Tan, Heping

2013-10-21

The lattice Boltzmann method (LBM) is extended to solve transient radiative transfer in one-dimensional slab containing scattering media subjected to a collimated short laser irradiation. By using a fully implicit backward differencing scheme to discretize the transient term in the radiative transfer equation, a new type of lattice structure is devised. The accuracy and computational efficiency of this algorithm are examined firstly. Afterwards, effects of the medium properties such as the extinction coefficient, the scattering albedo and the anisotropy factor, and the shapes of laser pulse on time-resolved signals of transmittance and reflectance are investigated. Results of the present method are found to compare very well with the data from the literature. For an oblique incidence, the LBM results in this paper are compared with those by Monte Carlo method generated by ourselves. In addition, transient radiative transfer in a two-Layer inhomogeneous media subjected to a short square pulse irradiation is investigated. At last, the LBM is further extended to study the transient radiative transfer in homogeneous medium with a refractive index discontinuity irradiated by the short pulse laser. Several trends on the time-resolved signals different from those for refractive index of 1 (i.e. refractive-index-matched boundary) are observed and analysed.

Phenological Parameters Estimation Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney D.; Ross, Kenton W.; Spruce, Joseph P.; Smoot, James C.; Ryan, Robert E.; Gasser, Gerald E.; Prados, Donald L.; Vaughan, Ronald D.

2010-01-01

The Phenological Parameters Estimation Tool (PPET) is a set of algorithms implemented in MATLAB that estimates key vegetative phenological parameters. For a given year, the PPET software package takes in temporally processed vegetation index data (3D spatio-temporal arrays) generated by the time series product tool (TSPT) and outputs spatial grids (2D arrays) of vegetation phenological parameters. As a precursor to PPET, the TSPT uses quality information for each pixel of each date to remove bad or suspect data, and then interpolates and digitally fills data voids in the time series to produce a continuous, smoothed vegetation index product. During processing, the TSPT displays NDVI (Normalized Difference Vegetation Index) time series plots and images from the temporally processed pixels. Both the TSPT and PPET currently use moderate resolution imaging spectroradiometer (MODIS) satellite multispectral data as a default, but each software package is modifiable and could be used with any high-temporal-rate remote sensing data collection system that is capable of producing vegetation indices. Raw MODIS data from the Aqua and Terra satellites is processed using the TSPT to generate a filtered time series data product. The PPET then uses the TSPT output to generate phenological parameters for desired locations. PPET output data tiles are mosaicked into a Conterminous United States (CONUS) data layer using ERDAS IMAGINE, or equivalent software package. Mosaics of the vegetation phenology data products are then reprojected to the desired map projection using ERDAS IMAGINE

Contributions of understory and/or overstory vegetations to soil microbial PLFA and nematode diversities in Eucalyptus monocultures.

PubMed

Zhao, Jie; Wan, Songze; Zhang, Chenlu; Liu, Zhanfeng; Zhou, Lixia; Fu, Shenglei

2014-01-01

Ecological interactions between aboveground and belowground biodiversity have received many attentions in the recent decades. Although soil biodiversity declined with the decrease of plant diversity, many previous studies found plant species identities were more important than plant diversity in controlling soil biodiversity. This study focused on the responses of soil biodiversity to the altering of plant functional groups, namely overstory and understory vegetations, rather than plant diversity gradient. We conducted an experiment by removing overstory and/or understory vegetation to compare their effects on soil microbial phospholipid fatty acid (PLFA) and nematode diversities in eucalyptus monocultures. Our results indicated that both overstory and understory vegetations could affect soil microbial PLFA and nematode diversities, which manifested as the decrease in Shannon-Wiener diversity index (H') and Pielou evenness index (J) and the increase in Simpson dominance index (λ) after vegetation removal. Soil microclimate change explained part of variance of soil biodiversity indices. Both overstory and understory vegetations positively correlated with soil microbial PLFA and nematode diversities. In addition, the alteration of soil biodiversity might be due to a mixing effect of bottom-up control and soil microclimate change after vegetation removal in the studied plantations. Given the studied ecosystem is common in humid subtropical and tropical region of the world, our findings might have great potential to extrapolate to large scales and could be conducive to ecosystem management and service.

Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters.

PubMed

Bousbih, Safa; Zribi, Mehrez; Lili-Chabaane, Zohra; Baghdadi, Nicolas; El Hajj, Mohammad; Gao, Qi; Mougenot, Bernard

2017-11-14

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects.

Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters

PubMed Central

Bousbih, Safa; Lili-Chabaane, Zohra; El Hajj, Mohammad; Gao, Qi

2017-01-01

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects. PMID:29135929

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.

NOAA-AVHRR image mosaics applied to vegetation identification

NASA Astrophysics Data System (ADS)

de Almeida, Maria d. G.; Ruddorff, Bernardo F.; Shimabukuro, Yosio E.

2001-06-01

In this paper, the maximum-value composite of images procedure from Normalized Difference Vegetation Index is used to get a cloud free image mosaic. The image mosaic is used to identify vegetation targets such as tropical forest, savanna and caatinga as well to make the vegetation cover mapping of Minas Gerais state, Brazil.

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Bao, Y.; Gao, Y.; Wang, Y.

2017-12-01

The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

Coupled topographic and vegetation patterns in coastal dunes: Remote sensing observations and ecomorphodynamic implications

NASA Astrophysics Data System (ADS)

Yousefi Lalimi, F.; Silvestri, S.; Moore, L. J.; Marani, M.

2017-01-01

Vegetation plays a key role in stabilizing coastal dunes and barrier islands by mediating sand transport, deposition, and erosion. Dune topography, in turn, affects vegetation growth, by determining local environmental conditions. However, our understanding of vegetation and dune topography as coupled and spatially extensive dynamical systems is limited. Here we develop and use remote sensing analyses to quantitatively characterize coastal dune ecotopographic patterns by simultaneously identifying the spatial distribution of topographic elevation and vegetation biomass. Lidar-derived leaf area index and hyperspectral-derived normalized difference vegetation index patterns yield vegetation distributions at the whole-system scale which are in agreement with each other and with field observations. Lidar-derived concurrent quantifications of biomass and topography show that plants more favorably develop on the landward side of the foredune crest and that the foredune crestline marks the position of an ecotone, which is interpreted as the result of a sheltering effect sharply changing local environmental conditions. We conclude that the position of the foredune crestline is a chief ecomorphodynamic feature resulting from the two-way interaction between vegetation and topography.

Automatic differentiation evaluated as a tool for rotorcraft design and optimization

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.

1995-01-01

This paper investigates the use of automatic differentiation (AD) as a means for generating sensitivity analyses in rotorcraft design and optimization. This technique transforms an existing computer program into a new program that performs sensitivity analysis in addition to the original analysis. The original FORTRAN program calculates a set of dependent (output) variables from a set of independent (input) variables, the new FORTRAN program calculates the partial derivatives of the dependent variables with respect to the independent variables. The AD technique is a systematic implementation of the chain rule of differentiation, this method produces derivatives to machine accuracy at a cost that is comparable with that of finite-differencing methods. For this study, an analysis code that consists of the Langley-developed hover analysis HOVT, the comprehensive rotor analysis CAMRAD/JA, and associated preprocessors is processed through the AD preprocessor ADIFOR 2.0. The resulting derivatives are compared with derivatives obtained from finite-differencing techniques. The derivatives obtained with ADIFOR 2.0 are exact within machine accuracy and do not depend on the selection of step-size, as are the derivatives obtained with finite-differencing techniques.

Prediction of the Thrust Performance and the Flowfield of Liquid Rocket Engines

NASA Technical Reports Server (NTRS)

Wang, T.-S.

1990-01-01

In an effort to improve the current solutions in the design and analysis of liquid propulsive engines, a computational fluid dynamics (CFD) model capable of calculating the reacting flows from the combustion chamber, through the nozzle to the external plume, was developed. The Space Shuttle Main Engine (SSME) fired at sea level, was investigated as a sample case. The CFD model, FDNS, is a pressure based, non-staggered grid, viscous/inviscid, ideal gas/real gas, reactive code. An adaptive upwinding differencing scheme is employed for the spatial discretization. The upwind scheme is based on fourth order central differencing with fourth order damping for smooth regions, and second order central differencing with second order damping for shock capturing. It is equipped with a CHMQGM equilibrium chemistry algorithm and a PARASOL finite rate chemistry algorithm using the point implicit method. The computed flow results and performance compared well with those of other standard codes and engine hot fire test data. In addition, the transient nozzle flowfield calculation was also performed to demonstrate the ability of FDNS in capturing the flow separation during the startup process.

Ice Sheet Change Detection by Satellite Image Differencing

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Post-fire Thermokarst Development Along a Planned Road Corridor in Arctic Alaska

NASA Astrophysics Data System (ADS)

Jones, B. M.; Grosse, G.; Larsen, C. F.; Hayes, D. J.; Arp, C. D.; Liu, L.; Miller, E.

2015-12-01

Wildfire disturbance in northern high latitude regions is an important factor contributing to ecosystem and landscape change. In permafrost influenced terrain, fire may initiate thermokarst development which impacts hydrology, vegetation, wildlife, carbon storage and infrastructure. In this study we differenced two airborne LiDAR datasets that were acquired in the aftermath of the large and severe Anaktuvuk River tundra fire, which in 2007 burned across a proposed road corridor in Arctic Alaska. The 2009 LiDAR dataset was acquired by the Alaska Department of Transportation in preparation for construction of a gravel road that would connect the Dalton Highway with the logistical camp of Umiat. The 2014 LiDAR dataset was acquired by the USGS to quantify potential post-fire thermokarst development over the first seven years following the tundra fire event. By differencing the two 1 m resolution digital terrain models, we measured permafrost thaw subsidence across 34% of the burned tundra area studied, and observed less than 1% in similar, undisturbed tundra terrain units. Ice-rich, yedoma upland terrain was most susceptible to thermokarst development following the disturbance, accounting for 50% of the areal and volumetric change detected, with some locations subsiding more than six meters over the study period. Calculation of rugosity, or surface roughness, in the two datasets showed a doubling in microtopography on average across the burned portion of the study area, with a 340% increase in yedoma upland terrain. An additional LiDAR dataset was acquired in April 2015 to document the role of thermokarst development on enhanced snow accumulation and subsequent snowmelt runoff within the burn area. Our findings will enable future vulnerability assessments of ice-rich permafrost terrain as a result of shifting disturbance regimes. Such assessments are needed to address questions focused on the impact of permafrost degradation on physical, ecological, and socio-economic processes.

Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

USGS Publications Warehouse

Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

2016-01-01

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.

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.

Assessing the risks of trace elements in environmental materials under selected greenhouse vegetable production systems of China.

PubMed

Chen, Yong; Huang, Biao; Hu, Wenyou; Weindorf, David C; Liu, Xiaoxiao; Niedermann, Silvana

2014-02-01

The risk assessment of trace elements of different environmental media in conventional and organic greenhouse vegetable production systems (CGVPS and OGVPS) can reveal the influence of different farming philosophy on the trace element accumulations and their effects on human health. These provide important basic data for the environmental protection and human health. This paper presents trace element accumulation characteristics of different land uses; reveals the difference of soil trace element accumulation both with and without consideration of background levels; compares the trace element uptake by main vegetables; and assesses the trace element risks of soils, vegetables, waters and agricultural inputs, using two selected greenhouse vegetable systems in Nanjing, China as examples. Results showed that greenhouse vegetable fields contained significant accumulations of Zn in CGVPS relative to rice-wheat rotation fields, open vegetable fields, and geochemical background levels, and this was the case for organic matter in OGVPS. The comparative analysis of the soil medium in two systems with consideration of geochemical background levels and evaluation of the geo-accumulation pollution index achieved a more reasonable comparison and accurate assessment relative to the direct comparison analysis and the evaluation of the Nemerow pollution index, respectively. According to the Chinese food safety standards and the value of the target hazard quotient or hazard index, trace element contents of vegetables were safe for local residents in both systems. However, the spatial distribution of the estimated hazard index for producers still presented certain specific hotspots which may cause potential risk for human health in CGVPS. The water was mainly influenced by nitrogen, especially for CGVPS, while the potential risk of Cd and Cu pollution came from sediments in OGVPS. The main inputs for trace elements were fertilizers which were relatively safe based on relevant standards; but excess application caused trace element accumulations in the environmental media. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluating the species energy relationship with the newest measures of ecosystem energy: NDVI versus MODIS primary production

Treesearch

Linda B. Phillips; Andrew J. Hansen; Curtis H. Flather

2008-01-01

Ecosystem energy has been shown to be a strong correlate with biological diversity at continental scales. Early efforts to characterize this association used the normalized difference vegetation index (NDVI) to represent ecosystem energy. While this spectral vegetation index covaries with measures of ecosystem energy such as net primary production, the covariation is...

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

Abstracting GIS Layers from Hyperspectral Imagery

DTIC Science & Technology

2009-03-01

Difference Vegetative Index ( NDVI ) 2-20 2.2.10 Separating Trees from Grass . . . . . . . . . . . 2-22 2.3 Spatial Analysis...2-18 2.10. Example of the Normalized Difference Vegetation Index ( NDVI ) applied to a hyperspectral image. . . . . . . . . . . . . . . . . . 2-20...3.5. Example of applying NDVI to a SOM. . . . . . . . . . . . . . . 3-8 3.6. Visualization of the NIR scatter tree ID algorithm. . . . . . . . 3-9 ix

Suppression of vegetation in LANDSAT ETM+ remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

2010-05-01

Vegetation cover is an impediment to the interpretation of multispectral remote sensing images for geological applications, especially in densely vegetated terrains. In order to enhance the underlying geological information in such terrains, it is desirable to suppress the reflectance component of vegetation. One form of spectral unmixing that has been successfully used for vegetation reflectance suppression in multispectral images is called "forced invariance". It is based on segregating components of the reflectance spectrum that are invariant with respect to a specific spectral index such as the NDVI. The forced invariance method uses algorithms such as software defoliation. However, the outputs of software defoliation are single channel data, which are not amenable to geological interpretations. Crippen and Blom (2001) proposed a new forced invariance algorithm that utilizes band statistics, rather than band ratios. The authors demonstrated the effectiveness of their algorithms on a LANDSAT TM scene from Nevada, USA, especially in open canopy areas in mixed and semi-arid terrains. In this presentation, we report the results of our experimentation with this algorithm on a densely to sparsely vegetated Landsat ETM+ scene. We selected a scene (Path 119, Row 39) acquired on 18th July, 2004. Two study areas located around the city of Hangzhou, eastern China were tested. One of them covers uninhabited hilly terrain characterized by low rugged topography, parts of the hills are densely vegetated; another one covers both inhabited urban areas and uninhabited hilly terrain, which is densely vegetated. Crippen and Blom's algorithm is implemented in the following sequential steps: (1) dark pixel correction; (2) vegetation index calculation; (3) estimation of statistical relationship between vegetation index and digital number (DN) values for each band; (4) calculation of a smooth best-fit curve for the above relationships; and finally, (5) selection of a target average DN value and scaling all pixels at each vegetation index level by an amount that shifts the curve to the target digital number (DN). The main drawback of their algorithm is severe distortions of the DN values of non-vegetated areas, a suggested solution is masking outliers such as cloud, water, etc. We therefore extend this algorithm by masking non-vegetated areas. Our algorithm comprises the following three steps: (1) masking of barren or sparsely vegetated areas using a threshold based on a vegetation index that is calculated after atmosphere correction (dark pixel correction and ACTOR were compared) in order to conserve their original spectral information through the subsequent processing; (2) applying Crippen and Blom's forced invariance algorithm to suppress the spectral response of vegetation only in vegetated areas; and (3) combining the processed vegetated areas with the masked barren or sparsely vegetated areas followed by histogram equalization to eliminate the differences in color-scales between these two types of areas, and enhance the integrated image. The output images of both study areas showed significant improvement over the original images in terms of suppression of vegetation reflectance and enhancement of the underlying geological information. The processed images show clear banding, probably associated with lithological variations in the underlying rock formations. The colors of non-vegetated pixels are distorted in the unmasked results but in the same location the pixels in the masked results show regions of higher contrast. We conclude that the algorithm offers an effective way to enhance geological information in LANDSAT TM/ETM+ images of terrains with significant vegetation cover. It is also suitable to other multispectral satellite data have bands in similar wavelength regions. In addition, an application of this method to hyperspectral data may be possible as long as it can provide the vegetation band ratios.

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.

Relative motion using analytical differential gravity

NASA Technical Reports Server (NTRS)

Gottlieb, Robert G.

1988-01-01

This paper presents a new approach to the computation of the motion of one satellite relative to another. The trajectory of the reference satellite is computed accurately subject to geopotential perturbations. This precise trajectory is used as a reference in computing the position of a nearby body, or bodies. The problem that arises in this approach is differencing nearly equal terms in the geopotential model, especially as the separation of the reference and nearby bodies approaches zero. By developing closed form expressions for differences in higher order and degree geopotential terms, the numerical problem inherent in the differencing approach is eliminated.

SCISEAL: A CFD code for analysis of fluid dynamic forces in seals

NASA Technical Reports Server (NTRS)

Athavale, Mahesh; Przekwas, Andrzej

1994-01-01

A viewgraph presentation is made of the objectives, capabilities, and test results of the computer code SCISEAL. Currently, the seal code has: a finite volume, pressure-based integration scheme; colocated variables with strong conservation approach; high-order spatial differencing, up to third-order; up to second-order temporal differencing; a comprehensive set of boundary conditions; a variety of turbulence models and surface roughness treatment; moving grid formulation for arbitrary rotor whirl; rotor dynamic coefficients calculated by the circular whirl and numerical shaker methods; and small perturbation capabilities to handle centered and eccentric seals.

A three dimensional multigrid multiblock multistage time stepping scheme for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa; Cannizzaro, Frank; Melson, N. D.

1991-01-01

A general multiblock method for the solution of the three-dimensional, unsteady, compressible, thin-layer Navier-Stokes equations has been developed. The convective and pressure terms are spatially discretized using Roe's flux differencing technique while the viscous terms are centrally differenced. An explicit Runge-Kutta method is used to advance the solution in time. Local time stepping, adaptive implicit residual smoothing, and the Full Approximation Storage (FAS) multigrid scheme are added to the explicit time stepping scheme to accelerate convergence to steady state. Results for three-dimensional test cases are presented and discussed.

A novel grounded to floating admittance converter with electronic control

NASA Astrophysics Data System (ADS)

Prasad, Dinesh; Ahmad, Javed; Srivastava, Mayank

2018-01-01

This article suggests a new grounded to floating admittance convertor employing only two voltage differencing transconductance amplifiers (VDTAs). The proposed circuit can convert any arbitrary grounded admittance into floating admittance with electronically controllable scaling factor. The presented converter enjoys the following beneficial: (1) no requirement of any additional passive element (2) scaling factor can be tuned electronically through bias currents of VDTAs (3) no matching constraint required (4) low values of active/passive sensitivity indexes and (5) excellent non ideal behavior that indicates no deviation in circuit behavior even under non ideal environment. Application of the proposed configuration in realization of floating resistor and floating capacitor has been presented and the workability of these floating elements has been confirmed by active filter design examples. SPICE simulations have been performed to demonstrate the performance of the proposed circuits.

Comparing Landsat-7 ETM+ and ASTER Imageries to Estimate Daily Evapotranspiration Within a Mediterranean Vineyard Watershed

NASA Technical Reports Server (NTRS)

Montes, Carlo; Jacob, Frederic

2017-01-01

We compared the capabilities of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imageries for mapping daily evapotranspiration (ET) within a Mediterranean vineyard watershed. We used Landsat and ASTER data simultaneously collected on four dates in 2007 and 2008, along with the simplified surface energy balance index (S-SEBI) model. We used previously ground-validated good quality ASTER estimates as reference, and we analyzed the differences with Landsat retrievals in light of the instrumental factors and methodology. Although Landsat and ASTER retrievals of S-SEBI inputs were different, estimates of daily ET from the two imageries were similar. This is ascribed to the S-SEBI spatial differencing in temperature, and opens the path for using historical Landsat time series over vineyards.

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.

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.

Comparison of Vegetation Indices from Rpas and SENTINEL-2 Imagery for Detecting Permanent Pastures

NASA Astrophysics Data System (ADS)

Piragnolo, M.; Lusiani, G.; Pirotti, F.

2018-04-01

Permanent pastures (PP) are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016). Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA) takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI), the Soil-adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Built Index (NDBI). The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

Shelter Index and a simple wind speed parameter to characterize vegetation control of sand transport threshold and Flu

NASA Astrophysics Data System (ADS)

Gillies, J. A.; Nield, J. M.; Nickling, W. G.; Furtak-Cole, E.

2014-12-01

Wind erosion and dust emissions occur in many dryland environments from a range of surfaces with different types and amounts of vegetation. Understanding how vegetation modulates these processes remains a research challenge. Here we present results from a study that examines the relationship between an index of shelter (SI=distance from a point to the nearest upwind vegetation/vegetation height) and particle threshold expressed as the ratio of wind speed measured at 0.45 times the mean plant height divided by the wind speed at 17 m when saltation commences, and saltation flux. The results are used to evaluate SI as a parameter to characterize the influence of vegetation on local winds and sediment transport conditions. Wind speed, wind direction, saltation activity and point saltation flux were measured at 35 locations in defined test areas (~13,000 m2) in two vegetation communities: mature streets of mesquite covered nebkhas and incipient nebkhas dominated by low mesquite plants. Measurement positions represent the most open areas, and hence those places most susceptible to wind erosion among the vegetation elements. Shelter index was calculated for each measurement position for each 10° wind direction bin using digital elevation models for each site acquired using terrestrial laser scanning. SI can show the susceptibility to wind erosion at different time scales, i.e., event, seasonal, or annual, but in a supply-limited system it can fail to define actual flux amounts due to a lack of knowledge of the distribution of sediment across the surface of interest with respect to the patterns of SI.

The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

NASA Astrophysics Data System (ADS)

Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

2017-11-01

Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

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.

Estimating wheat growth with radar vegetation indices

USDA-ARS?s Scientific Manuscript database

In this study, we computed the Radar Vegetation Index (RVI) using observations made with a ground based multi-frequency polarimetric scatterometer system over an entire wheat growth period. The temporal variations of the backscattering coefficients for L-, C-, and X-band, RVI, vegetation water conte...

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.

Identifying high production, low production and degraded rangelands in Senegal with normalized difference vegetation index data

USGS Publications Warehouse

Tappan, G. Gray; Wood, Lynette; Moore, Donald G.

1993-01-01

Seasonal herbaceous vegetation production on Senegal's native rangelands exhibits high spatial and temporal variability. This variability can be monitored using normalized difference vegetation index (NDVI) data computed from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) image data. Although annual fluctuations in rainfall account for some of the variability, numerous long-term production patterns are evident in the AVHRR time-series data. Different n productivity reflect variations in the region's climate, topography, soils, and land use. Areas of overgrazing and intensive cultivation have caused long-term soil and vegetation degradation. Rangelands of high and low productivity, and degraded rangelands were identified using NDVI. Time-series image data from 1987 though 1992 were used to map relative rangeland productivity. The results were compared to detailed resource maps on soils, vegetation and land use. Much of the variation in rangeland productivity correlated well to the known distribution of resources. The study developed an approach that identified a number of areas of degraded soils and low vegetation production.

Modeling gross primary production in semi-arid Inner Mongolia using MODIS imagery and eddy covariance data

Treesearch

Ranjeet John; Jiquan Chen; Asko Noormets; Xiangming Xiao; Jianye Xu; Nan Lu; Shiping Chen

2013-01-01

We evaluate the modelling of carbon fluxes from eddy covariance (EC) tower observations in different water-limited land-cover/land-use (LCLU) and biome types in semi-arid Inner Mongolia, China. The vegetation photosynthesis model (VPM) and modified VPM (MVPM), driven by the enhanced vegetation index (EVI) and land-surface water index (LSWI), which were derived from the...

Weak associations between the daily number of suicide cases and amount of daily sunlight.

PubMed

Seregi, Bernadett; Kapitány, Balázs; Maróti-Agóts, Ákos; Rihmer, Zoltán; Gonda, Xénia; Döme, Péter

2017-02-06

Several environmental factors with periodic changes in intensity during the calendar year have been put forward to explain the increase in suicide frequency during spring and summer. In the current study we investigated the effect of averaged daily sunshine duration of periods with different lengths and 'lags' (i.e. the number of days between the last day of the period for which the averaged sunshine duration was calculated and the day of suicide) on suicide risk. We obtained data on daily numbers of suicide cases and daily sunshine duration in Hungary from 1979 to 2013. In order to remove the seasonal components from the two time series (i.e. numbers of suicide and sunshine hours) we used the differencing method. Pearson correlations (n=22,950) were calculated to reveal associations between sunshine duration and suicide risk. The final sample consisted of 122,116 suicide cases. Regarding the entire investigated period, after differencing, sunshine duration and number of suicides on the same days showed a distinctly weak, but highly significant positive correlation in the total sample (r=0.067; p=1.17*10 -13 ). Positive significant correlations (p˂0.0001) between suicide risk on the index day and averaged sunshine duration in the previous days (up to 11days) were also found in the total sample. Our results from a large sample strongly support the hypothesis that sunshine has a prompt, but very weak increasing effect on the risk of suicide (especially violent cases among males). The main limitation is that possible confounding factors were not controlled for. Copyright © 2016 Elsevier Inc. All rights reserved.

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

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.

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.

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.

High-precision coseismic displacement estimation with a single-frequency GPS receiver

NASA Astrophysics Data System (ADS)

Guo, Bofeng; Zhang, Xiaohong; Ren, Xiaodong; Li, Xingxing

2015-07-01

To improve the performance of Global Positioning System (GPS) in the earthquake/tsunami early warning and rapid response applications, minimizing the blind zone and increasing the stability and accuracy of both the rapid source and rupture inversion, the density of existing GPS networks must be increased in the areas at risk. For economic reasons, low-cost single-frequency receivers would be preferable to make the sparse dual-frequency GPS networks denser. When using single-frequency GPS receivers, the main problem that must be solved is the ionospheric delay, which is a critical factor when determining accurate coseismic displacements. In this study, we introduce a modified Satellite-specific Epoch-differenced Ionospheric Delay (MSEID) model to compensate for the effect of ionospheric error on single-frequency GPS receivers. In the MSEID model, the time-differenced ionospheric delays observed from a regional dual-frequency GPS network to a common satellite are fitted to a plane rather than part of a sphere, and the parameters of this plane are determined by using the coordinates of the stations. When the parameters are known, time-differenced ionospheric delays for a single-frequency GPS receiver could be derived from the observations of those dual-frequency receivers. Using these ionospheric delay corrections, coseismic displacements of a single-frequency GPS receiver can be accurately calculated based on time-differenced carrier-phase measurements in real time. The performance of the proposed approach is validated using 5 Hz GPS data collected during the 2012 Nicoya Peninsula Earthquake (Mw 7.6, 2012 September 5) in Costa Rica. This shows that the proposed approach improves the accuracy of the displacement of a single-frequency GPS station, and coseismic displacements with an accuracy of a few centimetres are achieved over a 10-min interval.

Numerical solution of the incompressible Navier-Stokes equations. Ph.D. Thesis - Stanford Univ., Mar. 1989

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.

1990-01-01

The current work is initiated in an effort to obtain an efficient, accurate, and robust algorithm for the numerical solution of the incompressible Navier-Stokes equations in two- and three-dimensional generalized curvilinear coordinates for both steady-state and time-dependent flow problems. This is accomplished with the use of the method of artificial compressibility and a high-order flux-difference splitting technique for the differencing of the convective terms. Time accuracy is obtained in the numerical solutions by subiterating the equations in psuedo-time for each physical time step. The system of equations is solved with a line-relaxation scheme which allows the use of very large pseudo-time steps leading to fast convergence for steady-state problems as well as for the subiterations of time-dependent problems. Numerous laminar test flow problems are computed and presented with a comparison against analytically known solutions or experimental results. These include the flow in a driven cavity, the flow over a backward-facing step, the steady and unsteady flow over a circular cylinder, flow over an oscillating plate, flow through a one-dimensional inviscid channel with oscillating back pressure, the steady-state flow through a square duct with a 90 degree bend, and the flow through an artificial heart configuration with moving boundaries. An adequate comparison with the analytical or experimental results is obtained in all cases. Numerical comparisons of the upwind differencing with central differencing plus artificial dissipation indicates that the upwind differencing provides a much more robust algorithm, which requires significantly less computing time. The time-dependent problems require on the order of 10 to 20 subiterations, indicating that the elliptical nature of the problem does require a substantial amount of computing effort.

Global Enhanced Vegetation Index

NASA Technical Reports Server (NTRS)

2002-01-01

By carefully measuring the wavelengths and intensity of visible and near-infrared light reflected by the land surface back up into space, the Moderate-resolution Imaging Spectroradiometer (MODIS) Team can quantify the concentrations of green leaf vegetation around the world. The above MODIS Enhanced Vegetation Index (EVI) map shows the density of plant growth over the entire globe. Very low values of EVI (white and brown areas) correspond to barren areas of rock, sand, or snow. Moderate values (light greens) represent shrub and grassland, while high values indicate temperate and tropical rainforests (dark greens). The MODIS EVI gives scientists a new tool for monitoring major fluctuations in vegetation and understanding how they affect, and are affected by, regional climate trends. For more information, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Land Group/Vegetation Indices, Alfredo Huete, Principal Investigator, and Kamel Didan, University of Arizona

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.

A LAI inversion algorithm based on the unified model of canopy bidirectional reflectance distribution function for the Heihe River Basin

NASA Astrophysics Data System (ADS)

Ma, B.; Li, J.; Fan, W.; Ren, H.; Xu, X.

2017-12-01

Leaf area index (LAI) is one of the important parameters of vegetation canopy structure, which can represent the growth condition of vegetation effectively. The accuracy, availability and timeliness of LAI data can be improved greatly, which is of great importance to vegetation-related research, such as the study of atmospheric, land surface and hydrological processes to obtain LAI by remote sensing method. Heihe River Basin is the inland river basin in northwest China. There are various types of vegetation and all kinds of terrain conditions in the basin, so it is helpful for testing the accuracy of the model under the complex surface and evaluating the correctness of the model to study LAI in this area. On the other hand, located in west arid area of China, the ecological environment of Heihe Basin is fragile, LAI is an important parameter to represent the vegetation growth condition, and can help us understand the status of vegetation in the Heihe River Basin. Different from the previous LAI inversion models, the BRDF (bidirectional reflectance distribution function) unified model can be applied for both continuous vegetation and discrete vegetation, it is appropriate to the complex vegetation distribution. LAI is the key input parameter of the model. We establish the inversion algorithm that can exactly retrieve LAI using remote sensing image based on the unified model. First, we determine the vegetation type through the vegetation classification map to obtain the corresponding G function, leaf and surface reflectivity. Then, we need to determine the leaf area index (LAI), the aggregation index (ζ) and the sky scattered light ratio (β) range and the value of the interval, entering all the parameters into the model to calculate the corresponding reflectivity ρ and establish the lookup table of different vegetation. Finally, we can invert LAI on the basis of the established lookup table. The principle of inversion is least squares method. We have produced 1 km LAI products from 2000 to 2014, once every 8 days. The results show that the algorithm owns good stability and can effectively invert LAI in areas with very complex vegetation and terrain conditions.

Multi-index time series monitoring of drought and fire effects on desert grasslands

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Buckley, Steven; Wallace, Cynthia S.A.; Coe, Michelle A.

2016-01-01

The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

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)).

Development and Testing of a Laboratory Spray Table Methodology to Bioassay Simulated Levels of Aerial Spray Drift

DTIC Science & Technology

2009-05-01

was measured on Mylar cards through fluorometric analysis. Plant health measures height and normalized difference vegetation index NDVI were...plant health data were used to generate dose-response relationships. Dose-response curves relating change in plant height and change in measured NDVI ...Held Sensor Model 505, NTech Industries, Inc., Ukiah, California to measure the normalized difference vegetation index NDVI which is directly

Research on the remote sensing methods of drought monitoring in Chongqing

NASA Astrophysics Data System (ADS)

Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

2011-12-01

There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.

Efficient entanglement distribution over 200 kilometers.

PubMed

Dynes, J F; Takesue, H; Yuan, Z L; Sharpe, A W; Harada, K; Honjo, T; Kamada, H; Tadanaga, O; Nishida, Y; Asobe, M; Shields, A J

2009-07-06

Here we report the first demonstration of entanglement distribution over a record distance of 200 km which is of sufficient fidelity to realize secure communication. In contrast to previous entanglement distribution schemes, we use detection elements based on practical avalanche photodiodes (APDs) operating in a self-differencing mode. These APDs are low-cost, compact and easy to operate requiring only electrical cooling to achieve high single photon detection efficiency. The self-differencing APDs in combination with a reliable parametric down-conversion source demonstrate that entanglement distribution over ultra-long distances has become both possible and practical. Consequently the outlook is extremely promising for real world entanglement-based communication between distantly separated parties.

LEAF AREA INDEX CHANGE DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN USING IKOMOS AND LANDSAT ETM+ SATELLITE DATA

EPA Science Inventory

The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

LEAF AREA INDEX (LAI) CHANGES DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN IKONOS AND LANDSAT ETM+ SATELLITE DATA

EPA Science Inventory

The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

Retrieval of wheat growth parameters with radar vegetation indices

USDA-ARS?s Scientific Manuscript database

The Radar Vegetation Index (RVI) has a low sensitivity to changes in environmental conditions and has the potential as a tool to monitor the vegetation growth. In this study, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations m...

On the geodetic applications of simultaneous range-differencing to LAGEOS

NASA Technical Reports Server (NTRS)

Pablis, E. C.

1982-01-01

The possibility of improving the accuracy of geodetic results by use of simultaneously observed ranges to Lageos, in a differencing mode, from pairs of stations was studied. Simulation tests show that model errors can be effectively minimized by simultaneous range differencing (SRD) for a rather broad class of network satellite pass configurations. The methods of least squares approximation are compared with monomials and Chebyshev polynomials and the cubic spline interpolation. Analysis of three types of orbital biases (radial, along- and across track) shows that radial biases are the ones most efficiently minimized in the SRC mode. The degree to which the other two can be minimized depends on the type of parameters under estimation and the geometry of the problem. Sensitivity analyses of the SRD observation show that for baseline length estimations the most useful data are those collected in a direction parallel to the baseline and at a low elevation. Estimating individual baseline lengths with respect to an assumed but fixed orbit not only decreases the cost, but it further reduces the effects of model biases on the results as opposed to a network solution. Analogous results and conclusions are obtained for the estimates of the coordinates of the pole.

Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

NASA Astrophysics Data System (ADS)

Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

2017-06-01

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

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.

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.

Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator)

1984-01-01

The effect different wetland plant canopies have upon observed reflectance in Thematic Mapper bands is examined. The three major vegetation canopy types (broadleaf, gramineous and leafless) produce unique spectral responses for a similar quantity of live biomass. Biomass estimates computed from spectral data were most similar to biomass estimates determined from harvest data when models developed for a specific canopy were used. Precise determination of regression coefficients for each canopy type and modeling changes in the coefficients with various combinations of canopy types are being tested. The multispectral band scanner vegetation index estimates are very similar to the vegetation index estimates.

Calibration of UAS imagery inside and outside of shadows for improved vegetation index computation

NASA Astrophysics Data System (ADS)

Bondi, Elizabeth; Salvaggio, Carl; Montanaro, Matthew; Gerace, Aaron D.

2016-05-01

Vegetation health and vigor can be assessed with data from multi- and hyperspectral airborne and satellite- borne sensors using index products such as the normalized difference vegetation index (NDVI). Recent advances in unmanned aerial systems (UAS) technology have created the opportunity to access these same image data sets in a more cost effective manner with higher temporal and spatial resolution. Another advantage of these systems includes the ability to gather data in almost any weather condition, including complete cloud cover, when data has not been available before from traditional platforms. The ability to collect in these varied conditions, meteorological and temporal, will present researchers and producers with many new challenges. Particularly, cloud shadows and self-shadowing by vegetation must be taken into consideration in imagery collected from UAS platforms to avoid variation in NDVI due to changes in illumination within a single scene, and between collection flights. A workflow is presented to compensate for variations in vegetation indices due to shadows and variation in illumination levels in high resolution imagery collected from UAS platforms. Other calibration methods that producers may currently be utilizing produce NDVI products that still contain shadow boundaries and variations due to illumination, whereas the final NDVI mosaic from this workflow does not.

Transitions in High-Arctic Vegetation Growth Patterns and Ecosystem Productivity from 2000-2013 Tracked with Cameras

NASA Astrophysics Data System (ADS)

Westergaard-Nielsen, A.; Hansen, B. U.; Klosterman, S.; Pedersen, S. H.; Schmidt, N. M.; Abermann, J.; Lund, M.

2015-12-01

The changes in vegetation seasonality in high northern latitudes resulting from changes atmospheric temperatures and precipitation are still not well understood. Continued monitoring and research is therefore needed. In this study we use 13 years of time lapse camera data and climate data from high-Arctic Northeast Greenland to assess the seasonal response of a dwarf shrub heath, grassland, and fens to snow cover, soil moisture, and atmospheric and soil temperatures. Based on the camera data, we computed a greenness index which was subsequently used to analyze transition dates in vegetation seasonality. We show that snow cover and subsequent water from the melting snow pack is highly important for the seasonality. We found a significant advancement in start of growing season of 12 days but not a significant increase in growing season length. Both the timing and greenness index value of peak of growing season was significantly correlated to the available water in the pre-melt snow pack, mostly pronounced in vegetation with limited soil water. The end of growing season was likewise significantly correlated to the water equivalents in the pre-melt snowpack. Moreover, the vegetation greenness was highly correlated to GPP, and shifts in seasonality as tracked by the greenness index are thus expected to have direct influence on ecosystem productivity.

Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices.

PubMed

Bektaş Balçik, Filiz

2014-02-01

For the past 60 years, Istanbul has been experiencing an accelerated urban expansion. This urban expansion is leading to the replacement of natural surfaces by various artificial materials. This situation has a critical impact on the environment due to the alteration of heat energy balance. In this study, the effect upon the urban heat island (UHI) of Istanbul was analyzed using 2009 dated Landsat 5 Thematic Mapper (TM) data. An Index Based Built-up Index (IBI) was used to derive artificial surfaces in the study area. To produce the IBI index, Soil-Adjusted Vegetation Index, Normalized Difference Built-up Index, and Modified Normalized Difference Water Index were calculated. Land surface temperature (LST) distribution was derived from Landsat 5 TM images using a mono-window algorithm. In addition, 24 transects were selected, and different regression models were applied to explore the correlation between LST and IBI index. The results show that artificial surfaces have a positive exponential relationship with LST rather than a simple linear one. An ecological evaluation index of the region was calculated to explore the impact of both the vegetated land and the artificial surfaces on the UHI. Therefore, the quantitative relationship of urban components (artificial surfaces, vegetation, and water) and LST was examined using multivariate statistical analysis, and the correlation coefficient was obtained as 0.829. This suggested that the areas with a high rate of urbanization will accelerate the rise of LST and UHI in Istanbul.

Applications of Radarsat-1 synthetic aperture radar imagery to assess hurricane-related flooding of coastal Louisiana

USGS Publications Warehouse

Kiage, L.M.; Walker, N.D.; Balasubramanian, S.; Babin, A.; Barras, J.

2005-01-01

The Louisiana coast is subjected to hurricane impacts including flooding of human settlements, river channels and coastal marshes, and salt water intrusion. Information on the extent of flooding is often required quickly for emergency relief, repairs of infrastructure, and production of flood risk maps. This study investigates the feasibility of using Radarsat-1 SAR imagery to detect flooded areas in coastal Louisiana after Hurricane Lili, October 2002. Arithmetic differencing and multi-temporal enhancement techniques were employed to detect flooding and to investigate relationships between backscatter and water level changes. Strong positive correlations (R2=0.7-0.94) were observed between water level and SAR backscatter within marsh areas proximate to Atchafalaya Bay. Although variations in elevation and vegetation type did influence and complicate the radar signature at individual sites, multi-date differences in backscatter largely reflected the patterns of flooding within large marsh areas. Preliminary analyses show that SAR imagery was not useful in mapping urban flooding in New Orleans after Hurricane Katrina's landfall on 29 August 2005. ?? 2005 Taylor & Francis.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Changing volatility of U.S. annual tornado reports

NASA Astrophysics Data System (ADS)

Tippett, Michael K.

2014-10-01

United States (U.S.) tornado activity results in substantial loss of life and property damage each year. A simple measure of the U.S. tornado climatology is the average number of tornadoes per year. However, even this statistic is elusive because of nonstationary behavior due in large part to changes in reporting practices. Differencing of the annual report data results in a quantity without mean trends and whose standard deviation we denote as volatility, since it is an indication of the likely year-to-year variation in the number of tornadoes reported. While volatility changes detected prior to 2000 can be associated with known reporting practice changes, an increase in volatility in the 2000s across intensity levels cannot. A volatility increase is also seen in a tornado environment index which measures the favorability of atmospheric conditions to tornado activity, providing evidence that the recent increase in tornado report volatility is related to the physical environment.

A comparison of surface biophysical properties and remotely sensed variables from FIFE

NASA Technical Reports Server (NTRS)

Sellers, Piers; Heiser, Mark; Walthall, C. W.; Huemmrich, F.; Strebel, D. E.; Hall, F. G.

1990-01-01

A method for calculating surface energy balances is investigated which incorporates the vegetation index and/or other indicators of surface conductance at visible and near-IR channels. Data from the Konza Prairie are employed to confirm the hypothesized relationship between maximum canopy conductance and the observed simple-ratio vegetation index. The relationship is established, but more data regarding soil-surface contributions are required to estimate the total surface conductance to evapotranspiration.

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.

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.

Changes in Spring Vegetation Activity over Eurasian Boreal Forest Associated with Reduction of Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Koh, Y.; Jeong, J. H.; Kim, B. M.; Park, T. W.; Jeong, S. J.

2017-12-01

Vegetation activities over the high-latitude in the Northern-Hemisphere are known to be very sensitive to climate change, which can, in turn, affect the entire climate system. This is one of the important feedback effects on global climate change. In this study, we have detected a declining trend of vegetation index in the boreal forest (Taiga) region of Eurasia in early spring from the late 1990s, and confirmed that the cause is closely related to the decrease in winter temperature linked to the Arctic sea ice change. The reduction of Arctic sea ice induces weakening of the Polar vortex around the Arctic, which has a chilling effect throughout Eurasia until the early spring (March) by strengthening the Siberian high in the Eurasian continent. The decrease of vegetation growth is caused by the extreme cold phenomenon directly affecting the growth of the boreal trees. To verify this, we used vegetation-climate coupled models to investigate climate-vegetation sensitivity to sea ice reduction. As a result, when the Arctic sea ice decreased in the model simulation, the vegetation index of the boreal forest, especially needleleaf evergreen trees, decreased as similarly detected by observations.

Monitoring vegetation greenness with satellite data

Treesearch

Robert E. Burgan; Roberta A. Hartford

1993-01-01

Vegetation greenness can be monitored at 1-km resolution for the conterminous United States through data obtained from the Advanced Very High Resolution Radiometer on the NOAA-11 weather satellites. The data are used to calculate biweekly composites of the Normalized Difference Vegetation Index. The resulting composite images are updated weekly and made available to...

Predicting Southern Appalachian overstory vegetation with digital terrain data

Treesearch

Paul V. Bolstad; Wayne Swank; James Vose

1998-01-01

Vegetation in mountainous regions responds to small-scale variation in terrain, largely due to effects on both temperature and soil moisture. However, there are few studies of quantitative, terrain-based methods for predicting vegetation composition. This study investigated relationships between forest composition, elevation, and a derived index of terrain shape, and...

A remote sensing protocol for identifying rangelands with degraded productive capacity

Treesearch

Matthew C. Reeves; L. Scott Bagget

2014-01-01

Rangeland degradation is a growing problem throughout the world. An assessment process for com-paring the trend and state of vegetation productivity to objectively derived reference conditions wasdeveloped. Vegetation productivity was estimated from 2000 to 2012 using annual maximum Normalized Difference Vegetation Index (NDVI) from the MODIS satellite platform. Each...

Automatic Target Recognition for Hyperspectral Imagery

DTIC Science & Technology

2012-03-01

representation, b) NDVI representation .... 13 Figure 6. Vegetation Reflectance Spectra, taken directly from (Eismann, 2011) ........... 15 Figure 7...46 Figure 22. Example NDVI Mean and Shade Spectrum Signatures ................................. 47 Figure 23. Example Average...locate vegetation within an image normalized-difference vegetation index ( NDVI ) is applied. NDVI was first introduced by Rouse et al. while monitoring

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.

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.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland.

PubMed

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

NASA Astrophysics Data System (ADS)

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

The Circumpolar Arctic Vegetation Map: AVHRR-derived base maps, environmental controls, and integrated mapping procedures

Treesearch

D. A. WALKER; W. A. GOULD; MAIERH. A.; M. K. RAYNOLDS

2002-01-01

A new false-colour-infrared image derived from biweekly 1993 and 1995 Advanced Very High Resolution Radiometer (AVHRR) data provides a snow-free and cloud-free base image for the interpretation of vegetation as part of a 1:7.5M-scale Circumpolar Arctic Vegetation Map (CAVM). A maximum-NDVI (Normalized DiVerence Vegetation Index) image prepared from the same data...

Is grazing exclusion effective in restoring vegetation in degraded alpine grasslands in Tibet, China?

PubMed Central

Yan, Yan

2015-01-01

Overgrazing is considered one of the key disturbance factors that results in alpine grassland degradation in Tibet. Grazing exclusion by fencing has been widely used as an approach to restore degraded grasslands in Tibet since 2004. Is the grazing exclusion management strategy effective for the vegetation restoration of degraded alpine grasslands? Three alpine grassland types were selected in Tibet to investigate the effect of grazing exclusion on plant community structure and biomass. Our results showed that species biodiversity indicators, including the Pielou evenness index, the Shannon–Wiener diversity index, and the Simpson dominance index, did not significantly change under grazing exclusion conditions. In contrast, the total vegetation cover, the mean vegetation height of the community, and the aboveground biomass were significantly higher in the grazing exclusion grasslands than in the free grazed grasslands. These results indicated that grazing exclusion is an effective measure for maintaining community stability and improving aboveground vegetation growth in alpine grasslands. However, the statistical analysis showed that the growing season precipitation (GSP) plays a more important role than grazing exclusion in which influence on vegetation in alpine grasslands. In addition, because the results of the present study come from short term (6–8 years) grazing exclusion, it is still uncertain whether these improvements will be continuable if grazing exclusion is continuously implemented. Therefore, the assessments of the ecological effects of the grazing exclusion management strategy on degraded alpine grasslands in Tibet still need long term continued research. PMID:26157607

Is grazing exclusion effective in restoring vegetation in degraded alpine grasslands in Tibet, China?

PubMed

Yan, Yan; Lu, Xuyang

2015-01-01

Overgrazing is considered one of the key disturbance factors that results in alpine grassland degradation in Tibet. Grazing exclusion by fencing has been widely used as an approach to restore degraded grasslands in Tibet since 2004. Is the grazing exclusion management strategy effective for the vegetation restoration of degraded alpine grasslands? Three alpine grassland types were selected in Tibet to investigate the effect of grazing exclusion on plant community structure and biomass. Our results showed that species biodiversity indicators, including the Pielou evenness index, the Shannon-Wiener diversity index, and the Simpson dominance index, did not significantly change under grazing exclusion conditions. In contrast, the total vegetation cover, the mean vegetation height of the community, and the aboveground biomass were significantly higher in the grazing exclusion grasslands than in the free grazed grasslands. These results indicated that grazing exclusion is an effective measure for maintaining community stability and improving aboveground vegetation growth in alpine grasslands. However, the statistical analysis showed that the growing season precipitation (GSP) plays a more important role than grazing exclusion in which influence on vegetation in alpine grasslands. In addition, because the results of the present study come from short term (6-8 years) grazing exclusion, it is still uncertain whether these improvements will be continuable if grazing exclusion is continuously implemented. Therefore, the assessments of the ecological effects of the grazing exclusion management strategy on degraded alpine grasslands in Tibet still need long term continued research.

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.

[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.

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.

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.

Semisupervised GDTW kernel-based fuzzy c-means algorithm for mapping vegetation dynamics in mining region using normalized difference vegetation index time series

NASA Astrophysics Data System (ADS)

Jia, Duo; Wang, Cangjiao; Lei, Shaogang

2018-01-01

Mapping vegetation dynamic types in mining areas is significant for revealing the mechanisms of environmental damage and for guiding ecological construction. Dynamic types of vegetation can be identified by applying interannual normalized difference vegetation index (NDVI) time series. However, phase differences and time shifts in interannual time series decrease mapping accuracy in mining regions. To overcome these problems and to increase the accuracy of mapping vegetation dynamics, an interannual Landsat time series for optimum vegetation growing status was constructed first by using the enhanced spatial and temporal adaptive reflectance fusion model algorithm. We then proposed a Markov random field optimized semisupervised Gaussian dynamic time warping kernel-based fuzzy c-means (FCM) cluster algorithm for interannual NDVI time series to map dynamic vegetation types in mining regions. The proposed algorithm has been tested in the Shengli mining region and Shendong mining region, which are typical representatives of China's open-pit and underground mining regions, respectively. Experiments show that the proposed algorithm can solve the problems of phase differences and time shifts to achieve better performance when mapping vegetation dynamic types. The overall accuracies for the Shengli and Shendong mining regions were 93.32% and 89.60%, respectively, with improvements of 7.32% and 25.84% when compared with the original semisupervised FCM algorithm.

Vegetation recovery patterns assessment at landslides caused by catastrophic earthquake: a case study in central Taiwan.

PubMed

Chou, Wen-Chieh; Lin, Wen-Tzu; Lin, Chao-Yuan

2009-05-01

The catastrophic earthquake, 7.3 on the Richter scale, occurred on September 21, 1999 in Central Taiwan. Much of standing vegetation on slopes was eliminated and massive, scattered landslides were induced at the Jou-Jou Mountain area of the Wu-Chi basin in Nantou County. We evaluated three methods for assessing landslide hazard and vegetation recovery conditions. (1) Self-organizing map (SOM) neural network coupled with fuzzy technique was used to quickly extract the landslide. (2) The NDVI-based vegetation recovery index derived from multi-temporal SPOT satellite images was used to evaluate vegetation recovery rate in the denudation sites. (3) The spatial distribution index (SDI) based on land-cover topographic location was employed to analyze vegetation recovery patterns, including the invading, surviving and mixed patterns at the Jou-Jou Mountain area. On September 27, 1999, there were 849.20 ha of landslide area extracted using the self-organizing map and fuzzy technique combined model. After six years of natural vegetation succession, the landslide has gradually restored, and vegetation recovery rate reached up to 86%. On-site observation shows that many native pioneer plants have invaded onto the denudation sites even if disturbed by several typhoons. Two native surviving plants, Arundo formosana Hack and Pinus taiwanensis Hayata, play a vital role in natural vegetation succession in this area, especially for the sites on ridgeline and steep slopes.

Vegetation Cover based on Eagleson's Ecohydrological Optimality in Northeast China Transect (NECT)

NASA Astrophysics Data System (ADS)

Cong, Z.; Mo, K.; Qinshu, L.; Zhang, L.

2016-12-01

Vegetation is considered as the indicator of climate, thus the study of vegetation growth and distribution is of great importance to cognize the ecosystem construction and functions. Vegetation cover is used as an important index to describe vegetation conditions. In Eagleson's ecohydrological optimality, the theoretical optimal vegetation cover M* can be estimated by solving water balance equations. In this study, the theory is applied in the Northeast China Transect (NECT), one of International Geosphere-Biosphere Programs (IGBP) terrestrial transects. The spatial distribution of actual vegetation cover M, which is derived from Normalized Vegetation Index (NDVI) from Moderate-resolution Imaging Spectroradiometer (MODIS), shows that there is a significant gradient ranging from 1 in the east forests to 0 in the west desert. The result indicates that the theoretical M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). The reasonable calculated proportion of water balance components further demonstrates the applicability of the ecohydrological optimality theory. M* increases with the increase of LAI, leaf angle, stem fraction and temperature, and decreases with the increase of precipitation amount. This method offers the possibility to analyze the impacts of climate change to vegetation cover quantitatively, thus providing advices for eco-restoration projects.

Effects of Telecoupling on Global Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Viña, A.; Liu, J.

2016-12-01

With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

Assessment of soil-vegetation cover condition in river basins applying remote sensing data

NASA Astrophysics Data System (ADS)

Mishchenko, Natalia; Petrosian, Janna; Shirkin, Leonid; Repkin, Roman

2017-04-01

Constant observation of vegetation and soil cover is one of the key issues of river basins ecologic monitoring. Lately remotely determining vegetation indices have been used for this purpose alongside with terrestrial data. It is necessary to consider that observation objects have been continuously changing and these changes are comprehensive and depend on temporal and dimensional parameters. Remote sensing data, embracing vast areas and reflecting various interrelations, allow excluding accidental and short-term changes though concentrating on the transformation of the observed river basin ecosystem environmental condition. The research objective is to assess spatial - temporal peculiarities and the dynamics of soil-vegetation condition of the Klyazma basin as whole and minor river basins within the area. Research objects are located in the centre of European Russia. Data used in our research include both statistic and published data, characterizing soil-vegetation cover of the area, space images («Landsat» ETM+ etc.) Research methods. 1. Dynamics analysis NDVI (Normalized difference vegetation index) 2. Remote data have been correlated to terrestrial measurement results of phytomass reserve, phytoproductivity, soil fertility characteristics, crop capacity (http://biodat.ru) 3. For the digital processing of space images software Erdas Imagine has been used, GIS analysis has been carried out applying Arc GIS. NDVI computation for each image pixel helped to map general condition of the Klyazma vegetation cover and to determine geographic ranges without vegetation or with depressed vegetation. For instance high vegetation index geographic range has been defined which corresponded to Vladimir Opolye characterized with the most fertile grey forest soil in the region. Comparative assessment of soil vegetation cover of minor river basins within the Klyazma basin, judging by the terrestrial data, revealed its better condition in the Koloksha basin which is also located in the area of grey forest soil. Besides here the maximum value of vegetation index for all phytocenosis was detected. In the research the most dynamically changing parts of the Klyazma basin have been determined according to NDVI dynamics analysis. Analyzing the reasons for such changes of NDVI the most significant ecologic processes in the region connected to the changes of vegetation cover condition have been revealed. Fields overgrowing and agricultural crops replacement are the most important of them.

Improving the prediction of African savanna vegetation variables using time series of MODIS products

NASA Astrophysics Data System (ADS)

Tsalyuk, Miriam; Kelly, Maggi; Getz, Wayne M.

2017-09-01

African savanna vegetation is subject to extensive degradation as a result of rapid climate and land use change. To better understand these changes detailed assessment of vegetation structure is needed across an extensive spatial scale and at a fine temporal resolution. Applying remote sensing techniques to savanna vegetation is challenging due to sparse cover, high background soil signal, and difficulty to differentiate between spectral signals of bare soil and dry vegetation. In this paper, we attempt to resolve these challenges by analyzing time series of four MODIS Vegetation Products (VPs): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR) for Etosha National Park, a semiarid savanna in north-central Namibia. We create models to predict the density, cover, and biomass of the main savanna vegetation forms: grass, shrubs, and trees. To calibrate remote sensing data we developed an extensive and relatively rapid field methodology and measured herbaceous and woody vegetation during both the dry and wet seasons. We compared the efficacy of the four MODIS-derived VPs in predicting vegetation field measured variables. We then compared the optimal time span of VP time series to predict ground-measured vegetation. We found that Multiyear Partial Least Square Regression (PLSR) models were superior to single year or single date models. Our results show that NDVI-based PLSR models yield robust prediction of tree density (R2 = 0.79, relative Root Mean Square Error, rRMSE = 1.9%) and tree cover (R2 = 0.78, rRMSE = 0.3%). EVI provided the best model for shrub density (R2 = 0.82) and shrub cover (R2 = 0.83), but was only marginally superior over models based on other VPs. FPAR was the best predictor of vegetation biomass of trees (R2 = 0.76), shrubs (R2 = 0.83), and grass (R2 = 0.91). Finally, we addressed an enduring challenge in the remote sensing of semiarid vegetation by examining the transferability of predictive models through space and time. Our results show that models created in the wetter part of Etosha could accurately predict trees' and shrubs' variables in the drier part of the reserve and vice versa. Moreover, our results demonstrate that models created for vegetation variables in the dry season of 2011 could be successfully applied to predict vegetation in the wet season of 2012. We conclude that extensive field data combined with multiyear time series of MODIS vegetation products can produce robust predictive models for multiple vegetation forms in the African savanna. These methods advance the monitoring of savanna vegetation dynamics and contribute to improved management and conservation of these valuable ecosystems.

Fourth order exponential time differencing method with local discontinuous Galerkin approximation for coupled nonlinear Schrodinger equations

DOE PAGES

Liang, Xiao; Khaliq, Abdul Q. M.; Xing, Yulong

2015-01-23

In this paper, we study a local discontinuous Galerkin method combined with fourth order exponential time differencing Runge-Kutta time discretization and a fourth order conservative method for solving the nonlinear Schrödinger equations. Based on different choices of numerical fluxes, we propose both energy-conserving and energy-dissipative local discontinuous Galerkin methods, and have proven the error estimates for the semi-discrete methods applied to linear Schrödinger equation. The numerical methods are proven to be highly efficient and stable for long-range soliton computations. Finally, extensive numerical examples are provided to illustrate the accuracy, efficiency and reliability of the proposed methods.

A numerical study of the axisymmetric Couette-Taylor problem using a fast high-resolution second-order central scheme

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

Kupferman, R.

The author presents a numerical study of the axisymmetric Couette-Taylor problem using a finite difference scheme. The scheme is based on a staggered version of a second-order central-differencing method combined with a discrete Hodge projection. The use of central-differencing operators obviates the need to trace the characteristic flow associated with the hyperbolic terms. The result is a simple and efficient scheme which is readily adaptable to other geometries and to more complicated flows. The scheme exhibits competitive performance in terms of accuracy, resolution, and robustness. The numerical results agree accurately with linear stability theory and with previous numerical studies.

Response functions of free mass gravitational wave antennas

NASA Technical Reports Server (NTRS)

Estabrook, F. B.

1985-01-01

The work of Gursel, Linsay, Spero, Saulson, Whitcomb and Weiss (1984) on the response of a free-mass interferometric antenna is extended. Starting from first principles, the earlier work derived the response of a 2-arm gravitational wave antenna to plane polarized gravitational waves. Equivalent formulas (generalized slightly to allow for arbitrary elliptical polarization) are obtained by a simple differencing of the '3-pulse' Doppler response functions of two 1-arm antennas. A '4-pulse' response function is found, with quite complicated angular dependences for arbitrary incident polarization. The differencing method can as readily be used to write exact response functions ('3n+1 pulse') for antennas having multiple passes or more arms.

Tracking and Data Relay Satellite System (TDRSS) Support of User Spacecraft without TDRSS Transponders

NASA Technical Reports Server (NTRS)

Jackson, James A.; Marr, Greg C.; Maher, Michael J.

1995-01-01

NASA GSFC VNS TSG personnel have proposed the use of TDRSS to obtain telemetry and/or S-band one-way return Doppler tracking data for spacecraft which do not have TDRSS-compatible transponders and therefore were never considered candidates for TDRSS support. For spacecraft with less stable local oscillators (LO), one-way return Doppler tracking data is typically of poor quality. It has been demonstrated using UARS, WIND, and NOAA-J tracking data that the simultaneous use of two TDRSS spacecraft can yield differenced one-way return Doppler data of high quality which is usable for orbit determination by differencing away the effects of oscillator instability.

Flux splitting algorithms for two-dimensional viscous flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun; Liou, Meng-Sing

1989-01-01

The Roe flux difference splitting method was extended to treat 2-D viscous flows with nonequilibrium chemistry. The derivations have avoided unnecessary assumptions or approximations. For spatial discretization, the second-order Roe upwind differencing is used for the convective terms and central differencing for the viscous terms. An upwind-based TVD scheme is applied to eliminate oscillations and obtain a sharp representation of discontinuities. A two-state Runge-Kutta method is used to time integrate the discretized Navier-Stokes and species transport equations for the asymptotic steady solutions. The present method is then applied to two types of flows: the shock wave/boundary layer interaction problems and the jet in cross flows.

Flux splitting algorithms for two-dimensional viscous flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun; Liou, Meng-Sing

1989-01-01

The Roe flux-difference splitting method has been extended to treat two-dimensional viscous flows with nonequilibrium chemistry. The derivations have avoided unnecessary assumptions or approximations. For spatial discretization, the second-order Roe upwind differencing is used for the convective terms and central differencing for the viscous terms. An upwind-based TVD scheme is applied to eliminate oscillations and obtain a sharp representation of discontinuities. A two-stage Runge-Kutta method is used to time integrate the discretized Navier-Stokes and species transport equations for the asymptotic steady solutions. The present method is then applied to two types of flows: the shock wave/boundary layer interaction problems and the jet in cross flows.

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.

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

Soil Erosion Risk Map based on irregularity of the vegetative activity

NASA Astrophysics Data System (ADS)

Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

2016-04-01

Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified Fournier Index on NDVI values seems to synthesize the different parameters of the USLE, referring to rainfall, soil, geomorphology and vegetation cover. Acknowledgements Authors are grateful to TALE project (CICYT PCIN-2014-080) and DURERO project (Env.C1.3913442) for their financial support. References Fournier, F. (1960), Climat et erosion. P.U.F. Paris. Jensen, J.R. (2000). Remote Sensing of the Environment: An Earth Resource Perpective, Prentice Hall, New Jersey. Martínez Sotoca, J. J. (2014) estructura espacial de la sequía en pastos y sus aplicaciones en el seguro agrario indexado. (In Spanish) Master Thesis, UPM. Shamshad, A., Azhari M.N., Isaac, M.H., wan Hussin, W.M.A., Parida, B.P.. (2008). Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia. Catena, 72, 423-432. van der Knijff, J.M., Jones, R.J.A., Montanarella, L. (1999). Soil Erosion Risk Assessment Italy Soil Erosion Risk Assessment in Italy. European Commission Soil Bureau Joint Research Centre European Commission. EUR 19022EN.

Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

NASA Technical Reports Server (NTRS)

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

1989-01-01

Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

Remote sensing of temperate coniferous forest lead area index - The influence of canopy closure, understory vegetation and background reflectance

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

1990-01-01

Consideration is given to the effects of canopy closure, understory vegetation, and background reflectance on the relationship between Landsat TM data and the leaf area index (LAI) of temperate coniferous forests in the western U.S. A methodology for correcting TM data for atmospheric conditions and sun-surface-sensor geometry is discussed. Strong inverse curvilinear relationships were found between coniferous forest LAI and TM bands 3 and 5. It is suggested that these inverse relationships are due to increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI.

Evaluation of the photochemical reflectance index in AVIRIS imagery

NASA Technical Reports Server (NTRS)

Gamon, John A.; Roberts, Dar A.; Green, Robert O.

1995-01-01

In this paper, we evaluate the potential for extracting the 'photochemical reflectance index' (PRI; previously called the 'physiological reflectance index') from AVIRIS data. This index, which is derived from narrow-band reflectance at 531 and 570 nm, has proven to be a useful indicator of photosynthetic function at the leaf and canopy scales. At the leaf level, PRI varies with photosynthetic capacity, radiation-use efficiency, and vegetation type (unpublished data). This finding is consistent with the hypothesis that vegetation types exhibiting chronically reduced photosynthesis during periods of stress (e.g. drought-tolerant evergreens) invest proportionally more in photoprotective processes than vegetation with high photosynthetic capacity (e.g. crops or deciduous perennials). Vertical transects in tropical and boreal forest canopies have indicated declines in PRI associated with downregulation of photosynthesis at the canopy tops under sunny, dry midday conditions (unpublished data). This reduced PRI in upper canopy levels provides a further basis for examining this signal with the 'view from above' afforded by aircraft overflights. Although many factors could confound interpretation of a subtle physiological signal at the landscape scale, we conducted a preliminary examination of PRI extracted from existing, AVIRIS imagery of Stanford University's Jasper Ridge Biological Preserve obtained on the June 2nd, 1992, overflight. The goal was to use the hyperspectral capabilities of AVIRIS to evaluate the potential of this index for obtaining useful physiological data at the landscape scale. The expectation based on leaf- and canopy-level studies was that regions containing vegetation of reduced photosynthetic capacity (e.g. chaparral or evergreen woodland) would exhibit lower PRI values than regions of high capacity (e.g. deciduous woodland).

Using remotely sensed vegetation indices to model ecological pasture conditions in Kara-Unkur watershed, Kyrgyzstan

NASA Astrophysics Data System (ADS)

Masselink, Loes; Baartman, Jantiene; Verbesselt, Jan; Borchardt, Peter

2017-04-01

Kyrgyzstan has a long history of nomadic lifestyle in which pastures play an important role. However, currently the pastures are subject to severe grazing-induced degradation. Deteriorating levels of biomass, palatability and biodiversity reduce the pastures' productivity. To counter this and introduce sustainable pasture management, up-to-date information regarding the ecological conditions of the pastures is essential. This research aimed to investigate the potential of a remote sensing-based methodology to detect changing ecological pasture conditions in the Kara-Unkur watershed, Kyrgyzstan. The relations between Vegetation Indices (VIs) from Landsat ETM+ images and biomass, palatability and species richness field data were investigated. Both simple and multiple linear regression (MLR) analyses, including terrain attributes, were applied. Subsequently, trends of these three pasture conditions were mapped using time series analysis. The results show that biomass is most accurately estimated by a model including the Modified Soil Adjusted Vegetation Index (MSAVI) and a slope factor (R2 = 0.65, F = 0.0006). Regarding palatability, a model including the Enhanced Vegetation Index (EVI), Northness Index, Near Infrared (NIR) and Red band was most accurate (R2 = 0.61, F = 0.0160). Species richness was most accurately estimated by a model including Topographic Wetness Index (TWI), Eastness Index and estimated biomass (R2 = 0.81, F = 0.0028). Subsequent trend analyses of all three estimated ecological pasture conditions presented very similar trend patterns. Despite the need for a more robust validation, this study confirms the high potential of a remote sensing based methodology to detect changing ecological pasture conditions.

Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

NASA Astrophysics Data System (ADS)

Guzinski, R.; Anderson, M. C.; Kustas, W. P.; Nieto, H.; Sandholt, I.

2013-02-01

The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observation from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. Land-cover based modifications to the Priestley-Taylor scheme, used to estimate transpiration fluxes, are explored based on prior findings for conifer forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Treesearch

Yulong Zhang; Conghe Song; Lawrence E. Band; Ge Sun; Junxiang Li

2017-01-01

Accurately monitoring global vegetation dynamics with modern remote sensing is critical for understanding the functions and processes of the biosphere and its interactions with the planetary climate. The MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) product has been a primary data source for this purpose. To date, theMODIS teamhad released...

A COMPARISON OF THE SALINITY REGIME ALONG THE TEXAS COAST WITH TERRESTRIAL VEGETATION GREENNESS AND WATER USE IN THE GALVESTON BAY WATERSHED USING REMOTING SENSING

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (A VHRR) flown on NOAA satellites. NDVI variability was compared with reg...

TERRESTRIAL VEGETATION GREENNESS OF THE LOWER GALVESTON BAY WATERSHED FROM SATELLITE REMOTE SENSING AND ITS RELATION TO WATER AND THE SALINITY REGIME OF THE GALVESTON BAY ESTUARY

EPA Science Inventory

Spatial and temporal variability of vegetation greenness have been determined for coastal Texas using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR). Results are presented on relationships between grou...

Habitat fragmentation effects on the orchid bee communities in remnant forests of southeastern Brazil.

PubMed

Knoll, Fátima do Rosário Naschenveng; Penatti, N C

2012-10-01

The effect of habitat fragmentation on the structure of orchid bee communities was analyzed by the investigation of the existence of a spatial structure in the richness and abundance of Euglossini species and by determining the relationship between these data and environmental factors. The surveys were carried out in four different forest fragments and one university campus. Richness, abundance, and diversity of species were analyzed in relation to abiotic (size of the area, extent of the perimeter, perimeter/area ratio, and shape index) and biotic characteristics (vegetation index of the fragment and of the matrix of each of the locations studied). We observed a highly significant positive correlation between the diversity index and the vegetation index of the fragment, landscape and shape index. Our analysis demonstrated that the observed variation could be explained mainly by the vegetation index and the size of the fragment. Variations in relative abundance showed a tendency toward an aggregated spatial distribution between the fragments studied, as well as between the sampling stations within the same habitat, demonstrating the existence of a spatial structure on a small scale in the populations of Euglossini. This distribution will determine the composition of species that coexist in the area after fragmentation. These data help in understanding the differences and similarities in the structure of communities of Euglossini resulting from forest fragmentation.

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

McHugh, P.R.; Ramshaw, J.D.

MAGMA is a FORTRAN computer code designed to viscous flow in in situ vitrification melt pools. It models three-dimensional, incompressible, viscous flow and heat transfer. The momentum equation is coupled to the temperature field through the buoyancy force terms arising from the Boussinesq approximation. All fluid properties, except density, are assumed variable. Density is assumed constant except in the buoyancy force terms in the momentum equation. A simple melting model based on the enthalpy method allows the study of the melt front progression and latent heat effects. An indirect addressing scheme used in the numerical solution of the momentum equationmore » voids unnecessary calculations in cells devoid of liquid. Two-dimensional calculations can be performed using either rectangular or cylindrical coordinates, while three-dimensional calculations use rectangular coordinates. All derivatives are approximated by finite differences. The incompressible Navier-Stokes equations are solved using a new fully implicit iterative technique, while the energy equation is differenced explicitly in time. Spatial derivatives are written in conservative form using a uniform, rectangular, staggered mesh based on the marker and cell placement of variables. Convective terms are differenced using a weighted average of centered and donor cell differencing to ensure numerical stability. Complete descriptions of MAGMA governing equations, numerics, code structure, and code verification are provided. 14 refs.« less

Progress in multi-dimensional upwind differencing

NASA Technical Reports Server (NTRS)

Vanleer, Bram

1992-01-01

Multi-dimensional upwind-differencing schemes for the Euler equations are reviewed. On the basis of the first-order upwind scheme for a one-dimensional convection equation, the two approaches to upwind differencing are discussed: the fluctuation approach and the finite-volume approach. The usual extension of the finite-volume method to the multi-dimensional Euler equations is not entirely satisfactory, because the direction of wave propagation is always assumed to be normal to the cell faces. This leads to smearing of shock and shear waves when these are not grid-aligned. Multi-directional methods, in which upwind-biased fluxes are computed in a frame aligned with a dominant wave, overcome this problem, but at the expense of robustness. The same is true for the schemes incorporating a multi-dimensional wave model not based on multi-dimensional data but on an 'educated guess' of what they could be. The fluctuation approach offers the best possibilities for the development of genuinely multi-dimensional upwind schemes. Three building blocks are needed for such schemes: a wave model, a way to achieve conservation, and a compact convection scheme. Recent advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results are presented, illustrating the potential of the new multi-dimensional schemes.

Vegetative resistance to flow in South Florida; summary of vegetation sampling at sites NESRS3 and P33, Shark River slough, April 1996

USGS Publications Warehouse

Carter, Virginia; Ruhl, H.; Rybicki, N.B.; Reel, J.T.; Gammon, P.T.

1999-01-01

The U.S. Geological Survey is one of many agencies participating in the effort to restore the south Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetative sampling are (1) to provide detailed information on species composition, vegetative characteristics, vegetative structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetative sampling was conducted in the Shark River Slough in April, 1996. The data collected and presented here include live, dead, and periphyton biomass, vegetation characteristics and structure, and leaf area index.

Contribution of multitemporal polarimetric synthetic aperture radar data for monitoring winter wheat and rapeseed crops

NASA Astrophysics Data System (ADS)

Betbeder, Julie; Fieuzal, Remy; Philippets, Yannick; Ferro-Famil, Laurent; Baup, Frederic

2016-04-01

This paper aims to evaluate the contribution of multitemporal polarimetric synthetic aperture radar (SAR) data for winter wheat and rapeseed crops parameters [height, leaf area index, and dry biomass (DB)] estimation, during their whole vegetation cycles in comparison to backscattering coefficients and optical data. Angular sensitivities and dynamics of polarimetric indicators were also analyzed following the growth stages of these two common crop types using, in total, 14 radar images (Radarsat-2), 16 optical images (Formosat-2, Spot-4/5), and numerous ground data. The results of this study show the importance of correcting the angular effect on SAR signals especially for copolarized signals and polarimetric indicators associated to single-bounce scattering mechanisms. The analysis of the temporal dynamic of polarimetric indicators has shown their high potential to detect crop growth changes. Moreover, this study shows the high interest of using SAR parameters (backscattering coefficients and polarimetric indicators) for crop parameters estimation during the whole vegetation cycle instead of optical vegetation index. They particularly revealed their high potential for rapeseed height and DB monitoring [i.e., Shannon entropy polarimetry (r2=0.70) and radar vegetation index (r2=0.80), respectively].

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

Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Gaustad, K. L.; Mlawer, E. J.; Long, C. N.; Delamere, J.

2011-09-01

We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Gaustad, K. L.; Mlawer, E. J.; Long, C. N.; Delamere, J.

2011-05-01

We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

Analysis of vegetation condition and its relationship with meteorological variables in the Yarlung Zangbo River Basin of China

NASA Astrophysics Data System (ADS)

Han, Xianming; Zuo, Depeng; Xu, Zongxue; Cai, Siyang; Gao, Xiaoxi

2018-06-01

The Yarlung Zangbo River Basin is located in the southwest border of China, which is of great significance to the socioeconomic development and ecological environment of Southwest China. Normalized Difference Vegetation Index (NDVI) is an important index for investigating the change of vegetation cover, which is widely used as the representation value of vegetation cover. In this study, the NDVI is adopted to explore the vegetation condition in the Yarlung Zangbo River Basin during the recent 17 years, and the relationship between NDVI and meteorological variables has also been discussed. The results show that the annual maximum value of NDVI usually appears from July to September, in which August occupies a large proportion. The minimum value of NDVI appears from January to March, in which February takes up most of the percentage. The higher values of NDVI are generally located in the lower elevation area. When the altitude is higher than 3250 m, NDVI began to decline gradually, and the NDVI became gradual stabilization as the elevation is up to 6000 m. The correlation coefficient between NDVI and precipitation in the Yarlung Zangbo River Basin is greater than that with temperature. The Hurst index of the whole basin is 0.51, indicating that the NDVI of the Yarlung Zangbo River Basin shows a weak sustainability.

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

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.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to central plains stream conditions

USGS Publications Warehouse

Griffith, J.A.; Martinko, E.A.; Whistler, J.L.; Price, K.P.

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

NASA Astrophysics Data System (ADS)

Pan, Xin; Cao, Chen; Yang, Yingbao; Li, Xiaolong; Shan, Liangliang; Zhu, Xi

2018-04-01

The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of +/-0.02 predictor perturbances, respectively.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions.

PubMed

Griffith, Jerry A; Martinko, Edward A; Whistler, Jerry L; Price, Kevin P

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

The measurement of mangrove characteristics in southwest Florida using SPOT multispectral data

NASA Technical Reports Server (NTRS)

Jensen, John R.; Lin, Hongyue; Yang, Xinghe; Ramsey, Elijah, III; Davis, Bruce A.; Thoemke, Chris W.

1991-01-01

An intensive in situ sampling program near Marco Island, Florida during 19-23 October 1988 collected information on mangrove type, maximum canopy height, and percent canopy closure. These data were correlated with selected vegetation index information derived from analysis of SPOT multispectral (XS) data obtained on 21 October 1988. The Normalized Difference (ND) vegetation index information was the most highly correlated index with percent canopy closure (r = 0.91). Percent canopy closure information can be used as a surrogate for mangrove density which is of great value when predicting which parts of the mangrove ecosystem are at greatest risk after an oil spill occurs. Such information is very valuable when constructing oil spill Environmental Sensitivity Index (ESI) Maps for tropical regions of the world.

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

An Explicit Upwind Algorithm for Solving the Parabolized Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Korte, John J.

1991-01-01

An explicit, upwind algorithm was developed for the direct (noniterative) integration of the 3-D Parabolized Navier-Stokes (PNS) equations in a generalized coordinate system. The new algorithm uses upwind approximations of the numerical fluxes for the pressure and convection terms obtained by combining flux difference splittings (FDS) formed from the solution of an approximate Riemann (RP). The approximate RP is solved using an extension of the method developed by Roe for steady supersonic flow of an ideal gas. Roe's method is extended for use with the 3-D PNS equations expressed in generalized coordinates and to include Vigneron's technique of splitting the streamwise pressure gradient. The difficulty associated with applying Roe's scheme in the subsonic region is overcome. The second-order upwind differencing of the flux derivatives are obtained by adding FDS to either an original forward or backward differencing of the flux derivative. This approach is used to modify an explicit MacCormack differencing scheme into an upwind differencing scheme. The second order upwind flux approximations, applied with flux limiters, provide a method for numerically capturing shocks without the need for additional artificial damping terms which require adjustment by the user. In addition, a cubic equation is derived for determining Vegneron's pressure splitting coefficient using the updated streamwise flux vector. Decoding the streamwise flux vector with the updated value of Vigneron's pressure splitting improves the stability of the scheme. The new algorithm is applied to 2-D and 3-D supersonic and hypersonic laminar flow test cases. Results are presented for the experimental studies of Holden and of Tracy. In addition, a flow field solution is presented for a generic hypersonic aircraft at a Mach number of 24.5 and angle of attack of 1 degree. The computed results compare well to both experimental data and numerical results from other algorithms. Computational times required for the upwind PNS code are approximately equal to an explicit PNS MacCormack's code and existing implicit PNS solvers.

Can Mapping Algorithms Based on Raw Scores Overestimate QALYs Gained by Treatment? A Comparison of Mappings Between the Roland-Morris Disability Questionnaire and the EQ-5D-3L Based on Raw and Differenced Score Data.

PubMed

Madan, Jason; Khan, Kamran A; Petrou, Stavros; Lamb, Sarah E

2017-05-01

Mapping algorithms are increasingly being used to predict health-utility values based on responses or scores from non-preference-based measures, thereby informing economic evaluations. We explored whether predictions in the EuroQol 5-dimension 3-level instrument (EQ-5D-3L) health-utility gains from mapping algorithms might differ if estimated using differenced versus raw scores, using the Roland-Morris Disability Questionnaire (RMQ), a widely used health status measure for low back pain, as an example. We estimated algorithms mapping within-person changes in RMQ scores to changes in EQ-5D-3L health utilities using data from two clinical trials with repeated observations. We also used logistic regression models to estimate response mapping algorithms from these data to predict within-person changes in responses to each EQ-5D-3L dimension from changes in RMQ scores. Predicted health-utility gains from these mappings were compared with predictions based on raw RMQ data. Using differenced scores reduced the predicted health-utility gain from a unit decrease in RMQ score from 0.037 (standard error [SE] 0.001) to 0.020 (SE 0.002). Analysis of response mapping data suggests that the use of differenced data reduces the predicted impact of reducing RMQ scores across EQ-5D-3L dimensions and that patients can experience health-utility gains on the EQ-5D-3L 'usual activity' dimension independent from improvements captured by the RMQ. Mappings based on raw RMQ data overestimate the EQ-5D-3L health utility gains from interventions that reduce RMQ scores. Where possible, mapping algorithms should reflect within-person changes in health outcome and be estimated from datasets containing repeated observations if they are to be used to estimate incremental health-utility gains.

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

Integrated NDVI images for Niger 1986-1987. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Harrington, John A., Jr.; Wylie, Bruce K.; Tucker, Compton J.

1988-01-01

Two NOAA AVHRR images are presented which provide a comparison of the geographic distribution of an integration of the normalized difference vegetation index (NDVI) for the Sahel zone in Niger for the growing seasons of 1986 and 1987. The production of the images and the application of the images for resource management are discussed. Daily large area coverage with a spatial resolution of 1.1 km at nadir were transformed to the NDVI and geographically registered to produce the images.

Comparison of AVHRR and SMMR data for monitoring vegetation phenology on a continental scale

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Choudhury, B. J.

1989-01-01

AVHRR normalized difference vegetation index (NDVI) data for a one-year period were compared with Scanning Multichannel Microwave Radiometer microwave polarization difference temperature (MPDT) data for the study of vegetation phenology. It is shown that the MPDT response differs considerably from the seasonal NDVI pattern. The results do not support the hypothetical relationship between MPDT and leaf water content. It is found that only vegetation types with a substantial seasonal variation in the areal extent of vegetated cover show strong seasonality in MPDT data.

A National Crop Progress Monitoring System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Zhang, B.; Deng, M.; Yang, Z.

2011-12-01

Crop progress is an important piece of information for food security and agricultural commodities. Timely monitoring and reporting are mandated for the operation of agricultural statistical agencies. Traditionally, the weekly reporting issued by the National Agricultural Statistics Service (NASS) of the United States Department of Agriculture (USDA) is based on reports from the knowledgeable state and county agricultural officials and farmers. The results are spatially coarse and subjective. In this project, a remote-sensing-supported crop progress monitoring system is being developed intensively using the data and derived products from NASA Earth Observing satellites. Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 product - MOD09 (Surface Reflectance) is used for deriving daily normalized vegetation index (NDVI), vegetation condition index (VCI), and mean vegetation condition index (MVCI). Ratio change to previous year and multiple year mean can be also produced on demand. The time-series vegetation condition indices are further combined with the NASS' remote-sensing-derived Cropland Data Layer (CDL) to estimate crop condition and progress crop by crop. To facilitate the operational requirement and increase the accessibility of data and products by different users, each component of the system has being developed and implemented following open specifications under the Web Service reference model of Open Geospatial Consortium Inc. Sensor observations and data are accessed through Web Coverage Service (WCS), Web Feature Service (WFS), or Sensor Observation Service (SOS) if available. Products are also served through such open-specification-compliant services. For rendering and presentation, Web Map Service (WMS) is used. A Web-service based system is set up and deployed at dss.csiss.gmu.edu/NDVIDownload. Further development will adopt crop growth models, feed the models with remotely sensed precipitation and soil moisture information, and incorporate the model results with vegetation-index time series for crop progress stage estimation.

The abundance and importance value of tree in “Sendang Kalimah Toyyibah” surrounding and its implication to the spring

NASA Astrophysics Data System (ADS)

Wiryani, Erry; Murningsih; Jumari

2018-05-01

One important factor affecting sustainability of spring is composition of vegetation around it. “Sendang Kalimah Toyyibah” is one of many springs in Semarang with intensive utilization. Vulnerability of spring can be monitored by dominant vegetation species indicated by vegetation importance value indices, especially for tree. This research aimed to study the variation of tree species around “Sendang Kalimah Toyyibah”, to analyze the importance value index of tree species and to analyze the implication of tree species which had dominant importance value index on “Sendang Kalimah Toyyibah” spring. Data collection was conducted via line transect with the length of 200 m on 4 directions which were defined based on the stream direction and the spring as the central point. Each transect has 4 observation plots occupying 20 x 20 m2. Data collection was including tree species, abundance, presence frequency and basal area of tree. Data analysis was conducted for vegetation importance value index. The result showed that around “Sendang Kalimah Toyyibah” there were 28 tree species inwhich the abundance was dominated by Mahogany (33 individuals stands), Albizia (31 stands), Coffee (20 stands), Coconut (18 stands), Mangosteen (16 stands) and Banana (16 stands). Vegetation importance value index around “Sendang Kalimah Toyyibah” was dominated by the above 7 treeswith important values (IV) respectively species including Mahogany (28,97%), Albizia (26,70%), Mangosteen (23,47%), Java Black Bamboo (22,18%), Coffee (19,23%), Coconut (17,98%) and Durian (16,41%). Cumulatively, these 7 treesspecieses dominated the importance value of tree around “Sendang Kalimah Toyyibah” which was 154,95%. These dominant species had represented the ecosystem function in infiltration, filtration and absorption of water which were required for spring ecosystem sustainability.

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

NASA Astrophysics Data System (ADS)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm for BeiDou GEO satellites. The real-time positioning results prove that the GPS + BeiDou + Galileo RT-PPP comparing to GPS-only can effectively accelerate convergence time by about 60%, improve the positioning accuracy by about 30% and obtain averaged RMS 4 cm in horizontal and 6 cm in vertical; additionally RT-SPP accuracy in the prototype system can realize positioning accuracy with about averaged RMS 1 m in horizontal and 1.5-2 m in vertical, which are improved by 60% and 70% to SPP based on broadcast ephemeris, respectively.

Characterization of drought patterns through remote sensing over The Chihuahua Desert, Mexico"

NASA Astrophysics Data System (ADS)

Madrigal, J. M.; Lopez, A.; Garatuza, J.

2013-12-01

Drought is a phenomenon that has intensified during the last few decades in the arid and semi-arid zones of northern Mexico. In the Chihuahua desert, across Chihuahua, Durango and Coahuila states has caused loss of food sustainability (agriculture, livestock), an increase in human health problems, and detriment of ecosystem services as well as important economic losses. In order to understand this phenomenon, it is necessary to create tools that allow monitoring the territory's spatial heterogeneity and multi-temporality. With this purpose we propose the implementation of a drought model which includes the traditional indexes of climatic drought, such as the Palmer Drought Severity Index PDSI, the Standardized Index of Rainfall SPI, data from meteorological stations and biophysical variations obtained from the MODIS sensors product MOD13 NDVI from 2001 to 2010, as well as biophysical variables characteristic of the environment, such as land use and vegetation coverage, Eco-regions, soil moisture, digital elevation model and irrigate agriculture districts. With the MODIS images, a spatially coherent time series was created analyzing the study area's phenology (TIMESAT) created the Seasonal Greenness (SG) and Start of Season Anomaly (SOSA) for the mentioned nine years. Through this, the annual cycles were established. With a decision tree model, all the previously mentioned proposed variables were integrated. The proposed model produces a general map which characterizes the vegetation condition (extreme drought, severe drought, moderate drought, near normal). Even though different techniques have been proposed on the monitoring of droughts, most of them generate drought indexes with a spatial resolution of 1km (Wardlow, B. et. al 2008; Levent T. et al. 2013). One of the main concerns of researchers on the matter is on improving the spatial information content and on having a better representation of the phenomenon. We use the normalized difference vegetation index (NDVI) data acquired by MODIS instead of the Advanced Very High Resolution Radiometer (AVHRR). The results show a better drought pattern characterization over The Chihuahua Desert, Mexico". The future work will consist of making a sensibility and optimization study of the variables used in the CART model, including others such as evapotranspiration and rainfall. Additionally, this work will research on the potential of using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI).

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

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.

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

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.

Assessing Plant Senescence Reflectance Index retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

NASA Astrophysics Data System (ADS)

Ren, S.; Chen, X.; An, S.

2016-12-01

Other than green vegetation indices, Plant Senescence Reflectance Index (PSRI) is sensitive to carotenoids/chlorophyll ratio in plant leaves, and shows a reversed bell curve during the growing season. Up to now, performances of PSRI in monitoring vegetation phenology are still unclear. Here, we used Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 to determine PSRI-derived start (SOS) and end (EOS) dates of the growing season in the Inner Mongolian Grassland, and validated the reliability of PSRI-derived SOS and EOS dates using Normalized Difference Vegetation Index (NDVI) derived SOS and EOS dates. Then, we conducted temporal and spatial correlation analyses between SOS/EOS date and climatic factors. Moreover, we revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA

NASA Astrophysics Data System (ADS)

El-Vilaly, Mohamed Abd Salam; Didan, Kamel; Marsh, Stuart E.; van Leeuwen, Willem J. D.; Crimmins, Michael A.; Munoz, Armando Barreto

2018-03-01

For more than a decade, the Four Corners Region has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. These persistent droughts threaten ecosystem services, agriculture, and livestock activities, and expose the hypersensitivity of this region to inter-annual climate variability and change. Much of the intermountainWestern United States has sparse climate and vegetation monitoring stations, making fine-scale drought assessments difficult. Remote sensing data offers the opportunity to assess the impacts of the recent droughts on vegetation productivity across these areas. Here, we propose a drought assessment approach that integrates climate and topographical data with remote sensing vegetation index time series. Multisensor Normalized Difference Vegetation Index (NDVI) time series data from 1989 to 2010 at 5.6 km were analyzed to characterize the vegetation productivity changes and responses to the ongoing drought. A multi-linear regression was applied to metrics of vegetation productivity derived from the NDVI time series to detect vegetation productivity, an ecosystem service proxy, and changes. The results show that around 60.13% of the study area is observing a general decline of greenness ( p<0.05), while 3.87% show an unexpected green up, with the remaining areas showing no consistent change. Vegetation in the area show a significant positive correlation with elevation and precipitation gradients. These results, while, confirming the region's vegetation decline due to drought, shed further light on the future directions and challenges to the region's already stressed ecosystems. Whereas the results provide additional insights into this isolated and vulnerable region, the drought assessment approach used in this study may be adapted for application in other regions where surface-based climate and vegetation monitoring record is spatially and temporally limited.

Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

NASA Astrophysics Data System (ADS)

Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

2018-01-01

The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

Soil moisture and vegetation patterns in northern California forests

Treesearch

James R. Griffin

1967-01-01

Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...

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.

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

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

MODIS normalized difference vegetation index (NDVI) and vegetation phenology dynamics in the Inner Mongolia grassland

NASA Astrophysics Data System (ADS)

Gong, Z.; Kawamura, K.; Ishikawa, N.; Goto, M.; Wulan, T.; Alateng, D.; Yin, T.; Ito, Y.

2015-11-01

The Inner Mongolia grassland, one of the most important grazing regions in China, has long been threatened by land degradation and desertification, mainly due to overgrazing. To understand vegetation responses over the last decade, this study evaluated trends in vegetation cover and phenology dynamics in the Inner Mongolia grassland by applying a normalized difference vegetation index (NDVI) time series obtained by the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002-2014. The results showed that the cumulative annual NDVI increased to over 77.10 % in the permanent grassland region (2002-2014). The mean value of the total change showed that the start of season (SOS) date and the peak vegetation productivity date of the season (POS) had advanced by 5.79 and 2.43 days, respectively. The end of season (EOS) was delayed by 5.07 days. These changes lengthened the season by 10.86 days. Our results also confirmed that grassland changes are closely related to spring precipitation and increasing temperature at the early growing period because of global warming. Overall, productivity in the Inner Mongolia Autonomous Region tends to increase, but in some grassland areas with grazing, land degradation is ongoing.

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Temperature and heat in informal settlements in Nairobi

PubMed Central

Misiani, Herbert; Okoth, Jerrim; Jordan, Asha; Gohlke, Julia; Ouma, Gilbert; Arrighi, Julie; Zaitchik, Ben F.; Jjemba, Eddie; Verjee, Safia; Waugh, Darryn W.

2017-01-01

Nairobi, Kenya exhibits a wide variety of micro-climates and heterogeneous surfaces. Paved roads and high-rise buildings interspersed with low vegetation typify the central business district, while large neighborhoods of informal settlements or “slums” are characterized by dense, tin housing, little vegetation, and limited access to public utilities and services. To investigate how heat varies within Nairobi, we deployed a high density observation network in 2015/2016 to examine summertime temperature and humidity. We show how temperature, humidity and heat index differ in several informal settlements, including in Kibera, the largest slum neighborhood in Africa, and find that temperature and a thermal comfort index known colloquially as the heat index regularly exceed measurements at the Dagoretti observation station by several degrees Celsius. These temperatures are within the range of temperatures previously associated with mortality increases of several percent in youth and elderly populations in informal settlements. We relate these changes to surface properties such as satellite-derived albedo, vegetation indices, and elevation. PMID:29107977

Atmospheric effects on the NDVI - Strategies for its removal. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Tanre, D.; Holben, B. N.; Markham, B.; Gitelson, A.

1992-01-01

The compositing technique used to derive global vegetation index (NDVI) from the NOAA AVHRR radiances reduces the residual effect of water vapor and aerosol on the NDVI. The reduction in the atmospheric effect is shown using a comprehensive measured data set for desert conditions, and a simulation for grass with continental aerosol. A statistical analaysis of the probability of occurrence of aerosol optical thickness and precipitable water vapor measured in different climatic regimes is used for this simulation. It is concluded that for a long compositing period (e.g., 27 days), the residual aerosol optical thickness and precipitable water vapor are usually too small to be corrected. For a 9-day compositing, the residual average aerosol effect may be about twice the correction uncertainty. For Landsat TM or Earth Observing System Moderate Resolution Imaging Spectrometer (EOS-MODIS) data, the newly defined atmospherically resistant vegetation index (ARVI) is more promising than possible direct atmospheric correction schemes, except for heavy desert dust conditions.

Temperature and heat in informal settlements in Nairobi.

PubMed

Scott, Anna A; Misiani, Herbert; Okoth, Jerrim; Jordan, Asha; Gohlke, Julia; Ouma, Gilbert; Arrighi, Julie; Zaitchik, Ben F; Jjemba, Eddie; Verjee, Safia; Waugh, Darryn W

2017-01-01

Nairobi, Kenya exhibits a wide variety of micro-climates and heterogeneous surfaces. Paved roads and high-rise buildings interspersed with low vegetation typify the central business district, while large neighborhoods of informal settlements or "slums" are characterized by dense, tin housing, little vegetation, and limited access to public utilities and services. To investigate how heat varies within Nairobi, we deployed a high density observation network in 2015/2016 to examine summertime temperature and humidity. We show how temperature, humidity and heat index differ in several informal settlements, including in Kibera, the largest slum neighborhood in Africa, and find that temperature and a thermal comfort index known colloquially as the heat index regularly exceed measurements at the Dagoretti observation station by several degrees Celsius. These temperatures are within the range of temperatures previously associated with mortality increases of several percent in youth and elderly populations in informal settlements. We relate these changes to surface properties such as satellite-derived albedo, vegetation indices, and elevation.

Normalization of multidirectional red and NIR reflectances with the SAVI

NASA Technical Reports Server (NTRS)

Huete, A. R.; Hua, G.; Qi, J.; Chehbouni, A.; Van Leeuwen, W. J. D.

1992-01-01

Directional reflectance measurements were made over a semi-desert gramma grassland at various times of the growing season. View angle measurements from +40 to -40 degrees were made at various solar zenith angles and soil moisture conditions. The sensitivity of the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI) to bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation dynamics. The SAVI view angle response was found to be symmetric about nadir while the NDVI response was strongly anisotropic. This enabled the view angle behavior of the SAVI to be normalized with a cosine function. In contrast to the NDVI, the SAVI was able to minimize soil moisture and shadow influences for all measurement conditions.

Sawgrass Density, Biomass, and Leaf Area Index: A Flume Study in Support of Research on Wind Sheltering Effects in the Florida Everglades

USGS Publications Warehouse

Rybicki, Nancy B.; Reel, Justin T.; Ruhl, Henry A.; Gammon, Patricia T.; Carter, Virginia; Lee, Jonathan K.

2000-01-01

The U.S. Geological Survey is studying the wind sheltering effects of vegetation in the Florida Everglades. In order to test both the flow resistance and wind sheltering effects of sawgrass, uniform dense stands of sawgrass were grown in a tilting flume at Stennis Space Center, Mississippi. In June, 1997, one end of the flume was covered with a wind cowling with a removable top, and a series of experiments were conducted between June, 1997 and July, 1998. During each set of experiments, the sawgrass was sampled for vegetative characteristics, biomass, and leaf area index. The results of the analyses of the vegetation samples are summarized in a series of appendixes.

Vegetative resistance to flow in south Florida; summary of vegetation sampling at sites NESRS3 and P33, Shark River slough, November, 1996

USGS Publications Warehouse

Carter, Virginia; Reel, J.T.; Rybicki, N.B.; Ruhl, H.; Gammon, P.T.; Lee, J.K.

1999-01-01

The U.S. Geological Survey is one of many agencies participating in the effort to restore the South Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetation sampling are (1) to provide detailed information on species composition, vegetation characteristics, vegetation structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetation was sampled at two sites in the Shark River Slough in November, 1996. The data collected and presented here include those for live and dead standing sawgrass, other dead material, periphyton biomass, vegetation characteristics and structure, and leaf area index.

Thermal modeling of a cryogenic turbopump for space shuttle applications.

NASA Technical Reports Server (NTRS)

Knowles, P. J.

1971-01-01

Thermal modeling of a cryogenic pump and a hot-gas turbine in a turbopump assembly proposed for the Space Shuttle is described in this paper. A model, developed by identifying the heat-transfer regimes and incorporating their dependencies into a turbopump system model, included heat transfer for two-phase cryogen, hot-gas (200 R) impingement on turbine blades, gas impingement on rotating disks and parallel plate fluid flow. The ?thermal analyzer' program employed to develop this model was the TRW Systems Improved Numerical Differencing Analyzer (SINDA). This program uses finite differencing with lumped parameter representation for each node. Also discussed are model development, simulations of turbopump startup/shutdown operations, and the effects of varying turbopump parameters on the thermal performance.

Analysis of airfoil transitional separation bubbles

NASA Technical Reports Server (NTRS)

Davis, R. L.; Carter, J. E.

1984-01-01

A previously developed local inviscid-viscous interaction technique for the analysis of airfoil transitional separation bubbles, ALESEP (Airfoil Leading Edge Separation) has been modified to utilize a more accurate windward finite difference procedure in the reversed flow region, and a natural transition/turbulence model has been incorporated for the prediction of transition within the separation bubble. Numerous calculations and experimental comparisons are presented to demonstrate the effects of the windward differencing scheme and the natural transition/turbulence model. Grid sensitivity and convergence capabilities of this inviscid-viscous interaction technique are briefly addressed. A major contribution of this report is that with the use of windward differencing, a second, counter-rotating eddy has been found to exist in the wall layer of the primary separation bubble.

Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

NASA Astrophysics Data System (ADS)

Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

2014-03-01

To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions

NASA Technical Reports Server (NTRS)

Frouin, Robert

1993-01-01

The objectives of the investigation, namely 'to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions', were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f(sub par), can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f(sub par) estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented.

Pasture Drought Insurance Based on NDVI and SAVI

NASA Astrophysics Data System (ADS)

Escribano Rodríguez, J. A.; Tarquis, A. M.; Hernandez Díaz-Ambrona, C. G.

2012-04-01

Drought is a complex phenomenon, which is difficult to define. The term is used to refer to deficiency in rainfall, soil moisture, vegetation greenness, ecological conditions or socio economic conditions, and different drought types can be inferred. In this study, drought is considered as a period when the pasture growth is low in regard to long-term average conditions. The extensive livestock production is based on the natural resources available. The good management practices concurs the maximum livestock nutrition needs with the maximum pasture availability. Therefore, early drought detection and impact assessment on the amount of pasture biomass are important in several areas in Spain, whose economy strongly depends on livestock production. The use of remote sensing data presents a number of advantages when determining drought impact on vegetation. The information covers the whole of a territory and the repetition of images provides multi-temporal measurements. In addition, vegetation indexes, being NDVI (normalized difference vegetation index) and SAVI (soil-adjusted vegetation index) the most common ones, obtainedfrom satellite data allow areas affected by droughts to be identified. These indices are being used for estimation of vegetation photosynthesis activity and monitoring drought. The present study shows the application of these vegetation indices for pasture drought monitoring in three places in Spain and their correlation with several field measurements. During 2010 and 2011 three locations, El Cubo de Don Sancho (Salamanca), Trujillo (Cáceres) and Pozoblanco (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 of the chosen places.This satellite 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. It has 6 cameras in red, green and near infrared bands, equivalent to Landsat ones. A discussion on the correlations found between field measurements and both vegetation index considering seasonal pattern and location are presented. 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. AGL2010-21501/AGR is greatly appreciated.

Distinguishing vegetation from soil background information. [by gray mapping of Landsat MSS data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Wiegand, C. L.

1977-01-01

In aircraft and satellite multispectral scanner data, soil background signals are superimposed on or intermingled with information about vegetation. A procedure which accounts for soil background would, therefore, make a considerable contribution to an operational use of Landsat and other spectral data for monitoring the productivity of range, forest, and crop lands. A description is presented of an investigation which was conducted to obtain information for the development of such a procedure. The investigation included a study of the soil reflectance that supplies the background signal of vegetated surfaces. Landsat data as recorded on computer compatible tapes were used in the study. The results of the investigation are discussed, taking into account a study reported by Kauth and Thomas (1976). Attention is given to the determination of Kauth's plane of soils, sun angle effects, vegetation index modeling, and the evaluation of vegetation indexes. Graphs are presented which show the results obtained with a gray mapping technique. The technique makes it possible to display plant, soil, water, and cloud conditions for any Landsat overpass.

Vegetation diversity protects against childhood asthma: results from a large New Zealand birth cohort.

PubMed

Donovan, Geoffrey H; Gatziolis, Demetrios; Longley, Ian; Douwes, Jeroen

2018-05-07

We assessed the association between the natural environment and asthma in 49,956 New Zealand children born in 1998 and followed up until 2016 using routinely collected data. Children who lived in greener areas, as measured by the normalized difference vegetation index, were less likely to be asthmatic: a 1 s.d. increase in normalized difference vegetation index was associated with a 6.0% (95% CI 1.9-9.9%) lower risk of asthma. Vegetation diversity was also protective: a 1 s.d. increase in the number of natural land-cover types in a child's residential meshblock was associated with a 6.7% (95% CI 1.5-11.5%) lower risk. However, not all land-cover types were protective. A 1 s.d. increase in the area covered by gorse (Ulex europaeus) or exotic conifers, both non-native, low-biodiversity land-cover types, was associated with a 3.2% (95% CI 0.0-6.0%) and 4.2% (95% CI 0.9-7.5%) increased risk of asthma, respectively. The results suggest that exposure to greenness and vegetation diversity may be protective of asthma.

Human-induced geomorphology: Modeling slope failure in Dominical, Costa Rica using Landsat imagery

NASA Astrophysics Data System (ADS)

Miller, Andrew J.

Unchecked human development has ravaged the region between Dominical and Uvita, Costa Rica. Much of the development transition has been driven by tourism and further foreign direct investment in residential, service and commercial enterprises. The resulting land-use/land-cover change has removed traditional forest cover in exchange for impervious surfaces, physical structures, and bare ground which is no longer mechanically supported by woody vegetation. Combined with a tropical climate, deeply weathered soils and lithography which are prone to erosion, land cover change has led to an increase in slope failure occurrences. Given the remoteness of the Dominical-Uvita region, its rate of growth and the lack of monitoring, new techniques for monitoring land use and slope failure susceptibility are needed. Two new indices are presented here that employ a Digital Elevation Model (DEM) and widely available Landsat imagery to assist in this endeavor. The first index, or Vegetation Influenced Landslide Index (VILI), incorporates slope derived from a DEM and Lu et al.'s (2007) Surface Cover Index to quantify vegetative cover as a means of mechanical stabilization in landslide prone areas. The second index, or Slope Multiplier Index (SMI), uses individual Landsat data bands and basic Landsat band ratios as environmental proxies to replicate soil, vegetative and hydrologic properties. Both models achieve accuracy over 70% and rival results from more complicated published literature. The accuracy of the indices was assessed with the creation of a landslide inventory developed from field observations occurring in December 2007 and November 2008. The creation of these indices represents an efficient and accurate way of determining landslide susceptibility zonation in data poor areas where environmental protection practitioners may be overextended, under-trained or both.

Detection of salt marsh vegetation stress and recovery after the Deepwater Horizon Oil Spill in Barataria Bay, Gulf of Mexico using AVIRIS data.

PubMed

Khanna, Shruti; Santos, Maria J; Ustin, Susan L; Koltunov, Alexander; Kokaly, Raymond F; Roberts, Dar A

2013-01-01

The British Petroleum Deepwater Horizon Oil Spill in the Gulf of Mexico was the biggest oil spill in US history. To assess the impact of the oil spill on the saltmarsh plant community, we examined Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data flown over Barataria Bay, Louisiana in September 2010 and August 2011. Oil contamination was mapped using oil absorption features in pixel spectra and used to examine impact of oil along the oiled shorelines. Results showed that vegetation stress was restricted to the tidal zone extending 14 m inland from the shoreline in September 2010. Four indexes of plant stress and three indexes of canopy water content all consistently showed that stress was highest in pixels next to the shoreline and decreased with increasing distance from the shoreline. Index values along the oiled shoreline were significantly lower than those along the oil-free shoreline. Regression of index values with respect to distance from oil showed that in 2011, index values were no longer correlated with proximity to oil suggesting that the marsh was on its way to recovery. Change detection between the two dates showed that areas denuded of vegetation after the oil impact experienced varying degrees of re-vegetation in the following year. This recovery was poorest in the first three pixels adjacent to the shoreline. This study illustrates the usefulness of high spatial resolution airborne imaging spectroscopy to map actual locations where oil from the spill reached the shore and then to assess its impacts on the plant community. We demonstrate that post-oiling trends in terms of plant health and mortality could be detected and monitored, including recovery of these saltmarsh meadows one year after the oil spill.

Detection of salt marsh vegetation stress and recovery after the Deepwater Horizon Oil Spill in Barataria Bay, Gulf of Mexico using AVIRIS data

USGS Publications Warehouse

Khanna, Shruti; Santos, Maria J.; Ustin, Susan L.; Koltunov, Alexander; Kokaly, Raymond F.; Roberts, Dar A.

2013-01-01

The British Petroleum Deepwater Horizon Oil Spill in the Gulf of Mexico was the biggest oil spill in US history. To assess the impact of the oil spill on the saltmarsh plant community, we examined Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data flown over Barataria Bay, Louisiana in September 2010 and August 2011. Oil contamination was mapped using oil absorption features in pixel spectra and used to examine impact of oil along the oiled shorelines. Results showed that vegetation stress was restricted to the tidal zone extending 14 m inland from the shoreline in September 2010. Four indexes of plant stress and three indexes of canopy water content all consistently showed that stress was highest in pixels next to the shoreline and decreased with increasing distance from the shoreline. Index values along the oiled shoreline were significantly lower than those along the oil-free shoreline. Regression of index values with respect to distance from oil showed that in 2011, index values were no longer correlated with proximity to oil suggesting that the marsh was on its way to recovery. Change detection between the two dates showed that areas denuded of vegetation after the oil impact experienced varying degrees of re-vegetation in the following year. This recovery was poorest in the first three pixels adjacent to the shoreline. This study illustrates the usefulness of high spatial resolution airborne imaging spectroscopy to map actual locations where oil from the spill reached the shore and then to assess its impacts on the plant community. We demonstrate that post-oiling trends in terms of plant health and mortality could be detected and monitored, including recovery of these saltmarsh meadows one year after the oil spill.

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.

Detection of Salt Marsh Vegetation Stress and Recovery after the Deepwater Horizon Oil Spill in Barataria Bay, Gulf of Mexico Using AVIRIS Data

PubMed Central

Khanna, Shruti; Santos, Maria J.; Ustin, Susan L.; Koltunov, Alexander; Kokaly, Raymond F.; Roberts, Dar A.

2013-01-01

The British Petroleum Deepwater Horizon Oil Spill in the Gulf of Mexico was the biggest oil spill in US history. To assess the impact of the oil spill on the saltmarsh plant community, we examined Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data flown over Barataria Bay, Louisiana in September 2010 and August 2011. Oil contamination was mapped using oil absorption features in pixel spectra and used to examine impact of oil along the oiled shorelines. Results showed that vegetation stress was restricted to the tidal zone extending 14 m inland from the shoreline in September 2010. Four indexes of plant stress and three indexes of canopy water content all consistently showed that stress was highest in pixels next to the shoreline and decreased with increasing distance from the shoreline. Index values along the oiled shoreline were significantly lower than those along the oil-free shoreline. Regression of index values with respect to distance from oil showed that in 2011, index values were no longer correlated with proximity to oil suggesting that the marsh was on its way to recovery. Change detection between the two dates showed that areas denuded of vegetation after the oil impact experienced varying degrees of re-vegetation in the following year. This recovery was poorest in the first three pixels adjacent to the shoreline. This study illustrates the usefulness of high spatial resolution airborne imaging spectroscopy to map actual locations where oil from the spill reached the shore and then to assess its impacts on the plant community. We demonstrate that post-oiling trends in terms of plant health and mortality could be detected and monitored, including recovery of these saltmarsh meadows one year after the oil spill. PMID:24223872

Measurement of physiological traits of paddy rice in temperature gradient chamber using Normalized Difference Vegetation Index and Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Oh, D.; Cho, J.

2017-12-01

Global warming has been affecting the phenological and physiological conditions of crop plants due to heat stress. Thus, the scientific understanding of not only crop-yield change, but also growth progress during high temperature condition is necessary. In this study, growth response and yield of paddy rice depending on air temperature (Ta) has been studied in a Temperature Gradient Chamber (TGC) that is composed of higher Ta than actual Ta (ambient temperature). The results on imitating experiment of global warming provided the reduced production of crop by heat stress. Therefore, it is important to quickly detect the condition of a plant in order to minimize damage to heat stress on global warming. Phenological and physiological changes depending on Ta was detected using optical spectroscopy sensors because remote sensing is useful and efficient technology to monitor quickly and continually. Two vegetation indices, Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI), were applied to monitor paddy rice growth using hyperspectral and multispectral radiometer. Ta in TGC was gradually set from actual Ta + 0 ° to actual Ta + 3 °. The variations of NDVI and PRI were different during rice growth period, and also these patterns were changed depending on Ta condition. NDVI and PRI under +3 ° condition increase faster than ambient temperature. After heading stage, the values of NDVI and PRI were dropped. However, the NDVI and PRI of rice under heat stress were relatively slowly decreased. In addition, we found that the yield of rice decreased in the case of delayed drop patterns of NDVI and PRI after heading stage. Our results will be useful to understand crop plant conditions using vegetation index under global warming situations.

Monitoring boreal forest leaf area index across a Siberian burn chronosequence: a MODIS validation study

USGS Publications Warehouse

Cheng, X.; Vierling, Lee; Deering, D.; Conley, A.

2005-01-01

Landscapes containing differing amounts of ecological disturbance provide an excellent opportunity to validate and better understand the emerging Moderate Resolution Imaging Spectrometer (MODIS) vegetation products. Four sites, including 1‐year post‐fire coniferous, 13‐year post‐fire deciduous, 24‐year post‐fire deciduous, and >100 year old post‐fire coniferous forests, were selected to serve as a post‐fire chronosequence in the central Siberian region of Krasnoyarsk (57.3°N, 91.6°E) with which to study the MODIS leaf area index (LAI) and vegetation index (VI) products. The collection 4 MODIS LAI product correctly represented the summer site phenologies, but significantly underestimated the LAI value of the >100 year old coniferous forest during the November to April time period. Landsat 7‐derived enhanced vegetation index (EVI) performed better than normalized difference vegetation index (NDVI) to separate the deciduous and conifer forests, and both indices contained significant correlation with field‐derived LAI values at coniferous forest sites (r 2 = 0.61 and r 2 = 0.69, respectively). The reduced simple ratio (RSR) markedly improved LAI prediction from satellite measurements (r 2 = 0.89) relative to NDVI and EVI. LAI estimates derived from ETM+ images were scaled up to evaluate the 1 km resolution MODIS LAI product; from this analysis MODIS LAI overestimated values in the low LAI deciduous forests (where LAI<5) and underestimated values in the high LAI conifer forests (where LAI>6). Our results indicate that further research on the MODIS LAI product is warranted to better understand and improve remote LAI quantification in disturbed forest landscapes over the course of the year.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.; Brooks, V.

1997-01-01

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Metric Similarity in Vegetation-Based Wetland Assessment Methods

EPA Science Inventory

Wetland vegetation is a recognized indicator group for wetland assessments, but until recently few published protocols used plant-based indicators. To examine the proliferation of such protocols since 1999, this report reviewed 20 published index of biotic integrity (IBI) type p...

Improved biobased lubricants from chemically modified vegetable oils

USDA-ARS?s Scientific Manuscript database

Vegetable oils possess a number of desirable properties for lubricant application such as excellent boundary properties, high viscosity index, low volatility, low traction coefficient, renewability, and biodegradability. Unfortunately, they also have a number of weaknesses that make them less desira...

Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India

NASA Astrophysics Data System (ADS)

Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

2017-04-01

In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal resolution of eight days, returning a set of parameters for every eight-day period of the year. Those parameters are then used to predict vegetation health based on the SWI up to 32 days after the latest available SWI and NDVI observations. In this work, the prediction was carried out for multiple eight-day periods in the year 2015 for three representative districts in India, and then compared to the actually observed NDVI during these periods, showing very similar spatial patterns in most analyzed regions and periods. This approach enables the prediction of vegetation health based on root zone soil moisture instead of relying on agro-meteorological models which often lack crucial input data in remote regions.

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

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 Development of Alternative Food Cost Indexes

DTIC Science & Technology

1974-11-01

Frozen frufts, vegetables , fruit juices , and cake mixes are added and the quantity of purchased bread increased in this FCI. Comment was made that some... Grain , Frozen Vegetables , Mixed, Frozen Beans, Green, Frozen Peaches, Canned Apples, Fresh Oranges, Fresh Strawberries, Frozen Juice , Pineapple...also falls to recognize such accepted food service practices as the use of frozen fruits , vegetables , and juices , or prepared cake mixes, Tj,e

Crop sensors for automation of in-season nitrogen application

USDA-ARS?s Scientific Manuscript database

Crop canopy reflectance sensing can be used to assess in-season crop nitrogen (N) health for automatic control of N fertilization. Typically, sensor data are processed to an established index, such as the Normalized Difference Vegetative Index (NDVI) and differences in that index from a well-fertili...

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.

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.

RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs)

NASA Astrophysics Data System (ADS)

Kefauver, Shawn C.; El-Haddad, George; Vergara-Diaz, Omar; Araus, José Luis

2015-10-01

Extreme and abnormal weather events, as well as the more gradual meteorological changes associated with climate change, often coincide with not only increased abiotic risks (such as increases in temperature and decreases in precipitation), but also increased biotic risks due to environmental conditions that favor the rapid spread of crop pests and diseases. Durum wheat is by extension the most cultivated cereal in the south and east margins of the Mediterranean Basin. It is of strategic importance for Mediterranean agriculture to develop new varieties of durum wheat with greater production potential, better adaptation to increasingly adverse environmental conditions (drought) and better grain quality. Similarly, maize is the top staple crop for low-income populations in Sub-Saharan Africa and is currently suffering from the appearance of new diseases, which, together with increased abiotic stresses from climate change, are challenging the very sustainability of African societies. Current constraints in field phenotyping remain a major bottleneck for future breeding advances, but RGB-based High-Throughput Phenotyping Platforms (HTPPs) have shown promise for rapidly developing both disease-resistant and weather-resilient crops. RGB cameras have proven costeffective in studies assessing the effect of abiotic stresses, but have yet to be fully exploited to phenotype disease resistance. Recent analyses of durum wheat in Spain have shown RGB vegetation indexes to outperform multispectral indexes such as NDVI consistently in disease and yield prediction. Towards HTTP development for breeding maize disease resistance, some of the same RGB picture vegetation indexes outperformed NDVI (Normalized Difference Vegetation Index), with R2 values up to 0.65, compared to 0.56 for NDVI. . Specifically, hue, a*, u*, and Green Area (GA), as produced by FIJI and BreedPix open source software, performed similar to or better than NDVI in predicting yield and disease severity conditions for wheat and maize. Results using UAVs (Unmanned Aerial Vehicles) have produced similar results demonstrating the robust strengths, and limitations, of the more cost-effective RGB picture indexes.

Biochemical processes in sagebrush ecosystems: Interactions with terrain

NASA Technical Reports Server (NTRS)

Matson, P. (Principal Investigator); Reiners, W.; Strong, L.

1985-01-01

The objectives of a biogeochemical study of sagebrush ecosystems in Wyoming and their interactions with terrain are as follows: to describe the vegetational pattern on the landscape and elucidate controlling variables, to measure the soil properties and chemical cycling properties associated with the vegetation units, to associate soil properties with vegetation properties as measured on the ground, to develop remote sensing capabilities for vegetation and surface characteristics of the sagebrush landscape, to develop a system of sensing snow cover and indexing seasonal soil to moisture; and to develop relationships between temporal Thematic Mapper (TM) data and vegetation phenological state.

Ecohydrological optimality in the Northeast China Transect

NASA Astrophysics Data System (ADS)

Cong, Zhentao; Li, Qinshu; Mo, Kangle; Zhang, Lexin; Shen, Hong

2017-05-01

The Northeast China Transect (NECT) is one of the International Geosphere-Biosphere Program (IGBP) terrestrial transects, where there is a significant precipitation gradient from east to west, as well as a vegetation transition of forest-grassland-desert. It is remarkable to understand vegetation distribution and dynamics under climate change in this transect. We take canopy cover (M), derived from Normalized Difference Vegetation Index (NDVI), as an index to describe the properties of vegetation distribution and dynamics in the NECT. In Eagleson's ecohydrological optimality theory, the optimal canopy cover (M*) is determined by the trade-off between water supply depending on water balance and water demand depending on canopy transpiration. We apply Eagleson's ecohydrological optimality method in the NECT based on data from 2000 to 2013 to get M*, which is compared with M from NDVI to further discuss the sensitivity of M* to vegetation properties and climate factors. The result indicates that the average M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). Results of water balance also match the field-measured data in the references. The sensitivity analyses show that M* decreases with the increase of leaf area index (LAI), stem fraction and temperature, while it increases with the increase of leaf angle and precipitation amount. Eagleson's ecohydrological optimality method offers a quantitative way to understand the impacts of climate change on canopy cover and provides guidelines for ecorestoration projects.

USE OF REMOTELY SENSED DATA FOR PARAMETERIZING AND VALIDATING LAND-USE HYDROLOGIC MODELS

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA satellites. NDVI variability was compared with regi...

Species Diversity and Bird Feed in Residential Complex

NASA Astrophysics Data System (ADS)

Hadinoto; Suhesti, Eni

2017-12-01

Bird is one component of the ecosystem which has an important role in supporting the occurrence of an organism's life cycle. Therefore, the presence of birds in an area is important, because it can affect the existence and distribution of plant species. The purpose of this study is to calculate the diversity of bird species and identify the source of bird feed in the compound. This study was conducted by field surveys in the residential complex. In addition to the birds as a research object vegetation as habitat / foraging birds were also observed. Data were analyzed by using the bird diversity index, richenes index, bundance index, dominance analysis, analysis of bird distribution and analysis of the level of meeting types, while vegetation will be analyzed based on the type and part of what is eaten by birds. In Pandau Jaya housing complex, found as many as 12 species of birds which consists of seven families. Bird species often present is Cucak Kutilang (Pycnonotus aurigaster) of 20 individuals, Bondol Peking (Lonchura punctulata) 14 individuals and Perkutut Jawa (Geopelia striata) 10 individuals. Bird species diversity (H ‘) in Pandau Jaya housing complex is still relatively moderate with a value of 2.27, while the Evenness Index (E) of 0.91 and Richenes Index (R) of 2.45. Types of vegetation as a food source, among others: mango, guava, cherry, jackfruit, ketapang, coconut, areca, palm, banana, papaya, flowers and grasses.

Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Crago, Richard

1994-01-01

Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

NASA Technical Reports Server (NTRS)

Justice, Christopher O.; Eck, T. F.; Tanre, Didier; Holben, B. N.

1991-01-01

The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

[Effects of different vegetation restoration patterns on the diversity of soil nitrogen-fixing microbes in Hulunbeier sandy land, Inner Mongolia of North China].

PubMed

Li, Gang; Wang, Li-Juan; Li, Yu-Jie; Qiao, Jiang; Zhang, Hai-Fang; Song, Xiao-Long; Yang, Dian-Lin

2013-06-01

By using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and sequence analysis, this paper studied the nifH gene diversity and community structure of soil nitrogen-fixing microbes in Hulunbeier sandy land of Inner Mongolia under four years management of five vegetation restoration modes, i. e., mixed-planting of Agropyron cristatum, Hedysarum fruticosum, Caragana korshinskii, and Elymus nutans (ACHE) and of Agropyron cristatum and Hedysarum fruticosum (AC), and mono-planting of Caragana korshinskii (UC), Agropyron cristatum (UA), and Hedysarum fruticosum (UH), taking the bare land as the control (CK). There existed significant differences in the community composition of nitrogen-fixing microbes among the five vegetation restoration patterns. The Shannon index of the nifH gene was the highest under ACHE, followed by under AC, UC, UA, and UH, and the lowest in CK. Except that UH and CK had less difference in the Shannon index, the other four vegetation restoration modes had a significantly higher Shannon index than CK (P < 0.05). The phylogenetic analysis showed that the soil nitrogen-fixing microbes under UA, UH, and UC were mainly of cyanobacteria, but the soil nitrogen-fixing microbes under AC and ACHE changed obviously, mainly of proteobacteria, and also of cyanobacteria. The canonical correlation analysis showed that the soil total phosphorus, available phosphorus, total nitrogen, and nitrate nitrogen contents under the five vegetation restoration modes had significant effects on the nitrogen-fixing microbial communities, and there existed significant correlations among the soil total phosphorus, available phosphorus, total nitrogen, and nitrate nitrogen. It was suggested that the variations of the community composition of soil nitrogen-fixing microbes under the five vegetation restoration modes were resulted from the interactive and combined effects of the soil physical and chemical factors.

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

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.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

2017-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R (sup 2) equals 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R (sup 2) is greater than 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Fast Image Subtraction Using Multi-cores and GPUs

NASA Astrophysics Data System (ADS)

Hartung, Steven; Shukla, H.

2013-01-01

Many important image processing techniques in astronomy require a massive number of computations per pixel. Among them is an image differencing technique known as Optimal Image Subtraction (OIS), which is very useful for detecting and characterizing transient phenomena. Like many image processing routines, OIS computations increase proportionally with the number of pixels being processed, and the number of pixels in need of processing is increasing rapidly. Utilizing many-core graphical processing unit (GPU) technology in a hybrid conjunction with multi-core CPU and computer clustering technologies, this work presents a new astronomy image processing pipeline architecture. The chosen OIS implementation focuses on the 2nd order spatially-varying kernel with the Dirac delta function basis, a powerful image differencing method that has seen limited deployment in part because of the heavy computational burden. This tool can process standard image calibration and OIS differencing in a fashion that is scalable with the increasing data volume. It employs several parallel processing technologies in a hierarchical fashion in order to best utilize each of their strengths. The Linux/Unix based application can operate on a single computer, or on an MPI configured cluster, with or without GPU hardware. With GPU hardware available, even low-cost commercial video cards, the OIS convolution and subtraction times for large images can be accelerated by up to three orders of magnitude.

Association between Frequency of Consumption of Fruit, Vegetables, Nuts and Pulses and BMI: Analyses of the International Study of Asthma and Allergies in Childhood (ISAAC).

PubMed

Wall, Clare R; Stewart, Alistair W; Hancox, Robert J; Murphy, Rinki; Braithwaite, Irene; Beasley, Richard; Mitchell, Edwin A

2018-03-07

Diets which emphasize intakes of plant-based foods are recommended to reduce disease risk and for promoting healthy weight. The aim of this study was to examine the association between fruit, vegetables, pulses and nut intake and body mass index (BMI) across countries in adolescents (13-14 years) and children (6-7 years). Data from the International Study of Asthma and Allergies in Childhood; 77,243 children's parents and 201,871 adolescents was used to examine the association between dietary intake (Food Frequency Questionnaire) and BMI using general linear models, adjusting for country gross national index. Adolescents who consumed fruit, vegetables, pulses and nuts three or more times a week had a lower BMI than the never or occasional group; eating nuts three or more times a week, was associated with a BMI value of 0.274 kg/m² lower than the never group ( p < 0.001). Compared to children who never or occasionally reported eating vegetables, those reporting that they ate vegetables three or more times per week had a lower BMI of -0.079 kg/m². In this large global study, an inverse association was observed between BMI and the reported increasing intake of vegetables in 6-7 years old and fruit, vegetables, pulses and nuts in adolescents. This study supports current dietary recommendations which emphasize the consumption of vegetables, nut and pulses, although the effect sizes were small.

Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s

USGS Publications Warehouse

Stow, D.; Daeschner, Scott; Hope, A.; Douglas, David C.; Petersen, A.; Myneni, Ranga B.; Zhou, L.; Oechel, W.

2003-01-01

The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

Wetland habitat disturbance best predicts metrics of an amphibian index of biotic integrity

USGS Publications Warehouse

Stapanian, Martin A.; Micacchion, Mick; Adams, Jean V.

2015-01-01

Regression and classification trees were used to identify the best predictors of the five component metrics of the Ohio Amphibian Index of Biotic Integrity (AmphIBI) in 54 wetlands in Ohio, USA. Of the 17 wetland- and surrounding landscape-scale variables considered, the best predictor for all AmphIBI metrics was habitat alteration and development within the wetland. The results were qualitatively similar to the best predictors for a wetland vegetation index of biotic integrity, suggesting that similar management practices (e.g., reducing or eliminating nutrient enrichment from agriculture, mowing, grazing, logging, and removing down woody debris) within the boundaries of the wetland can be applied to effectively increase the quality of wetland vegetation and amphibian communities.

Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data. [Great Plains

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A. (Principal Investigator)

1978-01-01

The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

Elastohydrodynamics of farm-based blends comprising amphiphilic oils

USDA-ARS?s Scientific Manuscript database

Vegetable oils contain non-polar hydrocarbon chains and polar ester groups (and possibly also other functional groups such as hydroxyl groups in castor oil). The presence of polar and non-polar groups within the same molecule gives vegetable oil amphiphilic character. The density, refractive index, ...

A MODIS-based vegetation index climatology

USDA-ARS?s Scientific Manuscript database

Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

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...

Vegetative and reproductive phenology of a floodplain tree species Barringtonia acutangula from North East India.

PubMed

Nath, Shikhasmita; Nath, Arun Jyoti; Das, Ashesh Kumar

2016-03-01

Vegetative and reproductive phenology of Barringtonia acutangula, a floodplain tree species was studied at Chatla floodplain, Assam North East India with the aim to investigate vegetative and reproductive phenology under stressful environment of seasonal submergence and to assess the impact of environmental variables (temperature and precipitation) on tree phenophases. Quantitative assessment was made at 15 day interval for all the phenophases (leaf initiation, leaf-fall, flowering and fruiting) by tagging 40 (forty) trees over aperiod of two years (2012-14).To test seasonal influence on the phenology of Barringtonia acutangula different phenophases were correlated with environmental variables and statistical spearman's rank correlation coefficient was employed. Aridity index was computed that delineate influence of rainfall and temperature together on any phenophases. Leaf initiation showed positively significant correlation with temperature (r(s) = 0.601, p = < .05) during the year 2012-2013 whereas it was significantly correlated with rainfall (r(s) = 0.583, p = < .05) and aridity index (r(s) = 0.583, p = < .05) during the year 2013-2014. Leaf-fall was significant negatively correlated with temperature (r(s) = -0.623, p = < .05), rainfall (r(s) = -0.730, p = < .01) and aridity index (r(s) = -0.730, p = < .01) for both the studied years. Flowering was significantly influenced by temperature (r(s) = 0.639, p = < .05), rainfall (r(s) = 0.890, p = < .01) and aridity index (r(s) = 0.890, p = < .01) while in one month lag flowering was significantly correlated with rainfall (r(s) = 0.678, p = < .01) in 2012-13. Fruiting was also positively significant with temperature (r(s) = 0.795, P < .05), rainfall (r(s) = 0.835, P < .01) and aridity index (r(s) = 0.835, P < .01) for both the years. During one month lag period fruiting was positively correlated with temperature, rainfall and aridity index in both the years. Temperature, rainfall and aridity index were major determinants of the various vegetative and reproductive phenology of B. acutangula and any changes in these variables in future due to climate change, might have profound effect on phenophases of this tree species.

Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

NASA Astrophysics Data System (ADS)

Smith, W. K.; Biederman, J. A.; Scott, R. L.; Moore, D. J. P.; He, M.; Kimball, J. S.; Yan, D.; Hudson, A.; Barnes, M. L.; MacBean, N.; Fox, A. M.; Litvak, M. E.

2018-01-01

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under-represented by long-term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite-derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar-induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen-dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. These results suggest that incorporation of SIF could significantly improve satellite-based GPP estimates.

Forage quantity estimation from MERIS using band depth parameters

NASA Astrophysics Data System (ADS)

Ullah, Saleem; Yali, Si; Schlerf, Martin

Saleem Ullah1 , Si Yali1 , Martin Schlerf1 Forage quantity is an important factor influencing feeding pattern and distribution of wildlife. The main objective of this study was to evaluate the predictive performance of vegetation indices and band depth analysis parameters for estimation of green biomass using MERIS data. Green biomass was best predicted by NBDI (normalized band depth index) and yielded a calibration R2 of 0.73 and an accuracy (independent validation dataset, n=30) of 136.2 g/m2 (47 % of the measured mean) compared to a much lower accuracy obtained by soil adjusted vegetation index SAVI (444.6 g/m2, 154 % of the mean) and by other vegetation indices. This study will contribute to map and monitor foliar biomass over the year at regional scale which intern can aid the understanding of bird migration pattern. Keywords: Biomass, Nitrogen density, Nitrogen concentration, Vegetation indices, Band depth analysis parameters 1 Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands

Pre-school obesity is inversely associated with vegetable intake, grocery stores and outdoor play

PubMed Central

Kepper, M.; Tseng, T.-S.; Volaufova, J.; Scribner, R.; Nuss, H.; Sothern, M.

2016-01-01

Summary The study determined the association between body mass index (BMI) [B-Z] score and fruit and vegetable intake, frequency and ratio of fast food outlets and grocery stores in concentric areas around the child’s residence, outdoor play and total crime index. Data from 78 Louisiana pre-school children were analyzed using Pearson’s correlation and multiple regression analysis. Parental-reported fruit intake was linearly associated with increased number of grocery store counts in concentric areas around the child’s residence (P = 0.0406, P = 0.0281). Vegetable intake was inversely (P = 0.04) and the ratio of fast food outlets to grocery stores in a 2-mile concentric area around the child’s residence was positively (P = 0.05) associated to BMI z score after applying Best Model regression analysis (F = 3.06, P = 0.0346). Children residing in neighbourhoods with greater access to fast foods and lower access to fruits and vegetables may be at higher risk for developing obesity during pre-school years. PMID:26305391

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2000-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2001-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Walker, Jeffrey; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Use of Normalized Difference Vegetation Index (NDVI) habitat models to predict breeding birds on the San Pedro River, Arizona

USGS Publications Warehouse

McFarland, Tiffany Marie; van Riper, Charles

2013-01-01

Successful management practices of avian populations depend on understanding relationships between birds and their habitat, especially in rare habitats, such as riparian areas of the desert Southwest. Remote-sensing technology has become popular in habitat modeling, but most of these models focus on single species, leaving their applicability to understanding broader community structure and function largely untested. We investigated the usefulness of two Normalized Difference Vegetation Index (NDVI) habitat models to model avian abundance and species richness on the upper San Pedro River in southeastern Arizona. Although NDVI was positively correlated with our bird metrics, the amount of explained variation was low. We then investigated the addition of vegetation metrics and other remote-sensing metrics to improve our models. Although both vegetation metrics and remotely sensed metrics increased the power of our models, the overall explained variation was still low, suggesting that general avian community structure may be too complex for NDVI models.

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.

Possible causes of Arctic Tundra Vegetation Productivity Declines

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Bieniek, P.; Epstein, H. E.; Comiso, J. C.; Pinzon, J. E.; Tucker, C. J.

2017-12-01

Three decades of remotely sensed Normalized Difference Vegetation Index (NDVI) data document an overall increase in Arctic tundra vegetation greenness but the trends display considerable spatial variability. Pan-Arctic tundra vegetation greening is associated with increases in summer warmth that are, in large-part, driven by summer sea-ice retreat along Arctic coasts. Trends covering the period 1982-2016 are overall positive for summer open water, Summer Warmth Index (SWI, the sum of the degree months above zero from May-August), MaxNDVI (peak NDVI) and time integrated NDVI (TI-NDVI, sum of biweekly NDVI above 0.05 from May-September). Upon closer examination, it is clear that not all regions have positive trends, for example, there is an area of cooling in western Eurasia, which is broadly co-located with maxNDVI and TI-NDVI declines. While sea ice decline has continued over the satellite record, summer landsurface temperatures and vegetation productivity measures have not simply increased. Regional differences between warming and greening trends suggest that it is likely that multiple processes influence vegetation productivity beyond secular greening with increased summer warmth. This paper will present Pan-Arctic and regional analyses of the NDVI data in the context of climate drivers. Other possible drivers of vegetation productivity decline will be discussed such as increased standing water, delayed spring snow-melt, and winter thaw events. The status and limitations of data sets and modeling needed to advance our understanding of tundra vegetation productivity will be summarized and will serve as a starting point for planning the next steps in this topic. Methodical multi-disciplinary synthesis research that jointly considers vegetation type, permafrost conditions, altitude, as well as climate factors such as temperature, heat and moisture transport, and timing of snowfall and spring snowmelt is needed to better understand recent tundra vegetation productivity declines.

Remote sensing of solar radiation absorbed and reflected by vegetated land surfaces

NASA Technical Reports Server (NTRS)

Myneni, Ranga B.; Asrar, Ghassem; Tanre, Didier; Choudhury, Bhaskar J.

1992-01-01

1D and 3D radiative-transfer models have been used to investigate the problem of remotely sensed determination of vegetated land surface-absorbed and reflected solar radiation. Calculations were conducted for various illumination conditions to determine surface albedo, soil- and canopy-absorbed photosynthetically active and nonactive radiation, and normalized difference vegetation index. Simple predictive models are developed on the basis of the relationships among these parameters.

Eleventh-year response of loblolly pine and competing vegetation to woody and herbaceous plant control on a Georgia flatwoods site

Treesearch

Bruce R. Zutter; James H. Miller

1998-01-01

Through 11 growing seasons, growth of loblolly pine (Pinus taeda L.) increased after control of herbaceous, woody, or both herbaceous and woody vegetation (total control) for the first 3 years after planting on a bedded site in the Georgia coastal flatwoods. Gains in stand volume index from controlling either herbaceous or woody vegetation alone were approximately two-...

An approach to drought data web-dissemination

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Perez, Francesca; Balbo, Simone; Cámaro, Walther; Boccardo, Piero

2017-04-01

Drought data dissemination has always been a challenge for the scientific community. Firstly, a variety of widely known datasets is currently being used to describe different aspects of this same phenomenon. Secondly, new indexes are constantly being produced by scientists trying to better capture drought events. The present work aims at presenting how the drought monitoring communication issue was addressed by the ITHACA team. The ITHACA drought monitoring system makes use of two indicators: the Standardized Precipitation Index (SPI) and the Seasonal Small Integral Deviation (SSID). The first one is obtained considering the 3-months cumulating interval of the rainfall derived from the TRMM dataset; the second one is the percent deviation from the historical average value of the integral of the NDVI function describing the vegetation season. The SPI and the SSID are 30 and 5 km gridded respectively. The whole time-series of these two indicators (since year 2000 onwards), covering the whole Africa, are published by a WebGIS platform (http://drought.ithacaweb.org). On the one hand, although the SPI has been used for decades in different contexts and little explanation is due when presenting this indicator to an audience with a scientific background, the WebGIS platform shows a guide for its correct interpretation. On the other hand, being the SSID not commonly used in the field of vegetation analysis, the guide shown on the WebGIS platform is essential for the visitor to understand the data. Recently a new index has been created in order to synthesize, for a non-expert audience, the information provided by the indicators. It is aggregated per second order administrative levels and is calculated as follows: (i) a meteorological drought warning is issued when negative SPI and no vegetative season is detected (a blue palette is used); (ii) a warning value is assigned if SSID, SPI, or both, are negative (amber to brown palette is used) i.e., where the vegetative season is ongoing and the SSID is negative, a negative SPI value entails an agricultural drought warning, while a positive SPI implies a vegetation stress warning; (iv) a meteorological drought warning is issued when negative SPI during the vegetation season is detected but vegetation stress effects are not (i.e. positive SSID). The latest available Drought Warning Index is also published on the mentioned WebGIS platform. The index is stored in a database table: a single value is calculated for each administrative level. A table view on the database contains fields describing the geometry of the administrative level polygons and the respective index; this table view is published as a WMS service, by associating the symbology previously described. The WMS service is then captured in order to generate a live map with a series of basic WebGIS functionalities. The integrated index is undoubtedly useful for a non-expert user to understand immediately if a particular region is subject to a drought stress. However, the simplification introduces uncertainty as it implies several assumptions that couldn't be verified at a continental scale.

Shorter Harvest Cycles Counteract Increasing Annual Productivity in Industrial Plantation Forests: Trends from Three Decades of Remote Sensing in Southeastern Brazil

NASA Astrophysics Data System (ADS)

McMahon, D.; Jackson, R. B.

2017-12-01

Plantation forestry can produce woody biomass many times faster than native vegetation, particularly in the tropical regions where plantations have expanded rapidly in the past three decades. However, activists and practitioners have raised concerns over the sustainability of intensive plantations, suggesting that changes to soil properties may inhibit vegetation growth after multiple harvest cycles. We use a 32-year time series of remotely sensed vegetation indices derived from Landsat data, coupled with recent geospatial and wood volume data from plantation companies, to identify trends in management and vegetation productivity in thousands of individual eucalyptus plantation stands. We find that peak vegetation index values at canopy closure, which are correlated with annual wood volume increment, increase over successive harvest cycles, while the length of each cycle decreases. These opposing trends suggest that the number of harvests required to produce a given wood volume peaks around the second harvest cycle and then declines, likely due to refinement of management practices. Across the region, vegetation index data do not support the hypothesized decrease in productivity over multiple harvest cycles. Additional field data and ongoing soil analyses will complement the remote sensing approach to quantifying plantations' long-term effects on the land they occupy.

On the effect of using the Shapiro filter to smooth winds on a sphere

NASA Technical Reports Server (NTRS)

Takacs, L. L.; Balgovind, R. C.

1984-01-01

Spatial differencing schemes which are not enstrophy conserving nor implicitly damping require global filtering of short waves to eliminate the build-up of energy in the shortest wavelengths due to aliasing. Takacs and Balgovind (1983) have shown that filtering on a sphere with a latitude dependent damping function will cause spurious vorticity and divergence source terms to occur if care is not taken to ensure the irrotationality of the gradients of the stream function and velocity potential. Using a shallow water model with fourth-order energy-conserving spatial differencing, it is found that using a 16th-order Shapiro (1979) filter on the winds and heights to control nonlinear instability also creates spurious source terms when the winds are filtered in the meridional direction.

Black hole evolution by spectral methods

NASA Astrophysics Data System (ADS)

Kidder, Lawrence E.; Scheel, Mark A.; Teukolsky, Saul A.; Carlson, Eric D.; Cook, Gregory B.

2000-10-01

Current methods of evolving a spacetime containing one or more black holes are plagued by instabilities that prohibit long-term evolution. Some of these instabilities may be due to the numerical method used, traditionally finite differencing. In this paper, we explore the use of a pseudospectral collocation (PSC) method for the evolution of a spherically symmetric black hole spacetime in one dimension using a hyperbolic formulation of Einstein's equations. We demonstrate that our PSC method is able to evolve a spherically symmetric black hole spacetime forever without enforcing constraints, even if we add dynamics via a Klein-Gordon scalar field. We find that, in contrast with finite-differencing methods, black hole excision is a trivial operation using PSC applied to a hyperbolic formulation of Einstein's equations. We discuss the extension of this method to three spatial dimensions.

Best-Practice Criteria for Practical Security of Self-Differencing Avalanche Photodiode Detectors in Quantum Key Distribution

NASA Astrophysics Data System (ADS)

Koehler-Sidki, A.; Dynes, J. F.; Lucamarini, M.; Roberts, G. L.; Sharpe, A. W.; Yuan, Z. L.; Shields, A. J.

2018-04-01

Fast-gated avalanche photodiodes (APDs) are the most commonly used single photon detectors for high-bit-rate quantum key distribution (QKD). Their robustness against external attacks is crucial to the overall security of a QKD system, or even an entire QKD network. We investigate the behavior of a gigahertz-gated, self-differencing (In,Ga)As APD under strong illumination, a tactic Eve often uses to bring detectors under her control. Our experiment and modeling reveal that the negative feedback by the photocurrent safeguards the detector from being blinded through reducing its avalanche probability and/or strengthening the capacitive response. Based on this finding, we propose a set of best-practice criteria for designing and operating fast-gated APD detectors to ensure their practical security in QKD.

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...

Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data

NASA Astrophysics Data System (ADS)

Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

2018-03-01

In this paper, Bayesian inversion of a physically-based forest reflectance model is investigated to estimate of boreal forest canopy leaf area index (LAI) from EO-1 Hyperion hyperspectral data. The data consist of multiple forest stands with different species compositions and structures, imaged in three phases of the growing season. The Bayesian estimates of canopy LAI are compared to reference estimates based on a spectral vegetation index. The forest reflectance model contains also other unknown variables in addition to LAI, for example leaf single scattering albedo and understory reflectance. In the Bayesian approach, these variables are estimated simultaneously with LAI. The feasibility and seasonal variation of these estimates is also examined. Credible intervals for the estimates are also calculated and evaluated. The results show that the Bayesian inversion approach is significantly better than using a comparable spectral vegetation index regression.

Hydrologic index development and application to selected Coastwide Reference Monitoring System sites and Coastal Wetlands Planning, Protection and Restoration Act projects

USGS Publications Warehouse

Snedden, Gregg A.; Swenson, Erick M.

2012-01-01

Hourly time-series salinity and water-level data are collected at all stations within the Coastwide Reference Monitoring System (CRMS) network across coastal Louisiana. These data, in addition to vegetation and soils data collected as part of CRMS, are used to develop a suite of metrics and indices to assess wetland condition in coastal Louisiana. This document addresses the primary objectives of the CRMS hydrologic analytical team, which were to (1) adopt standard time-series analytical techniques that could effectively assess spatial and temporal variability in hydrologic characteristics across the Louisiana coastal zone on site, project, basin, and coastwide scales and (2) develop and apply an index based on wetland hydrology that can describe the suitability of local hydrology in the context of maximizing the productivity of wetland plant communities. Approaches to quantifying tidal variability (least squares harmonic analysis) and partitioning variability of time-series data to various time scales (spectral analysis) are presented. The relation between marsh elevation and the tidal frame of a given hydrograph is described. A hydrologic index that integrates water-level and salinity data, which are collected hourly, with vegetation data that are collected annually is developed. To demonstrate its utility, the hydrologic index is applied to 173 CRMS sites across the coast, and variability in index scores across marsh vegetation types (fresh, intermediate, brackish, and saline) is assessed. The index is also applied to 11 sites located in three Coastal Wetlands Planning, Protection and Restoration Act projects, and the ability of the index to convey temporal hydrologic variability in response to climatic stressors and restoration measures, as well as the effect that this community may have on wetland plant productivity, is illustrated.

Developing a vulnerability index for assessing riverbank erosion in large catchments

NASA Astrophysics Data System (ADS)

Regan, Siôn; Smith, Hugh

2017-04-01

Riverbank erosion is a natural process involved in floodplain development, but can have negative impacts such as excessive sediment supply to the river channel, undermining infrastructure and eroding valuable agricultural land. Catchment managers often work with limited budgets and for remediation efforts to be the most effective they should be targeted in areas that are at the highest risk of suffering excessive riverbank erosion. Recent developments in high resolution spatial data capture, such as aerial LiDAR have allowed for much more detailed representation of the riparian area, including the channel location and riparian vegetation. This presentation will propose a new dimensionless index that has been developed to identify and rank sections of river channel according to erosion vulnerability. The index combines information on channel position, slope and curvature extracted from LiDAR-derived DEMs with riparian vegetation cover. It also accounts for the extent of lateral confinement limiting erosion and bank silt-clay composition influencing erodibility. The index is designed to be applied to alluvial channels across large catchments (>500 km2) to support the identification riverbank erosion 'hotspots' at the reach scale (approximating 50-200 m intervals). The performance of the vulnerability index in discriminating actively eroding and non-eroding channel reaches was assessed in the River Lugg catchment, UK. Historic mapping and aerial photographs were used to determine the channel position, slope and riparian vegetation coverage in the 1960s. The index was then calculated for the historic river channel position and compared with ranked metrics of lateral channel change that occurred between the 1960s and present. This approach provides a basis for evaluating the utility of a simple vulnerability index that could be used for prioritising the location of future investments to reduce excessive riverbank erosion in large catchments.

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.

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.

Validation of Vegetation Index Time Series from Suomi NPP Visible Infrared Imaging Radiometer Suite Using Tower Radiation Flux Measurements

NASA Astrophysics Data System (ADS)

Miura, T.; Kato, A.; Wang, J.; Vargas, M.; Lindquist, M.

2015-12-01

Satellite vegetation index (VI) time series data serve as an important means to monitor and characterize seasonal changes of terrestrial vegetation and their interannual variability. It is, therefore, critical to ensure quality of such VI products and one method of validating VI product quality is cross-comparison with in situ flux tower measurements. In this study, we evaluated the quality of VI time series derived from Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft by cross-comparison with in situ radiation flux measurements at select flux tower sites over North America and Europe. VIIRS is a new polar-orbiting satellite sensor series, slated to replace National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer in the afternoon overpass and to continue the highly-calibrated data streams initiated with Moderate Resolution Imaging Spectrometer of National Aeronautics and Space Administration's Earth Observing System. The selected sites covered a wide range of biomes, including croplands, grasslands, evergreen needle forest, woody savanna, and open shrublands. The two VIIRS indices of the Top-of-Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI) and the atmospherically-corrected, Top-of-Canopy (TOC) Enhanced Vegetation Index (EVI) (daily, 375 m spatial resolution) were compared against the TOC NDVI and a two-band version of EVI (EVI2) calculated from tower radiation flux measurements, respectively. VIIRS and Tower VI time series showed comparable seasonal profiles across biomes with statistically significant correlations (> 0.60; p-value < 0.01). "Start-of-season (SOS)" phenological metric values extracted from VIIRS and Tower VI time series were also highly compatible (R2 > 0.95), with mean differences of 2.3 days and 5.0 days for the NDVI and the EVI, respectively. These results indicate that VIIRS VI time series can capture seasonal evolution of vegetated land surface as good as in situ radiometric measurements. Future studies that address biophysical or physiological interpretations of Tower VI time series derived from radiation flux measurements are desirable.

What's Being Served for Dinner? An Exploratory Investigation of the Associations between the Healthfulness of Family Meals and Child Dietary Intake.

PubMed

Trofholz, Amanda C; Tate, Allan D; Draxten, Michelle L; Rowley, Seth S; Schulte, Anna K; Neumark-Sztainer, Dianne; MacLehose, Richard F; Berge, Jerica M

2017-01-01

Little is known about the healthfulness of foods offered at family meals or the relationship between the food's healthfulness and child overall dietary intake. This exploratory study uses a newly developed Healthfulness of Meal Index to examine the association between the healthfulness of foods served at family dinners and child dietary intake. Direct observational, cross-sectional study. Primarily low-income, minority families (n=120) video recorded 8 days of family dinners and completed a corresponding meal screener. Dietary recalls were completed on the target child (6 to 12 years old). The Healthfulness of Meal Index was used to measure meal healthfulness and included component scores for whole fruit, 100% juice, vegetables, dark green vegetables, dairy, protein, added sugars, and high-sodium foods. Child dietary intake measured by three 24-hour dietary recalls. Linear regression models estimated the association between the healthfulness of foods served at dinner meals and overall child HEI. The majority of coded meals included foods from protein and high-sodium components; more than half included foods from dairy and vegetable components. Nearly half of the meals had an added-sugar component food (eg, soda or dessert). Few meals served foods from fruit, 100% juice, or dark green vegetable components. Many components served at family dinner meals were significantly associated with child daily intake of those same foods (ie, dark green vegetable, non-dark green vegetables, dairy, and added sugars). The Healthfulness of Meal Index total score was significantly associated with child HEI score. This study represents the first report of a new methodology to collect data of foods served at family dinners. Results indicated a significant association between the majority of components served at family dinner meals and child overall dietary intake. Validation of the Healthfulness of Meal Index and video-recorded family meal methodology is needed to strengthen these research methods for use in future studies. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

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.

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.

DEVELOPMENT OF AN INDEX OF ALIEN SPECIES INVASIVENESS: AN AID TO ASSESSING RIPARIAN VEGETATION CONDITION

EPA Science Inventory

Many riparian areas are invaded by alien plant species that negatively affect native species composition, community dynamics and ecosystem properties. We sampled vegetation along reaches of 31 low order streams in eastern Oregon, and characterized species assemblages at patch an...

Vegetation Cover Change in Yosemite National Park (California) Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Landsat image analysis over the past 20+ years showed that consistent increases in the satellite normalized difference vegetation index (NDVI) during relatively dry years were confined to large wildfire areas that burned in the late 1980s and 1990s.

Validation of the ANOCOVA model for regional scale ECa-ECe calibration

USDA-ARS?s Scientific Manuscript database

Over the past decade two approaches have emerged as the preferred means for assessing salinity at regional scale: (1) vegetative indices from satellite imagery (e.g., MODIS enhanced vegetative index, NDVI, etc.) and (2) analysis of covariance (ANOCOVA) calibration of apparent soil electrical conduct...

Revisiting the relationship between managed care and hospital consolidation.

PubMed

Town, Robert J; Wholey, Douglas; Feldman, Roger; Burns, Lawton R

2007-02-01

This paper analyzes whether the rise in managed care during the 1990s caused the increase in hospital concentration. We assemble data from the American Hospital Association, InterStudy and government censuses from 1990 to 2000. We employ linear regression analyses on long differenced data to estimate the impact of managed care penetration on hospital consolidation. Instrumental variable analogs of these regressions are also analyzed to control for potential endogeneity. All data are from secondary sources merged at the level of the Health Care Services Area. In 1990, the mean population-weighted hospital Herfindahl-Hirschman index (HHI) in a Health Services Area was .19. By 2000, the HHI had risen to .26. Most of this increase in hospital concentration is due to hospital consolidation. Over the same time frame HMO penetration increased three fold. However, our regression analysis strongly implies that the rise of managed care did not cause the hospital consolidation wave. This finding is robust to a number of different specifications.

Revisiting the Relationship between Managed Care and Hospital Consolidation

PubMed Central

Town, Robert J; Wholey, Douglas; Feldman, Roger; Burns, Lawton R

2007-01-01

Objective This paper analyzes whether the rise in managed care during the 1990s caused the increase in hospital concentration. Data Sources We assemble data from the American Hospital Association, InterStudy and government censuses from 1990 to 2000. Study Design We employ linear regression analyses on long differenced data to estimate the impact of managed care penetration on hospital consolidation. Instrumental variable analogs of these regressions are also analyzed to control for potential endogeneity. Data Collection All data are from secondary sources merged at the level of the Health Care Services Area. Principle Findings In 1990, the mean population-weighted hospital Herfindahl–Hirschman index (HHI) in a Health Services Area was .19. By 2000, the HHI had risen to .26. Most of this increase in hospital concentration is due to hospital consolidation. Over the same time frame HMO penetration increased three fold. However, our regression analysis strongly implies that the rise of managed care did not cause the hospital consolidation wave. This finding is robust to a number of different specifications. PMID:17355590

The Causal Effect of Education on Health: What is the Role of Health Behaviors?

PubMed

Brunello, Giorgio; Fort, Margherita; Schneeweis, Nicole; Winter-Ebmer, Rudolf

2016-03-01

We investigate the causal effect of education on health and the part of it that is attributable to health behaviors by distinguishing between short-run and long-run mediating effects: whereas, in the former, only behaviors in the immediate past are taken into account, in the latter, we consider the entire history of behaviors. We use two identification strategies: instrumental variables based on compulsory schooling reforms and a combined aggregation, differencing, and selection on an observables technique to address the endogeneity of both education and behaviors in the health production function. Using panel data for European countries, we find that education has a protective effect for European men and women aged 50+. We find that the mediating effects of health behaviors-measured by smoking, drinking, exercising, and the body mass index-account in the short run for around a quarter and in the long run for around a third of the entire effect of education on health. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images

NASA Astrophysics Data System (ADS)

Shang, Jiali; Liu, Jiangui; Huffman, Ted; Qian, Budong; Pattey, Elizabeth; Wang, Jinfei; Zhao, Ting; Geng, Xiaoyuan; Kroetsch, David; Dong, Taifeng; Lantz, Nicholas

2014-01-01

This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping within-field variability of crop growth conditions and tracking the seasonal growth dynamics. The study was carried out in southern Ontario, Canada, during the 2013 growing season for three annual crops, corn, soybeans, and winter wheat. Plant area index (PAI) was measured at different growth stages using digital hemispherical photography at two corn fields, two winter wheat fields, and two soybean fields. Comparison between several conventional vegetation indices derived from concurrently acquired image data by the two sensors showed a good agreement. The two-band enhanced vegetation index (EVI2) and the normalized difference vegetation index (NDVI) were derived from the surface reflectance of the two sensors. The study showed that EVI2 was more resistant to saturation at high biomass range than NDVI. A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R2) of 0.85 and root-mean-square error of 0.53. The estimated multitemporal product of green PAI was found to be able to capture the seasonal dynamics of the three crops.

Development of digital interactive processing system for NOAA satellites AVHRR data

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Murthy, N. N.

The paper discusses the digital image processing system for NOAA/AVHRR data including Land applications - configured around VAX 11/750 host computer supported with FPS 100 Array Processor, Comtal graphic display and HP Plotting devices; wherein the system software for relational Data Base together with query and editing facilities, Man-Machine Interface using form, menu and prompt inputs including validation of user entries for data type and range; preprocessing software for data calibration, Sun-angle correction, Geometric Corrections for Earth curvature effect and Earth rotation offsets and Earth location of AVHRR image have been accomplished. The implemented image enhancement techniques such as grey level stretching, histogram equalization and convolution are discussed. The software implementation details for the computation of vegetative index and normalized vegetative index using NOAA/AVHRR channels 1 and 2 data together with output are presented; scientific background for such computations and obtainability of similar indices from Landsat/MSS data are also included. The paper concludes by specifying the further software developments planned and the progress envisaged in the field of vegetation index studies.

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.

Analysis of vegetation changes in Cidanau watershed, Indonesia

NASA Astrophysics Data System (ADS)

Khairiah, R. N.; Kunihiko, Y.; Prasetyo, L. B.; Setiawan, Y.

2018-05-01

Vegetation change detection is needed for conserve of quality and water cycle in Cidanau watershed. The NDVI was applied to quantify the vegetation changes of Cidanau watershed for three different years 1989, 2001, and 2015. Using NDVI we mapped the reflectance from chlorophyll and distinguished varying amounts of vegetation at the pixel level by index. In the present study, as a preliminary study, we proposed a vegetation change detection analysis based on the NDVI from 1989 through 2015. Multi-temporal satellite data i.e. Landsat imagery with 30 m spatial resolution are used in the present study. It is reported that agroforestry land exhibited the greatest reductions in highly dense vegetation class in 1989-2001 and also moderate vegetation class in 2001-2015. It’s mean that amount of vegetation present in agroforestry land is getting lower year by year.

Dietary Patterns and Body Mass Index in Children with Autism and Typically Developing Children

PubMed Central

Evans, E. Whitney; Must, Aviva; Anderson, Sarah E.; Curtin, Carol; Scampini, Renee; Maslin, Melissa; Bandini, Linda

2012-01-01

To determine whether dietary patterns (juice and sweetened non-dairy beverages, fruits, vegetables, fruits & vegetables, snack foods, and kid’s meals) and associations between dietary patterns and body mass index (BMI) differed between 53 children with autism spectrum disorders (ASD) and 58 typically developing children, ages 3 to 11, multivariate regression models including interaction terms were used. Children with ASD were found to consume significantly more daily servings of sweetened beverages (2.6 versus 1.7, p=0.03) and snack foods (4.0 versus 3.0, p=0.01) and significantly fewer daily servings of fruits and vegetables (3.1 versus 4.4, p=0.006) than typically developing children. There was no evidence of statistical interaction between any of the dietary patterns and BMI z-score with autism status. Among all children, fruits and vegetables (p=0.004) and fruits alone (p=0.005) were positively associated with BMI z-score in our multivariate models. Children with ASD consume more energy-dense foods than typically developing children; however, in our sample, only fruits and vegetables were positively associated with BMI z-score. PMID:22936951

The Influence of Rainfall, Vegetation, Elephants and People on Fire Frequency of Miombo Woodlands, Northern Mozambique

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Okin, G. S.; Shugart, H. H.; Swap, R. J.

2008-12-01

Miombo woodlands are important in southern Africa as they occupy over 50% of the land and, their good and services support a large proportion of people in the region. Anthropogenic fires occur in miombo every year especially in the dry season (May - October). This study explores the influence of annual rainfall, elephant density, human density and corridors, and vegetation on the fire frequency. It was carried out in Niassa Reserve located in northern Mozambique, the largest and more pristine conservation area of miombo woodlands in the world. We used a time series analysis and statistical t-test of MODIS-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to explore the relationship between biomass and fire frequency. The influence of rainfall, elephants, people and vegetation on fire return was explored using a stepwise logistic regression analysis. The results of this study indicate that fire frequency is higher in places with high biomass at beginning of the dry season. In these areas fire seems to be more intense and to strongly reduce biomass in the late dry season. Land cover is the strongest predictor of fire frequency, but elephant density, annual rainfall and human corridors are also important.

The influence of rainfall, vegetation, elephants and people on fire frequency of miombo woodlands, northern Mozambique

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Okin, G. S.; Shugart, H.; Swap, R.

2007-12-01

Miombo woodlands are important in southern Africa as they occupy over 50% of the land and, their good and services support a large proportion of people in the region. Anthropogenic fires occur in miombo every year especially in the dry season (May - October). This study explores the influence of annual rainfall, elephant density, human density and corridors, and vegetation on the fire frequency. It was carried out in Niassa Reserve located in northern Mozambique, the largest and more pristine conservation area of miombo woodlands in the world. We used a time series analysis and statistical t-test of MODIS-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to explore the relationship between biomass and fire frequency. The influence of rainfall, elephants, people and vegetation on fire return was explored using a stepwise logistic regression analysis. The results of this study indicate that fire frequency is higher in places with high biomass at beginning of the dry season. In these areas fire seems to be more intense and to strongly reduce biomass in the late dry season. Land cover is the strongest predictor of fire frequency, but elephant density, annual rainfall and human corridors are also important.

Verification of watershed vegetation restoration policies, arid China

PubMed Central

Zhang, Chengqi; Li, Yu

2016-01-01

Verification of restoration policies that have been implemented is of significance to simultaneously reduce global environmental risks while also meeting economic development goals. This paper proposed a novel method according to the idea of multiple time scales to verify ecological restoration policies in the Shiyang River drainage basin, arid China. We integrated modern pollen transport characteristics of the entire basin and pollen records from 8 Holocene sedimentary sections, and quantitatively reconstructed the millennial-scale changes of watershed vegetation zones by defining a new pollen-precipitation index. Meanwhile, Empirical Orthogonal Function method was used to quantitatively analyze spatial and temporal variations of Normalized Difference Vegetation Index in summer (June to August) of 2000–2014. By contrasting the vegetation changes that mainly controlled by millennial-scale natural ecological evolution with that under conditions of modern ecological restoration measures, we found that vegetation changes of the entire Shiyang River drainage basin are synchronous in both two time scales, and the current ecological restoration policies met the requirements of long-term restoration objectives and showed promising early results on ecological environmental restoration. Our findings present an innovative method to verify river ecological restoration policies, and also provide the scientific basis to propose future emphasizes of ecological restoration strategies. PMID:27470948

Verification of watershed vegetation restoration policies, arid China

NASA Astrophysics Data System (ADS)

Zhang, Chengqi; Li, Yu

2016-07-01

Verification of restoration policies that have been implemented is of significance to simultaneously reduce global environmental risks while also meeting economic development goals. This paper proposed a novel method according to the idea of multiple time scales to verify ecological restoration policies in the Shiyang River drainage basin, arid China. We integrated modern pollen transport characteristics of the entire basin and pollen records from 8 Holocene sedimentary sections, and quantitatively reconstructed the millennial-scale changes of watershed vegetation zones by defining a new pollen-precipitation index. Meanwhile, Empirical Orthogonal Function method was used to quantitatively analyze spatial and temporal variations of Normalized Difference Vegetation Index in summer (June to August) of 2000-2014. By contrasting the vegetation changes that mainly controlled by millennial-scale natural ecological evolution with that under conditions of modern ecological restoration measures, we found that vegetation changes of the entire Shiyang River drainage basin are synchronous in both two time scales, and the current ecological restoration policies met the requirements of long-term restoration objectives and showed promising early results on ecological environmental restoration. Our findings present an innovative method to verify river ecological restoration policies, and also provide the scientific basis to propose future emphasizes of ecological restoration strategies.

Interannual growth dynamics of vegetation in the Kuparuk River watershed, Alaska based on the Normalized Difference Vegetation Index

USGS Publications Warehouse

Hope, A.S.; Boynton, W.L.; Stow, D.A.; Douglas, David C.

2003-01-01

Interannual above-ground production patterns are characterized for three tundra ecosystems in the Kuparuk River watershed of Alaska using NOAA-AVHRR Normalized Difference Vegetation Index (NDVI) data. NDVI values integrated over each growing season (SINDVI) were used to represent seasonal production patterns between 1989 and 1996. Spatial differences in ecosystem production were expected to follow north-south climatic and soil gradients, while interannual differences in production were expected to vary with variations in seasonal precipitation and temperature. It was hypothesized that the increased vegetation growth in high latitudes between 1981 and 1991 previously reported would continue through the period of investigation for the study watershed. Zonal differences in vegetation production were confirmed but interannual variations did not covary with seasonal precipitation or temperature totals. A sharp reduction in the SINDVI in 1992 followed by a consistent increase up to 1996 led to a further hypothesis that the interannual variations in SINDVI were associated with variations in stratospheric optical depth. Using published stratospheric optical depth values derived from the SAGE and SAGE-II satellites, it is demonstrated that variations in these depths are likely the primary cause of SINDVI interannual variability.

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.

What’s Being Served for Dinner?: An Exploratory Investigation of the Associations between the Healthfulness of Family Meals and Child Dietary Intake

PubMed Central

Trofholz, Amanda C.; Tate, Allan D.; Draxten, Michelle L.; Rowley, Seth S.; Schulte, Anna K.; Neumark-Sztainer, Dianne; MacLehose, Richard F.; Berge, Jerica M.

2016-01-01

Background Little is known about the healthfulness of foods offered at family meals or the relationship between the food’s healthfulness and child overall dietary intake. Objective This exploratory study uses a newly-developed Healthfulness of Meal (HOM) index to examine the association between the healthfulness of foods served at family dinners and child dietary intake. Design Direct observational, cross-sectional study. Participants/setting Primarily low-income, minority families (n=120) video-recorded 8 days of family dinners and completed a corresponding meal screener. Dietary recalls were completed on the target child (6–12 years old). The HOM index was used to measure meal healthfulness and included component scores for whole fruit, 100% juice, vegetables, dark green vegetables, dairy, protein, added sugars, and high sodium foods. Main outcome measures Child dietary intake measured by three 24-hour dietary recalls. Statistical analyses performed Linear regression models estimated the association between the foods served at dinner meals and overall child dietary intake. Results The majority of coded meals included foods from protein and high sodium components; over half included foods from dairy and vegetable components. Nearly half of the meals had an added sugar component food (e.g., soda, dessert). Few meals served foods from fruit, 100% juice, or dark green vegetable components. Many components served at family dinner meals were significantly associated with child daily intake of those same foods (i.e., dark green, non-dark green vegetables, dairy, and added sugars). The HOM index total score was significantly associated with child HEI score. Conclusions This study represents the first report of a new methodology to collect data of foods served at family dinners. Results indicated a significant association between the majority of components served at family dinner meals and child overall dietary intake. Validation of the HOM index and video-recorded family meal methodology is needed to strengthen these research methods for use in future studies. PMID:27666378

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.

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

NASA Technical Reports Server (NTRS)

Goad, Clyde C.; Chadwell, C. David

1993-01-01

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

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 Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2015-01-01

Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

Thirty Years of Vegetation Change in the Coastal Santa Cruz Mountains of Northern California Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Results from Landsat satellite image times series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90% of the (predominantly second-growth) evergreen forest locations sampled.

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...

Meteorological satellite data: A tool to describe the health of the world's agriculture

NASA Technical Reports Server (NTRS)

Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator); Scott, L.

1981-01-01

Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86.

Wheat yield estimation at the farm level using TM Landsat and agrometeorological data

NASA Technical Reports Server (NTRS)

Rudorff, B. F. T.; Batista, G. T.

1991-01-01

A model for estimating wheat yields on the farm level was developed, that integrates the Landsat TM data and agrometeorological information. Results obtained for a test site in southern Brasil for years of 1986 and 1987 show that the vegetation index derived from Landsat TM could account for the 60 to 40 percent wheat-yield variability observed between the two crop years. Compared to results using either the Landsat TM vegetation index or the agrometeorological data alone, the joint use of both types of data in a single model yielded a significant improvement.

Fruit and vegetable intake, body mass index and waist circumference among young female students in Isfahan.

PubMed

Ghalaeh, Reihaneh Seyed; Gholi, Zahra; Bank, Sahar Saraf; Azadbakht, Leila

2012-01-01

Obesity is growing rapidly in our country. Nutrition is an important issue of obesity. The aim of this study was to determine the association between fruit and vegetable intake with the waist circumference and the body mass index (BMI) among young female university students. This cross-sectional study was conducted on 236 healthy female university students aged between 18 and 30 years old, who were selected randomly from the students of Isfahan University of Medical Sciences, Iran. A previously validated semi-quantitative food frequency questionnaire was used to assess the entire dietary component intake. Physical activity was assessed by daily recording of the physical activities. The prevalence of obesity, central adiposity and overweight was 1.7, 0.9 and 8.1%, respectively. The mean value of BMI and the waist circumference was 21.54 kg/m(2) and 70.37 cm, respectively. There was an inverse correlation between the fruit and vegetable intake and body weight (r = -0.1, P = 0.03) as well as BMI (r = -0.1, P = 0.04) and also there was an inverse correlation between the fruit intake and body weight (r = -0.1, P = 0.01) and BMI (r = -0.1, P = 0.01). There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with the waist circumference. There were significant correlations between fruit and also fruit and vegetable and body weight and BMI among female university students. There was no significant correlation between fruit and vegetable as well as fruit or vegetable separately with waist circumference.

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Kimes, Daniel S.; Nelson, Ross F.

1998-01-01

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

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).

Evaluation of vegetation post-fire resilience in the Alpine region using descriptors derived from MODIS spectral index time series

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Fava, Francesco; Busetto, Lorenzo; Crosta, Giovanni Franco; Colombo, Roberto

2013-04-01

In this study a method based on the analysis of MODerate-resolution Imaging Spectroradiometer (MODIS) time series is proposed to estimate the post-fire resilience of mountain vegetation (broadleaf forest and prairies) in the Italian Alps. Resilience is defined herewith as the ability of a dynamical system to counteract disturbances. It can be quantified by the amount of time the disturbed system takes to resume, in statistical terms, an ecological functionality comparable with its undisturbed behavior. Satellite images of the Normalized Difference Vegetation Index (NDVI) and of the Enhanced Vegetation Index (EVI) with spatial resolution of 250m and temporal resolution of 16 days in the 2000-2012 time period were used. Wildfire affected areas in the Lombardy region between the years 2000 and 2010 were analysed. Only large fires (affected area >40ha) were selected. For each burned area, an undisturbed adjacent control site was located. Data pre-processing consisted in the smoothing of MODIS time series for noise removal and then a double logistic function was fitted. Land surface phenology descriptors (proxies for growing season start/end/length and green biomass) were extracted in order to characterize the time evolution of the vegetation. Descriptors from a burned area were compared to those extracted from the respective control site by means of the one-way analysis of variance. According to the number of subsequent years which exhibit statistically meaningful difference between burned and control site, five classes of resilience were identified and a set of thematic maps was created for each descriptor. The same method was applied to all 84 aggregated events and to events aggregated by main land cover. EVI index results more sensitive to fire impact than NDVI index. Analysis shows that fire causes both a reduction of the biomass and a variation in the phenology of the Alpine vegetation. Results suggest an average ecosystem resilience of 6-7 years. Moreover, broadleaf forest and prairies show different post-fire behavior in terms of land surface phenology descriptors. In addition to the above analysis, another method is proposed, which derives from the qualitative theory of dynamical systems. The (time dependent) spectral index of a burned area over the period of one year was plotted against its counterpart from the control site. Yearly plots (or scattergrams) before and after the fire were obtained. Each plot is a sequence of points on the plane, which are the vertices of a generally self-intersecting polygonal chain. Some geometrical descriptors were obtained from the yearly chains of each fire. Principal Components Analysis (PCA) of geometrical descriptors was applied to a set of case studies and the obtained results provide a system dynamics interpretation of the natural process.

Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland

NASA Astrophysics Data System (ADS)

Cerasoli, Sofia; Costa e Silva, Filipe; Silva, João M. N.

2016-06-01

The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus ( Cistus salviifolius) and ulex ( Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence ( ΔF/ Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland.

PubMed

Cerasoli, Sofia; Costa E Silva, Filipe; Silva, João M N

2016-06-01

The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus (Cistus salviifolius) and ulex (Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence (ΔF/Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

Bioaccessibility and risk assessment of essential and non-essential elements in vegetables commonly consumed in Swaziland.

PubMed

Mnisi, Robert Londi; Ndibewu, Peter P; Mafu, Lihle D; Bwembya, Gabriel C

2017-10-01

The green leafy vegetables (Mormodica involucrate, Bidens pilosa and Amaranthus spinosus) are economic; seasonal; locally grown and easily available; easy to propagate and store; highly nutritious food substances that form an important component of diets. This study applies a physiology based extraction technique (PBET) to mimic digestion of these vegetables to determine the fraction of essential (Fe and Zn) and non-essential elements (Cd, Cr and Pb) that are made available for absorption after ingestion. Prior to the application of the PBET, the vegetables were cooked adopting indigenous Swazi cooking methods. Cooking mobilized most of the metals out of the vegetable mass, and the final substrate concentrations are: raw > cooked > supernatant for all the metals, and the order of average metal leaching was: Pb (82.2%) >Cr (70.6%) >Zn (67.5%) >Fe (60.2%) >Cd (53.6%). This meant that the bioavailable concentrations are significantly lower than in the original vegetable mass, if only the solid mass is consumed. Bioaccessibility was higher in the gastric tract than in the intestinal phases of the PBET for all the metals in all the vegetables. Risk assessment protocols employed on the non-essential elements (Cr, Cd and Pb) showed that the associated risks of ingesting metal contaminated vegetables are higher for children, than they are for adults, based on the target hazard quotient (THQ) index. However, the overall health risk associated with ingestion of these metals is low, for both children and adults, based on the HR index. Conclusively, this study expounds on the nutritional and risk benefits associated with ingesting naturally grown vegetables. Copyright © 2017 Elsevier Inc. All rights reserved.

FlowShape: a runoff connectivity index for patched environments, based on shape and orientation of runoff sources

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Malkinson, Dan; Ursino, Nadia; Wittenberg, Lea

2016-04-01

The properties of vegetation cover are recognized to be a key factor in determining runoff processes and yield over natural areas. Still, how the actual vegetation spatial distribution affects these processes is not completely understood. In Mediterranean semi-arid regions, patched landscapes are often found, with clumped vegetation, grass or shrubs, surrounded by bare soil patches. These two phases produce a sink-source system for runoff, as precipitation falling over bare areas barely infiltrates and rather flows downslope. In contrast, vegetated patches have high infiltrability and can partially retain the runon water. We hypothesize that, at a relatively small scale, the shape and orientation of bare soil patches with respect to the runoff flow direction is a significant for the connectivity of the runoff flow paths, and consequently for runoff values. We derive an index, FlowShape, which is candidate to be a good proxy for runoff connectivity and thus runoff production in patched environments. FlowShape is an area-weighted average of the geometrical properties of each bare soil patch. Eight experimental plots in northern Israel were monitored during 2 years after a wildfire which occurred in 2006. Runoff was collected and measured - along with rainfall depth - after each rainfall event, at different levels of vegetation cover corresponding to post-fire recovery of vegetation and seasonality. We obtained a good correlation between FlowShape and the runoff coefficient, at two conditions: a minimal percentage of vegetation cover over the plot, and minimal rainfall depth. Our results support the hypothesis that the spatial distribution of the two phases (vegetation and bare soil) in patched landscapes dictates, at least partially, runoff yield. The correlation between the runoff coefficient and FlowShape, which accounts for shape and orientation of soil patches, is higher than the correlation between the runoff coefficient and the bare soil percentage alone. Besides that, the existence of a vegetation cover threshold under which FlowShape loses correlation with runoff yield, suggests that different processes occur at different levels of vegetation cover. On bare or almost bare plots, runoff flows as a sheet, and small isolated plants do not impose a directionality to the flow or interrupt runoff connectivity. On the other hand, rainfall depth - and possibly rainfall intensity - also affect the hydrological processes of infiltration and runoff production, and thus the applicability of any purely geometrical index. We compared the correlation to runoff coefficient with the FlowShape and FlowLength, a well-known index for runoff connectivity (Mayor et al., 2008) which is defined as the average of runoff flow paths over the plot. As microtopography was not available, our plots were idealized as planar hillslopes. We found that FlowShape is a better predictor than FlowLength for runoff yield over our experimental plots.

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

Integrated Analysis of Climate, Soil, Topography and Vegetative Growth in Iberian Viticultural Regions

PubMed Central

Fraga, Helder; Malheiro, Aureliano C.; Moutinho-Pereira, José; Cardoso, Rita M.; Soares, Pedro M. M.; Cancela, Javier J.; Pinto, Joaquim G.; Santos, João A.

2014-01-01

The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate. PMID:25251495

Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

PubMed

Fraga, Helder; Malheiro, Aureliano C; Moutinho-Pereira, José; Cardoso, Rita M; Soares, Pedro M M; Cancela, Javier J; Pinto, Joaquim G; Santos, João A

2014-01-01

The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

NASA Astrophysics Data System (ADS)

Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

2018-03-01

Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

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.

Spectral radiance estimates of leaf area and leaf phytomass of small grains and native vegetation

NASA Technical Reports Server (NTRS)

Aase, J. K.; Brown, B. S.; Millard, J. P.

1986-01-01

Similarities and/or dissimilarities in radiance characteristics were studied among barley (Hordeum vulgare L.), oats (Avena fatua L.), spring and winter wheat (Triticum aestivum L.), and short-grass prairie vegetation. The site was a Williams loam soil (fine-loamy mixed, Typic Argiborolls) near Sidney, Montana. Radiances were measured with a truck-mounted radiometer. The radiometer was equipped with four wavelength bands: 0.45 to 0.52, 0.52 to 0.60, 0.63 to 0.69, and 0.76 to 0.90 micron. Airborne scanner measurements were made at an altitude of 600 m four times during the season under clear sky conditions. The airborne scanner was equipped with the same four bands as the truck-mounted radiometer plus the following: 1.00 to 1.30, 1.55 to 1.75, 2.08 to 2.35, and 10.4 to 12.5 microns. Comparisons using individual wave bands, the near IR/red, (0.76 to 0.90 micron)/(0.63 to 0.69 micron) ratio and the normalized difference vegetation index, ND = (IR - red)/(IR + red), showed that only during limited times during the growing season were some of the small grains distinguishable from one another and from native rangeland vegetation. There was a common relation for all small grains between leaf area index and green leaf phytomass and between leaf area index or green leaf phytomass and the IR/red ratio.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

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.

Regional assessment of trends in vegetation change dynamics using principal component analysis

NASA Astrophysics Data System (ADS)

Osunmadewa, B. A.; Csaplovics, E.; R. A., Majdaldin; Adeofun, C. O.; Aralova, D.

2016-10-01

Vegetation forms the basis for the existence of animal and human. Due to changes in climate and human perturbation, most of the natural vegetation of the world has undergone some form of transformation both in composition and structure. Increased anthropogenic activities over the last decades had pose serious threat on the natural vegetation in Nigeria, many vegetated areas are either transformed to other land use such as deforestation for agricultural purpose or completely lost due to indiscriminate removal of trees for charcoal, fuelwood and timber production. This study therefore aims at examining the rate of change in vegetation cover, the degree of change and the application of Principal Component Analysis (PCA) in the dry sub-humid region of Nigeria using Normalized Difference Vegetation Index (NDVI) data spanning from 1983-2011. The method used for the analysis is the T-mode orientation approach also known as standardized PCA, while trends are examined using ordinary least square, median trend (Theil-Sen) and monotonic trend. The result of the trend analysis shows both positive and negative trend in vegetation change dynamics over the 29 years period examined. Five components were used for the Principal Component Analysis. The results of the first component explains about 98 % of the total variance of the vegetation (NDVI) while components 2-5 have lower variance percentage (< 1%). Two ancillary land use land cover data of 2000 and 2009 from European Space Agency (ESA) were used to further explain changes observed in the Normalized Difference Vegetation Index. The result of the land use data shows changes in land use pattern which can be attributed to anthropogenic activities such as cutting of trees for charcoal production, fuelwood and agricultural practices. The result of this study shows the ability of remote sensing data for monitoring vegetation change in the dry-sub humid region of Nigeria.