Identifying environmental risk factors and mapping the risk of human West Nile virus in South Dakota.

NASA Astrophysics Data System (ADS)

Hess, A.; Davis, J. K.; Wimberly, M. C.

2017-12-01

Human West Nile virus (WNV) first arrived in the USA in 1999 and has since then spread across the country. Today, the highest incidence rates are found in the state of South Dakota. The disease occurrence depends on the complex interaction between the mosquito vector, the bird host and the dead-end human host. Understanding the spatial domain of this interaction and being able to identify disease transmission hotspots is crucial for effective disease prevention and mosquito control. In this study we use geospatial environmental information to understand what drives the spatial distribution of cases of human West Nile virus in South Dakota and to map relative infection risk across the state. To map the risk of human West Nile virus in South Dakota, we used geocoded human case data from the years 2004-2016. Satellite data from the Landsat ETM+ and MODIS for the years 2003 to 2016 were used to characterize environmental patterns. From these datasets we calculated indices, such as the normalized differenced vegetation index (NDVI) and the normalized differenced water index (NDWI). In addition, datasets such as the National Land Data Assimilation System (NLDAS), National Land Cover Dataset (NLCD), National Wetland inventory (NWI), National Elevation Dataset (NED) and Soil Survey Geographic Database (SSURGO) were utilized. Environmental variables were summarized for a buffer zone around the case and control points. We used a boosted regression tree model to identify the most important variables describing the risk of WNV infection. We generated a risk map by applying this model across the entire state. We found that the highest relative risk is present in the James River valley in northeastern South Dakota. Factors that were identified as influencing the transmission risk include inter-annual variability of vegetation cover, water availability and temperature. Land covers such as grasslands, low developed areas and wetlands were also found to be good predictors for human West Nile Virus risk. We suggest that the combination of satellite data derived land cover indices with other geospatial environmental datasets can help to create improved disease transmission risk analyses.

Assessment of Fire Severity and Post-Fire Regeneration Based on Topographical Features Using Multitemporal Landsat Imagery: a Case Study in Mersin, Turkey

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.; Kaya, S.

2016-06-01

Satellite based remote sensing technologies and Geographical Information Systems (GIS) present operable and cost-effective solutions for mapping fires and observing post-fire regeneration. Mersin-Gülnar wildfire, which occurred in August 2008 in Turkey, selected as study site. The fire was devastating and continued 55 days. According to Turkish General Directorate of Forestry reports, it caused two deaths and left hundreds of people homeless. The aim of this study is to determine the fire severity and monitor vegetation recovery with using multitemporal spectral indices together with topographical factors. Pre-fire and post-fire Landsat ETM+ images were obtained to assess the related fire severity with using the widely-used differenced Normalized Burn Ratio (dNBR) algorithm. Also, the Normalized Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were used to determine vegetation regeneration dynamics for a period of six consecutive years. In addition, aspect image derived from Aster Global Digital Elevation Model (GDEM) were used to determine vegetation regeneration regime of the study area. Results showed that 5388 ha of area burned with moderate to high severity damage. As expected, NDVI and SAVI values distinctly declined post-fire and then began to increase in the coming years. Mean NDVI value of burned area changed from 0.48 to 0.17 due to wildfire, whilst mean SAVI value changed from 0.61 to 0.26. Re-growth rates calculated for NDVI and SAVI 57% and 63% respectively, six years after the fire. Moreover, NDVI and SAVI were estimated six consecutive year period by taking into consideration east, south, north and west facing slopes. Analysis showed that north-facing and east-facing slopes have higher regeneration rates in compared to other aspects. This study serves as a window to an understanding of the process of fire severity and vegetation regeneration that is vital in wildfire management systems.

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.

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.

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.

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.

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.

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.

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.

Detecting forest canopy change due to insect activity using Landsat MSS

NASA Technical Reports Server (NTRS)

Nelson, R. F.

1983-01-01

Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

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

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

NASA Astrophysics Data System (ADS)

Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0.92) and RapidEye data (r2 = 0.91).

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.

Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA

Treesearch

Jay D. Miller; Eric E. Knapp; Carl H. Key; Carl N. Skinner; Clint J. Isbell; R. Max Creasy; Joseph W. Sherlock

2009-01-01

Multispectral satellite data have become a common tool used in the mapping of wildland fire effects. Fire severity, defined as the degree to which a site has been altered, is often the variable mapped. The Normalized Burn Ratio (NBR) used in an absolute difference change detection protocol (dNBR), has become the remote sensing method of choice for US Federal land...

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.

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.

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.

Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests

Treesearch

Elizabeth E. Hoy; Nancy H.F. French; Merritt R. Turetsky; Simon N. Trigg; Eric S. Kasischke

2008-01-01

Satellite remotely sensed data of fire disturbance offers important information; however, current methods to study fire severity may need modifications for boreal regions. We assessed the potential of the differenced Normalized Burn Ratio (dNBR) and other spectroscopic indices and image transforms derived from Landsat TM/ETM+ data for mapping fire severity in Alaskan...

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.

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.

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...

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.

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.

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.

Quantifying soil burn severity for hydrologic modeling to assess post-fire effects on sediment delivery

NASA Astrophysics Data System (ADS)

Dobre, Mariana; Brooks, Erin; Lew, Roger; Kolden, Crystal; Quinn, Dylan; Elliot, William; Robichaud, Pete

2017-04-01

Soil erosion is a secondary fire effect with great implications for many ecosystem resources. Depending on the burn severity, topography, and the weather immediately after the fire, soil erosion can impact municipal water supplies, degrade water quality, and reduce reservoirs' storage capacity. Scientists and managers use field and remotely sensed data to quickly assess post-fire burn severity in ecologically-sensitive areas. From these assessments, mitigation activities are implemented to minimize post-fire flood and soil erosion and to facilitate post-fire vegetation recovery. Alternatively, land managers can use fire behavior and spread models (e.g. FlamMap, FARSITE, FOFEM, or CONSUME) to identify sensitive areas a priori, and apply strategies such as fuel reduction treatments to proactively minimize the risk of wildfire spread and increased burn severity. There is a growing interest in linking fire behavior and spread models with hydrology-based soil erosion models to provide site-specific assessment of mitigation treatments on post-fire runoff and erosion. The challenge remains, however, that many burn severity mapping and modeling products quantify vegetation loss rather than measuring soil burn severity. Wildfire burn severity is spatially heterogeneous and depends on the pre-fire vegetation cover, fuel load, topography, and weather. Severities also differ depending on the variable of interest (e.g. soil, vegetation). In the United States, Burned Area Reflectance Classification (BARC) maps, derived from Landsat satellite images, are used as an initial burn severity assessment. BARC maps are classified from either a Normalized Burn Ratio (NBR) or differenced Normalized Burned Ratio (dNBR) scene into four classes (Unburned, Low, Moderate, and High severity). The development of soil burn severity maps requires further manual field validation efforts to transform the BARC maps into a product more applicable for post-fire soil rehabilitation activities. Alternative spectral indices and modeled output approaches may prove better predictors of soil burn severity and hydrologic effects, but these have not yet been assessed in a model framework. In this project we compare field-verified soil burn severity maps to satellite-derived and modeled burn severity maps. We quantify the extent to which there are systematic differences in these mapping products. We then use the Water Erosion Prediction Project (WEPP) hydrologic soil erosion model to assess sediment delivery from these fires using the predicted and observed soil burn severity maps. Finally, we discuss differences in observed and predicted soil burn severity maps and application to watersheds in the Pacific Northwest to estimate post-fire sediment delivery.

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.

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.

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

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.

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.

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.

Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Kokaly, R.F.; Rockwell, B.W.; Haire, S.L.; King, T.V.V.

2007-01-01

Forest fires leave behind a changed ecosystem with a patchwork of surface cover that includes ash, charred organic matter, soils and soil minerals, and dead, damaged, and living vegetation. The distributions of these materials affect post-fire processes of erosion, nutrient cycling, and vegetation regrowth. We analyzed high spatial resolution (2.4??m pixel size) Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over the Cerro Grande fire, to map post-fire surface cover into 10 classes, including ash, soil minerals, scorched conifer trees, and green vegetation. The Cerro Grande fire occurred near Los Alamos, New Mexico, in May 2000. The AVIRIS data were collected September 3, 2000. The surface cover map revealed complex patterns of ash, iron oxide minerals, and clay minerals in areas of complete combustion. Scorched conifer trees, which retained dry needles heated by the fire but not fully combusted by the flames, were found to cover much of the post-fire landscape. These scorched trees were found in narrow zones at the edges of completely burned areas. A surface cover map was also made using Landsat Enhanced Thematic Mapper plus (ETM+) data, collected September 5, 2000, and a maximum likelihood, supervised classification. When compared to AVIRIS, the Landsat classification grossly overestimated cover by dry conifer and ash classes and severely underestimated soil and green vegetation cover. In a comparison of AVIRIS surface cover to the Burned Area Emergency Rehabilitation (BAER) map of burn severity, the BAER high burn severity areas did not capture the variable patterns of post-fire surface cover by ash, soil, and scorched conifer trees seen in the AVIRIS map. The BAER map, derived from air photos, also did not capture the distribution of scorched trees that were observed in the AVIRIS map. Similarly, the moderate severity class of Landsat-derived burn severity maps generated from the differenced Normalized Burn Ratio (dNBR) calculation had low agreement with the AVIRIS classes of scorched conifer trees. Burn severity and surface cover images were found to contain complementary information, with the dNBR map presenting an image of degree of change caused by fire and the AVIRIS-derived map showing specific surface cover resulting from fire.

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.

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.

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.

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.

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.

Prediction and control of chaotic processes using nonlinear adaptive networks

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

Jones, R.D.; Barnes, C.W.; Flake, G.W.

1990-01-01

We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

USGS Publications Warehouse

,

2005-01-01

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

Recovery of biological soil crust richness and cover 12-16 years after wildfires in Idaho, USA

NASA Astrophysics Data System (ADS)

Root, Heather T.; Brinda, John C.; Dodson, E. Kyle

2017-09-01

Changing fire regimes in western North America may impact biological soil crust (BSC) communities that influence many ecosystem functions, such as soil stability and C and N cycling. However, longer-term effects of wildfire on BSC abundance, species richness, functional groups, and ecosystem functions after wildfire (i.e., BSC resilience) are still poorly understood. We sampled BSC lichen and bryophyte communities at four sites in Idaho, USA, within foothill steppe communities that included wildfires from 12 to 16 years old. We established six plots outside each burn perimeter and compared them with six plots of varying severity within each fire perimeter at each site. BSC cover was most strongly negatively impacted by wildfire at sites that had well-developed BSC communities in adjacent unburned plots. BSC species richness was estimated to be 65 % greater in unburned plots compared with burned plots, and fire effects did not vary among sites. In contrast, there was no evidence that vascular plant functional groups or fire severity (as measured by satellite metrics differenced normalized burn ratio (dNBR) or relativized differenced normalized burn ratio (RdNBR)) significantly affected longer-term BSC responses. Three large-statured BSC functional groups that may be important in controlling wind and water erosion (squamulose lichens, vagrant lichens, and tall turf mosses) exhibited a significant decrease in abundance in burned areas relative to adjacent unburned areas. The decreases in BSC cover and richness along with decreased abundance of several functional groups suggest that wildfire can negatively impact ecosystem function in these semiarid ecosystems for at least 1 to 2 decades. This is a concern given that increased fire frequency is predicted for the region due to exotic grass invasion and climate change.

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.

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.

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

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.

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.

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.

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.

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).

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

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.

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.

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.

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.

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.

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

Research support of the WETNET Program

NASA Technical Reports Server (NTRS)

Estes, John E.; Mcgwire, Kenneth C.; Scepan, Joseph; Henderson, SY; Lawless, Michael

1995-01-01

This study examines various aspects of the Microwave Vegetation Index (MVI). MVI is a derived signal created by differencing the spectral response of the 37 GHz horizontally and vertically polarized passive microwave signals. The microwave signal employed to derive this index is thought to be primarily influenced by vegetation structure, vegetation growth, standing water, and precipitation. The state of California is the study site for this research. Imagery from the Special Sensor Microwave/Imager (SSM/I) is used for the creation of MVI datasets analyzed in this research. The object of this research is to determine whether MVI corresponds with some quantifiable vegetation parameter (such as vegetation density) or whether the index is more affected by known biogeophysical parameters such antecedent precipitation. A secondary question associated with the above is whether the vegetation attributes that MVI is employed to determine can be more easily and accurately evaluated by other remote sensing means. An important associated question to be addressed in the study is the effect of different multi-temporal composting techniques on the derived MVI dataset. This work advances our understanding of the fundamental nature of MVI by studying vegetation as a mixture of structural types, such as forest and grassland. The study further advances our understanding by creating multitemporal precipitation datasets to compare the affects of precipitation upon MVI. This work will help to lay the groundwork for the use of passive microwave spectral information either as an adjunct to visible and near infrared imagery in areas where that is feasible or for the use of passive microwave alone in areas of moderate cloud coverage. In this research, an MVI dataset, spanning the period February 15, 1989 through April 25, 1990, has been created using National Aeronautic and Space Administration (NASA) supplied brightness temperature data. Information from the DMSP satellite 37 GHz wavelength SSM/I sensor in both horizontal and vertical polarization has been processed using the MVI algorithm. In conjunction with the MVI algorithm a multitemporal compositing technique was used to create datasets that correspond to 14 day periods. In this technical report, Section Two contains background information on the State of California and the three MVI study sites. Section Three describes the methods used to create the MVI and independent variables datasets. Section Four presents the results of the experiment. Section Five summarizes and concludes the work.

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.

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.

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.

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.

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.

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

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...

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

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.

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.

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.

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

40 CFR 230.43 - Vegetated shallows.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Special Aquatic Sites § 230.43 Vegetated shallows. (a) Vegetated shallows are permanently inundated areas that under normal circumstances support communities of rooted aquatic vegetation, such as turtle grass...) releasing chemicals that adversely affect plants and animals; (4) increasing turbidity levels, thereby...

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...

[THE CORRECTION OF TROPHIC DISORDERS IN CHILDREN OF CHRONIC GASTRODUODENITIS WITH METHOD LOW-FREQUENCY LIGHT-MAGNETOTHERAPY].

PubMed

Kolosova, T A; Sadovnikova, I V; Belousova, T E

2015-01-01

The results of a survey of school children with chronic gastroduodenitis when applying at an early period the medical rehabilitation with method low-frequency light-magnetotherapy. During treatment of hospital was evaluated vegetative-trophic status with methods of cardiointervalography and thermovision functional tests. In normalizes clinical parameters was correction in dynamics of the vegetative status in children, it confirms the effectiveness of the therapy. It is proved, that the use of low-frequency light-magnetotherapy has a positive effect on the vegetative--trophic provision an organism and normalizes the vegetative dysfunction.

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.

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.

Fire severity and ecosytem responses following crown fires in California shrublands

USGS Publications Warehouse

Keeley, J.E.; Brennan, T.; Pfaff, A.H.

2008-01-01

Chaparral shrublands burn in large high-intensity crown fires. Managers interested in how these wildfires affect ecosystem processes generally rely on surrogate measures of fire intensity known as fire severity metrics. In shrublands burned in the autumn of 2003, a study of 250 sites investigated factors determining fire severity and ecosystem responses.Using structural equation modeling we show that stand age, prefire shrub density, and the shortest interval of the prior fire history had significant direct effects on fire severity, explaining >50% of the variation in severity.Fire severity per se is of interest to resource managers primarily because it is presumed to be an indicator of important ecosystem processes such as vegetative regeneration, community recovery, and erosion. Fire severity contributed relatively little to explaining patterns of regeneration after fire. Two generalizations can be drawn: fire severity effects are mostly short-lived, i.e., by the second year they are greatly diminished, and fire severity may have opposite effects on different functional types.Species richness exhibited a negative relationship to fire severity in the first year, but fire severity impacts were substantially less in the second postfire year and varied by functional type. Much of this relationship was due to alien plants that are sensitive to high fire severity; at all scales from 1 to 1000 m2, the percentage of alien species in the postfire flora declined with increased fire severity. Other aspects of disturbance history are also important determinants of alien cover and richness as both increased with the number of times the site had burned and decreased with time since last fire.A substantial number of studies have shown that remote-sensing indices are correlated with field measurements of fire severity. Across our sites, absolute differenced normalized burn ratio (dNBR) was strongly correlated with field measures of fire severity and with fire history at a site but relative dNBR was not. Despite being correlated with fire severity, absolute dNBR showed little or no relationship with important ecosystem responses to wildfire such as shrub resprouting or total vegetative regeneration. These findings point to a critical need for further research on interpreting remote sensing indices as applied to postfire management of these shrublands.

Fire severity and ecosytem responses following crown fires in California shrublands.

PubMed

Keeley, Jon E; Brennan, Teresa; Pfaff, Anne H

2008-09-01

Chaparral shrublands burn in large high-intensity crown fires. Managers interested in how these wildfires affect ecosystem processes generally rely on surrogate measures of fire intensity known as fire severity metrics. In shrublands burned in the autumn of 2003, a study of 250 sites investigated factors determining fire severity and ecosystem responses. Using structural equation modeling we show that stand age, prefire shrub density, and the shortest interval of the prior fire history had significant direct effects on fire severity, explaining > 50% of the variation in severity. Fire severity per se is of interest to resource managers primarily because it is presumed to be an indicator of important ecosystem processes such as vegetative regeneration, community recovery, and erosion. Fire severity contributed relatively little to explaining patterns of regeneration after fire. Two generalizations can be drawn: fire severity effects are mostly shortlived, i.e., by the second year they are greatly diminished, and fire severity may have opposite effects on different functional types. Species richness exhibited a negative relationship to fire severity in the first year, but fire severity impacts were substantially less in the second postfire year and varied by functional type. Much of this relationship was due to alien plants that are sensitive to high fire severity; at all scales from 1 to 1000 m2, the percentage of alien species in the postfire flora declined with increased fire severity. Other aspects of disturbance history are also important determinants of alien cover and richness as both increased with the number of times the site had burned and decreased with time since last fire. A substantial number of studies have shown that remote-sensing indices are correlated with field measurements of fire severity. Across our sites, absolute differenced normalized burn ratio (dNBR) was strongly correlated with field measures of fire severity and with fire history at a site but relative dNBR was not. Despite being correlated with fire severity, absolute dNBR showed little or no relationship with important ecosystem responses to wildfire such as shrub resprouting or total vegetative regeneration. These findings point to a critical need for further research on interpreting remote sensing indices as applied to postfire management of these shrublands.

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.

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.

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.

Influence of different topographic correction strategies on mountain vegetation classification accuracy in the Lancang Watershed, China

NASA Astrophysics Data System (ADS)

Zhang, Zhiming; de Wulf, Robert R.; van Coillie, Frieke M. B.; Verbeke, Lieven P. C.; de Clercq, Eva M.; Ou, Xiaokun

2011-01-01

Mapping of vegetation using remote sensing in mountainous areas is considerably hampered by topographic effects on the spectral response pattern. A variety of topographic normalization techniques have been proposed to correct these illumination effects due to topography. The purpose of this study was to compare six different topographic normalization methods (Cosine correction, Minnaert correction, C-correction, Sun-canopy-sensor correction, two-stage topographic normalization, and slope matching technique) for their effectiveness in enhancing vegetation classification in mountainous environments. Since most of the vegetation classes in the rugged terrain of the Lancang Watershed (China) did not feature a normal distribution, artificial neural networks (ANNs) were employed as a classifier. Comparing the ANN classifications, none of the topographic correction methods could significantly improve ETM+ image classification overall accuracy. Nevertheless, at the class level, the accuracy of pine forest could be increased by using topographically corrected images. On the contrary, oak forest and mixed forest accuracies were significantly decreased by using corrected images. The results also showed that none of the topographic normalization strategies was satisfactorily able to correct for the topographic effects in severely shadowed areas.

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.

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.

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.

Building a delta: Interactions between water, sediment, and vegetation in an experimental system

NASA Astrophysics Data System (ADS)

Piliouras, A.; Kim, W.; Carlson, B.

2013-12-01

Vegetation is an important part of morphodynamics in river deltas, but it has not been thoroughly investigated in physical delta models. We conducted a set of experiments in the Sediment Transport and Earth-surface Processes (STEP) Basin at the University of Texas at Austin to examine the effects of vegetation on delta growth and dynamics. One experiment was conducted without vegetation (Run 1), and four (Runs 2-5) were conducted using alfalfa (Medicago sativa) as a proxy for riparian vegetation, one of which included cycles between flood and normal flow discharges (Run 5). Results indicate that vegetation increased sediment trapping on the delta topset, increasing delta slope and decreasing progradation rate as compared to the unvegetated experiment. Vegetation also caused a lack of channelization when the topset reached 20% plant cover, after which progradational delta lobes were no longer evident. Discharge fluctuations in Run 5, however, led to more topset reworking, resulting in lower vegetation density (< 20%) and the persistence of highly incisional channels. Experiments run only at flood stage resulted in consistently net depositional deltas with very little channel incision, regardless of the amount of vegetation. The addition of water and sediment discharge fluctuations in Run 5, however, created a cyclic pattern between periods of topset aggradation and periods of channel incision that were net erosional. We conclude that there is a two-way interaction between the vegetation and the channels through discharge fluctuations that aid in delta growth. (1) During floods, vegetation acts an efficient sediment trapper on the floodplain to aid in topset aggradation and maintain channel relief. During normal flow, vegetation also stabilizes channel banks, allowing channels to focus their flow and erode sediment from the bed. (2) During floods, channels transport sediment to the shoreline to create new deposits that can be colonized by vegetation and deliver sediment to the topset to increase vegetation elevation. During normal flow, channels rework the delta topset and remove seeds from occupied flow paths.

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

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

NASA Astrophysics Data System (ADS)

Wang, H.

2017-12-01

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

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.

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.

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.

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.

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.

A Study of Derivative Filters Using the Discrete Fourier Transform. Final Report M. S. Thesis

NASA Technical Reports Server (NTRS)

Ioup, G. E.

1980-01-01

Important properties of derivative (difference) filters using the discrete Fourier transform are investigated. The filters are designed using the derivative theorem of Fourier analysis. Because physical data are generally degraded by noise, the derivative filter is modified to diminish the effects of the noise, especially the noise amplification which normally occurs while differencing. The basis for these modifications is the reduction of those Fourier components for which the noise most dominates the data. The various filters are tested by applying them to find differences of two-dimensional data to which various amounts of signal dependent noise, as measured by a root mean square value, have been added. The modifications, circular and square ideal low-pass filters and a cut-off pyramid filter, are all found to reduce noise in the derivative without significantly degrading the result.

Simulation of Plasma Transport in a Toroidal Annulus with TEMPEST

NASA Astrophysics Data System (ADS)

Xiong, Z.

2005-10-01

TEMPEST is an edge gyro-kinetic continuum code currently under development at LLNL to study boundary plasma transport over a region extending from inside the H-mode pedestal across the separatrix to the divertor plates. Here we report simulation results from the 4D (θ, ψ, E, μ) TEMPEST, for benchmark purpose, in an annulus region immediately inside the separatrix of a large aspect ratio, circular cross-section tokamak. Besides the normal poloidal trapping regions, there are radial inaccessible regions at a fixed poloid angle, energy and magnetic moment due to the radial variation of the B field. To handle such cases, a fifth-order WENO differencing scheme is used in the radial direction. The particle and heat transport coefficients are obtained for different collisional regimes and compared with the neo-classical transport theory.

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.

Surface Deformation Associated with the 1983 Borah Peak Earthquake Measured from Digital Surface Model Differencing

NASA Astrophysics Data System (ADS)

Reitman, N. G.; Briggs, R.; Gold, R. D.; DuRoss, C. B.

2015-12-01

Post-earthquake, field-based assessments of surface displacement commonly underestimate offsets observed with remote sensing techniques (e.g., InSAR, image cross-correlation) because they fail to capture the total deformation field. Modern earthquakes are readily characterized by comparing pre- and post-event remote sensing data, but historical earthquakes often lack pre-event data. To overcome this challenge, we use historical aerial photographs to derive pre-event digital surface models (DSMs), which we compare to modern, post-event DSMs. Our case study focuses on resolving on- and off-fault deformation along the Lost River fault that accompanied the 1983 M6.9 Borah Peak, Idaho, normal-faulting earthquake. We use 343 aerial images from 1952-1966 and vertical control points selected from National Geodetic Survey benchmarks measured prior to 1983 to construct a pre-event point cloud (average ~ 0.25 pts/m2) and corresponding DSM. The post-event point cloud (average ~ 1 pt/m2) and corresponding DSM are derived from WorldView 1 and 2 scenes processed with NASA's Ames Stereo Pipeline. The point clouds and DSMs are coregistered using vertical control points, an iterative closest point algorithm, and a DSM coregistration algorithm. Preliminary results of differencing the coregistered DSMs reveal a signal spanning the surface rupture that is consistent with tectonic displacement. Ongoing work is focused on quantifying the significance of this signal and error analysis. We expect this technique to yield a more complete understanding of on- and off-fault deformation patterns associated with the Borah Peak earthquake along the Lost River fault and to help improve assessments of surface deformation for other historical ruptures.

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.

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.

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.

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.

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.

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

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

PubMed

Liao, Hong-kai; Long, Jian

2011-09-01

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

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.

Assessing cadmium exposure risks of vegetables with plant uptake factor and soil property.

PubMed

Yang, Yang; Chang, Andrew C; Wang, Meie; Chen, Weiping; Peng, Chi

2018-07-01

Plant uptake factors (PUFs) are of great importance in human cadmium (Cd) exposure risk assessment while it has been often treated in a generic way. We collected 1077 pairs of vegetable-soil samples from production fields to characterize Cd PUFs and demonstrated their utility in assessing Cd exposure risks to consumers of locally grown vegetables. The Cd PUFs varied with plant species and pH and organic matter content of soils. Once normalized PUFs against soil parameters, the PUFs distributions were log-normal in nature. In this manner, the PUFs were represented by definable probability distributions instead of a deterministic figure. The Cd exposure risks were then assessed using the normalized PUF based on the Monte Carlo simulation algorithm. Factors affecting the extent of Cd exposures were isolated through sensitivity analyses. Normalized PUF would illustrate the outcomes for uncontaminated and slightly contaminated soils. Among the vegetables, lettuce was potentially hazardous for residents due to its high Cd accumulation but low Zn concentration. To protect 95% of the lettuce production from causing excessive Cd exposure risks, pH of soils needed to be 5.9 and above. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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.

Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.

1987-01-01

A two-stream approximation to the radiative-transfer equation is used to calculate the vegetation indices (simple ratio and normalized difference), the fraction of incident photosynthetically active radiation (PAR) absorbed by the canopy, and the daily mean canopy net photosynthesis under clear-sky conditions. The model calculations are tested against field observations over wheat, cotton, corn, and soybean. The relationships between the vegetation indices and radiation absorption or net photosynthesis are generally found to be curvilinear, and changes in the soil reflectance affected these relationships. The curvilinearity of the relationship between normalized differences and PAR absorption decreases as the magnitude of soil reflectance increases. The vegetation indices might provide the fractional radiation absorption with some a priori knowledge about soil reflectance. The relationship between the vegetation indices and net photosynthesis must be distinguished for C3 and C4 crops. Effects of spatial heterogeneity are discussed.

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.

Ice sheet altimetry

NASA Technical Reports Server (NTRS)

Brooks, R. L.

1981-01-01

Generalized surface slopes were computed for the Antarctic and Greenland ice sheets by differencing plotted contour levels and dividing them by the distance between the contours. It was observed that more than 90% of the ice sheets have surface slopes less than 1%. Seasat test mode-1 Seasat altimeter measurements over Greenland were analyzed by comparisons with collinear and intersecting normal mode Seasat altimeter passes. Over the ice sheet, the computed surface elevations from test mode-1 measurements were consistently lower by about 45 m and the AGC levels were down by approximately 6 dB. No test mode-1 data were acquired over Antarctica. It is concluded that analysis of the existing altimeter data base over the two ice sheets is crucial in designing a future improved altimeter tracking capability. It is recommended that additional waveform retracking be performed to characterize ice sheet topography as a function of geographic area and elevation.

An efficient iteration strategy for the solution of the Euler equations

NASA Technical Reports Server (NTRS)

Walters, R. W.; Dwoyer, D. L.

1985-01-01

A line Gauss-Seidel (LGS) relaxation algorithm in conjunction with a one-parameter family of upwind discretizations of the Euler equations in two-dimensions is described. The basic algorithm has the property that convergence to the steady-state is quadratic for fully supersonic flows and linear otherwise. This is in contrast to the block ADI methods (either central or upwind differenced) and the upwind biased relaxation schemes, all of which converge linearly, independent of the flow regime. Moreover, the algorithm presented here is easily enhanced to detect regions of subsonic flow embedded in supersonic flow. This allows marching by lines in the supersonic regions, converging each line quadratically, and iterating in the subsonic regions, thus yielding a very efficient iteration strategy. Numerical results are presented for two-dimensional supersonic and transonic flows containing both oblique and normal shock waves which confirm the efficiency of the iteration strategy.

Efficient solutions to the Euler equations for supersonic flow with embedded subsonic regions

NASA Technical Reports Server (NTRS)

Walters, Robert W.; Dwoyer, Douglas L.

1987-01-01

A line Gauss-Seidel (LGS) relaxation algorithm in conjunction with a one-parameter family of upwind discretizations of the Euler equations in two dimensions is described. Convergence of the basic algorithm to the steady state is quadratic for fully supersonic flows and is linear for other flows. This is in contrast to the block alternating direction implicit methods (either central or upwind differenced) and the upwind biased relaxation schemes, all of which converge linearly, independent of the flow regime. Moreover, the algorithm presented herein is easily coupled with methods to detect regions of subsonic flow embedded in supersonic flow. This allows marching by lines in the supersonic regions, converging each line quadratically, and iterating in the subsonic regions, and yields a very efficient iteration strategy. Numerical results are presented for two-dimensional supersonic and transonic flows containing oblique and normal shock waves which confirm the efficiency of the iteration strategy.

Burn severity mapping in Australia 2009

USGS Publications Warehouse

McKinley, Randy; Clark, J.; Lecker, Jennifer

2012-01-01

In 2009, the Victoria Department of Sustainability and Environment estimated approximately 430,000 hectares of Victoria Australia were burned by numerous bushfires. Burned Area Emergency Response (BAER) teams from the United States were deployed to Victoria to assist local fire managers. The U.S. Geological Survey Earth Resources Observation and Science Center (USGS/EROS) and U.S. Forest Service Remote Sensing Applications Center (USFS/RSAC) aided the support effort by providing satellite-derived "soil burn severity " maps for over 280,000 burned hectares. In the United States, BAER teams are assembled to make rapid assessments of burned lands to identify potential hazards to public health and property. An early step in the assessment process is the creation of a soil burn severity map used to identify hazard areas and prioritize treatment locations. These maps are developed primarily using Landsat satellite imagery and the differenced Normalized Burn Ratio (dNBR) algorithm.

Second- and third-order upwind difference schemes for hyperbolic conservation laws

NASA Technical Reports Server (NTRS)

Yang, J. Y.

1984-01-01

Second- and third-order two time-level five-point explicit upwind-difference schemes are described for the numerical solution of hyperbolic systems of conservation laws and applied to the Euler equations of inviscid gas dynamics. Nonliner smoothing techniques are used to make the schemes total variation diminishing. In the method both hyperbolicity and conservation properties of the hyperbolic conservation laws are combined in a very natural way by introducing a normalized Jacobian matrix of the hyperbolic system. Entropy satisfying shock transition operators which are consistent with the upwind differencing are locally introduced when transonic shock transition is detected. Schemes thus constructed are suitable for shockcapturing calculations. The stability and the global order of accuracy of the proposed schemes are examined. Numerical experiments for the inviscid Burgers equation and the compressible Euler equations in one and two space dimensions involving various situations of aerodynamic interest are included and compared.

Calculations of turbulent separated flows

NASA Technical Reports Server (NTRS)

Zhu, J.; Shih, T. H.

1993-01-01

A numerical study of incompressible turbulent separated flows is carried out by using two-equation turbulence models of the K-epsilon type. On the basis of realizability analysis, a new formulation of the eddy-viscosity is proposed which ensures the positiveness of turbulent normal stresses - a realizability condition that most existing two-equation turbulence models are unable to satisfy. The present model is applied to calculate two backward-facing step flows. Calculations with the standard K-epsilon model and a recently developed RNG-based K-epsilon model are also made for comparison. The calculations are performed with a finite-volume method. A second-order accurate differencing scheme and sufficiently fine grids are used to ensure the numerical accuracy of solutions. The calculated results are compared with the experimental data for both mean and turbulent quantities. The comparison shows that the present model performs quite well for separated flows.

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

A Simple and Effective Image Normalization Method to Monitor Boreal Forest Change in a Siberian Burn Chronosequence across Sensors and across Time

NASA Astrophysics Data System (ADS)

Chen, X.; Vierling, L. A.; Deering, D. W.

2004-12-01

Satellite data offer unique perspectives for monitoring and quantifying land cover change, however, the radiometric consistency among co-located multi-temporal images is difficult to maintain due to variations in sensors and atmosphere. To detect accurate landscape change using multi-temporal images, we developed a new relative radiometric normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on 9 June 1990 (Landsat 4), 20 June 2000, and 26 August 2001 (Landsat 7) for analyses over boreal forests near the Siberian city of Krasnoyarsk. Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Reduced Simple Ratio (RSR) were investigated in the normalization study. The temporally invariant cluster (TIC) centers were identified through a point density map of the base image and the target image and a normalization regression line was created through all TIC centers. The target image digital data were then converted using the regression function so that the two images could be compared using the resulting common radiometric scale. We found that EVI was very sensitive to vegetation structure and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. NDVI was a very effective vegetation index to reduce the influence of shadow, while EVI was very sensitive to shadowing. After normalization, correlations of NDVI and EVI with field collected total Leaf Area Index (LAI) data in 2000 and 2001 were significantly improved; the r-square values in these regressions increased from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI ¡°cancellation effect¡± where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared with some previous relative normalization methods, this new method can avoid subjective selection of a normalization regression line. It does not require high level programming and statistical analyses, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare.

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.

Drought in the Rockies

NASA Technical Reports Server (NTRS)

2002-01-01

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

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...

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.

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

Treesearch

David L. Evans; Raymond L. Czaplewski

1996-01-01

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

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...

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

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.

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.

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.

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.

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

Treesearch

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

2014-01-01

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

A 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...

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.

Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.

PubMed

Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

2013-05-01

Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.

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.

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.

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

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.

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.

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.

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.

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

PubMed

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

2016-06-15

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

Error reduction program: A progress report

NASA Technical Reports Server (NTRS)

Syed, S. A.

1984-01-01

Five finite differences schemes were evaluated for minimum numerical diffusion in an effort to identify and incorporate the best error reduction scheme into a 3D combustor performance code. Based on this evaluated, two finite volume method schemes were selected for further study. Both the quadratic upstream differencing scheme (QUDS) and the bounded skew upstream differencing scheme two (BSUDS2) were coded into a two dimensional computer code and their accuracy and stability determined by running several test cases. It was found that BSUDS2 was more stable than QUDS. It was also found that the accuracy of both schemes is dependent on the angle that the streamline make with the mesh with QUDS being more accurate at smaller angles and BSUDS2 more accurate at larger angles. The BSUDS2 scheme was selected for extension into three dimensions.

Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harder, Phillip; Schirmer, Michael; Pomeroy, John; Helgason, Warren

2016-11-01

Quantifying the spatial distribution of snow is crucial to predict and assess its water resource potential and understand land-atmosphere interactions. High-resolution remote sensing of snow depth has been limited to terrestrial and airborne laser scanning and more recently with application of structure from motion (SfM) techniques to airborne (manned and unmanned) imagery. In this study, photography from a small unmanned aerial vehicle (UAV) was used to generate digital surface models (DSMs) and orthomosaics for snow cover at a cultivated agricultural Canadian prairie and a sparsely vegetated Rocky Mountain alpine ridgetop site using SfM. The accuracy and repeatability of this method to quantify snow depth, changes in depth and its spatial variability was assessed for different terrain types over time. Root mean square errors in snow depth estimation from differencing snow-covered and non-snow-covered DSMs were 8.8 cm for a short prairie grain stubble surface, 13.7 cm for a tall prairie grain stubble surface and 8.5 cm for an alpine mountain surface. This technique provided useful information on maximum snow accumulation and snow-covered area depletion at all sites, while temporal changes in snow depth could also be quantified at the alpine site due to the deeper snowpack and consequent higher signal-to-noise ratio. The application of SfM to UAV photographs returns meaningful information in areas with mean snow depth > 30 cm, but the direct observation of snow depth depletion of shallow snowpacks with this method is not feasible. Accuracy varied with surface characteristics, sunlight and wind speed during the flight, with the most consistent performance found for wind speeds < 10 m s-1, clear skies, high sun angles and surfaces with negligible vegetation cover.

The study and realization of BDS un-differenced network-RTK based on raw observations

NASA Astrophysics Data System (ADS)

Tu, Rui; Zhang, Pengfei; Zhang, Rui; Lu, Cuixian; Liu, Jinhai; Lu, Xiaochun

2017-06-01

A BeiDou Navigation Satellite System (BDS) Un-Differenced (UD) Network Real Time Kinematic (URTK) positioning algorithm, which is based on raw observations, is developed in this study. Given an integer ambiguity datum, the UD integer ambiguity can be recovered from Double-Differenced (DD) integer ambiguities, thus the UD observation corrections can be calculated and interpolated for the rover station to achieve the fast positioning. As this URTK model uses raw observations instead of the ionospheric-free combinations, it is applicable for both dual- and single-frequency users to realize the URTK service. The algorithm was validated with the experimental BDS data collected at four regional stations from day of year 080 to 083 in 2016. The achieved results confirmed the high efficiency of the proposed URTK for providing the rover users a rapid and precise positioning service compared to the standard NRTK. In our test, the BDS URTK can provide a positioning service with cm level accuracy, i.e., 1 cm in the horizontal components, and 2-3 cm in the vertical component. Within the regional network, the mean convergence time for the users to fix the UD ambiguities is 2.7 s for the dual-frequency observations and of 6.3 s for the single-frequency observations after the DD ambiguity resolution. Furthermore, due to the feature of realizing URTK technology under the UD processing mode, it is possible to integrate the global Precise Point Positioning (PPP) and the local NRTK into a seamless positioning service.

Precise Tracking of the Magellan and Pioneer Venus Orbiters by Same-Beam Interferometry. Part 2: Orbit Determination Analysis

NASA Technical Reports Server (NTRS)

Folkner, W. M.; Border, J. S.; Nandi, S.; Zukor, K. S.

1993-01-01

A new radio metric positioning technique has demonstrated improved orbit determination accuracy for the Magellan and Pioneer Venus Orbiter orbiters. The new technique, known as Same-Beam Interferometry (SBI), is applicable to the positioning of multiple planetary rovers, landers, and orbiters which may simultaneously be observed in the same beamwidth of Earth-based radio antennas. Measurements of carrier phase are differenced between spacecraft and between receiving stations to determine the plane-of-sky components of the separation vector(s) between the spacecraft. The SBI measurements complement the information contained in line-of-sight Doppler measurements, leading to improved orbit determination accuracy. Orbit determination solutions have been obtained for a number of 48-hour data arcs using combinations of Doppler, differenced-Doppler, and SBI data acquired in the spring of 1991. Orbit determination accuracy is assessed by comparing orbit solutions from adjacent data arcs. The orbit solution differences are shown to agree with expected orbit determination uncertainties. The results from this demonstration show that the orbit determination accuracy for Magellan obtained by using Doppler plus SBI data is better than the accuracy achieved using Doppler plus differenced-Doppler by a factor of four and better than the accuracy achieved using only Doppler by a factor of eighteen. The orbit determination accuracy for Pioneer Venus Orbiter using Doppler plus SBI data is better than the accuracy using only Doppler data by 30 percent.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

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.

APPLYING SATELLITE IMAGERY TO TRIAGE ASSESSMENT OF ECOSYSTEM HEALTH

EPA Science Inventory

Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR)imagery to develop calibration patterns of change in the Normalized Difference Vegetation Ind...

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.

Comparative analysis of data quality and applications in vegetation of HJ-1A CCD images

NASA Astrophysics Data System (ADS)

Wei, Hongwei; Tian, Qingjiu; Huang, Yan; Wang, Yan

2014-05-01

To study the data quality and to find the differences in vegetation monitoring applications, the same region at Chuzhou Lai 'an, the data of HJ-1A CCD1 on the April 1st, 2012 and the data of HJ-1A CCD2 on the March 31, 2012 have being comparative analysis by the method of objective quality (image)assessment which selecting over five spectral image evaluation parameters: radiation precision (mean, variance, inclination, steepness), information entropy, signal-to-noise ratio, sharpness, contrast, and normalized differential vegetation index. The results show that there is little differences between the HJ-1A CCD1 and CCD2 by objective evaluation of data quality except radiation precision conform to their design theory, so the conclusion is that the difference of them without considering on the usual unless continuation;and Combination of field observation data Lai'an spectral data and GPS data (each point),selecting the normalized difference vegetation index as CCD1, CCD2 in vegetation monitoring application on the evaluation of the differences, and the specific process is based on GPS data is divided into nine small plots of spectral data ,and image data of nine one-to-one correspondence plots, and their normalized difference vegetation index values were calculated ,and measured spectra data resampling HJ-1A CCD1, CCD2 spectral response function calculated NDVI, and the results show that there is little differences between the HJ-1A CCD1 and CCD2 by objective evaluation of data quality, and, the differences of wheat `s reflection and normalized vegetation index is mainly due to calibration coefficients of CCD1 and CCD2, the differences of the solar elevation angle when obtaining the image and atmospheric conditions, so it has to consider the performance indicators as well as access conditions of CCD1 and CCD2, and to be take the normalization techniques for processing for the comparison analysis in the use of HJ-1A CCD Data to surface dynamic changes; Finally, in order to study the response of the spectral response function proposed spectral response function of impact factor, and in view of the spectral response function measured spectral data resampling only HJ-1A CCD spectral response function, calculated according to the formula of the equivalent reflectivity quantitative spectral response function, and spectral normalization of proposed theoretical Technical Support. The Objective evaluation of its application of HJ-1A CCD1, and CCD2 data quality differences research has important implications for broader application to further promote China-made remote sensing satellite data, future research also needs calibration coefficient, the solar elevation angle atmospheric conditions and its image scanning angle be taken into account, and to make the corresponding normalized its impact quantitative research has important significance for the timing changes in the application of the ecological environment in China.

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.

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.

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.

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.

Overview of Minerals

MedlinePlus

... and dark green vegetables Required for metabolism of nitrogen, the activation of certain enzymes, and normal cell ... normal nerve and muscle function Involved in electrolyte balance 3.5 grams — Selenium Meats, seafood, nuts, and ...

Nonlinear time series analysis of electrocardiograms

NASA Astrophysics Data System (ADS)

Bezerianos, A.; Bountis, T.; Papaioannou, G.; Polydoropoulos, P.

1995-03-01

In recent years there has been an increasing number of papers in the literature, applying the methods and techniques of Nonlinear Dynamics to the time series of electrical activity in normal electrocardiograms (ECGs) of various human subjects. Most of these studies are based primarily on correlation dimension estimates, and conclude that the dynamics of the ECG signal is deterministic and occurs on a chaotic attractor, whose dimension can distinguish between healthy and severely malfunctioning cases. In this paper, we first demonstrate that correlation dimension calculations must be used with care, as they do not always yield reliable estimates of the attractor's ``dimension.'' We then carry out a number of additional tests (time differencing, smoothing, principal component analysis, surrogate data analysis, etc.) on the ECGs of three ``normal'' subjects and three ``heavy smokers'' at rest and after mild exercising, whose cardiac rhythms look very similar. Our main conclusion is that no major dynamical differences are evident in these signals. A preliminary estimate of three to four basic variables governing the dynamics (based on correlation dimension calculations) is updated to five to six, when temporal correlations between points are removed. Finally, in almost all cases, the transition between resting and mild exercising seems to imply a small increase in the complexity of cardiac dynamics.

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...

Earth orientation from lunar laser range-differencing. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Leick, A.

1978-01-01

For the optimal use of high precision lunar laser ranging (LLR), an investigation regarding a clear definition of the underlying coordinate systems, identification of estimable quantities, favorable station geometry and optimal observation schedule is given.

The DANTE Boltzmann transport solver: An unstructured mesh, 3-D, spherical harmonics algorithm compatible with parallel computer architectures

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

McGhee, J.M.; Roberts, R.M.; Morel, J.E.

1997-06-01

A spherical harmonics research code (DANTE) has been developed which is compatible with parallel computer architectures. DANTE provides 3-D, multi-material, deterministic, transport capabilities using an arbitrary finite element mesh. The linearized Boltzmann transport equation is solved in a second order self-adjoint form utilizing a Galerkin finite element spatial differencing scheme. The core solver utilizes a preconditioned conjugate gradient algorithm. Other distinguishing features of the code include options for discrete-ordinates and simplified spherical harmonics angular differencing, an exact Marshak boundary treatment for arbitrarily oriented boundary faces, in-line matrix construction techniques to minimize memory consumption, and an effective diffusion based preconditioner formore » scattering dominated problems. Algorithm efficiency is demonstrated for a massively parallel SIMD architecture (CM-5), and compatibility with MPP multiprocessor platforms or workstation clusters is anticipated.« less

Intrinsic imperfection of self-differencing single-photon detectors harms the security of high-speed quantum cryptography systems

NASA Astrophysics Data System (ADS)

Jiang, Mu-Sheng; Sun, Shi-Hai; Tang, Guang-Zhao; Ma, Xiang-Chun; Li, Chun-Yan; Liang, Lin-Mei

2013-12-01

Thanks to the high-speed self-differencing single-photon detector (SD-SPD), the secret key rate of quantum key distribution (QKD), which can, in principle, offer unconditionally secure private communications between two users (Alice and Bob), can exceed 1 Mbit/s. However, the SD-SPD may contain loopholes, which can be exploited by an eavesdropper (Eve) to hack into the unconditional security of the high-speed QKD systems. In this paper, we analyze the fact that the SD-SPD can be remotely controlled by Eve in order to spy on full information without being discovered, then proof-of-principle experiments are demonstrated. Here, we point out that this loophole is introduced directly by the operating principle of the SD-SPD, thus, it cannot be removed, except for the fact that some active countermeasures are applied by the legitimate parties.

Computations of the three-dimensional flow and heat transfer within a coolant passage of a radial turbine blade

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Roelke, R. J.; Steinthorsson, E.

1991-01-01

A numerical code is developed for computing three-dimensional, turbulent, compressible flow within coolant passages of turbine blades. The code is based on a formulation of the compressible Navier-Stokes equations in a rotating frame of reference in which the velocity dependent variable is specified with respect to the rotating frame instead of the inertial frame. The algorithm employed to obtain solutions to the governing equation is a finite-volume LU algorithm that allows convection, source, as well as diffusion terms to be treated implicitly. In this study, all convection terms are upwind differenced by using flux-vector splitting, and all diffusion terms are centrally differenced. This paper describes the formulation and algorithm employed in the code. Some computed solutions for the flow within a coolant passage of a radial turbine are also presented.

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays.

PubMed

Shi, Junpeng; Hu, Guoping; Sun, Fenggang; Zong, Binfeng; Wang, Xin

2017-08-24

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions.

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays

PubMed Central

Hu, Guoping; Zong, Binfeng; Wang, Xin

2017-01-01

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions. PMID:28837115

Gravitational Microlensing Observations of Two New Exoplanets Using the Deep Impact High Resolution Instrument

NASA Astrophysics Data System (ADS)

Barry, Richard K.; Bennett, D. P.; Klaasen, K.; Becker, A. C.; Christiansen, J.; Albrow, M.

2014-01-01

We have worked to characterize two exoplanets newly detected from the ground: OGLE-2012-BLG-0406 and OGLE-2012-BLG-0838, using microlensing observations of the Galactic Bulge recently obtained by NASA’s Deep Impact (DI) spacecraft, in combination with ground data. These observations of the crowded Bulge fields from Earth and from an observatory at a distance of ~1 AU have permitted the extraction of a microlensing parallax signature - critical for breaking exoplanet model degeneracies. For this effort, we used DI’s High Resolution Instrument, launched with a permanent defocus aberration due to an error in cryogenic testing. We show how the effects of a very large, chromatic PSF can be reduced in differencing photometry. We also compare two approaches to differencing photometry - one of which employs the Bramich algorithm and another using the Fruchter & Hook drizzle algorithm.

Controlling Reflections from Mesh Refinement Interfaces in Numerical Relativity

NASA Technical Reports Server (NTRS)

Baker, John G.; Van Meter, James R.

2005-01-01

A leading approach to improving the accuracy on numerical relativity simulations of black hole systems is through fixed or adaptive mesh refinement techniques. We describe a generic numerical error which manifests as slowly converging, artificial reflections from refinement boundaries in a broad class of mesh-refinement implementations, potentially limiting the effectiveness of mesh- refinement techniques for some numerical relativity applications. We elucidate this numerical effect by presenting a model problem which exhibits the phenomenon, but which is simple enough that its numerical error can be understood analytically. Our analysis shows that the effect is caused by variations in finite differencing error generated across low and high resolution regions, and that its slow convergence is caused by the presence of dramatic speed differences among propagation modes typical of 3+1 relativity. Lastly, we resolve the problem, presenting a class of finite-differencing stencil modifications which eliminate this pathology in both our model problem and in numerical relativity examples.

The terminal area simulation system. Volume 1: Theoretical formulation

NASA Technical Reports Server (NTRS)

Proctor, F. H.

1987-01-01

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

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.

A decadal glimpse on climate and burn severity influences on ponderosa pine post-fire recovery

NASA Astrophysics Data System (ADS)

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

2016-12-01

Climate change is predicted to affect plants at the margins of their distribution. Thus, ecosystem recovery after fire is likely to vary with climate and may be slowest in drier and hotter areas. However, fire regime characteristics, including burn severity, may also affect vegetation recovery. We assessed vegetation recovery one and 9-15 years post-fire in North American ponderosa pine ecosystems distributed across climate and burn severity gradients. Using climate predictors derived from downscaled 1993-2011 climate normals, we predicted vegetation recovery as indicated by Normalized Burn Ratio derived from 1984-2012 Landsat time series imagery. Additionally, we collected field vegetation measurements to examine local topographic controls on burn severity and post-fire vegetation recovery. At a regional scale, we hypothesized a positive relationship between precipitation and recovery time and a negative relationship between temperature and recovery time. At the local scale, we hypothesized southern aspects to recovery slower than northern aspects. We also predicted higher burn severity to slow recovery. Field data found attenuated ponderosa pine recovery in hotter and drier regions across all burn severity classes. We concluded that downscaled climate data and Landsat imagery collected at commensurate scales may provide insight into climate effects on post-fire vegetation recovery relevant to ponderosa pine forest managers.

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.

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

PubMed Central

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

2016-01-01

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

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...

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.

Millennial climatic fluctuations are key to the structure of last glacial ecosystems.

PubMed

Huntley, Brian; Allen, Judy R M; Collingham, Yvonne C; Hickler, Thomas; Lister, Adrian M; Singarayer, Joy; Stuart, Anthony J; Sykes, Martin T; Valdes, Paul J

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in "normal" and "hosing" experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The "hosing" experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the "normal" experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems.

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.

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.

A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

USGS Publications Warehouse

Chen, X.; Vierling, Lee; Deering, D.

2005-01-01

Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phenological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes. ?? 2005 Elsevier Inc. All rights reserved.

Influence of flaps and engines on aircraft wake vortices

DOT National Transportation Integrated Search

1974-09-01

Although pervious investigations have shown that the nature of aircraft wake vortices depends on the aircraft type and flap configuration, the causes for these differences have not been clearly identified. In this Note we show that observed differenc...

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.

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.

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]), ...

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 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.

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

Processes of Compression-Expansion and Subsidence-Uplift detected by the Spatial Inclinometer (IESHI) in the El Hierro Island eruption (October, 2011)

NASA Astrophysics Data System (ADS)

Prates, G.; Berrocoso, M.; Fernández-Ros, A.; García, A.; Ortiz, R.

2012-04-01

El Hierro Island (Canary Islands, Spain) has undergone a submarine eruption a few kilometers to its southeast, detected October 10, on the rift alignment that cuts across the island. However, the seismicity level suddenly increased around July 17 and ground deformation was detected by the only continuously observed GNSS-GPS (Global Navigation Satellite Systems - Global Positioning System) benchmark FRON in the El Golfo area. Based on that information several other GNSS-GPS benchmarks were installed, some of which continuously observed as well. A normal vector analysis was applied to these collected data. The normal vector magnitude variation identified local extension-compression regimes, while the normal vector inclination showed the relative height variation between the three benchmarks that define the plan to which normal vector is analyzed. To accomplish this analysis the data was previously processed to achieve positioning solutions every 30 minutes using the Bernese GPS Software 5.0, further enhanced by a Discrete Kalman Filter, giving an overall millimeter level precision. These solutions were reached using the IGS (International GNSS Service) ultra-rapid orbits and the double-differenced ionosphere-free combination. With this strategy the positioning solutions were attained in near real-time. Later with the IGS rapid orbits the data was reprocessed to provide added confidence to the solutions. Two triangles were then considered, a smaller one located in the El Golfo area within the historically collapsed caldera, and a larger one defined by benchmarks placed in Valverde, El Golfo and La Restinga, the town closest to the eruption's location, covering almost the entire Island's surface above sea level. With these two triangles the pre-eruption and post-eruption deformation suffered by El Hierro's surface will be further analyzed.

Fire frequency, area burned, and severity: A quantitative approach to defining a normal fire year

USGS Publications Warehouse

Lutz, J.A.; Key, C.H.; Kolden, C.A.; Kane, J.T.; van Wagtendonk, J.W.

2011-01-01

Fire frequency, area burned, and fire severity are important attributes of a fire regime, but few studies have quantified the interrelationships among them in evaluating a fire year. Although area burned is often used to summarize a fire season, burned area may not be well correlated with either the number or ecological effect of fires. Using the Landsat data archive, we examined all 148 wildland fires (prescribed fires and wildfires) >40 ha from 1984 through 2009 for the portion of the Sierra Nevada centered on Yosemite National Park, California, USA. We calculated mean fire frequency and mean annual area burned from a combination of field- and satellite-derived data. We used the continuous probability distribution of the differenced Normalized Burn Ratio (dNBR) values to describe fire severity. For fires >40 ha, fire frequency, annual area burned, and cumulative severity were consistent in only 13 of 26 years (50 %), but all pair-wise comparisons among these fire regime attributes were significant. Borrowing from long-established practice in climate science, we defined "fire normals" to be the 26 year means of fire frequency, annual area burned, and the area under the cumulative probability distribution of dNBR. Fire severity normals were significantly lower when they were aggregated by year compared to aggregation by area. Cumulative severity distributions for each year were best modeled with Weibull functions (all 26 years, r2 ??? 0.99; P < 0.001). Explicit modeling of the cumulative severity distributions may allow more comprehensive modeling of climate-severity and area-severity relationships. Together, the three metrics of number of fires, size of fires, and severity of fires provide land managers with a more comprehensive summary of a given fire year than any single metric.

AN IMMERSED BOUNDARY METHOD FOR COMPLEX INCOMPRESSIBLE FLOWS

EPA Science Inventory

An immersed boundary method for time-dependant, three- dimensional, incompressible flows is presented in this paper. The incompressible Navier-Stokes equations are discretized using a low-diffusion flux splitting method for the inviscid fluxes and a second order central differenc...

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.

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...

Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia

NASA Astrophysics Data System (ADS)

Sabajo, Clifton R.; le Maire, Guerric; June, Tania; Meijide, Ana; Roupsard, Olivier; Knohl, Alexander

2017-10-01

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.

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.

Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

USGS Publications Warehouse

Garrity, Steven R.; Allen, Craig D.; Brumby, Steven P.; Gangodagamage, Chandana; McDowell, Nate G.; Cai, D. Michael

2013-01-01

Widespread tree mortality events have recently been observed in several biomes. To effectively quantify the severity and extent of these events, tools that allow for rapid assessment at the landscape scale are required. Past studies using high spatial resolution satellite imagery have primarily focused on detecting green, red, and gray tree canopies during and shortly after tree damage or mortality has occurred. However, detecting trees in various stages of death is not always possible due to limited availability of archived satellite imagery. Here we assess the capability of high spatial resolution satellite imagery for tree mortality detection in a southwestern U.S. mixed species woodland using archived satellite images acquired prior to mortality and well after dead trees had dropped their leaves. We developed a multistep classification approach that uses: supervised masking of non-tree image elements; bi-temporal (pre- and post-mortality) differencing of normalized difference vegetation index (NDVI) and red:green ratio (RGI); and unsupervised multivariate clustering of pixels into live and dead tree classes using a Gaussian mixture model. Classification accuracies were improved in a final step by tuning the rules of pixel classification using the posterior probabilities of class membership obtained from the Gaussian mixture model. Classifications were produced for two images acquired post-mortality with overall accuracies of 97.9% and 98.5%, respectively. Classified images were combined with land cover data to characterize the spatiotemporal characteristics of tree mortality across areas with differences in tree species composition. We found that 38% of tree crown area was lost during the drought period between 2002 and 2006. The majority of tree mortality during this period was concentrated in piñon-juniper (Pinus edulis-Juniperus monosperma) woodlands. An additional 20% of the tree canopy died or was removed between 2006 and 2011, primarily in areas experiencing wildfire and management activity. -Our results demonstrate that unsupervised clustering of bi-temporal NDVI and RGI differences can be used to detect tree mortality resulting from numerous causes and in several forest cover types.

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.

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.

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...

Influence of vegetation dynamic modeling on the allocation of green and blue waters

NASA Astrophysics Data System (ADS)

Ruiz-Pérez, Guiomar; Francés, Félix

2015-04-01

The long history of the Mediterranean region is dominated by the interactions and co-evolution between man and its natural environment. It is important to consider that the Mediterranean region is recurrently or permanently confronted with the scarcity of the water. The issue of climate change is (and will be) aggravating this situation. This raises the question of a loss of services that ecosystems provide to human and also the amount of available water to be used by vegetation. The question of the water cycle, therefore, should be considered in an integrated manner by taking into account both blue water (water in liquid form used for the human needs or which flows into the oceans) and green water (water having the vapor for resulting from evaporation and transpiration processes). In spite of this, traditionally, very few hydrological models have incorporated the vegetation dynamic as a state variable. In fact, most of them are able to represent fairly well the observed discharge, but usually including the vegetation as a static parameter. However, in the last decade, the number of hydrological models which explicitly take into account the vegetation development as a state variable has increased substantially. In this work, we want to analyze if it is really necessary to use a dynamic vegetation model to quantify adequately the distribution of water into blue and green water. The study site is located in the Public Forest Monte de la Hunde y Palomeras (Spain). The vegetation in the study area is dominated by Aleppo pine of high tree density with scant presence of other species. Two different daily models were applied (with static and dynamic vegetation representation respectively) in three different scenarios: dry year (2005), normal year (2008) and wet year (2010). The static vegetation model simulates the evapotranspiration considering the vegetation as a stationary parameter. Contrarily, the dynamic vegetation model connects the hydrological model with a parsimonious dynamic vegetation sub-model which assumes the vegetation biomass as a state variable. Using both models, we estimated the amount of 'blue' water and the amount of 'green' water (according to the previous definitions) in each scenario. Comparing the results, we observed that the static model underestimated the amount of green water in any case (dry, normal or wet year). In fact, the value of the ratio between blue and green water is higher in all scenarios for the static option (0.23 in the dry year, 0.42 in the normal year and 0.96 in the wet year) than the obtained ones for the dynamic model (0.098, 0.29 and 0.76, respectively). It means that we are overestimating the amount of water available for human needs if we assume vegetation as static. This type of error can be very dangerous for water resources predictions with future climates, especially in Mediterranean areas due to their water scarcity.

Drought impact on vegetation in pre and post fire events in Iberian Peninsula

NASA Astrophysics Data System (ADS)

Gouveia, C. M.; Bastos, A.; Trigo, R. M.; DaCamara, C.

2012-04-01

In 2004/2005, the Iberian Peninsula was stricken by an exceptional drought that affected more than one third of Portugal and part of southern Spain during more than 9 months. This severe drought had a strong negative impact on vegetation dynamics, as it coincided with the period of high photosynthetic activity (Gouveia et al., 2009). Since water availability is a crucial factor in post-fire vegetation recovery, it is desirable to assess the impact that such water-stress conditions had on fire sensitivity and post-fire vegetation recovery. Fire events in the European Mediterranean areas have become a serious problem and a major ecosystem disturbance, increasing erosion and soil degradation. In Portugal, the years 2003 and 2005 were particularly devastating. In 2003 it was registered the maximal burnt area since 1980, with more than 425000 ha burned, representing about 5% of Portuguese mainland. The 2005 fire season registered the highest number of fire occurrences in Portugal and the second year with the greatest number of fires in Spain. The high number of fire events observed during the summer 2005 in the Iberian Peninsula is linked, in part, to the extreme drought conditions that prevailed during the preceding winter and spring seasons of 2004/2005. Vegetation recovery after the 2003 and 2005 fire seasons was estimated using the mono-parametric model developed by Gouveia et al. (2010), which relies on monthly values of Normalized Difference Vegetation Index (NDVI), from 1999 to 2009, at 1kmresolution, as obtained from the VEGETATION-SPOT5 instrument.. This model was further used to evaluate the effect of drought in pre and post vegetation activity. Besides the standard NDVI, the Normalized Difference Water Index (NDWI) and the Normalized Difference Drought Index (NDDI) were computed in order to evaluate drought intensity. In the case of the burnt scars of 2003, when data corresponding to the months of drought are removed, recovery times are considerably shorter. The extreme water stress conditions to which vegetation is subject during drought events appear, therefore, to delay the regeneration process, which is to be expected since water availability is determinant to primary productivity. On the other hand, in the case of 2005 burnt areas, vegetation is more stressed and dryer in summer than in spring and, in general, fire damage is higher for pixels with higher vegetation density and higher moisture content during the months before the fire. These relationships are also related with the distinct vegetation behavior of the different land covers: in general, shrubland holds less quantity of very dry biomass, while needle leaf presents higher amounts of fairly dry biomass. Gouveia C., Trigo R.M., DaCamara C.C (2009) "Drought and Vegetation Stress Monitoring in Portugal using Satellite Data". Natural Hazards and Earth System Sciences, 9, 1-11 Gouveia C., DaCamara C.C, Trigo R.M. (2010). "Post-fire vegetation dynamics in Portugal". Natural Hazards and Earth System Sciences, 10, 4, 673-684.

Monitoring of the permeable pavement demonstration site at Edison Environmental Center

EPA Science Inventory

The EPA’s Urban Watershed Management Branch has installed an instrumented, working full-scale 110-space pervious pavement parking lot and has been monitoring several environmental stressors and runoff. This parking lot demonstration site has allowed the investigation of differenc...

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.

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.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

The effect of stochastic modeling of ionospheric effect on the various lengths of baseline determination

NASA Astrophysics Data System (ADS)

Kwon, J.; Yang, H.

2006-12-01

Although GPS provides continuous and accurate position information, there are still some rooms for improvement of its positional accuracy, especially in the medium and long range baseline determination. In general, in case of more than 50 km baseline length, the effect of ionospheric delay is the one causing the largest degradation in positional accuracy. For example, the ionospheric delay in terms of double differenced mode easily reaches 10 cm with baseline length of 101 km. Therefore, many researchers have been tried to mitigate/reduce the effect using various modeling methods. In this paper, the optimal stochastic modeling of the ionospheric delay in terms of baseline length is presented. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. Here, the ionospheric delay is stochastically modeled by well-known Gaussian, 1st and 3rd order Gauss-Markov process. The parameters required in those models such as correlation distance and time is determined by the least-square adjustment using ionosphere-only observables. Mainly the results and analysis from this study show the effect of stochastic models of the ionospheric delay in terms of the baseline length, models, and parameters used. In the above example with 101 km baseline length, it was found that the positional accuracy with appropriate ionospheric modeling (Gaussian) was about ±2 cm whereas it reaches about ±15 cm with no stochastic modeling. It is expected that the approach in this study contributes to improve positional accuracy, especially in medium and long range baseline determination.

Single-Receiver GPS Phase Bias Resolution

NASA Technical Reports Server (NTRS)

Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.

2010-01-01

Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

Satellite-observed changes in vegetation sensitivities to surface soil moisture and total water storage variations since the 2011 Texas drought

NASA Astrophysics Data System (ADS)

A, Geruo; Velicogna, Isabella; Kimball, John S.; Du, Jinyang; Kim, Youngwook; Colliander, Andreas; Njoku, Eni

2017-05-01

We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallow-depth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation-moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on vegetation-moisture relationship, and unique information regarding vegetation resilience and the recovery of hydrological drought.

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

PubMed

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

2016-09-01

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

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

Treesearch

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

1992-01-01

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

The Spectral Invariant Approximation Within Canopy Radiative Transfer to Support the Use of the EPIC/DSCOVR Oxygen B-band for Monitoring Vegetation

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Knyazikhin, Yuri

2017-01-01

EPIC (Earth Polychromatic Imaging Camera) is a 10-channel spectroradiometer onboard DSCOVR (Deep Space Climate Observatory) spacecraft. In addition to the near-infrared (NIR, 780 nm) and the 'red' (680 nm) channels, EPIC also has the O2 A-band (764+/-0.2 nm) and B-band (687.75+/-0.2 nm). The EPIC Normalized Difference Vegetation Index (NDVI) is defined as the difference between NIR and 'red' channels normalized to their sum. However, the use of the O2 B-band instead of the 'red' channel mitigates the effect of atmosphere on remote sensing of surface reflectance because O2 reduces contribution from the radiation scattered by the atmosphere. Applying the radiative transfer theory and the spectral invariant approximation to EPIC observations, the paper provides supportive arguments for using the O2 band instead of the red channel for monitoring vegetation dynamics. Our results suggest that the use of the O2 B-band enhances the sensitivity of the top-of-atmosphere NDVI to the presence of vegetation.

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.

Climate Change Implications to Vegetation Production in Alaska

NASA Technical Reports Server (NTRS)

Neigh, Christopher S.R.

2008-01-01

Investigation of long-term meteorological satellite data revealed statistically significant vegetation response to climate drivers of temperature, precipitation and solar radiation with exclusion of fire disturbance in Alaska. Abiotic trends were correlated to satellite remote sensing observations of normalized difference vegetation index to understand biophysical processes that could impact ecosystem carbon storage. Warming resulted in disparate trajectories for vegetation growth due to precipitation and photosynthetically active radiation variation. Interior spruce forest low lands in late summer through winter had precipitation deficit which resulted in extensive fire disturbance and browning of undisturbed vegetation with reduced post-fire recovery while Northern slope moist alpine tundra had increased production due to warmer-wetter conditions during the late 1990s and early 2000s. Coupled investigation of Alaska s vegetation response to warming climate found spatially dynamic abiotic processes with vegetation browning not a result from increased fire disturbance.

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

NASA Technical Reports Server (NTRS)

Greegor, D.; Norwine, J. (Principal Investigator)

1981-01-01

A climatological model/variable termed the sponge (a measure of moisture availability based on daily temperature maxima and minima, and precipitation) was tested for potential biogeograhic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic form, suggest that, as generalized climatic index, sponge is particularly appropriate for large-area and global vegetation monitoring. The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge and AVHRR data was initiated. Along an east-west Texas gradient, vegetation, sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values along the Texas gradient suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

A remote sensing based vegetation classification logic for global land cover analysis

USGS Publications Warehouse

Running, Steven W.; Loveland, Thomas R.; Pierce, Lars L.; Nemani, R.R.; Hunt, E. Raymond

1995-01-01

This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.

SINDA, Systems Improved Numerical Differencing Analyzer

NASA Technical Reports Server (NTRS)

Fink, L. C.; Pan, H. M. Y.; Ishimoto, T.

1972-01-01

Computer program has been written to analyze group of 100-node areas and then provide for summation of any number of 100-node areas to obtain temperature profile. SINDA program options offer user variety of methods for solution of thermal analog modes presented in network format.

Effective image differencing with convolutional neural networks for real-time transient hunting

NASA Astrophysics Data System (ADS)

Sedaghat, Nima; Mahabal, Ashish

2018-06-01

Large sky surveys are increasingly relying on image subtraction pipelines for real-time (and archival) transient detection. In this process one has to contend with varying point-spread function (PSF) and small brightness variations in many sources, as well as artefacts resulting from saturated stars and, in general, matching errors. Very often the differencing is done with a reference image that is deeper than individual images and the attendant difference in noise characteristics can also lead to artefacts. We present here a deep-learning approach to transient detection that encapsulates all the steps of a traditional image-subtraction pipeline - image registration, background subtraction, noise removal, PSF matching and subtraction - in a single real-time convolutional network. Once trained, the method works lightening-fast and, given that it performs multiple steps in one go, the time saved and false positives eliminated for multi-CCD surveys like Zwicky Transient Facility and Large Synoptic Survey Telescope will be immense, as millions of subtractions will be needed per night.

Proportionality between Doppler noise and integrated signal path electron density validated by differenced S-X range

NASA Technical Reports Server (NTRS)

Berman, A. L.

1977-01-01

Observations of Viking differenced S-band/X-band (S-X) range are shown to correlate strongly with Viking Doppler noise. A ratio of proportionality between downlink S-band plasma-induced range error and two-way Doppler noise is calculated. A new parameter (similar to the parameter epsilon which defines the ratio of local electron density fluctuations to mean electron density) is defined as a function of observed data sample interval (Tau) where the time-scale of the observations is 15 Tau. This parameter is interpreted to yield the ratio of net observed phase (or electron density) fluctuations to integrated electron density (in RMS meters/meter). Using this parameter and the thin phase-changing screen approximation, a value for the scale size L is calculated. To be consistent with Doppler noise observations, it is seen necessary for L to be proportional to closest approach distance a, and a strong function of the observed data sample interval, and hence the time-scale of the observations.

Continuous non-invasive blood glucose monitoring by spectral image differencing method

NASA Astrophysics Data System (ADS)

Huang, Hao; Liao, Ningfang; Cheng, Haobo; Liang, Jing

2018-01-01

Currently, the use of implantable enzyme electrode sensor is the main method for continuous blood glucose monitoring. But the effect of electrochemical reactions and the significant drift caused by bioelectricity in body will reduce the accuracy of the glucose measurements. So the enzyme-based glucose sensors need to be calibrated several times each day by the finger-prick blood corrections. This increases the patient's pain. In this paper, we proposed a method for continuous Non-invasive blood glucose monitoring by spectral image differencing method in the near infrared band. The method uses a high-precision CCD detector to switch the filter in a very short period of time, obtains the spectral images. And then by using the morphological method to obtain the spectral image differences, the dynamic change of blood sugar is reflected in the image difference data. Through the experiment proved that this method can be used to monitor blood glucose dynamically to a certain extent.

Field programmable analog array based on current differencing transconductance amplifiers and its application to high-order filter

NASA Astrophysics Data System (ADS)

He, Haizhen; Luo, Rongming; Hu, Zhenhua; Wen, Lei

2017-07-01

A current-mode field programmable analog array(FPAA) is presented in this paper. The proposed FPAA consists of 9 configurable analog blocks(CABs) which are based on current differencing transconductance amplifiers (CDTA) and trans-impedance amplifier (TIA). The proposed CABs interconnect through global lines. These global lines contain some bridge switches, which used to reduce the parasitic capacitance effectively. High-order current-mode low-pass and band-pass filter with transmission zeros based on the simulation of general passive RLC ladder prototypes is proposed and mapped into the FPAA structure in order to demonstrate the versatility of the FPAA. These filters exhibit good performance on bandwidth. Filter's cutoff frequency can be tuned from 1.2MHz to 40MHz.The proposed FPAA is simulated in a standard Charted 0.18μm CMOS process with +/-1.2V power supply to confirm the presented theory, and the results have good agreement with the theoretical analysis.

Time-asymptotic solutions of the Navier-Stokes equation for free shear flows using an alternating-direction implicit method

NASA Technical Reports Server (NTRS)

Rudy, D. H.; Morris, D. J.

1976-01-01

An uncoupled time asymptotic alternating direction implicit method for solving the Navier-Stokes equations was tested on two laminar parallel mixing flows. A constant total temperature was assumed in order to eliminate the need to solve the full energy equation; consequently, static temperature was evaluated by using algebraic relationship. For the mixing of two supersonic streams at a Reynolds number of 1,000, convergent solutions were obtained for a time step 5 times the maximum allowable size for an explicit method. The solution diverged for a time step 10 times the explicit limit. Improved convergence was obtained when upwind differencing was used for convective terms. Larger time steps were not possible with either upwind differencing or the diagonally dominant scheme. Artificial viscosity was added to the continuity equation in order to eliminate divergence for the mixing of a subsonic stream with a supersonic stream at a Reynolds number of 1,000.

Method of resolving radio phase ambiguity in satellite orbit determination

NASA Technical Reports Server (NTRS)

Councelman, Charles C., III; Abbot, Richard I.

1989-01-01

For satellite orbit determination, the most accurate observable available today is microwave radio phase, which can be differenced between observing stations and between satellites to cancel both transmitter- and receiver-related errors. For maximum accuracy, the integer cycle ambiguities of the doubly differenced observations must be resolved. To perform this ambiguity resolution, a bootstrapping strategy is proposed. This strategy requires the tracking stations to have a wide ranging progression of spacings. By conventional 'integrated Doppler' processing of the observations from the most widely spaced stations, the orbits are determined well enough to permit resolution of the ambiguities for the most closely spaced stations. The resolution of these ambiguities reduces the uncertainty of the orbit determination enough to enable ambiguity resolution for more widely spaced stations, which further reduces the orbital uncertainty. In a test of this strategy with six tracking stations, both the formal and the true errors of determining Global Positioning System satellite orbits were reduced by a factor of 2.

Efficient and stable exponential time differencing Runge-Kutta methods for phase field elastic bending energy models

NASA Astrophysics Data System (ADS)

Wang, Xiaoqiang; Ju, Lili; Du, Qiang

2016-07-01

The Willmore flow formulated by phase field dynamics based on the elastic bending energy model has been widely used to describe the shape transformation of biological lipid vesicles. In this paper, we develop and investigate some efficient and stable numerical methods for simulating the unconstrained phase field Willmore dynamics and the phase field Willmore dynamics with fixed volume and surface area constraints. The proposed methods can be high-order accurate and are completely explicit in nature, by combining exponential time differencing Runge-Kutta approximations for time integration with spectral discretizations for spatial operators on regular meshes. We also incorporate novel linear operator splitting techniques into the numerical schemes to improve the discrete energy stability. In order to avoid extra numerical instability brought by use of large penalty parameters in solving the constrained phase field Willmore dynamics problem, a modified augmented Lagrange multiplier approach is proposed and adopted. Various numerical experiments are performed to demonstrate accuracy and stability of the proposed methods.

Drought in Southwestern United States

NASA Technical Reports Server (NTRS)

2007-01-01

The southwestern United States pined for water in late March and early April 2007. This image is based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite from March 22 through April 6, 2007, and it shows the Normalized Difference Vegetation Index, or NDVI, for the period. In this NDVI color scale, green indicates areas of healthier-than-usual vegetation, and only small patches of green appear in this image, near the California-Nevada border and in Utah. Larger areas of below-normal vegetation are more common, especially throughout California. Pale yellow indicates areas with generally average vegetation. Gray areas appear where no data were available, likely due to persistent clouds or snow cover. According to the April 10, 2007, update from the U.S. Drought Monitor, most of the southwestern United Sates, including Utah, Nevada, California, and Arizona, experienced moderate to extreme drought. The hardest hit areas were southeastern California and southwestern Arizona. Writing for the Drought Monitor, David Miskus of the Joint Agricultural Weather Facility reported that March 2007 had been unusually dry for the southwestern United States. While California's and Utah's reservoir storage was only slightly below normal, reservoir storage was well below normal for New Mexico and Arizona. In early April, an international research team published an online paper in Science noting that droughts could become more common for the southwestern United States and northern Mexico, as these areas were already showing signs of drying. Relying on the same computer models used in the Intergovernmental Panel on Climate Change (IPCC) report released in early 2007, the researchers who published in Science concluded that global warming could make droughts more common, not just in the American Southwest, but also in semiarid regions of southern Europe, Mediterranean northern Africa, and the Middle East.

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Limbic hyperconnectivity in the vegetative state.

PubMed

Di Perri, Carol; Bastianello, Stefano; Bartsch, Andreas J; Pistarini, Caterina; Maggioni, Giorgio; Magrassi, Lorenzo; Imberti, Roberto; Pichiecchio, Anna; Vitali, Paolo; Laureys, Steven; Di Salle, Francesco

2013-10-15

To investigate functional connectivity between the default mode network (DMN) and other networks in disorders of consciousness. We analyzed MRI data from 11 patients in a vegetative state and 7 patients in a minimally conscious state along with age- and sex-matched healthy control subjects. MRI data analysis included nonlinear spatial normalization to compensate for disease-related anatomical distortions. We studied brain connectivity data from resting-state MRI temporal series, combining noninferential (independent component analysis) and inferential (seed-based general linear model) methods. In DMN hypoconnectivity conditions, a patient's DMN functional connectivity shifts and paradoxically increases in limbic structures, including the orbitofrontal cortex, insula, hypothalamus, and the ventral tegmental area. Concurrently with DMN hypoconnectivity, we report limbic hyperconnectivity in patients in vegetative and minimally conscious states. This hyperconnectivity may reflect the persistent engagement of residual neural activity in self-reinforcing neural loops, which, in turn, could disrupt normal patterns of connectivity.

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

USGS Publications Warehouse

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Running, Steven W.

1989-01-01

Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

2015-04-01

Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbanceInternational Journal of Applied Earth Observation and Geoinformation 26 441-446 Lanorte A, M Danese, R Lasaponara, B Murgante 2014 Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis International Journal of Applied Earth Observation and Geoinformation 20, 42-51 Tuia D, F Ratle, R Lasaponara, L Telesca, M Kanevski 2008 Scan statistics analysis of forest fire clusters Communications in Nonlinear Science and Numerical Simulation 13 (8), 1689-1694 Telesca L, R Lasaponara 2006 Pre and post fire behavioral trends revealed in satellite NDVI time series Geophysical Research Letters 33 (14) Lasaponara R 2005 Intercomparison of AVHRR based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy International Journal of Remote Sensing 26 (5), 853-870

Neighborhood Greenness and Chronic Health Conditions in Medicare Beneficiaries.

PubMed

Brown, Scott C; Lombard, Joanna; Wang, Kefeng; Byrne, Margaret M; Toro, Matthew; Plater-Zyberk, Elizabeth; Feaster, Daniel J; Kardys, Jack; Nardi, Maria I; Perez-Gomez, Gianna; Pantin, Hilda M; Szapocznik, José

2016-07-01

Prior studies suggest that exposure to the natural environment may impact health. The present study examines the association between objective measures of block-level greenness (vegetative presence) and chronic medical conditions, including cardiometabolic conditions, in a large population-based sample of Medicare beneficiaries in Miami-Dade County, Florida. The sample included 249,405 Medicare beneficiaries aged ≥65 years whose location (ZIP+4) within Miami-Dade County, Florida, did not change, from 2010 to 2011. Data were obtained in 2013 and multilevel analyses conducted in 2014 to examine relationships between greenness, measured by mean Normalized Difference Vegetation Index from satellite imagery at the Census block level, and chronic health conditions in 2011, adjusting for neighborhood median household income, individual age, gender, race, and ethnicity. Higher greenness was significantly associated with better health, adjusting for covariates: An increase in mean block-level Normalized Difference Vegetation Index from 1 SD less to 1 SD more than the mean was associated with 49 fewer chronic conditions per 1,000 individuals, which is approximately similar to a reduction in age of the overall study population by 3 years. This same level of increase in mean Normalized Difference Vegetation Index was associated with a reduced risk of diabetes by 14%, hypertension by 13%, and hyperlipidemia by 10%. Planned post-hoc analyses revealed stronger and more consistently positive relationships between greenness and health in lower- than higher-income neighborhoods. Greenness or vegetative presence may be effective in promoting health in older populations, particularly in poor neighborhoods, possibly due to increased time outdoors, physical activity, or stress mitigation. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Detecting channel riparian vegetation response to best-management-practices implementation in ephemeral streams with the use of spot high-resolution visible imagery

USGS Publications Warehouse

Kamp, Kendall Vande; Rigge, Matthew B.; Troelstrup, Nels H.; Smart, Alexander J.; Wylie, Bruce

2013-01-01

Heavily grazed riparian areas are commonly subject to channel incision, a lower water table, and reduced vegetation, resulting in sediment delivery above normal regimes. Riparian and in-channel vegetation functions as a roughness element and dissipates flow energy, maintaining stable channel geometry. Ash Creek, a tributary of the Bad River in western South Dakota contains a high proportion of incised channels, remnants of historically high grazing pressure. Best management practices (BMP), including off-stream watering sources and cross fencing, were implemented throughout the Bad River watershed during an Environmental Protection Agency (EPA) 319 effort to address high sediment loads. We monitored prairie cordgrass (Spartina pectinata Link) establishment within stream channels for 16 yr following BMP implementation. Photos were used to group stream reaches (n = 103) subjectively into three classes; absent (estimated  40% cover; n = 16) based on the relative amount of prairie cordgrass during 2010 assessments of ephemeral channels. Reaches containing drainage areas of 0.54 to 692 ha were delineated with the use of 2010 National Agriculture Imagery Program (NAIP) imagery. Normalized difference vegetation index (NDVI) values were extracted from 5 to 39 sample points proportional to reach length using a series of Satellite Pour l'Observation de la Terre (SPOT) satellite imagery. Normalized NDVI (nNDVI) of 2 152 sample points were determined from pre- and post-BMP images. Mean nNDVI values for each reach ranged from 0.33 to 1.77. ANOVA revealed significant increase in nNDVI in locations classified as present prairie cordgrass cover following BMP implementation. Establishment of prairie cordgrass following BMP implementation was successfully detected remotely. Riparian vegetation such as prairie cordgrass adds channel roughness that reduces the flow energy responsible for channel degradation.

Increasing portion sizes of fruits and vegetables in an elementary school lunch program can increase fruit and vegetable consumption.

PubMed

Miller, Nicole; Reicks, Marla; Redden, Joseph P; Mann, Traci; Mykerezi, Elton; Vickers, Zata

2015-08-01

Increasing portion size can increase children's consumption of food. The goal of this study was to determine whether increasing the portion sizes of fruits and vegetables in an elementary school cafeteria environment would increase children's consumption of them. We measured each child's consumption of the fruit and vegetables served in a cafeteria line on a control day (normal cafeteria procedures) and on two intervention days. When we increased the portion size of 3 of the 4 fruits and vegetables by about 50%, children who took those foods increased their consumption of them. Although this was an effective strategy for increasing fruit and vegetable consumption among students who took those foods, many children chose not to take any fruits or vegetables. Further efforts are needed to increase children's selection and consumption of fruits and vegetables in an environment of competing foods of higher palatability. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spectral Unmixing of Vegetation, Soil and Dry Carbon in Arid Regions: Comparing Multispectral and Hyperspectral Observations

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Heidebrecht, Kathleen B.

2001-01-01

Remote sensing of vegetation cover and condition is critically needed to understand the impacts of land use and climate variability in and and semi-arid regions. However, remote sensing of vegetation change in these environments is difficult for several reasons. First, individual plant canopies are typically small and do not reach the spatial scale of typical Landsat-like satellite image pixels. Second, the phenological status and subsequent dry carbon (or non-photosynthetic) fraction of plant canopies varies dramatically in both space and time throughout and and semi-arid regions. Detection of only the 'green' part of the vegetation using a metric such as the normalized difference vegetation index (NDVI) thus yields limited information on the presence and condition of plants in these ecosystems. Monitoring of both photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) is needed to understand a range of ecosystem characteristics including vegetation presence, cover and abundance, physiological and biogeochemical functioning, drought severity, fire fuel load, disturbance events and recovery from disturbance.

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

Semi-Automatic Normalization of Multitemporal Remote Images Based on Vegetative Pseudo-Invariant Features

PubMed Central

Garcia-Torres, Luis; Caballero-Novella, Juan J.; Gómez-Candón, David; De-Castro, Ana Isabel

2014-01-01

A procedure to achieve the semi-automatic relative image normalization of multitemporal remote images of an agricultural scene called ARIN was developed using the following procedures: 1) defining the same parcel of selected vegetative pseudo-invariant features (VPIFs) in each multitemporal image; 2) extracting data concerning the VPIF spectral bands from each image; 3) calculating the correction factors (CFs) for each image band to fit each image band to the average value of the image series; and 4) obtaining the normalized images by linear transformation of each original image band through the corresponding CF. ARIN software was developed to semi-automatically perform the ARIN procedure. We have validated ARIN using seven GeoEye-1 satellite images taken over the same location in Southern Spain from early April to October 2010 at an interval of approximately 3 to 4 weeks. The following three VPIFs were chosen: citrus orchards (CIT), olive orchards (OLI) and poplar groves (POP). In the ARIN-normalized images, the range, standard deviation (s. d.) and root mean square error (RMSE) of the spectral bands and vegetation indices were considerably reduced compared to the original images, regardless of the VPIF or the combination of VPIFs selected for normalization, which demonstrates the method’s efficacy. The correlation coefficients between the CFs among VPIFs for any spectral band (and all bands overall) were calculated to be at least 0.85 and were significant at P = 0.95, indicating that the normalization procedure was comparably performed regardless of the VPIF chosen. ARIN method was designed only for agricultural and forestry landscapes where VPIFs can be identified. PMID:24604031

Determination of optimum viewing angles for the angular normalization of land surface temperature over vegetated surface.

PubMed

Ren, Huazhong; Yan, Guangjian; Liu, Rongyuan; Li, Zhao-Liang; Qin, Qiming; Nerry, Françoise; Liu, Qiang

2015-03-27

Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST) retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF) is first extended to the thermal infrared (TIR) domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (Te-nadir) from different viewing directions, and the results show that this model can obtain reliable Te-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The Te-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors.

Determination of Optimum Viewing Angles for the Angular Normalization of Land Surface Temperature over Vegetated Surface

PubMed Central

Ren, Huazhong; Yan, Guangjian; Liu, Rongyuan; Li, Zhao-Liang; Qin, Qiming; Nerry, Françoise; Liu, Qiang

2015-01-01

Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST) retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF) is first extended to the thermal infrared (TIR) domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (Te-nadir) from different viewing directions, and the results show that this model can obtain reliable Te-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The Te-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors. PMID:25825975

IMPACTS OF VEGETATION DYNAMICS ON THE IDENTIFICATION OF LAND COVER CHANGE IN A BIOLOGICALLY COMPLEX COMMUNITY IN NORTH CAROLINA, USA

EPA Science Inventory

A land-cover (LC) change detection experiment was performed in the biologically complex landscape of the Neuse Rive Basin (NRB), NC using Landsat 5 and 7 imagery collected in May of 1993 and 2000. Methods included pixel-wise Normalized Difference Vegetation Index (NDVI) and Mult...

Deforestation in Mwanza District, Malawi, from 1981 to 1992 as determined from Landsat MSS imagery

Treesearch

Andrew T. Hudak; Carol A. Wessman

2000-01-01

Malawi is critically short of fuelwood, the primary energy source for its poverty-stricken populace. Deforestation from 1981 to 1992 in Mwanza District in southern Malawi was assessed using Normalized Difference Vegetation Index (NDVI) values calculated from multitemporal Landsat Multispectral Scanner (MSS) images. A control site, where vegetation change was assumed to...

In situ sensors, weighing lysimeters and COSMOS under vegetated and bare conditions with subsurface drip irrigation

USDA-ARS?s Scientific Manuscript database

Long term weighing lysimeter records may have utility for assessment of climate changes occurring during the period of record. They typically enclose a depth of soil that exceeds the root zone of vegetation normally grown on them and have drainagy systems so that more or less natural hydrologic flux...

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau.

PubMed

Duffaut Espinosa, L A; Posadas, A N; Carbajal, M; Quiroz, R

2017-01-01

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.

Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau

PubMed Central

Posadas, A. N.; Carbajal, M.; Quiroz, R.

2017-01-01

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study. PMID:28125607

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.

7 CFR 989.24a - Non-normal outlets.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 8 2014-01-01 2014-01-01 false Non-normal outlets. 989.24a Section 989.24a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE RAISINS PRODUCED FROM GRAPES...

7 CFR 989.24a - Non-normal outlets.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Non-normal outlets. 989.24a Section 989.24a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE RAISINS PRODUCED FROM GRAPES...

7 CFR 989.24a - Non-normal outlets.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 8 2013-01-01 2013-01-01 false Non-normal outlets. 989.24a Section 989.24a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (MARKETING AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE RAISINS PRODUCED FROM GRAPES...

7 CFR 989.24a - Non-normal outlets.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 8 2012-01-01 2012-01-01 false Non-normal outlets. 989.24a Section 989.24a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE RAISINS PRODUCED FROM GRAPES...

Vegetation spatial variability and its effect on vegetation indices

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

[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.

Advances in Rotor Performance and Turbulent Wake Simulation Using DES and Adaptive Mesh Refinement

NASA Technical Reports Server (NTRS)

Chaderjian, Neal M.

2012-01-01

Time-dependent Navier-Stokes simulations have been carried out for a rigid V22 rotor in hover, and a flexible UH-60A rotor in forward flight. Emphasis is placed on understanding and characterizing the effects of high-order spatial differencing, grid resolution, and Spalart-Allmaras (SA) detached eddy simulation (DES) in predicting the rotor figure of merit (FM) and resolving the turbulent rotor wake. The FM was accurately predicted within experimental error using SA-DES. Moreover, a new adaptive mesh refinement (AMR) procedure revealed a complex and more realistic turbulent rotor wake, including the formation of turbulent structures resembling vortical worms. Time-dependent flow visualization played a crucial role in understanding the physical mechanisms involved in these complex viscous flows. The predicted vortex core growth with wake age was in good agreement with experiment. High-resolution wakes for the UH-60A in forward flight exhibited complex turbulent interactions and turbulent worms, similar to the V22. The normal force and pitching moment coefficients were in good agreement with flight-test data.

Lichen ecology and diversity of a sagebrush steppe in Oregon: 1977 to the present

USDA-ARS?s Scientific Manuscript database

A lichen checklist is presented of 141 species from the Lawrence Memorial Grassland Preserve and nearby lands in Wasco County, Oregon, based on collections made in the 1970s and 1990s. Collections include epiphytic, lignicolous, saxicolous, muscicolous and terricolous species. To evaluate differenc...

Interdependence of PRECIS Role Operators: A Quantitative Analysis of Their Associations.

ERIC Educational Resources Information Center

Mahapatra, Manoranjan; Biswas, Subal Chandra

1986-01-01

Analyzes associations among different role operators quantitatively by taking input strings from 200 abstracts, each related to subject fields of taxation, genetic psychology, and Shakespearean drama, and subjecting them to the Chi-square test. Significant associations by other differencing operators and connectives are discussed. A schema of role…

Comparing fire severity models from post-fire and pre/post-fire differenced imagery

USDA-ARS?s Scientific Manuscript database

Wildland fires are common in rangelands worldwide. The potential for high severity fires to affect long-term changes in rangelands is considerable, and for this reason assessing fire severity shortly after the fire is critical. Such assessments are typically carried out following Burned Area Emergen...

Continuous electrocardiogram reveals differenced in the short-term cardiotoxic response of Wistar-Kyoto and spontaneously hypertensive rats to doxorubicin

EPA Science Inventory

Electrocardiography (ECG) is one of the standard technologies used to monitor and assess cardiac function, and provide insight into the mechanisms driving myocardial pathology. Increased understanding of the effects of cardiovascular disease on rat ECG may help make ECG assessmen...

Using Approximate Dynamic Programming to Solve the Stochastic Demand Military Inventory Routing Problem with Direct Delivery

DTIC Science & Technology

due to the dangers of utilizing convoy operations. However, enemy actions, austere conditions, and inclement weather pose a significant risk to a...squares temporal differencing for policy evaluation. We construct a representative problem instance based on an austere combat environment in order to

Rapid-Response or Repeat-Mode Topography from Aerial Structure from Motion

NASA Astrophysics Data System (ADS)

Nissen, E.; Johnson, K. L.; Fitzgerald, F. S.; Morgan, M.; White, J.

2014-12-01

This decade has seen a surge of interest in Structure-from-Motion (SfM) as a means of generating high-resolution topography and coregistered texture maps from stereo digital photographs. Using an unstructured set of overlapping photographs captured from multiple viewpoints and minimal GPS ground control, SfM solves simultaneously for scene topography and camera positions, orientations and lens parameters. The use of cheap unmanned aerial vehicles or tethered helium balloons as camera platforms expedites data collection and overcomes many of the cost, time and logistical limitations of LiDAR surveying, making it a potentially valuable tool for rapid response mapping and repeat monitoring applications. We begin this presentation by assessing what data resolutions and precisions are achievable using a simple aerial camera platform and commercial SfM software (we use the popular Agisoft Photoscan package). SfM point clouds generated at two small (~0.1 km2), sparsely-vegetated field sites in California compare favorably with overlapping airborne and terrestrial LiDAR surveys, with closest point distances of a few centimeters between the independent datasets. Next, we go on to explore the method in more challenging conditions, in response to a major landslide in Mesa County, Colorado, on 25th May 2014. Photographs collected from a small UAV were used to generate a high-resolution model of the 4.5 x 1 km landslide several days before an airborne LiDAR survey could be organized and flown. An initial estimate of the mass balance of the landslide could quickly be made by differencing this model against pre-event topography generated using stereo photographs collected in 2009 as part of the National Agricultural Imagery Program (NAIP). This case study therefore demonstrates the rich potential offered by this technique, as well as some of the challenges, particularly with respect to the treatment of vegetation.

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

NASA Astrophysics Data System (ADS)

Kustas, William P.; Alfieri, Joseph G.; Anderson, Martha C.; Colaizzi, Paul D.; Prueger, John H.; Evett, Steven R.; Neale, Christopher M. U.; French, Andrew N.; Hipps, Lawrence E.; Chávez, José L.; Copeland, Karen S.; Howell, Terry A.

2012-12-01

Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of Norman et al. (1995) [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by Evett et al. (2012) [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint.

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.

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.

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

NASA Technical Reports Server (NTRS)

Greegor, D. H.; Norwine, J.

1981-01-01

A new experimental climatological model/variable termed the sponge, a measure of moisture availability based on daily temperature maxima and minima and precipitation, is tested for potential biogeographic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic from, suggest that, as a generalized climatic index, sponge's simplicity and sensitivity make particularly appropriate for trans-regional biogeographic studies (e.g., large-area and global vegetation monitoring). The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

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

NASA Astrophysics Data System (ADS)

Liu, Nanfeng; Treitz, Paul

2016-10-01

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

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.

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.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

PubMed

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-10-07

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

PubMed Central

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-01-01

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. PMID:27713530

The influence of extensive vegetated roofs on runoff water quality.

PubMed

Berndtsson, Justyna Czemiel; Emilsson, Tobias; Bengtsson, Lars

2006-02-15

The influence of extensive sedum-moss vegetated roofs on runoff water quality was studied for four full scale installations located in southern Sweden. The aim of the study was to ascertain whether the vegetated roof behaves as a sink or a source of pollutants and whether the age of a vegetated roof influences runoff quality. The runoff quality from vegetated roofs was also compared with the runoff quality from non-vegetated roofs located in study areas. The following metals and nutrients were investigated: Cd, Cr, Cu, Fe, K, Mn, Pb, Zn, NO3-N, NH4-N, Tot-N, PO4-P, and Tot-P. The results show that, with the exception of nitrogen, vegetated roofs behave as source of contaminants. While in lower concentrations than normally found in urban runoff, some metals appear in concentrations that would correspond to moderately polluted natural water. Nitrate nitrogen is retained by the vegetation or soil or both. Apart from the oldest, the studied vegetated roofs contribute phosphate phosphorus to the runoff. The maintenance of the vegetation systems on the roofs has to be carefully designed in order to avoid storm-water contamination; for instance, the use of easily dissolvable fertilizers should be avoided.

Spatio-Temporal Change of Vegetation Coverage and its Driving Forces Based on Landsat Images: a Case Study of Changchun City

NASA Astrophysics Data System (ADS)

Dong, L.; Jiang, H.; Yang, L.

2018-04-01

Based on the Landsat images in 2006, 2011 and 2015, and the method of dimidiate pixel model, the Normalized Difference Vegetation Index (NDVI) and the vegetation coverage, this paper analyzes the spatio-temporal variation of vegetation coverage in Changchun, China from 2006 to 2015, and investigates the response of vegetation coverage change to natural and artificial factors. The research results show that in nearly 10 years, the vegetation coverage in Changchun dropped remarkably, and reached the minimum in 2011. Moreover, the decrease of maximum NDVI was significant, with a decrease of about 27.43 %, from 2006 to 2015. The vegetation coverage change in different regions of the research area was significantly different. Among them, the vegetation change in Changchun showed a little drop, and it decreased firstly and then increased slowly in Yushu, Nong'an and Dehui. In addition, the temperature and precipitation change, land reclamation all affect the vegetation coverage. In short, the study of vegetation coverage change contributes scientific and technical support to government and environmental protection department, so as to promote the coordinated development of ecology and economy.

Spring and autumn phenological variability across environmental gradients of Great Smoky Mountains National Park, USA

Treesearch

Steven P. Norman; William W. Hargrove; William M. Christie

2017-01-01

Mountainous regions experience complex phenological behavior along climatic, vegetational and topographic gradients. In this paper, we use a MODIS time series of the Normalized Difference Vegetation Index (NDVI) to understand the causes of variations in spring and autumn timing from 2000 to 2015, for a landscape renowned for its biological diversity. By filtering for...

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...

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

Systemic control of cell division and endoreduplication by NAA and BAP by modulating CDKs in root tip cells of Allium cepa.

PubMed

Tank, Jigna G; Thaker, Vrinda S

2014-01-01

Molecular mechanism regulated by auxin and cytokinin during endoreduplication, cell division, and elongation process is studied by using Allium cepa roots as a model system. The activity of CDK genes modulated by auxin and cytokinin during cell division, elongation, and endoreduplication process is explained in this research work. To study the significance of auxin and cytokinin in the management of cell division and endoreduplication process in plant meristematic cells at molecular level endoreduplication was developed in root tips of Allium cepa by giving colchicine treatment. There were inhibition of vegetative growth, formation of c-tumor at root tip, and development of endoreduplicated cells after colchicine treatment. This c-tumor was further treated with NAA and BAP to reinitiate vegetative growth in roots. BAP gave positive response in reinitiation of vegetative growth of roots from center of c-tumor. However, NAA gave negative response in reinitiation of vegetative growth of roots from c-tumor. Further, CDKs gene expression analysis from normal, endoreduplicated, and phytohormone (NAA or BAP) treated root tip was done and remarkable changes in transcription level of CDK genes in normal, endoreduplicated, and phytohormones treated cells were observed.

Systemic Control of Cell Division and Endoreduplication by NAA and BAP by Modulating CDKs in Root Tip Cells of Allium cepa

PubMed Central

Tank, Jigna G.; Thaker, Vrinda S.

2014-01-01

Molecular mechanism regulated by auxin and cytokinin during endoreduplication, cell division, and elongation process is studied by using Allium cepa roots as a model system. The activity of CDK genes modulated by auxin and cytokinin during cell division, elongation, and endoreduplication process is explained in this research work. To study the significance of auxin and cytokinin in the management of cell division and endoreduplication process in plant meristematic cells at molecular level endoreduplication was developed in root tips of Allium cepa by giving colchicine treatment. There were inhibition of vegetative growth, formation of c-tumor at root tip, and development of endoreduplicated cells after colchicine treatment. This c-tumor was further treated with NAA and BAP to reinitiate vegetative growth in roots. BAP gave positive response in reinitiation of vegetative growth of roots from center of c-tumor. However, NAA gave negative response in reinitiation of vegetative growth of roots from c-tumor. Further, CDKs gene expression analysis from normal, endoreduplicated, and phytohormone (NAA or BAP) treated root tip was done and remarkable changes in transcription level of CDK genes in normal, endoreduplicated, and phytohormones treated cells were observed. PMID:24955358

[Fast discrimination of edible vegetable oil based on Raman spectroscopy].

PubMed

Zhou, Xiu-Jun; Dai, Lian-Kui; Li, Sheng

2012-07-01

A novel method to fast discriminate edible vegetable oils by Raman spectroscopy is presented. The training set is composed of different edible vegetable oils with known classes. Based on their original Raman spectra, baseline correction and normalization were applied to obtain standard spectra. Two characteristic peaks describing the unsaturated degree of vegetable oil were selected as feature vectors; then the centers of all classes were calculated. For an edible vegetable oil with unknown class, the same pretreatment and feature extraction methods were used. The Euclidian distances between the feature vector of the unknown sample and the center of each class were calculated, and the class of the unknown sample was finally determined by the minimum distance. For 43 edible vegetable oil samples from seven different classes, experimental results show that the clustering effect of each class was more obvious and the class distance was much larger with the new feature extraction method compared with PCA. The above classification model can be applied to discriminate unknown edible vegetable oils rapidly and accurately.

Forecasting vegetation greenness with satellite and climate data

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R2 values range from 0.97-0.80 for 2-12 week forecasts, with higher R2 associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.

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.

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

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.

Fruit and vegetable intake and their pesticide residues in relation to semen quality among men from a fertility clinic

PubMed Central

Chiu, Y.H.; Afeiche, M.C.; Gaskins, A.J.; Williams, P.L.; Petrozza, J.C.; Tanrikut, C.; Hauser, R.; Chavarro, J.E.

2015-01-01

STUDY QUESTION Is consumption of fruits and vegetables with high levels of pesticide residues associated with lower semen quality? SUMMARY ANSWER Consumption of fruits and vegetables with high levels of pesticide residues was associated with a lower total sperm count and a lower percentage of morphologically normal sperm among men presenting to a fertility clinic. WHAT IS KNOWN ALREADY Occupational and environmental exposure to pesticides is associated with lower semen quality. Whether the same is true for exposure through diet is unknown. STUDY DESIGN, SIZE, DURATION Men enrolled in the Environment and Reproductive Health (EARTH) Study, an ongoing prospective cohort at an academic medical fertility center. Male partners (n = 155) in subfertile couples provided 338 semen samples during 2007–2012. PARTICIPANTS/MATERIALS, SETTING, METHODS Semen samples were collected over an 18-month period following diet assessment. Sperm concentration and motility were evaluated by computer-aided semen analysis (CASA). Fruits and vegetables were categorized as containing high or low-to-moderate pesticide residues based on data from the annual United States Department of Agriculture Pesticide Data Program. Linear mixed models were used to analyze the association of fruit and vegetable intake with sperm parameters accounting for within-person correlations across repeat samples while adjusting for potential confounders. MAIN RESULTS AND THE ROLE OF CHANCE Total fruit and vegetable intake was unrelated to semen quality parameters. High pesticide residue fruit and vegetable intake, however, was associated with poorer semen quality. On average, men in highest quartile of high pesticide residue fruit and vegetable intake (≥1.5 servings/day) had 49% (95% confidence interval (CI): 31%, 63%) lower total sperm count and 32% (95% CI: 7%, 58%) lower percentage of morphologically normal sperm than men in the lowest quartile of intake (<0.5 servings/day) (P, trend = 0.003 and 0.02, respectively). Low-to-moderate pesticide residue fruit and vegetable intake was associated with a higher percentage of morphologically normal sperm (P, trend = 0.04). LIMITATIONS, REASONS FOR CAUTION Surveillance data, rather than individual pesticide assessment, was used to assess the pesticide residue status of fruits and vegetables. CASA is a useful method for clinical evaluation but may be considered less favorable for accurate semen analysis in the research setting. Owing to the observational nature of the study, confirmation is required by interventional studies as well. WIDER IMPLICATIONS OF THE FINDINGS To our knowledge, this is the first report on the consumption of fruits and vegetables with high levels of pesticide residue in relation to semen quality. Further confirmation of these findings is warranted. STUDY FUNDING/COMPETING INTEREST(S) Supported by National Institutes of Health grants ES009718, ES022955, ES000002, P30 DK046200 and Ruth L. Kirschstein National Research Service Award T32 DK007703-16. None of the authors has any conflicts of interest to declare. PMID:25824023

Fruit and vegetable intake and their pesticide residues in relation to semen quality among men from a fertility clinic.

PubMed

Chiu, Y H; Afeiche, M C; Gaskins, A J; Williams, P L; Petrozza, J C; Tanrikut, C; Hauser, R; Chavarro, J E

2015-06-01

Is consumption of fruits and vegetables with high levels of pesticide residues associated with lower semen quality? Consumption of fruits and vegetables with high levels of pesticide residues was associated with a lower total sperm count and a lower percentage of morphologically normal sperm among men presenting to a fertility clinic. Occupational and environmental exposure to pesticides is associated with lower semen quality. Whether the same is true for exposure through diet is unknown. Men enrolled in the Environment and Reproductive Health (EARTH) Study, an ongoing prospective cohort at an academic medical fertility center. Male partners (n = 155) in subfertile couples provided 338 semen samples during 2007-2012. Semen samples were collected over an 18-month period following diet assessment. Sperm concentration and motility were evaluated by computer-aided semen analysis (CASA). Fruits and vegetables were categorized as containing high or low-to-moderate pesticide residues based on data from the annual United States Department of Agriculture Pesticide Data Program. Linear mixed models were used to analyze the association of fruit and vegetable intake with sperm parameters accounting for within-person correlations across repeat samples while adjusting for potential confounders. Total fruit and vegetable intake was unrelated to semen quality parameters. High pesticide residue fruit and vegetable intake, however, was associated with poorer semen quality. On average, men in highest quartile of high pesticide residue fruit and vegetable intake (≥1.5 servings/day) had 49% (95% confidence interval (CI): 31%, 63%) lower total sperm count and 32% (95% CI: 7%, 58%) lower percentage of morphologically normal sperm than men in the lowest quartile of intake (<0.5 servings/day) (P, trend = 0.003 and 0.02, respectively). Low-to-moderate pesticide residue fruit and vegetable intake was associated with a higher percentage of morphologically normal sperm (P, trend = 0.04). Surveillance data, rather than individual pesticide assessment, was used to assess the pesticide residue status of fruits and vegetables. CASA is a useful method for clinical evaluation but may be considered less favorable for accurate semen analysis in the research setting. Owing to the observational nature of the study, confirmation is required by interventional studies as well. To our knowledge, this is the first report on the consumption of fruits and vegetables with high levels of pesticide residue in relation to semen quality. Further confirmation of these findings is warranted. Supported by National Institutes of Health grants ES009718, ES022955, ES000002, P30 DK046200 and Ruth L. Kirschstein National Research Service Award T32 DK007703-16. None of the authors has any conflicts of interest to declare. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Using the remote sensing vegetation condition to assess the drought stress

NASA Astrophysics Data System (ADS)

Semerádová, Daniela; Trnka, Miroslav; Hlavinka, Petr; Balek, Jan; Bohovic, Roman; Tadesse, Tsegaye; Hayes, Michael; Wardlow, Brian; Žalud, Zdeněk

2015-04-01

The occurrence of the meteorological and soil drought is one of the major hydrometeorological extremes with significant impacts on agriculture, horticulture and forestry. The drought monitor system for the Czech Republic was released in 2012. It is based on a daily step calculations of soil moisture for the whole area of the Czech Republic divided into regular grids with a spatial resolution of 500 m. The results are published on the weekly operated webpage (www.intersucho.cz). Using freely available data from the MODIS (Moderate Resolution Imaging Spectroradiometer instrument onboard Terra satellite) the vegetation state condition is taken into account as support tool for vegetation drought impact assessment. Based on the surface reflectance bands the Normalized Difference Vegetation Index (NDVI) is calculated. Consequently, weekly NDVI anomaly is expressed as Percent of Average Actual Greenness (PAAG) in relation to the average for the period of 2000-2014. The system contains filter algorithms that eliminate the noise in the satellite NDVI data mainly due to cloud effects. The following operation allows for changing crop patterns between seasons and aggregates filtered values to the 5x5 km resolution with regard to the main land use categories. The aim of this study was to compare the satellite based vegetation condition to the results of soil moisture calculation in order to detect the impacts of drought on vegetation during seasons with low and normal precipitation sums. This contribution was supported by COST CZ program, project No. LD14121 and the Operational Program of the Czech Republic, project No. CZ.1.07/2.3.00/20.0248.

One input-class and two input-class classifications for differentiating olive oil from other edible vegetable oils by use of the normal-phase liquid chromatography fingerprint of the methyl-transesterified fraction.

PubMed

Jiménez-Carvelo, Ana M; Pérez-Castaño, Estefanía; González-Casado, Antonio; Cuadros-Rodríguez, Luis

2017-04-15

A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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.

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

PubMed Central

van Leeuwen, Willem J. D.

2008-01-01

This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests. PMID:27879809

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

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Fatty acid composition of intramuscular fat from pastoral yak and Tibetan sheep

USDA-ARS?s Scientific Manuscript database

Fatty acid (FA) composition of intramuscular fat from mature male yak (n=6) and mature Tibetan sheep (n=6) grazed on the same pasture in the Qinghai-Tibetan Plateau was analyzed by gas chromatograph/mass spectrometer to characterize fat composition of these species and to evaluate possible differenc...

Website-based PNG image steganography using the modified Vigenere Cipher, least significant bit, and dictionary based compression methods

NASA Astrophysics Data System (ADS)

Rojali, Salman, Afan Galih; George

2017-08-01

Along with the development of information technology in meeting the needs, various adverse actions and difficult to avoid are emerging. One of such action is data theft. Therefore, this study will discuss about cryptography and steganography that aims to overcome these problems. This study will use the Modification Vigenere Cipher, Least Significant Bit and Dictionary Based Compression methods. To determine the performance of study, Peak Signal to Noise Ratio (PSNR) method is used to measure objectively and Mean Opinion Score (MOS) method is used to measure subjectively, also, the performance of this study will be compared to other method such as Spread Spectrum and Pixel Value differencing. After comparing, it can be concluded that this study can provide better performance when compared to other methods (Spread Spectrum and Pixel Value Differencing) and has a range of MSE values (0.0191622-0.05275) and PSNR (60.909 to 65.306) with a hidden file size of 18 kb and has a MOS value range (4.214 to 4.722) or image quality that is approaching very good.

Gigahertz-gated InGaAs/InP single-photon detector with detection efficiency exceeding 55% at 1550 nm

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

Comandar, L. C.; Engineering Department, Cambridge University, 9 J J Thomson Ave, Cambridge CB3 0FA; Fröhlich, B.

We report on a gated single-photon detector based on InGaAs/InP avalanche photodiodes (APDs) with a single-photon detection efficiency exceeding 55% at 1550 nm. Our detector is gated at 1 GHz and employs the self-differencing technique for gate transient suppression. It can operate nearly dead time free, except for the one clock cycle dead time intrinsic to self-differencing, and we demonstrate a count rate of 500 Mcps. We present a careful analysis of the optimal driving conditions of the APD measured with a dead time free detector characterization setup. It is found that a shortened gate width of 360 ps together with anmore » increased driving signal amplitude and operation at higher temperatures leads to improved performance of the detector. We achieve an afterpulse probability of 7% at 50% detection efficiency with dead time free measurement and a record efficiency for InGaAs/InP APDs of 55% at an afterpulse probability of only 10.2% with a moderate dead time of 10 ns.« less

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

Mass Loss of Larsen B Tributary Glaciers (Antarctic Peninsula) Unabated Since 2002

NASA Technical Reports Server (NTRS)

Berthier, Etienne; Scambos, Ted; Shuman, Christopher A.

2012-01-01

Ice mass loss continues at a high rate among the large glacier tributaries of the Larsen B Ice Shelf following its disintegration in 2002. We evaluate recent mass loss by mapping elevation changes between 2006 and 201011 using differencing of digital elevation models (DEMs). The measurement accuracy of these elevation changes is confirmed by a null test, subtracting DEMs acquired within a few weeks. The overall 2006201011 mass loss rate (9.0 2.1 Gt a-1) is similar to the 2001022006 rate (8.8 1.6 Gt a-1), derived using DEM differencing and laser altimetry. This unchanged overall loss masks a varying pattern of thinning and ice loss for individual glacier basins. On Crane Glacier, the thinning pulse, initially greatest near the calving front, is now broadening and migrating upstream. The largest losses are now observed for the HektoriaGreen glacier basin, having increased by 33 since 2006. Our method has enabled us to resolve large residual uncertainties in the Larsen B sector and confirm its state of ongoing rapid mass loss.

SP mountain data analysis

NASA Technical Reports Server (NTRS)

Rawson, R. F.; Hamilton, R. E.; Liskow, C. L.; Dias, A. R.; Jackson, P. L.

1981-01-01

An analysis of synthetic aperture radar data of SP Mountain was undertaken to demonstrate the use of digital image processing techniques to aid in geologic interpretation of SAR data. These data were collected with the ERIM X- and L-band airborne SAR using like- and cross-polarizations. The resulting signal films were used to produce computer compatible tapes, from which four-channel imagery was generated. Slant range-to-ground range and range-azimuth-scale corrections were made in order to facilitate image registration; intensity corrections were also made. Manual interpretation of the imagery showed that L-band represented the geology of the area better than X-band. Several differences between the various images were also noted. Further digital analysis of the corrected data was done for enhancement purposes. This analysis included application of an MSS differencing routine and development of a routine for removal of relief displacement. It was found that accurate registration of the SAR channels is critical to the effectiveness of the differencing routine. Use of the relief displacement algorithm on the SP Mountain data demonstrated the feasibility of the technique.

Solutions of the Taylor-Green Vortex Problem Using High-Resolution Explicit Finite Difference Methods

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2013-01-01

A computational fluid dynamics code that solves the compressible Navier-Stokes equations was applied to the Taylor-Green vortex problem to examine the code s ability to accurately simulate the vortex decay and subsequent turbulence. The code, WRLES (Wave Resolving Large-Eddy Simulation), uses explicit central-differencing to compute the spatial derivatives and explicit Low Dispersion Runge-Kutta methods for the temporal discretization. The flow was first studied and characterized using Bogey & Bailley s 13-point dispersion relation preserving (DRP) scheme. The kinetic energy dissipation rate, computed both directly and from the enstrophy field, vorticity contours, and the energy spectra are examined. Results are in excellent agreement with a reference solution obtained using a spectral method and provide insight into computations of turbulent flows. In addition the following studies were performed: a comparison of 4th-, 8th-, 12th- and DRP spatial differencing schemes, the effect of the solution filtering on the results, the effect of large-eddy simulation sub-grid scale models, and the effect of high-order discretization of the viscous terms.

Numerical simulation of axisymmetric turbulent flow in combustors and diffusors. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Yung, Chain Nan

1988-01-01

A method for predicting turbulent flow in combustors and diffusers is developed. The Navier-Stokes equations, incorporating a turbulence kappa-epsilon model equation, were solved in a nonorthogonal curvilinear coordinate system. The solution applied the finite volume method to discretize the differential equations and utilized the SIMPLE algorithm iteratively to solve the differenced equations. A zonal grid method, wherein the flow field was divided into several subsections, was developed. This approach permitted different computational schemes to be used in the various zones. In addition, grid generation was made a more simple task. However, treatment of the zonal boundaries required special handling. Boundary overlap and interpolating techniques were used and an adjustment of the flow variables was required to assure conservation of mass, momentum and energy fluxes. The numerical accuracy was assessed using different finite differencing methods, i.e., hybrid, quadratic upwind and skew upwind, to represent the convection terms. Flows in different geometries of combustors and diffusers were simulated and results compared with experimental data and good agreement was obtained.

Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

NASA Astrophysics Data System (ADS)

Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

2015-04-01

Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in order to improve planning, business strategies but also to target the drought relief in case of major drought event. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".

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.

Comparing vegetation cover in the Santee Experimental Forest, South Carolina (USA), before and after hurricane Hugo: 1989-2011

Treesearch

Giovanni R. Cosentino

2013-01-01

Hurricane Hugo struck the coast of South Carolina on September 21, 1989 as a category 4 hurricane on the Saffir-Simpson Scale. Landsat Thematic mapper was utilized to determine the extent of damage experienced at the Santee Experimental Forest (SEF) (a part of Francis Marion National Forest) in South Carolina. Normalized Difference Vegetation Index (NDVI) and the...

Ronald A. Hoskinson’s Gulf War Diary

DTIC Science & Technology

1997-01-01

usually fresh fruits and vegetables purchased off of the local economy. Unfortunately, these supplements normally gave soldiers dysentery. Since this ad...economy, such as Pepsi’s, fruit, pastries, and vegetables . Shelter: If the food situation was not simple, the shelter situation was: everybody...had a lot of heartburn with this policy; therefore, there were many incidents of "selective disobedience," with soldiers squirreling away pistols

Wildlife habitats in managed rangelands—the Great Basin of southeastern Oregon: riparian zones.

Treesearch

Jack Ward Thomas; Chris Maser; Jon E. Rodiek

1979-01-01

Riparian zones can be identified by the presence of vegetation that requires free or unbound water or conditions that are more moist than normal (fig. 1) (Franklin and Dyrness 1973, Minore and Smith 1971). Riparian zones can vary considerably in size and vegetative complex because of the many combinations that can be created between water sources (fig. 2) and physical...

Evapotranspiration, Water Table Fluctuations, and Riparian Restoration: Report Documentary 2007-2008 Work

DTIC Science & Technology

2010-09-01

is delineated in upper third in 2006 image. .............................................................................. 23 Figure 19. NDVI ...values are compared for SPOT imagery from 29 May 2006 and 24 August 2006. Fire areas with reduced NDVI from Malpais fire are clearly seen on both sides...results comparing vegetation type and normalized difference vegetation index ( NDVI ), and (4) presents initial results from the groundwater flow field

Association of habitual high-fat intake and desire for protein and sweet food.

PubMed

Tatano, Hiroshi; Yamanaka-Okumura, Hisami; Zhou, Bei; Adachi, Chisaki; Kawakami, Yuka; Katayama, Takafumi; Masuda, Masashi; Takeda, Eiji; Taketani, Yutaka

2016-01-01

Reducing dietary calorie density (CD) is useful in body weight management. This study investigates the association between dietary habits and preferences for different CDs. We conducted a randomized crossover study of 232 healthy subjects who consumed packed lunch boxes containing a control, high-meat and low-rice, low-vegetable, medium-fat and low-vegetable, high-fat, and high-fat and low-vegetable meals over six sessions. The subjective levels of sensory properties were assessed over time using a visual analog scale and the area under the curve. Subjects were assessed for dietary habits using a brief-type self-administered diet history questionnaire (BDHQ) and were divided into two groups based on a daily fat energy ratio ≥ 25% (high fat [HF], n=116) and < 25% (normal, n=116) that was matched for age, body mass index, and sex ratio. Our findings indicate that the desire for sweetness was higher in the HF group than in the normal group, regardless of the meals consumed. Particularly, among the 500-kcal low-CD meals, a high-protein meal provided greater fullness and satisfaction and lower prospective consumption in the HF group than in the normal group. Therefore, our study demonstrates that postprandial appetite sensation is associated with dietary habits of fat intake. J. Med. Invest. 63: 241-247, August, 2016.

Inferring local competition intensity from patch size distributions: a test using biological soil crusts

USGS Publications Warehouse

Bowker, Matthew A.; Maestre, Fernando T.

2012-01-01

Dryland vegetation is inherently patchy. This patchiness goes on to impact ecology, hydrology, and biogeochemistry. Recently, researchers have proposed that dryland vegetation patch sizes follow a power law which is due to local plant facilitation. It is unknown what patch size distribution prevails when competition predominates over facilitation, or if such a pattern could be used to detect competition. We investigated this question in an alternative vegetation type, mosses and lichens of biological soil crusts, which exhibit a smaller scale patch-interpatch configuration. This micro-vegetation is characterized by competition for space. We proposed that multiplicative effects of genetics, environment and competition should result in a log-normal patch size distribution. When testing the prevalence of log-normal versus power law patch size distributions, we found that the log-normal was the better distribution in 53% of cases and a reasonable fit in 83%. In contrast, the power law was better in 39% of cases, and in 8% of instances both distributions fit equally well. We further hypothesized that the log-normal distribution parameters would be predictably influenced by competition strength. There was qualitative agreement between one of the distribution's parameters (μ) and a novel intransitive (lacking a 'best' competitor) competition index, suggesting that as intransitivity increases, patch sizes decrease. The correlation of μ with other competition indicators based on spatial segregation of species (the C-score) depended on aridity. In less arid sites, μ was negatively correlated with the C-score (suggesting smaller patches under stronger competition), while positive correlations (suggesting larger patches under stronger competition) were observed at more arid sites. We propose that this is due to an increasing prevalence of competition transitivity as aridity increases. These findings broaden the emerging theory surrounding dryland patch size distributions and, with refinement, may help us infer cryptic ecological processes from easily observed spatial patterns in the field.

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

NASA Astrophysics Data System (ADS)

Xue, Lihong; Yang, Linzhang

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

On the use of satellite VEGETATION time series for monitoring post fire vegetation recovery

NASA Astrophysics Data System (ADS)

de Santis, F.; Didonna, I.

2009-04-01

Fire is one of the most critical factors of disturbance in worldwide ecosystems. The effects of fires on soil, plants, landscape and ecosystems depend on many factors, among them fire frequency, fire severity and plant resistance. The characterization of vegetation post-fire behaviour is a fundamental issue to model and evaluate the fire resilience, which the ability of vegetation to recover after fire. Recent changes in fire regime, due to abandonment of local land use practice and climate change, can induce significant variations in vegetation fire resilience. In the Mediterranean-type communities, post fire vegetation trends have been analysed in a wide range of habitats, although pre- and post-fire investigation has been widely performed at stand level. But, factors controlling regeneration at the landscape scale are less well known. In this study, a time series of normalized difference vegetation index (NDVI) data derived from SPOT-VEGETATION was used to examine the recovery characteristics of fire affected vegetation in some test areas of the Mediterranean ecosystems of Southern Italy. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) data from 1998 to 2005 were analyzed in order to evaluate the resilient effects in a some significant test sites of southern Italy. In particular, we considered: (i) one stable area site, one site affected by one fire during the investigated time window, (iii) one site affected by two consecutive fires during the investigated time window. In order to eliminate the phenological fluctuations, for each decadal composition of each pixel, we focused on the departure NDVId = [NDVI - ]/, where is the decadal mean and  is the decadal standard deviation. The decadal mean and the standard deviation were calculated for each decade, e.g. 1st decade of January, by averaging over all years in the record. We analyzed both: 1) Time variation of NDVI from 1998 to 2005 of pixels for the fire affected and fire unaffected areas. 2) Post-fire NDVI spatial patterns on each image date were compared to the pre-fire pattern to determine the extent to which the pre-fire pattern was re-established, and the rate of this recovery. Results show the ability of vegetation to recovery after a single fire. Nevertheless, such ability can be strongly reduced by successive fires. The recursive fire occurrence can significantly diminish the green biomass especially when disturbances occur at short intervals of time.

Monitoring post-fire recovery of shrublands in Mediterranean-type ecosystems using MODIS and TM/ETM+ data

NASA Astrophysics Data System (ADS)

Hope, Allen; Albers, Noah; Bart, Ryan

2010-05-01

Wildland fires in Mediterranean-Type Ecosystems (MTEs) are episodic events that dramatically alter land-cover conditions. Monitoring post-fire vegetation recovery is important for land management applications such as the scheduling of prescribed burns, post-fire resource management and soil erosion control. Full recovery of MTE shrublands may take many years and have a prolonged effect on water, energy and carbon fluxes in these ecosystems. Comparative studies of fynbos ecosystems in the Cape Floristic Region of South Africa (Western Cape Region) and chaparral ecosystems of California have demonstrated that there is a considerable degree of convergence in some aspects of post-fire vegetation regeneration and marked differences in other aspects. Since these MTEs have contrasting rainfall and soil nutrient conditions, an obvious question arises as to the similarity or dissimilarity in remotely sensed post-fire recovery pathways of vegetation stands in these two regions and the extent to which fire severity and drought impact the rate of vegetation recovery. Post-fire recovery pathways of chaparral and fynbos vegetation stands were characterized using the normalized difference vegetation index (NDVI) based on TM/ETM+ and MODIS (250 m) data. Procedures based on stands of unburned vegetation (control) were implemented to normalize the NDVI for variations associated with inter-annual differences in rainfall. Only vegetation stands that had not burned for 20 years were examined in this study to eliminate potential effects of variable fire histories on the recovery pathways. Post-fire recovery patterns of vegetation in both regions and across different vegetation types were found to be very similar. Post-fire stand age was the primary control over vegetation recovery and the NDVI returned to pre-fire values within seven to 10 years of the fires. Droughts were shown to cause slight interruptions in recovery rates while fire severity had no discernable effect. Intra-stand variability in the NDVI (pixel-scale) also returned to pre-fire values within the same time frame but increased with water stress associated with droughts. While these studies indicated that the NDVI of fynbos and chaparral stands recovered to pre-fire values within 10 years, it is recognized that other ecosystem characteristics may take considerably longer to recover. Despite the larger pixel size, MODIS data were found to be more suitable for monitoring vegetation post-fire recovery than TM/ETM+ data, requiring considerably less pre-processing and providing substantially more information regarding phenological characteristics of recovery pathways. Future studies will include consideration of fire history in the post-fire recovery characteristics of vegetation in these two MTEs.

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.

On the effects of signal processing on sample entropy for postural control.

PubMed

Lubetzky, Anat V; Harel, Daphna; Lubetzky, Eyal

2018-01-01

Sample entropy, a measure of time series regularity, has become increasingly popular in postural control research. We are developing a virtual reality assessment of sensory integration for postural control in people with vestibular dysfunction and wished to apply sample entropy as an outcome measure. However, despite the common use of sample entropy to quantify postural sway, we found lack of consistency in the literature regarding center-of-pressure signal manipulations prior to the computation of sample entropy. We therefore wished to investigate the effect of parameters choice and signal processing on participants' sample entropy outcome. For that purpose, we compared center-of-pressure sample entropy data between patients with vestibular dysfunction and age-matched controls. Within our assessment, participants observed virtual reality scenes, while standing on floor or a compliant surface. We then analyzed the effect of: modification of the radius of similarity (r) and the embedding dimension (m); down-sampling or filtering and differencing or detrending. When analyzing the raw center-of-pressure data, we found a significant main effect of surface in medio-lateral and anterior-posterior directions across r's and m's. We also found a significant interaction group × surface in the medio-lateral direction when r was 0.05 or 0.1 with a monotonic increase in p value with increasing r in both m's. These effects were maintained with down-sampling by 2, 3, and 4 and with detrending but not with filtering and differencing. Based on these findings, we suggest that for sample entropy to be compared across postural control studies, there needs to be increased consistency, particularly of signal handling prior to the calculation of sample entropy. Procedures such as filtering, differencing or detrending affect sample entropy values and could artificially alter the time series pattern. Therefore, if such procedures are performed they should be well justified.

Performance Assessment of Two GPS Receivers on Space Shuttle

NASA Technical Reports Server (NTRS)

Schroeder, Christine A.; Schutz, Bob E.

1996-01-01

Space Shuttle STS-69 was launched on September 7, 1995, carrying the Wake Shield Facility (WSF-02) among its payloads. The mission included two GPS receivers: a Collins 3M receiver onboard the Endeavour and an Osborne flight TurboRogue, known as the TurboStar, onboard the WSF-02. Two of the WSF-02 GPS Experiment objectives were to: (1) assess the ability to use GPS in a relative satellite positioning mode using the receivers on Endeavour and WSF-02; and (2) assess the performance of the receivers to support high precision orbit determination at the 400 km altitude. Three ground tests of the receivers were conducted in order to characterize the respective receivers. The analysis of the tests utilized the Double Differencing technique. A similar test in orbit was conducted during STS-69 while the WSF-02 was held by the Endeavour robot arm for a one hour period. In these tests, biases were observed in the double difference pseudorange measurements, implying that biases up to 140 m exist which do not cancel in double differencing. These biases appear to exist in the Collins receiver, but their effect can be mitigated by including measurement bias parameters to accommodate them in an estimation process. An additional test was conducted in which the orbit of the combined Endeavour/WSF-02 was determined independently with each receiver. These one hour arcs were based on forming double differences with 13 TurboRogue receivers in the global IGS network and estimating pseudorange biases for the Collins. Various analyses suggest the TurboStar overall orbit accuracy is about one to two meters for this period, based on double differenced phase residuals of 34 cm. These residuals indicate the level of unmodeled forces on Endeavour produced by gravitational and nongravitational effects. The rms differences between the two independently determined orbits are better than 10 meters, thereby demonstrating the accuracy of the Collins-determined orbit at this level as well as the accuracy of the relative positioning using these two receivers.

Extended image differencing for change detection in UAV video mosaics

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang; Schumann, Arne

2014-03-01

Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

An improved analysis of gravity drainage experiments for estimating the unsaturated soil hydraulic functions

NASA Astrophysics Data System (ADS)

Sisson, James B.; van Genuchten, Martinus Th.

1991-04-01

The unsaturated hydraulic properties are important parameters in any quantitative description of water and solute transport in partially saturated soils. Currently, most in situ methods for estimating the unsaturated hydraulic conductivity (K) are based on analyses that require estimates of the soil water flux and the pressure head gradient. These analyses typically involve differencing of field-measured pressure head (h) and volumetric water content (θ) data, a process that can significantly amplify instrumental and measurement errors. More reliable methods result when differencing of field data can be avoided. One such method is based on estimates of the gravity drainage curve K'(θ) = dK/dθ which may be computed from observations of θ and/or h during the drainage phase of infiltration drainage experiments assuming unit gradient hydraulic conditions. The purpose of this study was to compare estimates of the unsaturated soil hydraulic functions on the basis of different combinations of field data θ, h, K, and K'. Five different data sets were used for the analysis: (1) θ-h, (2) K-θ, (3) K'-θ (4) K-θ-h, and (5) K'-θ-h. The analysis was applied to previously published data for the Norfolk, Troup, and Bethany soils. The K-θ-h and K'-θ-h data sets consistently produced nearly identical estimates of the hydraulic functions. The K-θ and K'-θ data also resulted in similar curves, although results in this case were less consistent than those produced by the K-θ-h and K'-θ-h data sets. We conclude from this study that differencing of field data can be avoided and hence that there is no need to calculate soil water fluxes and pressure head gradients from inherently noisy field-measured θ and h data. The gravity drainage analysis also provides results over a much broader range of hydraulic conductivity values than is possible with the more standard instantaneous profile analysis, especially when augmented with independently measured soil water retention data.

Estimation of Microbial Contamination of Food from Prevalence and Concentration Data: Application to Listeria monocytogenes in Fresh Vegetables▿

PubMed Central

Crépet, Amélie; Albert, Isabelle; Dervin, Catherine; Carlin, Frédéric

2007-01-01

A normal distribution and a mixture model of two normal distributions in a Bayesian approach using prevalence and concentration data were used to establish the distribution of contamination of the food-borne pathogenic bacteria Listeria monocytogenes in unprocessed and minimally processed fresh vegetables. A total of 165 prevalence studies, including 15 studies with concentration data, were taken from the scientific literature and from technical reports and used for statistical analysis. The predicted mean of the normal distribution of the logarithms of viable L. monocytogenes per gram of fresh vegetables was −2.63 log viable L. monocytogenes organisms/g, and its standard deviation was 1.48 log viable L. monocytogenes organisms/g. These values were determined by considering one contaminated sample in prevalence studies in which samples are in fact negative. This deliberate overestimation is necessary to complete calculations. With the mixture model, the predicted mean of the distribution of the logarithm of viable L. monocytogenes per gram of fresh vegetables was −3.38 log viable L. monocytogenes organisms/g and its standard deviation was 1.46 log viable L. monocytogenes organisms/g. The probabilities of fresh unprocessed and minimally processed vegetables being contaminated with concentrations higher than 1, 2, and 3 log viable L. monocytogenes organisms/g were 1.44, 0.63, and 0.17%, respectively. Introducing a sensitivity rate of 80 or 95% in the mixture model had a small effect on the estimation of the contamination. In contrast, introducing a low sensitivity rate (40%) resulted in marked differences, especially for high percentiles. There was a significantly lower estimation of contamination in the papers and reports of 2000 to 2005 than in those of 1988 to 1999 and a lower estimation of contamination of leafy salads than that of sprouts and other vegetables. The interest of the mixture model for the estimation of microbial contamination is discussed. PMID:17098926

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.

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

PubMed

Cui, Yaoping

2013-07-01

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

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

NASA Astrophysics Data System (ADS)

Cui, Yaoping

2013-07-01

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

Identification and visualization of dominant patterns and anomalies in remotely sensed vegetation phenology using a parallel tool for principal components analysis

Treesearch

Richard Tran Mills; Jitendra Kumar; Forrest M. Hoffman; William W. Hargrove; Joseph P. Spruce; Steven P. Norman

2013-01-01

We investigated the use of principal components analysis (PCA) to visualize dominant patterns and identify anomalies in a multi-year land surface phenology data set (231 m × 231 m normalized difference vegetation index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)) used for detecting threats to forest health in the conterminous...

The Effects of Atmospheric Constituents on the Normalized Difference Vegetation Index in West Africa.

DTIC Science & Technology

1992-01-01

decades (Nicholson 1989). The combined effects of drought and human activities, such as overgrazing, can adversely effect the Sahelian vegetation. In recent...KOUT) Tillabery, Niger (TILL) Aioun El Atrous, Mauritania (AIOU) Kaolack, Senegal (KAOL) Akjoujt, Mauritania (AKJO) Rufisque, Senegal (RUFI) Atar ...Mauritania ( ATAR ) St. Louis, Senegal (ST L) Boutilimit, Mauritania (BOUT) Letters in parenthesis correspond to Figure 6 parameters in a individual month

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

DTIC Science & Technology

2010-06-01

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

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.

Spectral modelling of multicomponent landscapes in the Sahel

NASA Technical Reports Server (NTRS)

Hanan, N. P.; Prince, S. D.; Hiernaux, P. H. Y.

1991-01-01

Simple additive models are used to examine the infuence of differing soil types on the spatial average spectral reflectance and normalized difference vegetation index (NDVI). The spatial average NDVI is shown to be a function of the brightness (red plus near-infrared reflectances), the NDVI, and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of vegetation. The red and near-infrared component reflectances of soil and vegetation are determined on the basis of aerial photoradiometer data from Mali. The relationship between the vegetation component NDVI and plant cover is found to be better than between the NDVI of the entire landscape and plant cover. It is concluded that the usefulness of this modeling approach depends on the existence of clearly distinguishable landscape components.

On the relationship between thermal emissivity and the Normalized Difference Vegetation Index for natural surfaces

NASA Technical Reports Server (NTRS)

Van De Griend, A. A.; Owe, M.

1993-01-01

The spatial variation of both the thermal emissivity (8-14 microns) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-IR radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0.94. This empirical relationship is of potential use for energy balance studies using thermal IR remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Comparison of MODIS and AVHRR 16-day normalized difference vegetation index composite data

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei; Reed, Bradley C.; Dwyer, John L.; Eidenshink, Jeffery C.

2004-01-01

Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acquired by the MODIS and AVHRR sensors were compared over the same time periods and a variety of land cover classes within the conterminous USA. The relationship between the AVHRR derived NDVI values and those of future sensors is critical to continued long term monitoring of land surface properties. The results indicate that the 16-day composite values are quite similar over the 23 intervals of 2001 that were analyzed, and a linear relationship exists between the NDVI values from the two sensors. The composite AVHRR NDVI data were associated with over 90% of the variation in the MODIS NDVI values. Copyright 2004 by the American Geophysical Union.

Attribution of trends in global vegetation greenness from 1982 to 2011

NASA Astrophysics Data System (ADS)

Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

2012-12-01

Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

The Use of Sun Elevation Angle for Stereogrammetric Boreal Forest Height in Open Canopies

NASA Technical Reports Server (NTRS)

Montesano, Paul M.; Neigh, Christopher; Sun, Guoqing; Duncanson, Laura Innice; Van Den Hoek, Jamon; Ranson, Kenneth Jon

2017-01-01

Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; less than 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereo pairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereo pairs, (2) identify multiple spatially coincident DSMs whose stereo pairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and(4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereo pair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian Larix forests with slopes less than10, our results show that HRSI DSM acquired with sun elevation angles greater than 35deg and less than 25deg (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors less than 0.68 m relative to lidar. The latter, particularly those with angles less than 10deg, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (6.0 m, sigma = 1.4 m) was consistent with the distribution of plot-level mean tree heights (6.5m, sigma = 1.2 m). We conclude that the variation in sun elevation angle at time of stereo pair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register rand difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.

NDVI-Based analysis on the influence of human activities on vegetation variation on Hainan Island

NASA Astrophysics Data System (ADS)

Luo, Hongxia; Dai, Shengpei; Xie, Zhenghui; Fang, Jihua

2018-02-01

Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we analyzed the predicted NDVI values variation and the influence of human activities on vegetation on Hainan Island during 2001-2015. We investigated the roles of human activities in vegetation variation, particularly from 2002 when implemented the Grain-for-Greenprogram on Hainan Island. The trend analysis, linear regression model and residual analysis were used to analyze the data. The results of the study showed that (1) The predicted vegetation on Hainan Island showed an general upward trend with a linear growth rate of 0.0025/10y (p<0.05) over the past 15 years. The areas where vegetation increasedaccounted for 52.28%, while the areas where vegetation decreased accounted for 47.72%. (2) The residual NDVI values across the region significantly increased, with a growth rate of 0.023/10y.The vegetation increased across 35.95% of Hainan Island, while it decreased in 20.2% of the area as a result of human activities. (3) In general, human activities had played a positive role in the vegetation increase on Hainan Island, and the residual NDVI trend of this region showed positive outcomes for vegetation variation after implementing ecological engineering projects. However, it indicated a growing risk of vegetation degradation in the coastal region of Hainan Island as a result of rapid urbanization, land reclamation.

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.

Effect of eating vegetables before carbohydrates on glucose excursions in patients with type 2 diabetes

PubMed Central

Imai, Saeko; Fukui, Michiaki; Kajiyama, Shizuo

2014-01-01

The aim of this review was to evaluate whether eating vegetables before carbohydrates could reduce the postprandial glucose, insulin, and improve long-term glycemic control in Japanese patients with type 2 diabetes. We studied the effect of eating vegetables before carbohydrates on postprandial plasma glucose, insulin, and glycemic control for 2.5 y in patients with type 2 diabetes. The postprandial glucose and insulin levels decreased significantly when the patients ate vegetables before carbohydrates compared to the reverse regimen, and the improvement of glycemic control was observed for 2.5 y. We also compared the postprandial glucose and glucose fluctuations assessed by continuous glucose monitoring system for 72-h in patients with type 2 diabetes and subjects with normal glucose tolerance when subjects ate vegetables before carbohydrates and carbohydrates before vegetables in a randomized crossover design. The glycemic excursions and incremental glucose peak were significantly lower when the subjects ate vegetables before carbohydrates compared to the reverse regimen. This evidence supports the effectiveness of eating vegetables before carbohydrates on glucose excursions in the short-term and glycemic control in the long-term in patients with type 2 diabetes. PMID:24426184

Effect of eating vegetables before carbohydrates on glucose excursions in patients with type 2 diabetes.

PubMed

Imai, Saeko; Fukui, Michiaki; Kajiyama, Shizuo

2014-01-01

The aim of this review was to evaluate whether eating vegetables before carbohydrates could reduce the postprandial glucose, insulin, and improve long-term glycemic control in Japanese patients with type 2 diabetes. We studied the effect of eating vegetables before carbohydrates on postprandial plasma glucose, insulin, and glycemic control for 2.5 y in patients with type 2 diabetes. The postprandial glucose and insulin levels decreased significantly when the patients ate vegetables before carbohydrates compared to the reverse regimen, and the improvement of glycemic control was observed for 2.5 y. We also compared the postprandial glucose and glucose fluctuations assessed by continuous glucose monitoring system for 72-h in patients with type 2 diabetes and subjects with normal glucose tolerance when subjects ate vegetables before carbohydrates and carbohydrates before vegetables in a randomized crossover design. The glycemic excursions and incremental glucose peak were significantly lower when the subjects ate vegetables before carbohydrates compared to the reverse regimen. This evidence supports the effectiveness of eating vegetables before carbohydrates on glucose excursions in the short-term and glycemic control in the long-term in patients with type 2 diabetes.

On modelling the relationship between vegetation greenness and water balance and land use change.

PubMed

Berry, Sandra L; Mackey, Brendan

2018-06-13

Here we sought a biologically meaningful, climate variable that captures water-energy availability and is suitable for high resolution (250 m × 250 m) modelling of the fraction of photosynthetically active radiation intercepted by the sunlit canopy (F V ) derived from a 10-year (July 2000 - June 2010) time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized difference vegetation index (NDVI) satellite imagery for Australia. The long-term mean annual evaporation deficit, and mean annual water availability indices all yielded strong linear relationships with mean F V ([Formula: see text], %). We hypothesised whether some of the scatter about the relationships was related to land-use changes that have disrupted the vegetation-climate-soil equilibrium. Using continental-scale spatial data layers of protected area status and vegetation condition classes we repeated our analyses with restricted datasets. [Formula: see text] of intact native vegetation within protected areas was greater than all modified vegetation classes. There was a consistent decline in the slopes of the regression relationships with increasing intensity of woody vegetation clearing and livestock grazing. Where native vegetation has been transformed by land use there was a 25% reduction in predicted [Formula: see text].

Detection and identification of six Monilinia spp. causing brown rot using TaqMan real-time PCR from pure cultures and infected apple fruit

USDA-ARS?s Scientific Manuscript database

Brown rot is a severe disease affecting stone and pome fruits. This disease was recently confirmed to be caused by the following six closely related species: Monilinia fructicola, Monilinia laxa, Monilinia fructigena, Monilia polystroma, Monilia mumecola and Monilia yunnanensis. Because of differenc...

Child-Led and Interest-Inspired Learning, Home Education, Learning Differences and the Impact of Regulation

ERIC Educational Resources Information Center

Liberto, Giuliana

2016-01-01

Research into the impact of non-consultative home education regulatory change in New South Wales (NSW), Australia, identified clear benefits of a child-led, interest-inspired approach to learning and a negative impact on student learning and well-being outcomes, particularly for learning-differenced children, of restricted practice freedom.…

Sediment Grain Size Measurements: Is There a Differenc Between Digested and Un-digested Samples? And Does the Organic Carbon of the Sample Play a Role

EPA Science Inventory

Grain size is a physical measurement commonly made in the analysis of many benthic systems. Grain size influences benthic community composition, can influence contaminant loading and can indicate the energy regime of a system. We have recently investigated the relationship betw...

Field comparison of the installation and cost of placement of epoxy-coated and MMFX 2 steel deck reinforcement : establishing a baseline for future deck monitoring.

DOT National Transportation Integrated Search

2009-01-01

As part of the Innovative Bridge Research and Construction Program (IBRCP), this study was conducted to use the full-scale construction project of the Route 123 Bridge over the Occoquan River in Northern Virginia to identify and compare any differenc...

Races of Heliconius erato (Nymphalidae: Heliconiinae) found on different sides of the Andes show wing size differences

USDA-ARS?s Scientific Manuscript database

Differences in wing size in geographical races of Heliconius erato distributed over the western and eastern sides of the Andes are reported on here. Individuals from the eastern side of the Andes are statistically larger in size than the ones on the western side of the Andes. A statistical differenc...

Joint production and substitution in timber supply: a panel data analysis

Treesearch

Torjus F Bolkesjo; Joseph Buongiorno; Birger Solberg

2010-01-01

Supply equations for sawlog and pulpwood were developed with a panel of data from 102 Norwegian municipalities, observed from 1980 to 2000. Static and dynamic models were estimated by cross-section, time-series andpanel data methods. A static model estimated by first differencing gavethe best overall results in terms of theoretical expectations, pattern ofresiduals,...

Chrysler improved numerical differencing analyzer for third generation computers CINDA-3G

NASA Technical Reports Server (NTRS)

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

1972-01-01

New and versatile method has been developed to supplement or replace use of original CINDA thermal analyzer program in order to take advantage of improved systems software and machine speeds of third generation computers. CINDA-3G program options offer variety of methods for solution of thermal analog models presented in network format.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Heavy metals health risk assessment for population via consumption of vegetables grown in old mining area; a case study: Banat County, Romania

PubMed Central

2011-01-01

Background The aim of this study is to measure the levels of heavy metals (Fe, Mn, Zn, Cu, Ni, Cd and Pb) found in common vegetables (parsley, carrot, onion, lettuce, cucumber and green beans) grown in contaminated mining areas compared with those grown in reference clear area and to determine their potential detrimental effects via calculation of the daily metal intake (DImetal) and Target Hazard Quotients (THQ) for normal daily consumption of these vegetables, for male and female gender. Results Compared with the reference in contaminated areas, soil and plant contents of all analyzed metals are higher, usually over normally content for Mn, Zn, Cu, Cd and Pb. Particularly, in soil, higher values than intervention threshold values (ITV) were found for Cu and Pb and higher than maximum allowable limits (MAL) for Zn, Cu, Cd and Pb for parsley roots and leaves, carrot roots, cabbage, lettuce and cucumber. DImetal and THQ values for male and female were calculated for each vegetable and metal and for which oral reference doses exist. The combined THQ values calculated are concerning in that they are usually below the safe level of THQ<1 for all vegetables grown in reference area. In contaminated Moldova Noua (M) area the combined THQ exceeded the safe level only for parsley roots, while in more contaminated Ruschita (R) area combined THQ exceeded the safe level for parsley and carrot roots, lettuce and cabbage. Cd and Pb, most toxic metals to humans, have an increasing prevalence in the combined THQ for leafy (cabbage and lettuce) and fruit vegetables (cucumber). In the root vegetables only Pb has an increasing prevalence in combined THQ values. In all areas female THQ is higher than male THQ. Conclusion The results of this study regarding metal contents in soils, vegetables, DImetal and THQ suggest that the consumption of some vegetables (especially parsley, carrot and cabbage and less for lettuce, cucumber and green beans) is not free of risks in these areas. The complex THQ parameter use in health risk assessment of heavy metals provides a better image than using only a simple parameter (contents of metals in soils and vegetables). PMID:22017878

Cross Correlation versus Normalized Mutual Information on Image Registration

NASA Technical Reports Server (NTRS)

Tan, Bin; Tilton, James C.; Lin, Guoqing

2016-01-01

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

Vegetation Water Content Mapping in a Diverse Agricultural Landscape: National Airborne Field Experiment 2006

NASA Technical Reports Server (NTRS)

Cosh, Michael H.; Jing Tao; Jackson, Thomas J.; McKee, Lynn; O'Neill, Peggy

2011-01-01

Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE 06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE 06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture. Using field vegetation sampling and ground-based reflectance measurements, the knowledge base for relating the Normalized Difference Water Index (NDWI) and the vegetation water content was extended to a greater diversity of agricultural crops, which included dryland and irrigated wheat, alfalfa, and canola. Critical to the generation of vegetation water content maps, the land cover for this region was determined from satellite visible/infrared imagery and ground surveys with an accuracy of 95.5% and a kappa coefficient of 0.95. The vegetation water content was estimated with a root mean square error of 0.33 kg/sq m. The results of this investigation contribute to a more robust database of global vegetation water content observations and demonstrate that the approach can be applied with high accuracy. Keywords: Vegetation, field experimentation, thematic mapper, NDWI, agriculture.

Deep cytoplasmic rearrangements in ventralized Xenopus embryos

NASA Technical Reports Server (NTRS)

Brown, E. E.; Denegre, J. M.; Danilchik, M. V.

1993-01-01

Following fertilization in Xenopus, dramatic rearrangements of the egg cytoplasm relocalize maternally synthesized egg components. During the first cell cycle the vegetal yolk mass rotates relative to the egg surface, toward the sperm entry point (SEP) (J. P. Vincent, G. F. Oster, and J. C. Gerhart, 1986, Dev. Biol. 113, 484-500), while concomitant deep cytoplasmic rearrangements occur in the animal hemisphere (M. V. Danilchik and J. M. Denegre, 1991, Development 111, 845-856). In this paper we examine the role of vegetal yolk mass rotation in producing the animal cytoplasmic rearrangements. We inhibited rotation by uv-irradiating embryos during the first cell cycle, a treatment that yields an extremely ventralized phenotype. Both uv-irradiated embryos and unirradiated control embryos show cytoplasmic rearrangements in the animal hemisphere during the first cell cycle. Cytoplasmic rearrangements on the SEP side of the embryo associated with the path of the sperm pronucleus, plus a swirl on the anti-SEP (dorsal) side, are seen, whether or not yolk mass rotation has occurred. This result suggests a role for the expanding sperm aster in directing animal hemisphere cytoplasmic movements. In unirradiated control embryos the anti-SEP (dorsal) swirl is larger than that in uv-irradiated embryos and often extends into the vegetal hemisphere, consistent with the animal cytoplasm having been pulled dorsally and vegetally by the sliding vegetal yolk mass. Thus the yolk mass rotation may normally enhance the dorsalward cytoplasmic movement, begun by the sperm aster, enough to induce normal axis formation. We extended our observations of unirradiated control and uv-irradiated embryos through early cleavages. The vegetal extent of the anti-SEP (dorsal) swirl pattern seen in control embryos persists through the early cleavage period, such that labeled animal cytoplasm extends deep into dorsal third-tier blastomeres at the 32-cell stage. Significantly, in uv-irradiated embryos, which have not undergone vegetal rotation, most of this labeled material remains more equatorial.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

7 CFR 993.62 - Diversion privileges.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN... which would not, under normal producer practices, be dried and delivered to a handler. (f...

7 CFR 993.62 - Diversion privileges.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN... which would not, under normal producer practices, be dried and delivered to a handler. (f...

7 CFR 993.62 - Diversion privileges.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AGREEMENTS AND ORDERS; FRUITS, VEGETABLES, NUTS), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN... which would not, under normal producer practices, be dried and delivered to a handler. (f...

7 CFR 993.62 - Diversion privileges.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE DRIED PRUNES PRODUCED IN... which would not, under normal producer practices, be dried and delivered to a handler. (f...

23 CFR 777.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... substances into organic matter and recycled on a continuing basis. Compensatory mitigation means restoration... normal circumstances do support, a prevalence of vegetation typically adapted for life in saturated soil...

23 CFR 777.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... substances into organic matter and recycled on a continuing basis. Compensatory mitigation means restoration... normal circumstances do support, a prevalence of vegetation typically adapted for life in saturated soil...

23 CFR 777.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... substances into organic matter and recycled on a continuing basis. Compensatory mitigation means restoration... normal circumstances do support, a prevalence of vegetation typically adapted for life in saturated soil...

23 CFR 777.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... substances into organic matter and recycled on a continuing basis. Compensatory mitigation means restoration... normal circumstances do support, a prevalence of vegetation typically adapted for life in saturated soil...

23 CFR 777.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... substances into organic matter and recycled on a continuing basis. Compensatory mitigation means restoration... normal circumstances do support, a prevalence of vegetation typically adapted for life in saturated soil...

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

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

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

Seasonal vegetation differences from ERTS imagery

NASA Technical Reports Server (NTRS)

Ashley, M. D.; Rea, J.

1975-01-01

Knowledge of the times when crop and forest vegetation experience seasonally related changes in development is important in understanding growth and yield relationships. This article describes how densitometry of earth resources technology satellite (ERTS-1) multispectral scanner (MSS) imagery can be used to identify such phenological events. Adjustments for instrument calibration, aperture size, gray-scale differences between overpasses, and normalization of changing solar elevation are considered in detail. Seasonal vegetation differences can be identified by densitometry of band 5 (0.6-0.7 microns) and band 7 (0.8-1.1 microns) MSS imagery. Band-to-band ratios of the densities depicted the changes more graphically than the individual band readings.

Environmental Assessment Addressing the Emerald Breeze Resort, Santa Rosa Island, Fort Walton Beach, Florida

DTIC Science & Technology

2009-09-11

conditions in their upper part. Anaerobic soil conditions are conducive to the establishment of vegetation that is adapted for growth under oxygen...sufficient to support, and that under normal circumstances do support, a prevalence of vegetation typically adapted to life in saturated soil...species adapted to dense commercial development and heavy vehicular traffic would be expected to move back into the area after development of the

Changes in Meadow Vegetation Cover in Kings Canyon National Park (California) Based on Three Decades of Landsat Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Landsat (30 meter resolution) image analysis over the past 25 years in Kings Canyon National Park was used to track changes in the normalized difference vegetation index (NDVI). Results showed that NDVI values from the wet year of 2010 were significantly lower than NDVI values from the comparatively dry year of 2013 in the majority of meadow areas in the National Park.

Analysis on Temporal-Spatial Changes of Vegetation Cverrge in Farming-Pastoral Ecotone of Inner Mongolia

NASA Astrophysics Data System (ADS)

Yan, X.; Li, J.; Yang, Z.

2018-04-01

Chen Barag Banner is located in the typical farming-pastoral ecotone of Inner Mongolia, and it is also the core area of Hulunbuir steppe. Typical agricultural and pastoral staggered production mode so that the vegetation growth of the region not only determines the local ecological environment, and animal husbandry production, but also have a significant impact on the whole Hulunbuir ecological security and economic development. Therefore, it is necessary to monitor the change of vegetation in this area. Based on 17 MODIS Normalized Difference Vegetation Index (NDVI) images, the authors reconstructed the dynamic change characteristics of Fraction vegetation coverage (FVC) in Chen Barag Banner from 2000 to 2016. In this paper, first at all, Pixel Decomposition Models was introduced to inversion FVC, and the time series of vegetation coverage was reconstructed. Then we analyzed the temporal-spatial changes of FVC by employing transition matrix. Finally, through image analyzing and processing, the results showed that the vegetation coverage in the study area was influenced by effectors including climate, topography and human actives. In the past 17 years, the overall effect of vegetation coverage showed a downward trend of fluctuation. The average vegetation coverage decreased from 58.81 % in 2000 to 48.14 % in 2016, and the area of vegetation cover degradation accounts for 40.09 % of the total change area. Therefore, the overall degradation trend was obvious.

Phytonadione

MedlinePlus

... doctor about the amount of vitamin K-rich foods to include in your diet while taking phytonadione. ... not increase or decrease your normal intake of foods such as green leafy vegetables, liver, broccoli, and ...

7 CFR 51.2653 - Well formed.

Code of Federal Regulations, 2010 CFR

2010-01-01

... FRESH FRUITS, VEGETABLES AND OTHER PRODUCTS 1,2 (INSPECTION, CERTIFICATION, AND STANDARDS) United States... cherry has the normal shape characteristic of the variety, except that mature well developed doubles...

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.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Higher Intake of Fruit, but Not Vegetables or Fiber, at Baseline Is Associated with Lower Risk of Becoming Overweight or Obese in Middle-Aged and Older Women of Normal BMI at Baseline.

PubMed

Rautiainen, Susanne; Wang, Lu; Lee, I-Min; Manson, JoAnn E; Buring, Julie E; Sesso, Howard D

2015-05-01

Fruit, vegetable, and dietary fiber intake have been associated with lower risk of cardiovascular disease (CVD); however, little is known about their role in obesity prevention. Our goal was to investigate whether intake of fruits, vegetables, and dietary fiber is associated with weight change and the risk of becoming overweight and obese. We studied 18,146 women aged ≥45 y from the Women's Health Study free of CVD and cancer with an initial body mass index (BMI) of 18.5 to <25 kg/m². Fruit, vegetable, and dietary fiber intakes were assessed at baseline through a 131-item food-frequency questionnaire, along with obesity-related risk factors. Women self-reported body weight on annual questionnaires. During a mean follow-up of 15.9 y, 8125 women became overweight or obese (BMI ≥25 kg/m²). Intakes of total fruits and vegetables, fruits, and dietary fiber were not associated with the longitudinal changes in body weight, whereas higher vegetable intake was associated with greater weight gain (P-trend: 0.02). In multivariable analyses, controlling for total energy intake and physical activity along with other lifestyle, clinical, and dietary factors, women in the highest vs. lowest quintile of fruit intake had an HR of 0.87 (95% CI: 0.80, 0.94; P-trend: 0.01) of becoming overweight or obese. No association was observed for vegetable or dietary fiber intake. The association between fruit intake and risk of becoming overweight or obese was modified by baseline BMI (P-interaction: <0.0001) where the strongest inverse association was observed among women with a BMI <23 kg/m² (HR: 0.82; 95% CI: 0.71, 0.94). Our results suggest that greater baseline intake of fruit, but not vegetables or fiber, by middle-aged and older women with a normal BMI at baseline is associated with lower risk of becoming overweight or obese. © 2015 American Society for Nutrition.

Higher Intake of Fruit, but Not Vegetables or Fiber, at Baseline Is Associated with Lower Risk of Becoming Overweight or Obese in Middle-Aged and Older Women of Normal BMI at Baseline123

PubMed Central

Rautiainen, Susanne; Wang, Lu; Lee, I-Min; Manson, JoAnn E; Buring, Julie E; Sesso, Howard D

2015-01-01

Background: Fruit, vegetable, and dietary fiber intake have been associated with lower risk of cardiovascular disease (CVD); however, little is known about their role in obesity prevention. Objective: Our goal was to investigate whether intake of fruits, vegetables, and dietary fiber is associated with weight change and the risk of becoming overweight and obese. Methods: We studied 18,146 women aged ≥45 y from the Women’s Health Study free of CVD and cancer with an initial body mass index (BMI) of 18.5 to <25 kg/m2. Fruit, vegetable, and dietary fiber intakes were assessed at baseline through a 131-item food-frequency questionnaire, along with obesity-related risk factors. Women self-reported body weight on annual questionnaires. Results: During a mean follow-up of 15.9 y, 8125 women became overweight or obese (BMI ≥25 kg/m2). Intakes of total fruits and vegetables, fruits, and dietary fiber were not associated with the longitudinal changes in body weight, whereas higher vegetable intake was associated with greater weight gain (P-trend: 0.02). In multivariable analyses, controlling for total energy intake and physical activity along with other lifestyle, clinical, and dietary factors, women in the highest vs. lowest quintile of fruit intake had an HR of 0.87 (95% CI: 0.80, 0.94; P-trend: 0.01) of becoming overweight or obese. No association was observed for vegetable or dietary fiber intake. The association between fruit intake and risk of becoming overweight or obese was modified by baseline BMI (P-interaction: <0.0001) where the strongest inverse association was observed among women with a BMI <23 kg/m2 (HR: 0.82; 95% CI: 0.71, 0.94). Conclusion: Our results suggest that greater baseline intake of fruit, but not vegetables or fiber, by middle-aged and older women with a normal BMI at baseline is associated with lower risk of becoming overweight or obese. PMID:25934663

Computation of confined coflow jets with three turbulence models

NASA Technical Reports Server (NTRS)

Zhu, J.; Shih, T. H.

1993-01-01

A numerical study of confined jets in a cylindrical duct is carried out to examine the performance of two recently proposed turbulence models: an RNG-based K-epsilon model and a realizable Reynolds stress algebraic equation model. The former is of the same form as the standard K-epsilon model but has different model coefficients. The latter uses an explicit quadratic stress-strain relationship to model the turbulent stresses and is capable of ensuring the positivity of each turbulent normal stress. The flow considered involves recirculation with unfixed separation and reattachment points and severe adverse pressure gradients, thereby providing a valuable test of the predictive capability of the models for complex flows. Calculations are performed with a finite-volume procedure. Numerical credibility of the solutions is ensured by using second-order accurate differencing schemes and sufficiently fine grids. Calculations with the standard K-epsilon model are also made for comparison. Detailed comparisons with experiments show that the realizable Reynolds stress algebraic equation model consistently works better than does the standard K-epsilon model in capturing the essential flow features, while the RNG-based K-epsilon model does not seem to give improvements over the standard K-epsilon model under the flow conditions considered.

A spectrally accurate boundary-layer code for infinite swept wings

NASA Technical Reports Server (NTRS)

Pruett, C. David

1994-01-01

This report documents the development, validation, and application of a spectrally accurate boundary-layer code, WINGBL2, which has been designed specifically for use in stability analyses of swept-wing configurations. Currently, we consider only the quasi-three-dimensional case of an infinitely long wing of constant cross section. The effects of streamwise curvature, streamwise pressure gradient, and wall suction and/or blowing are taken into account in the governing equations and boundary conditions. The boundary-layer equations are formulated both for the attachment-line flow and for the evolving boundary layer. The boundary-layer equations are solved by marching in the direction perpendicular to the leading edge, for which high-order (up to fifth) backward differencing techniques are used. In the wall-normal direction, a spectral collocation method, based upon Chebyshev polynomial approximations, is exploited. The accuracy, efficiency, and user-friendliness of WINGBL2 make it well suited for applications to linear stability theory, parabolized stability equation methodology, direct numerical simulation, and large-eddy simulation. The method is validated against existing schemes for three test cases, including incompressible swept Hiemenz flow and Mach 2.4 flow over an airfoil swept at 70 deg to the free stream.

Vitamin C

MedlinePlus

... body needs to grow and develop normally. Vitamin C is an antioxidant. It is important for your ... healing and helps the body absorb iron. Vitamin C comes from fruits and vegetables. Good sources include ...

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)

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Arid land monitoring using Landsat albedo difference images

USGS Publications Warehouse

Robinove, Charles J.; Chavez, Pat S.; Gehring, Dale G.; Holmgren, Ralph

1981-01-01

The Landsat albedo, or percentage of incoming radiation reflected from the ground in the wavelength range of 0.5 [mu]m to 1.1 [mu]m, is calculated from an equation using the Landsat digital brightness values and solar irradiance values, and correcting for atmospheric scattering, multispectral scanner calibration, and sun angle. The albedo calculated for each pixel is used to create an albedo image, whose grey scale is proportional to the albedo. Differencing sequential registered images and mapping selected values of the difference is used to create quantitative maps of increased or decreased albedo values of the terrain. All maps and other output products are in black and white rather than color, thus making the method quite economical. Decreases of albedo in arid regions may indicate improvement of land quality; increases may indicate degradation. Tests of the albedo difference mapping method in the Desert Experimental Range in southwestern Utah (a cold desert with little long-term terrain change) for a four-year period show that mapped changes can be correlated with erosion from flash floods, increased or decreased soil moisture, and increases or decreases in the density of desert vegetation, both perennial shrubs and annual plants. All terrain changes identified in this test were related to variations in precipitation. Although further tests of this method in hot deserts showing severe "desertification" are needed, the method is nevertheless recommended for experimental use in monitoring terrain change in other arid and semiarid regions of the world.

Emerging Stress and Relative Resiliency of Giant Sequoia Groves Experiencing Multiyear Dry Periods in a Warming Climate

NASA Astrophysics Data System (ADS)

Su, Yanjun; Bales, Roger C.; Ma, Qin; Nydick, Koren; Ray, Ram L.; Li, Wenkai; Guo, Qinghua

2017-11-01

The relative greenness and wetness of Giant Sequoia (Sequoiadendron giganteum) groves and the surrounding Sierra Nevada, California forests were investigated using patterns in vegetation indices from Landsat imagery for the period 1985-2015. Vegetation greenness (normalized difference vegetation index) and thus forest biomass in groves increased by about 6% over that 30 year period, suggesting a 10% increase in evapotranspiration. No significant change in the surrounding nongrove forest was observed. In this period, local temperature measurements showed an increase of about 2.2°C. The wetness of groves (normalized difference wetness index) showed no overall long-term trend but responded to changes in annual water-year precipitation and temperature. The long-term trends of grove greenness and wetness varied by elevation, with the lower rain-snow transition elevation zone (1,700-2,100 m) marking a change from an increasing trend at lower elevations to a decreasing trend at higher elevations. The 2011-2015 drought brought an unprecedented drop in grove wetness, over 5 times the 1985-2010 standard deviation, and wetness in SEGI groves dropped 50% more than in nongrove areas. Overall, the wetness and greenness of SEGI groves showed a larger response to the warming climate and drought than nongrove areas. The influence of droughts on the wetness of SEGI groves reflected effects of both the multidecadal increase in forest biomass and the effects of warmer drought-year temperatures on the evaporative demand of current grove vegetation, plus sufficient regolith water storage of rain and snowmelt to sustain that vegetation through seasonal and multiyear dry periods.

Grassland Npp Monitoring Based on Multi-Source Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Cai, Y. R.; Zheng, J. H.; Du, M. J.; Mu, C.; Peng, J.

2018-04-01

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006-2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

Viking S-band Doppler RMS phase fluctuations used to calibrate the mean 1976 equatorial corona

NASA Technical Reports Server (NTRS)

Berman, A. L.; Wackley, J. A.

1977-01-01

Viking S-band Doppler RMS phase fluctuations (noise) and comparisons of Viking Doppler noise to Viking differenced S-X range measurements are used to construct a mean equatorial electron density model for 1976. Using Pioneer Doppler noise results (at high heliographic latitudes, also from 1976), an equivalent nonequatorial electron density model is approximated.

Finite difference methods for the solution of unsteady potential flows

NASA Technical Reports Server (NTRS)

Caradonna, F. X.

1982-01-01

Various problems which are confronted in the development of an unsteady finite difference potential code are reviewed mainly in the context of what is done for a typical small disturbance and full potential method. The issues discussed include choice of equations, linearization and conservation, differencing schemes, and algorithm development. A number of applications, including unsteady three dimensional rotor calculations, are demonstrated.

Model Specifications for Estimating Labor Market Returns to Associate Degrees: How Robust Are Fixed Effects Estimates? A CAPSEE Working Paper

ERIC Educational Resources Information Center

Belfield, Clive; Bailey, Thomas

2017-01-01

Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex…

New insights into soil temperature time series modeling: linear or nonlinear?

NASA Astrophysics Data System (ADS)

Bonakdari, Hossein; Moeeni, Hamid; Ebtehaj, Isa; Zeynoddin, Mohammad; Mahoammadian, Abdolmajid; Gharabaghi, Bahram

2018-03-01

Soil temperature (ST) is an important dynamic parameter, whose prediction is a major research topic in various fields including agriculture because ST has a critical role in hydrological processes at the soil surface. In this study, a new linear methodology is proposed based on stochastic methods for modeling daily soil temperature (DST). With this approach, the ST series components are determined to carry out modeling and spectral analysis. The results of this process are compared with two linear methods based on seasonal standardization and seasonal differencing in terms of four DST series. The series used in this study were measured at two stations, Champaign and Springfield, at depths of 10 and 20 cm. The results indicate that in all ST series reviewed, the periodic term is the most robust among all components. According to a comparison of the three methods applied to analyze the various series components, it appears that spectral analysis combined with stochastic methods outperformed the seasonal standardization and seasonal differencing methods. In addition to comparing the proposed methodology with linear methods, the ST modeling results were compared with the two nonlinear methods in two forms: considering hydrological variables (HV) as input variables and DST modeling as a time series. In a previous study at the mentioned sites, Kim and Singh Theor Appl Climatol 118:465-479, (2014) applied the popular Multilayer Perceptron (MLP) neural network and Adaptive Neuro-Fuzzy Inference System (ANFIS) nonlinear methods and considered HV as input variables. The comparison results signify that the relative error projected in estimating DST by the proposed methodology was about 6%, while this value with MLP and ANFIS was over 15%. Moreover, MLP and ANFIS models were employed for DST time series modeling. Due to these models' relatively inferior performance to the proposed methodology, two hybrid models were implemented: the weights and membership function of MLP and ANFIS (respectively) were optimized with the particle swarm optimization (PSO) algorithm in conjunction with the wavelet transform and nonlinear methods (Wavelet-MLP & Wavelet-ANFIS). A comparison of the proposed methodology with individual and hybrid nonlinear models in predicting DST time series indicates the lowest Akaike Information Criterion (AIC) index value, which considers model simplicity and accuracy simultaneously at different depths and stations. The methodology presented in this study can thus serve as an excellent alternative to complex nonlinear methods that are normally employed to examine DST.

PROTEUS two-dimensional Navier-Stokes computer code, version 1.0. Volume 1: Analysis description

NASA Technical Reports Server (NTRS)

Towne, Charles E.; Schwab, John R.; Benson, Thomas J.; Suresh, Ambady

1990-01-01

A new computer code was developed to solve the two-dimensional or axisymmetric, Reynolds averaged, unsteady compressible Navier-Stokes equations in strong conservation law form. The thin-layer or Euler equations may also be solved. Turbulence is modeled using an algebraic eddy viscosity model. The objective was to develop a code for aerospace applications that is easy to use and easy to modify. Code readability, modularity, and documentation were emphasized. The equations are written in nonorthogonal body-fitted coordinates, and solved by marching in time using a fully-coupled alternating direction-implicit procedure with generalized first- or second-order time differencing. All terms are linearized using second-order Taylor series. The boundary conditions are treated implicitly, and may be steady, unsteady, or spatially periodic. Simple Cartesian or polar grids may be generated internally by the program. More complex geometries require an externally generated computational coordinate system. The documentation is divided into three volumes. Volume 1 is the Analysis Description, and describes in detail the governing equations, the turbulence model, the linearization of the equations and boundary conditions, the time and space differencing formulas, the ADI solution procedure, and the artificial viscosity models.

Application of an Upwind High Resolution Finite-Differencing Scheme and Multigrid Method in Steady-State Incompressible Flow Simulations

NASA Technical Reports Server (NTRS)

Yang, Cheng I.; Guo, Yan-Hu; Liu, C.- H.

1996-01-01

The analysis and design of a submarine propulsor requires the ability to predict the characteristics of both laminar and turbulent flows to a higher degree of accuracy. This report presents results of certain benchmark computations based on an upwind, high-resolution, finite-differencing Navier-Stokes solver. The purpose of the computations is to evaluate the ability, the accuracy and the performance of the solver in the simulation of detailed features of viscous flows. Features of interest include flow separation and reattachment, surface pressure and skin friction distributions. Those features are particularly relevant to the propulsor analysis. Test cases with a wide range of Reynolds numbers are selected; therefore, the effects of the convective and the diffusive terms of the solver can be evaluated separately. Test cases include flows over bluff bodies, such as circular cylinders and spheres, at various low Reynolds numbers, flows over a flat plate with and without turbulence effects, and turbulent flows over axisymmetric bodies with and without propulsor effects. Finally, to enhance the iterative solution procedure, a full approximation scheme V-cycle multigrid method is implemented. Preliminary results indicate that the method significantly reduces the computational effort.

Hand-held UXO Discriminator

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

Gasperikova, E.; Smith, J.T.; Kappler, K.N.

2010-04-01

With prior funding (UX-1225, MM-0437, and MM-0838), we have successfully designed and built a cart-mounted Berkeley UXO Discriminator (BUD) and demonstrated its performance at various test sites (e.g., Gasperikova et al., 2007, 2009). It is a multi-transmitter multi-receiver active electromagnetic system that is able to discriminate UXO from scrap at a single measurement position, hence eliminates equirement of a very accurate sensor location. The cart-mounted system comprises of three orthogonal transmitters and eight pairs of differenced receivers (Smith et al., 2007). Receiver coils are located on ymmetry lines through the center of the system and see identical fields during themore » on-time of the pulse in all of the transmitter coils. They can then be wired in opposition to produce zero output during the n-ime of the pulses in three orthogonal transmitters. Moreover, this configuration dramatically reduces noise in the measurements by canceling the background electromagnetic fields (these fields are uniform ver the scale of the receiver array and are consequently nulled by the differencing operation), and by canceling the noise contributed by the tilt of the receivers in the Earth's magnetic field, and therefore reatly enhances receivers sensitivity to the gradients of the target.« less

An RGB colour image steganography scheme using overlapping block-based pixel-value differencing

PubMed Central

Pal, Arup Kumar

2017-01-01

This paper presents a steganographic scheme based on the RGB colour cover image. The secret message bits are embedded into each colour pixel sequentially by the pixel-value differencing (PVD) technique. PVD basically works on two consecutive non-overlapping components; as a result, the straightforward conventional PVD technique is not applicable to embed the secret message bits into a colour pixel, since a colour pixel consists of three colour components, i.e. red, green and blue. Hence, in the proposed scheme, initially the three colour components are represented into two overlapping blocks like the combination of red and green colour components, while another one is the combination of green and blue colour components, respectively. Later, the PVD technique is employed on each block independently to embed the secret data. The two overlapping blocks are readjusted to attain the modified three colour components. The notion of overlapping blocks has improved the embedding capacity of the cover image. The scheme has been tested on a set of colour images and satisfactory results have been achieved in terms of embedding capacity and upholding the acceptable visual quality of the stego-image. PMID:28484623

Accurate Adaptive Level Set Method and Sharpening Technique for Three Dimensional Deforming Interfaces

NASA Technical Reports Server (NTRS)

Kim, Hyoungin; Liou, Meng-Sing

2011-01-01

In this paper, we demonstrate improved accuracy of the level set method for resolving deforming interfaces by proposing two key elements: (1) accurate level set solutions on adapted Cartesian grids by judiciously choosing interpolation polynomials in regions of different grid levels and (2) enhanced reinitialization by an interface sharpening procedure. The level set equation is solved using a fifth order WENO scheme or a second order central differencing scheme depending on availability of uniform stencils at each grid point. Grid adaptation criteria are determined so that the Hamiltonian functions at nodes adjacent to interfaces are always calculated by the fifth order WENO scheme. This selective usage between the fifth order WENO and second order central differencing schemes is confirmed to give more accurate results compared to those in literature for standard test problems. In order to further improve accuracy especially near thin filaments, we suggest an artificial sharpening method, which is in a similar form with the conventional re-initialization method but utilizes sign of curvature instead of sign of the level set function. Consequently, volume loss due to numerical dissipation on thin filaments is remarkably reduced for the test problems

Improved Multispectral Skin Detection and its Application to Search Space Reduction for Dismount Detection Based on Histograms of Oriented Gradients

DTIC Science & Technology

2010-03-01

2-29 2.7.4 Normalized Difference Skin Index (NDSI) . . . . 2-30 2.7.5 Normalized Difference Vegetation Index ( NDVI ) 2-31 2.7.6...C-1 C.2 NDVI Method . . . . . . . . . . . . . . . . . . . . . . . C-4 Bibliography... NDVI ,NDSI) and (NDGRI,NDSI) values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 4.3. Joint distributions of ( NDVI ,NDSI) and

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.

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

USGS Publications Warehouse

Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

2010-01-01

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Herbal Earth

NASA Image and Video Library

2017-12-08

Subtle vegetation changes are visible in this year-long visualization. Large-scale patterns vary with seasons, but the local variations in green are also sensitive precipitation, drought and fire. High values of Normalized Difference Vegetation Index, or NDVI, represent dense green functioning vegetation and low NDVI values represent sparse green vegetation or vegetation under stress from limiting conditions, such as drought. The visualization was created from a year’s worth of data from April 2012 to April 2013. The information was sent back to Earth from the Visible-Infrared Imager/Radiometer Suite (VIIRS) instrument aboard the Suomi National Polar-orbiting Partnership or Suomi NPP satellite, a partnership between NASA and the National Oceanic and Atmospheric Administration, or NOAA. Credit: NASA/NOAA To read more go to: www.nasa.gov/mission_pages/NPP/news/vegetation.html NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

An algorithm for retrieving rock-desertification from multispectral remote sensing images

NASA Astrophysics Data System (ADS)

Xia, Xueqi; Tian, Qingjiu; Liao, Yan

2009-06-01

Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

Analyzing the non-stationary space relationship of a city's degree of vegetation and social economic conditions in Shanghai, China using OLS and GWR models

NASA Astrophysics Data System (ADS)

Wang, Kejing; Zhang, Yuan; An, Youzhi; Jing, Zhuoxin; Wang, Chao

2013-09-01

With the fast urbanization process, how does the vegetation environment change in one of the most economically developed metropolis, Shanghai in East China? To answer this question, there is a pressing demand to explore the non-stationary relationship between socio-economic conditions and vegetation across Shanghai. In this study, environmental data on vegetation cover, the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery in 2003 were integrated with socio-economic data to reflect the city's vegetative conditions at the census block group level. To explore regional variations in the relationship of vegetation and socio-economic conditions, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to characterize mean NDVI against three independent socio-economic variables, an urban land use ratio, Gross Domestic Product (GDP) and population density. The study results show that a considerable distinctive spatial variation exists in the relationship for each model. The GWR model has superior effects and higher precision than the OLS model at the census block group scale. So, it is more suitable to account for local effects and geographical variations. This study also indicates that unreasonable excessive urbanization, together with non-sustainable economic development, has a negative influence of vegetation vigor for some neighborhoods in Shanghai.

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.

[Vegetation change in Shenzhen City based on NDVI change classification].

PubMed

Li, Yi-Jing; Zeng, Hui; Wel, Jian-Bing

2008-05-01

Based on the TM images of 1988 and 2003 as well as the land-use change survey data in 2004, the vegetation change in Shenzhen City was assessed by a NDVI (normalized difference vegetation index) change classification method, and the impacts from natural and social constraining factors were analyzed. The results showed that as a whole, the rapid urbanization in 1988-2003 had less impact on the vegetation cover in the City, but in its plain areas with low altitude, the vegetation cover degraded more obviously. The main causes of the localized ecological degradation were the invasion of built-ups to woods and orchards, land transformation from woods to orchards at the altitude of above 100 m, and low percentage of green land in some built-ups areas. In the future, the protection and construction of vegetation in Shenzhen should focus on strengthening the protection and restoration of remnant woods, trying to avoid the built-ups' expansion to woods and orchards where are better vegetation-covered, rectifying the unreasonable orchard constructions at the altitude of above 100 m, and consolidating the greenbelt construction inside the built-ups. It was considered that the NDVI change classification method could work well in efficiently uncovering the trend of macroscale vegetation change, and avoiding the effect of random noise in data.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

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

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

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.

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.

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.

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.

Extraction of urban vegetation with Pleiades multiangular images

NASA Astrophysics Data System (ADS)

Lefebvre, Antoine; Nabucet, Jean; Corpetti, Thomas; Courty, Nicolas; Hubert-Moy, Laurence

2016-10-01

Vegetation is essential in urban environments since it provides significant services in terms of health, heat, property value, ecology ... As part of the European Union Biodiversity Strategy Plan for 2020, the protection and development of green-infrastructures is strengthened in urban areas. In order to evaluate and monitor the quality of the green infra-structures, this article investigates contributions of Pléiades multi-angular images to extract and characterize low and high urban vegetation. From such images one can extract both spectral and elevation information from optical images. Our method is composed of 3 main steps : (1) the computation of a normalized Digital Surface Model from the multi-angular images ; (2) Extraction of spectral and contextual features ; (3) a classification of vegetation classes (tree and grass) performed with a random forest classifier. Results performed in the city of Rennes in France show the ability of multi-angular images to extract DEM in urban area despite building height. It also highlights its importance and its complementarity with contextual information to extract urban vegetation.

[Effects of climate and grazing on the vegetation cover change in Xilinguole League of Inner Mongolia, North China].

PubMed

Wang, Hai-Mei; Li, Zheng-Hai; Wang, Zhen

2013-01-01

Based on the monthly temperature and precipitation data of 15 meteorological stations and the statistical data of livestock density in Xilinguole League in 1981-2007, and by using ArcGIS, this paper analyzed the spatial distribution of the climate aridity and livestock density in the League, and in combining with the ten-day data of the normalized difference vegetation index (NDVI) in 1981-2007, the driving factors of the vegetation cover change in the League were discussed. In the study period, there was a satisfactory linear regression relationship between the climate aridity and the vegetation coverage. The NDVI and the livestock density had a favorable binomial regression relationship. With the increase of NDVI, the livestock density increased first and decreased then. The vegetation coverage had a complex linear relationship with livestock density and climate aridity. The NDVI had a positive correlation with climate aridity, but a negative correlation with livestock density. Compared with livestock density, climate aridity had far greater effects on the NDVI.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Monitoring height and greenness of non-woody floodplain vegetation with UAV time series

NASA Astrophysics Data System (ADS)

van Iersel, Wimala; Straatsma, Menno; Addink, Elisabeth; Middelkoop, Hans

2018-07-01

Vegetation in river floodplains has important functions for biodiversity, but can also have a negative influence on flood safety. Floodplain vegetation is becoming increasingly heterogeneous in space and time as a result of river restoration projects. To document the spatio-temporal patterns of the floodplain vegetation, the need arises for efficient monitoring techniques. Monitoring is commonly performed by mapping floodplains based on single-epoch remote sensing data, thereby not considering seasonal dynamics of vegetation. The rising availability of unmanned airborne vehicles (UAV) increases monitoring frequency potential. Therefore, we aimed to evaluate the performance of multi-temporal high-spatial-resolution imagery, collected with a UAV, to record the dynamics in floodplain vegetation height and greenness over a growing season. Since the classification accuracy of current airborne surveys remains insufficient for low vegetation types, we focussed on seasonal variation of herbaceous and grassy vegetation with a height up to 3 m. Field reference data on vegetation height were collected six times during one year in 28 field plots within a single floodplain along the Waal River, the main distributary of the Rhine River in the Netherlands. Simultaneously with each field survey, we recorded UAV true-colour and false-colour imagery from which normalized digital surface models (nDSMs) and a consumer-grade camera vegetation index (CGCVI) were calculated. We observed that: (1) the accuracy of a UAV-derived digital terrain model (DTM) varies over the growing season and is most accurate during winter when the vegetation is dormant, (2) vegetation height can be determined from the nDSMs in leaf-on conditions via linear regression (RSME = 0.17-0.33 m), (3) the multitemporal nDSMs yielded meaningful temporal profiles of greenness and vegetation height and (4) herbaceous vegetation shows hysteresis for greenness and vegetation height, but no clear hysteresis was observed for grassland vegetation. These results show the high potential of using UAV-borne sensors for increasing the classification accuracy of low floodplain vegetation within the framework of floodplain monitoring.

Influence of seasoning on vegetable selection, liking and intent to purchase.

PubMed

Manero, Joanna; Phillips, Carter; Ellison, Brenna; Lee, Soo-Yeun; Nickols-Richardson, Sharon M; Chapman-Novakofski, Karen M

2017-09-01

Low vegetable intake continues to be a health concern, and strategies to increase vegetable intake have resulted in only small increases. One strategy that has received less attention is the use of seasonings. This study's objective was to determine the impact of seasoning on vegetable selection, liking, and intent to purchase. We conducted a 3-week study in a public café on a university campus. Customers buying a main dish could select a vegetable side (seasoned [SS] or steamed [ST]) at no cost. Based on café data and power analysis (alpha 0.05, 80% power), 2 days per vegetable pair were conducted with carrot, broccoli, and green bean pairs randomized 3 days/week 1 and 3, with normal service week 2. Selection was greater for SS vs ST, n = 335 vs. 143 for all 3 vegetables combined; n = 97 vs 47 for carrots; n = 114 vs. 55 for broccoli; n = 124 vs. 41 for green beans (p < 0.001 Chi-Square). Liking responses were similar for SS vs ST and were high for all vegetables. Response distribution was not significantly different for SS vs ST vegetables when people were asked if they would purchase the vegetable that they selected. More customers chose the 'somewhat likely' and 'very likely' (n = 353) than the 'not likely' and 'definitely would not' (n = 121) purchase responses. Regression showed that people who did not often consume a vegetable with lunch while dining out were 1.59 times more likely to select the SS vegetables over the ST (p = 0.007). Given a choice, consumers were more likely to select a seasoned vegetable. With low vegetable consumption as a predictor of seasoned vegetable choice, offering seasoned vegetables may increase intake in those with poor vegetable intake in a café setting. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Wildlife habitat evaluation demonstration project. [Michigan

NASA Technical Reports Server (NTRS)

Burgoyne, G. E., Jr.; Visser, L. G.

1981-01-01

To support the deer range improvement project in Michigan, the capability of LANDSAT data in assessing deer habitat in terms of areas and mixes of species and age classes of vegetation is being examined to determine whether such data could substitute for traditional cover type information sources. A second goal of the demonstration project is to determine whether LANDSAT data can be used to supplement and improve the information normally used for making deer habitat management decisions, either by providing vegetative cover for private land or by providing information about the interspersion and juxtaposition of valuable vegetative cover types. The procedure to be used for evaluating in LANDSAT data of the Lake County test site is described.

The 1990 conterminous U. S. AVHRR data set

USGS Publications Warehouse

Eidenshink, Jeffery C.

1992-01-01

The U.S. Geological Survey, using NOAA-ll Advanced Very High Resolution Radiometer (AVHRR) 1-km data, has produced a time series of 19 biweekly maximum normalized difference vegetation index (NDV!) composites of the conterminous United States for the 1990 growing season. Each biweekly composite included data from approximately 20 calibrated and georegistered daily overpasses. The output is a data set which includes all five calibrated AVHRR channels, NOV! values, three satellite/solar viewing angles, and date of observation pointer for each biweekly composite. The data set is intended for assessing seasonal variations in vegetation condition and provides a foundation for studying long-term changes in vegetation resulting from human interactions or global climate alterations.

Climatic and topographical factors affecting the vegetative carbon stock of rangelands in arid and semiarid regions of China

USGS Publications Warehouse

Zhengchao, Ren; Huazhong, Zhu; Shi, Hua; Xiaoni, Liu

2016-01-01

Rangeland systems play an important role in ecological stabilization and the terrestrial carbon cycle in arid and semiarid regions. However, little is known about the vegetative carbon dynamics and climatic and topographical factors that affect vegetative carbon stock in these rangelands. Our goal was to assess vegetative carbon stock by examining meteorological data in conjunction with NDVI (normalized difference vegetation index) time series datasets from 2001–2012. An improved CASA (Carnegie Ames Stanford Approach) model was then applied to simulate the spatiotemporal dynamic variation of vegetative carbon stock, and analyze its response to climatic and topographical factors. We estimated the vegetative carbon stock of rangeland in Gansu province, China to be 4.4× 1014 gC, increasing linearly at an annual rate of 9.8×1011 gC. The mean vegetative carbon density of the whole rangeland was 136.5 gC m-2. Vegetative carbon density and total carbon varied temporally and spatially and were highly associated with temperature, precipitation and solar radiation. Vegetative carbon density reached the maximal value on elevation at 2500–3500 m, a slope of >30°and easterly aspect. The effect of precipitation, temperature and solar radiation on the vegetative carbon density of five rangeland types (desert and salinized meadow, steppe, alpine meadow, shrub and tussock, and marginal grassland in the forest) depends on the acquired quantity of water and heat for rangeland plants at all spatial scales. The results of this study provide new evidence for explaining spatiotemporal heterogeneity in vegetative carbon dynamics and responses to global change for rangeland vegetative carbon stock, and offer a theoretical and practical basis for grassland agriculture management in arid and semiarid regions.

7 CFR 51.1007 - Fairly well formed.

Code of Federal Regulations, 2010 CFR

2010-01-01

... MARKETING ACT OF 1946 FRESH FRUITS, VEGETABLES AND OTHER PRODUCTS 1,2 (INSPECTION, CERTIFICATION, AND.... Fairly well formed means that the fruit shows normal characteristic shape for the Persian variety and is...

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

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

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.

Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

NASA Astrophysics Data System (ADS)

Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

2005-10-01

Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

15 CFR 922.182 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... space for individual and population growth and normal behavior of humpback whales, and include sites... vegetation growth, or the upper limit of debris left by the wash of the waves. Take or taking a humpback...

15 CFR 922.182 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... space for individual and population growth and normal behavior of humpback whales, and include sites... vegetation growth, or the upper limit of debris left by the wash of the waves. Take or taking a humpback...

15 CFR 922.182 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... space for individual and population growth and normal behavior of humpback whales, and include sites... vegetation growth, or the upper limit of debris left by the wash of the waves. Take or taking a humpback...

15 CFR 922.182 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... space for individual and population growth and normal behavior of humpback whales, and include sites... vegetation growth, or the upper limit of debris left by the wash of the waves. Take or taking a humpback...

15 CFR 922.182 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... space for individual and population growth and normal behavior of humpback whales, and include sites... vegetation growth, or the upper limit of debris left by the wash of the waves. Take or taking a humpback...

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

Post-Katrina Land-Cover, Elevation, and Volume Change Assessment along the South Shore of Lake Pontchartrain, Louisiana, U.S.A.

DTIC Science & Technology

2011-01-01

was greater than 1 or less than 0. The second was a Normalized Difference Vegetation Index ( NDVI ) band ratio between a near-infrared band (738 nm) and...separation methods worked well, neither produced perfect results. Ultimately, the NDVI method was chosen because it could also be used to further...In addition, it is a broadly tested method often used to identify and measure vegetation (Tucker, 1979). The NDVI result was also used to separate

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

Concepts for Sensor Data Fusion to Detect Vegetation Stress and Implications on Ecosystem Health Following Hurricane Katrina

DTIC Science & Technology

2008-09-01

Description NDVI Narrow-band Normalized Difference Vegetation Index (can check all possible two-band combinations, and determine best band combinations...were calculated for each site. The band indices were: • NDVI (Hyperion bands 45 & 33) (Figure 2) • NDWI (Hyperion bands 51 & 109) • PRI (Hyperion...between categories for these groups. NDVI and NDWI were very close to achiev- ing a significant result, and were still particularly good at separating two

A numerical study of the steady scalar convective diffusion equation for small viscosity

NASA Technical Reports Server (NTRS)

Giles, M. B.; Rose, M. E.

1983-01-01

A time-independent convection diffusion equation is studied by means of a compact finite difference scheme and numerical solutions are compared to the analytic inviscid solutions. The correct internal and external boundary layer behavior is observed, due to an inherent feature of the scheme which automatically produces upwind differencing in inviscid regions and the correct viscous behavior in viscous regions.

Atmospheric cloud physics thermal systems analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

Interior Fluid Dynamics of Liquid-Filled Projectiles

DTIC Science & Technology

1989-12-01

the Sandia code. The previous codes are primarily based on finite-difference approximations with relatively coarse grid and were designed without...exploits Chorin’s method of artificial compressibility. The steady solution at 11 X 24 X 21 grid points in r, 0, z-direction is obtained by integrating...differences in radial and axial direction and pseudoepectral differencing in the azimuthal direction. Nonuniform grids are introduced for increased

Domain Derivatives in Dielectric Rough Surface Scattering

DTIC Science & Technology

2015-01-01

and require the gradient of the objective function in the unknown model parameter vector at each stage of iteration. For large N, finite...differencing becomes numerically intensive, and an efficient alternative is domain differentiation in which the full gradient is obtained by solving a single...derivative calculation of the gradient for a locally perturbed dielectric interface. The method is non-variational, and algebraic in nature in that it

Wave Current Interactions and Wave-blocking Predictions Using NHWAVE Model

DTIC Science & Technology

2013-03-01

Navier-Stokes equation. In this approach, as with previous modeling techniques, there is difficulty in simulating the free surface that inhibits accurate...hydrostatic, free - surface , rotational flows in multiple dimensions. It is useful in predicting transformations of surface waves and rapidly varied...Stelling, G., and M. Zijlema, 2003: An accurate and efficient finite-differencing algorithm for non-hydrostatic free surface flow with application to

Progress in Multi-Dimensional Upwind Differencing

DTIC Science & Technology

1992-09-01

Fligure 4a a shiock less t raii~so ilc soliit ion is reached from Ii itial val ies conitaining 1shiocks anid S sonic poinits: agarin. thle residiial...8217 j~ vi are chu i.ewil thtii( lealst alliilied \\wit the conivectiloll direct nwi. in1 .3 tlimeIros alj’uled. (hiul *IS a treg h11f,1r p( ir~to1to .3

Sensitivity of the normalized difference vegetation index to subpixel canopy cover, soil albedo, and pixel scale

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.

1990-01-01

An analytical framework is provided for examining the physically based behavior of the normalized difference vegetation index (NDVI) in terms of the variability in bulk subpixel landscape components and with respect to variations in pixel scales, within the context of the stochastic-geometric canopy reflectance model. Analysis focuses on regional scale variability in horizontal plant density and soil background reflectance distribution. Modeling is generalized to different plant geometries and solar angles through the use of the nondimensional solar-geometric similarity parameter. Results demonstrate that, for Poisson-distributed plants and for one deterministic distribution, NDVI increases with increasing subpixel fractional canopy amount, decreasing soil background reflectance, and increasing shadows, at least within the limitations of the geometric reflectance model. The NDVI of a pecan orchard and a juniper landscape is presented and discussed.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

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.

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.

Phenology Shifts at Start vs. End of Growing Season in Temperate Vegetation Over the Northern Hemisphere for the Period 1982-2008

NASA Technical Reports Server (NTRS)

Jeong, Su-Jong; Ho, Chang-Hoi; Gim, Hyeon-Ju; Brown, Molley E.

2011-01-01

Changes in vegetative growing seasons are dominant indicators of the dynamic response of ecosystems to climate change. Therefore, knowledge of growing seasons over the past decades is essential to predict ecosystem changes. In this study, the long-term changes in the growing seasons of temperate vegetation over the Northern Hemisphere were examined by analyzing satellite-measured normalized difference vegetation index and reanalysis temperature during 1982 2008. Results showed that the length of the growing season (LOS) increased over the analysis period; however, the role of changes at the start of the growing season (SOS) and at the end of the growing season (EOS) differed depending on the time period. On a hemispheric scale, SOS advanced by 5.2 days in the early period (1982-1999) but advanced by only 0.2 days in the later period (2000-2008). EOS was delayed by 4.3 days in the early period, and it was further delayed by another 2.3 days in the later period. The difference between SOS and EOS in the later period was due to less warming during the preseason (January-April) before SOS compared with the magnitude of warming in the preseason (June September) before EOS. At a regional scale, delayed EOS in later periods was shown. In North America, EOS was delayed by 8.1 days in the early period and delayed by another 1.3 days in the later period. In Europe, the delayed EOS by 8.2 days was more significant than the advanced SOS by 3.2 days in the later period. However, in East Asia, the overall increase in LOS during the early period was weakened in the later period. Admitting regional heterogeneity, changes in hemispheric features suggest that the longer-lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf-out. Keywords: climate change, growing season, NDVI (normalized difference vegetation index), Northern Hemisphere, phenology,

Pest damage assessment in fruits and vegetables using thermal imaging

NASA Astrophysics Data System (ADS)

Vadakkapattu Canthadai, Badrinath; Muthuraju, M. Esakki; Pachava, Vengalrao; Sengupta, Dipankar

2015-05-01

In some fruits and vegetables, it is difficult to visually identify the ones which are pest infested. This particular aspect is important for quarantine and commercial operations. In this article, we propose to present the results of a novel technique using thermal imaging camera to detect the nature and extent of pest damage in fruits and vegetables, besides indicating the level of maturity and often the presence of the pest. Our key idea relies on the fact that there is a difference in the heat capacity of normal and damaged ones and also observed the change in surface temperature over time that is slower in damaged ones. This paper presents the concept of non-destructive evaluation using thermal imaging technique for identifying pest damage levels of fruits and vegetables based on investigations carried out on random samples collected from a local market.

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Statistics of backscatter radar return from vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Chen, K. S.; Fung, A. K.

1992-01-01

The statistical characteristics of radar return from vegetation targets are investigated through a simulation study based upon the first-order scattered field. For simulation purposes, the vegetation targets are modeled as a layer of randomly oriented and spaced finite cylinders, needles, or discs, or a combination of them. The finite cylinder is used to represent a branch or a trunk, the needle for a stem or a coniferous leaf, and the disc for a decidous leaf. For a plane wave illuminating a vegetation canopy, simulation results show that the signal returned from a layer of disc- or needle-shaped leaves follows the Gamma distribution, and that the signal returned from a layer of branches resembles the log normal distribution. The Gamma distribution also represents the signal returned from a layer of a mixture of branches and leaves regardless of the leaf shapes. Results also indicate that the polarization state does not have a significant impact on signal distribution.

Biomass measurement from LANDSAT: Drought and energy applications

NASA Technical Reports Server (NTRS)

Maxwell, E. L.

1981-01-01

The theory supporting the use of vegetation indices derived from LANDSAT data for the direct measurement of biomass is reviewed. The use of multispectral data to measure biomass is a natural and viable application since the photosynthetic production of biomass gives vegetation its unique spectral properties. Vegetation indices also perform a normalization function which tends to make them insensitive to atmospheric and soil color variations. Optical and digital LANDSAT products are discussed relative to the use of vegetation indices to monitor drought impact. Based on results obtained in Colorado, operational use of LANDSAT to monitor drought is cost effective, practical and ready for implementation today. The direct measurement of biomass energy resources may also benefit from LANDSAT technology. Measurement of total biomass and annual primary production may be feasible. Identification of that component of biomass resources available for energy use will require other sources of information, however.

Trends in normalized difference vegetation index (NDVI) associated with urban development in northern West Siberia

NASA Astrophysics Data System (ADS)

Esau, Igor; Miles, Victoria V.; Davy, Richard; Miles, Martin W.; Kurchatova, Anna

2016-08-01

Exploration and exploitation of oil and gas reserves of northern West Siberia has promoted rapid industrialization and urban development in the region. This development leaves significant footprints on the sensitive northern environment, which is already stressed by the global warming. This study reports the region-wide changes in the vegetation cover as well as the corresponding changes in and around 28 selected urbanized areas. The study utilizes the normalized difference vegetation index (NDVI) from high-resolution (250 m) MODIS data acquired for summer months (June through August) over 15 years (2000-2014). The results reveal the increase of NDVI (or "greening") over the northern (tundra and tundra-forest) part of the region. Simultaneously, the southern, forested part shows the widespread decrease of NDVI (or "browning"). These region-wide patterns are, however, highly fragmented. The statistically significant NDVI trends occupy only a small fraction of the region. Urbanization destroys the vegetation cover within the developed areas and at about 5-10 km distance around them. The studied urbanized areas have the NDVI values by 15 to 45 % lower than the corresponding areas at 20-40 km distance. The largest NDVI reduction is typical for the newly developed areas, whereas the older areas show recovery of the vegetation cover. The study reveals a robust indication of the accelerated greening near the older urban areas. Many Siberian cities become greener even against the wider browning trends at their background. Literature discussion suggests that the observed urban greening could be associated not only with special tending of the within-city green areas but also with the urban heat islands and succession of more productive shrub and tree species growing on warmer sandy soils.

Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data

USGS Publications Warehouse

Jarchow, Christopher J.; Nagler, Pamela L.; Glenn, Edward P.

2017-01-01

In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P < 0.05) and a decrease from 2014 to 2015; however, 2015 levels were still significantly higher than in 2013. ETa was also higher in 2014 vs. 2013, with an estimated 74.5 million cubic meters in 2013 and 88.9 in 2014. The most intense greening occurred in the zone of inundation but also extended into the non-flooded part of the riparian zone, indicating replenishment of groundwater. These findings suggest the peak response by vegetation to the flow lasted about one year, followed by a decrease in NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.

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.

Climate-disease connections: Rift Valley Fever in Kenya

NASA Technical Reports Server (NTRS)

Anyamba, A.; Linthicum, K. J.; Tucker, C. J.

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Nino/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

Climate-disease connections: Rift Valley Fever in Kenya.

PubMed

Anyamba, A; Linthicum, K J; Tucker, C J

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Niño/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

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

NASA Astrophysics Data System (ADS)

White, Joseph D.; Swint, Pamela

2014-01-01

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

Analysis of smoke and cloud impact on seasonal and interannual variations in normalized difference vegetation index in Amazon

NASA Astrophysics Data System (ADS)

Kobayashi, H.; Dye, D. G.

2004-12-01

Normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) is a unique measurement of long-term variations in global vegetation dynamics. The NDVI data have been used for the detection of the seasonal and interannual variations in vegetation. However, as reported in several studies, NDVI decreases with the increase in clouds and/or smoke aerosol contaminated in the pixels. This study assesses the smoke and clouds effect on long-term Global Inventory Modeling and Mapping Studies (GIMMS) and Pathfinder AVHRR Land (PAL) NDVI data in Amazon. This knowledge will help developing the correction method in the tropics in the future. To assess the smoke and cloud effects on GIMMS and PAL, we used another satellite-derived data sets; NDVI derived from SPOT/VEGETATION (VGT) data and Aerosol Index (AI) derived from Total Ozone Mapping Spectrometer (TOMS). Since April 1998, VGT has measured the earth surface globally including in Amazon. The advantage of the VGT is that it has blue channel where the smoke and cloud can be easily detected. By analyzing the VGT NDVI and comparing with the AVHRR-based NDVI, we inferred smoke and cloud effect on the AVHRR-based NDVI. From the results of the VGT analysis, we found the large NDVI seasonality in South and Southeastern Amazon. In these areas, the NDVI gradually increased from April to July and decreased from August to October. However the sufficient NDVI data were not existed from August to November when the smoke and cloud pixels were masked using blue reflectance. Thus it is said that the smoke and clouds mainly cause the large decreases in NDVI between August and November and NDVI has little vegetation signature in these months. Also we examined the interannual variations in NDVI and smoke aerosol. Then the decrease in NDVI is well consistent with the increase in the increase in AI. Our results suggest that the months between April and July are the most reliable season to monitor the vegetation.

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

USGS Publications Warehouse

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

2014-01-01

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

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

Study on the Feasibility of RGB Substitute CIR for Automatic Removal Vegetation Occlusion Based on Ground Close-Range Building Images

NASA Astrophysics Data System (ADS)

Li, C.; Li, F.; Liu, Y.; Li, X.; Liu, P.; Xiao, B.

2012-07-01

Building 3D reconstruction based on ground remote sensing data (image, video and lidar) inevitably faces the problem that buildings are always occluded by vegetation, so how to automatically remove and repair vegetation occlusion is a very important preprocessing work for image understanding, compute vision and digital photogrammetry. In the traditional multispectral remote sensing which is achieved by aeronautics and space platforms, the Red and Near-infrared (NIR) bands, such as NDVI (Normalized Difference Vegetation Index), are useful to distinguish vegetation and clouds, amongst other targets. However, especially in the ground platform, CIR (Color Infra Red) is little utilized by compute vision and digital photogrammetry which usually only take true color RBG into account. Therefore whether CIR is necessary for vegetation segmentation or not has significance in that most of close-range cameras don't contain such NIR band. Moreover, the CIE L*a*b color space, which transform from RGB, seems not of much interest by photogrammetrists despite its powerfulness in image classification and analysis. So, CIE (L, a, b) feature and support vector machine (SVM) is suggested for vegetation segmentation to substitute for CIR. Finally, experimental results of visual effect and automation are given. The conclusion is that it's feasible to remove and segment vegetation occlusion without NIR band. This work should pave the way for texture reconstruction and repair for future 3D reconstruction.

Spatio-temporal Patterns of Vegetation and Its Relationship with Precipitation and Temperature in the Yarlung Zangbo River Basin, China

NASA Astrophysics Data System (ADS)

LIU, X.; Xu, Z.; Peng, D.

2017-12-01

Vegetation growth plays a significant role on runoff variation at high altitude, and precipitation and temperature are both key factors affecting vegetation conditions. As one of the greatest international rivers in China, the Yarlung Zangbo River in the southern Qinghai-Tibetan Plateau was selected, and the spatio-temporal patterns of vegetation were analyzed by using NDVI (Normalized Difference Vegetation Index) during 1998 2014. The relationship between NDVI and precipitation as well as temperature was also investigated in this study. Results showed that the value of NDVI increases with the decrease of elevation and the largest value appears in the broadleaf forest cover. Almost all annual NDVI variations exhibit an increasing tendency, particularly for the broadleaf forest cover. On the viewpoint of statistics, only 29% pixels of NDVI with increasing tendency are of significance for the other cover, while for cultivated vegetation cover, around 82% pixels of NDVI were detected with significant increasing tendency. In addition, vegetation growth showed lagging response to precipitation, and the lag time is around one month. Moreover, in the region with elevation over 5000 m, negative relationship between NDVI and precipitation for alpine vegetation was found. Approximately 75% of NDVI variations are dominated by precipitation and temperature. These findings may provide a reference to investigate runoff variations and strengthen ecological protection for similar high-altitude areas in the future.

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

PubMed

Sun, Jian; Qin, Xiaojing; Yang, Jun

2016-01-01

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