Science.gov

Sample records for adjusted vegetation index

  1. Suitability of the normalized difference vegetation index and the adjusted transformed soil-adjusted vegetation index for spatially characterizing loggerhead shrike habitats in North American mixed prairie

    NASA Astrophysics Data System (ADS)

    Shen, Li; He, Yuhong; Guo, Xulin

    2013-01-01

    Habitat loss has become one major cause of prairie loggerhead shrike population decline, which is associated with some important grassland biophysical features. However, our understanding of what and how biophysical variables can spatially characterize shrike habitats is poor. The purpose of this study is to investigate the suitability of two vegetation indices (VIs) for spatially characterizing shrike habitats in North American mixed prairies. Our research, conducted in Grasslands National Park of Canada, is based on the normalized difference vegetation index (NDVI) and the adjusted transformed soil-adjusted vegetation index (ATSAVI) as derived from both in situ measurements and SPOT imagery for three types of nesting categories at three spatial scales. Our results demonstrated that shrikes in mixed North American prairies prefer sparsely vegetated areas with a leaf area index less than 2.01 and shrub cover of around 25%. Our results also demonstrated that ATSAVI is superior to NDVI in estimating vegetation abundance and structure. Loggerhead shrikes seems to prefer habitats characterized by NDVI ranging from 0.562 to 0.616 and ATSAVI ranging from 0.319 to 0.372 with the spatial scale varying from 100 to 20 m. ATSAVI also had better performance in detecting the spatial variation of shrike habitats due to its higher sensitivity to background information.

  2. A novel moisture adjusted vegetation index (MAVI) to reduce background reflectance and topographical effects on LAI retrieval.

    PubMed

    Zhu, Gaolong; Ju, Weimin; Chen, J M; Liu, Yibo

    2014-01-01

    A new moisture adjusted vegetation index (MAVI) is proposed using the red, near infrared, and shortwave infrared (SWIR) reflectance in band-ratio form in this paper. The effectiveness of MAVI in retrieving leaf area index (LAI) is investigated using Landsat-5 data and field LAI measurements in two forest and two grassland areas. The ability of MAVI to retrieve forest LAI under different background conditions is further evaluated using canopy reflectance of Jack Pine and Black Spruce forests simulated by the 4-Scale model. Compared with several commonly used two-band vegetation index, such as normalized difference vegetation index, soil adjusted vegetation index, modified soil adjusted vegetation index, optimized soil adjusted vegetation index, MAVI is a better predictor of LAI, on average, which can explain 70% of variations of LAI in the four study areas. Similar to other SWIR-related three-band vegetation index, such as modified normalized difference vegetation index (MNDVI) and reduced simple ratio (RSR), MAVI is able to reduce the background reflectance effects on forest canopy LAI retrieval. MAVI is more suitable for retrieving LAI than RSR and MNDVI, because it avoids the difficulty in properly determining the maximum and minimum SWIR values required in RSR and MNDVI, which improves the robustness of MAVI in retrieving LAI of different land cover types. Moreover, MAVI is expressed as ratios between different spectral bands, greatly reducing the noise caused by topographical variations, which makes it more suitable for applications in mountainous area.

  3. Global Enhanced Vegetation Index

    NASA Technical Reports Server (NTRS)

    2002-01-01

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

  4. 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.

  5. Estimating the vegetation water content using a radar vegetation index

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation water content is an important biophysical parameter. Here, the Radar Vegetation Index (RVI) based on polarimetric backscatter observations was evaluated for estimating vegetation water content. Analysis utilized a data set obtained by a ground-based multi-frequency polarimetric scatterome...

  6. The vegetative index number and crop identification

    NASA Technical Reports Server (NTRS)

    Ashburn, P. (Principal Investigator)

    1979-01-01

    A vegetative index number of numerical value was calculated from the digital values of the LANDSAT system to provide some measure of green growing vegetation. The usefulness of the green numbers for schemes in crop identification and acreage estimation is investigated and the Ashburn vegetation index (AVI) is compared with the Kauth-Thomas vegetation index (KVI) for crop identification schemes. Results of wheat acreage estimation using LACIE Procedure 1 and the AVI for eight sample segments are given. Tables show comparisons between the AVI and the KVI as well as visual results of the AVI.

  7. The use of new index for surface roughness of vegetation

    NASA Astrophysics Data System (ADS)

    Konda, Asako; Yamamoto, Hirokazu; Kajiwara, Koji; Honda, Yoshiaki

    2005-01-01

    Propose of a new Vegetation Index is purposes. Ordinal vegetation Index can show intensity of vegetation on the ground. It can not show structure of vegetation surface or texture. Proposed vegetation index utilizes BRF property. It is generated from data from 2 orbit of satellite and be able to show structure of vegetation surface or texture. Principles of this index is coming from field observation using RC helicopter. Each vegetation canopy has different texture and roughness. New index, named BSI (Bi-directional reflectance Structure Index) shows difference of vegetation canopy. It is calculated by using the data of NOAA/AVHRR, ADEOS OCTS. ADEOS-II GLI can derive BSI.

  8. [MTCARI: A kind of vegetation index monitoring vegetation leaf chlorophyll content based on hyperspectral remote sensing].

    PubMed

    Meng, Qing-ye; Dong, Heng; Qin, Qi-ming; Wang, Jin-liang; Zhao, Jiang-hua

    2012-08-01

    The chlorophyll content of plant has relative correlation with photosynthetic capacity and growth levels of plant. It affects the plant canopy spectra, so the authors can use hyperspectral remote sensing to monitor chlorophyll content. By analyzing existing mature vegetation index model, the present research pointed out that the TCARI model has deficiencies, and then tried to improve the model. Then using the PROSPECT+SAIL model to simulate the canopy spectral under different levels of chlorophyll content and leaf area index (LAI), the related constant factor has been calculated. The research finally got modified transformed chlorophyll absorption ratio index (MTCARI). And then this research used optimized soil background adjust index (OSAVI) to improve the model. Using the measured data for test and verification, the model has good reliability.

  9. 10 CFR 765.12 - Inflation index adjustment procedures.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND THORIUM PROCESSING SITES Reimbursement Criteria § 765.12 Inflation index adjustment procedures. (a)...

  10. 10 CFR 765.12 - Inflation index adjustment procedures.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 4 2014-01-01 2014-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND THORIUM PROCESSING SITES Reimbursement Criteria § 765.12 Inflation index adjustment procedures. (a)...

  11. 10 CFR 765.12 - Inflation index adjustment procedures.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 4 2013-01-01 2013-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND THORIUM PROCESSING SITES Reimbursement Criteria § 765.12 Inflation index adjustment procedures. (a)...

  12. 10 CFR 765.12 - Inflation index adjustment procedures.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 4 2012-01-01 2012-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND THORIUM PROCESSING SITES Reimbursement Criteria § 765.12 Inflation index adjustment procedures. (a)...

  13. 10 CFR 765.12 - Inflation index adjustment procedures.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Inflation index adjustment procedures. 765.12 Section 765.12 Energy DEPARTMENT OF ENERGY REIMBURSEMENT FOR COSTS OF REMEDIAL ACTION AT ACTIVE URANIUM AND THORIUM PROCESSING SITES Reimbursement Criteria § 765.12 Inflation index adjustment procedures. (a)...

  14. A short note on calculating the adjusted SAR index

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A simple algebraic technique is presented for computing the adjusted SAR Index proposed by Suarez (1981). The statistical formula presented in this note facilitates the computation of the adjusted SAR without the use of either a look-up table, custom computer software or the need to compute exact a...

  15. 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 Central

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

    2007-01-01

    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 theoretically analyzed differences in the topographic effect on the EVI and the NDVI based on a non-Lambertian model and two airborne-based images acquired from a mountainous area covered by high-density Japanese cypress plantation were used as a case study. 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 should be removed in the reflectance data before the 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.

  16. [Soil moisture estimation model based on multiple vegetation index].

    PubMed

    Wu, Hai-long; Yu, Xin-xiao; Zhang, Zhen-ming; Zhang, Yan

    2014-06-01

    Estimating soil moisture conveniently and exactly is a hot issues in water resource monitoring among agriculture and forestry. Estimating soil moisture based on vegetation index has been recognized and applied widely. 8 vegetation indexes were figured out based on the hyper-spectral data measured by portable spectrometer. The higher correlation indexes among 8 vegetation indexes and surface vegetation temperature were selected by Gray Relative Analysis method (GRA). Then, these selected indexes were analyzed using Multiple Linear Regression to establish soil moisture estimation model based on multiple vegetation indexes, and the model accuracy was evaluated. The accuracy evaluation indicated that the fitting was satisfied and the significance was 0.000 (P < 0.001). High correlation was turned out between estimated and measured soil moisture with R2 reached 0.636 1 and RMSE 2.149 9. This method introduced multiple vegetation indexes into soil water content estimating over micro scale by non-contact measuring method using portable spectrometer. The exact estimation could be an appropriate replacement for remote sensing inversion and direct measurement. The model could estimate soil moisture quickly and accurately, and provide theory and technology reference for water resource management in agriculture and forestry.

  17. Psychometric properties of the index of relocation adjustment.

    PubMed

    Bekhet, Abir K; Zauszniewski, Jaclene A

    2014-06-01

    More and more American older adults are relocating to retirement communities, and they experience challenges in adjusting to new surroundings that may increase their depression and mortality. An instrument not previously tested in the United States, the Index of Relocation Adjustment (IRA), may help in early identification of poor relocation adjustment. This study examined the psychometric properties of the IRA using secondary data from a convenience sample of 104 older adults who relocated to 6 retirement communities in Northeast Ohio. Cronbach's alpha was .86. The IRA was correlated with measures of positive cognitions (r = .48, p < .01) and relocation controllability (r = -.62, p < .01), suggesting construct validity. Results indicated a single factor reflecting relocation adjustment with loadings for all items ranging from .62 to .83. The IRA is potentially useful as a screening measure for early detection of poor adjustment among relocated older adults.

  18. A MODIS-based vegetation index climatology

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. [Impact of moss soil crust on vegetation indexes interpretation].

    PubMed

    Fang, Shi-bo; Zhang, Xin-shi

    2011-03-01

    Vegetation indexes were the most common and the most important parameters to characterizing large-scale terrestrial ecosystems. It is vital to get precise vegetation indexes for running land surface process models and computation of NPP change, moisture and heat fluxes over surface. Biological soil crusts (BSC) are widely distributed in arid and semi-arid, polar and sub-polar regions. The spectral characteristics of dry and wet BSCs were quite different, which could produce much higher vegetation indexes value for the wet BSC than for the dry BSC as reported. But no research was reported about whether the BSC would impact on regional vegetation indexes and how much dry and wet BSC had impact on regional vegetation indexes. In the present paper, the most common vegetation index NDVI were used to analyze how the moss soil crusts (MSC) dry and wet changes affect regional NDVI values. It was showed that 100% coverage of the wet MSC have a much higher NDVI value (0.657) than the dry MSC NDVI value (0.320), with increased 0.337. Dry and wet MSC NDVI value reached significant difference between the levels of 0.000. In the study area, MSC, which had the average coverage of 12.25%, would have a great contribution to the composition of vegetation index. Linear mixed model was employed to analyze how the NDVI would change in regional scale as wet MSC become dry MSC inversion. The impact of wet moss crust than the dry moss crust in the study area can make the regional NDVI increasing by 0.04 (14.3%). Due to the MSC existence and rainfall variation in arid and semi-arid zones, it was bound to result in NDVI change instability in a short time in the region. For the wet MSC's spectral reflectance curve is similar to those of the higher plants, misinterpretation of the vegetation dynamics could be more severe due to the "maximum value composite" (MVC) technique used to compose the global vegetation maps in the study of vegetation dynamics. The researches would be useful for

  20. 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.

  1. Analysis of Vegetation Index Variations and the Asian Monsoon Climate

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  2. Spectral vegetation indexes and the remote sensing of biophysical parameters

    NASA Technical Reports Server (NTRS)

    Huemmrich, Karl F.; Goward, Samuel N.

    1992-01-01

    Combinations of remotely sensed data from different spectral bands have been combined into spectral vegetation indexes (SVIs) and used to determine biophysical parameters. The characteristics of two-band SVIs made up of visible and near-infrared reflectances are examined. Two canopy reflectance models, a turbid media model and a geometrical model, are used to study the effects of different canopy structures on the measurement of leaf area index and the fraction of photosynthetically intercepted active radiation.

  3. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  5. Normalized Difference Vegetation Index for Fanno Creek, Oregon

    USGS Publications Warehouse

    Sobieszczyk, Steven

    2011-01-01

    Fanno Creek is a tributary to the Tualatin River and flows though parts of the southwest Portland metropolitan area. The stream is heavily influenced by urban runoff and shows characteristic flashy streamflow and poor water quality commonly associated with urban streams. This data set represents the Normalized Difference Vegetation Index (NDVI), or "greenness" of the Fanno Creek floodplain study area. Aerial photography was used to isolate areas of vegetation based on comparing different bandwidths within the imagery. In this case, the NDVI is calculated as the quotient of the near infrared band minus the red band divided by the near infared plus the red band. NDVI = (NIR - R)/(NIR + R).

  6. 78 FR 8530 - Price Index Adjustments for Contribution and Expenditure Limitations and Lobbyist Bundling...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-06

    ... Price Index Adjustments for Contribution and Expenditure Limitations and Lobbyist Bundling Disclosure Threshold AGENCY: Federal Election Commission. ACTION: Notice of adjustments to contribution and expenditure...'' or ``the Commission'') is adjusting certain contribution and expenditure limitations and the...

  7. 76 FR 8368 - Price Index Adjustments for Contribution and Expenditure Limits and Lobbyist Bundling Disclosure...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-14

    ... Price Index Adjustments for Contribution and Expenditure Limits and Lobbyist Bundling Disclosure Threshold AGENCY: Federal Election Commission. ACTION: Notice of adjustments to contribution and expenditure...'' or ``the Commission'') is adjusting certain contribution and expenditure limits and the...

  8. 75 FR 8353 - Price Index Adjustments for Expenditure Limitations and Lobbyist Bundling Disclosure Threshold

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-24

    ... Price Index Adjustments for Expenditure Limitations and Lobbyist Bundling Disclosure Threshold AGENCY: Federal Election Commission. ACTION: Notice of adjustments to expenditure limitations and lobbyist... Commission'') is adjusting certain expenditure limitations and the lobbyist bundling disclosure threshold...

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

    PubMed

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

    2006-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  11. [Research on Accuracy and Stability of Inversing Vegetation Chlorophyll Content by Spectral Index Method].

    PubMed

    Jiang, Hai-ling; Yang, Hang; Chen, Xiao-ping; Wang, Shu-dong; Li, Xue-ke; Liu, Kai; Cen, Yi

    2015-04-01

    Spectral index method was widely applied to the inversion of crop chlorophyll content. In the present study, PSR3500 spectrometer and SPAD-502 chlorophyll fluorometer were used to acquire the spectrum and relative chlorophyll content (SPAD value) of winter wheat leaves on May 2nd 2013 when it was at the jointing stage of winter wheat. Then the measured spectra were resampled to simulate TM multispectral data and Hyperion hyperspectral data respectively, using the Gaussian spectral response function. We chose four typical spectral indices including normalized difference vegetation index (NDVD, triangle vegetation index (TVI), the ratio of modified transformed chlorophyll absorption ratio index (MCARI) to optimized soil adjusted vegetation index (OSAVI) (MCARI/OSAVI) and vegetation index based on universal pattern decomposition (VIUPD), which were constructed with the feature bands sensitive to the vegetation chlorophyll. After calculating these spectral indices based on the resampling TM and Hyperion data, the regression equation between spectral indices and chlorophyll content was established. For TM, the result indicates that VIUPD has the best correlation with chlorophyll (R2 = 0.819 7) followed by NDVI (R2 = 0.791 8), while MCARI/OSAVI and TVI also show a good correlation with R2 higher than 0.5. For the simulated Hyperion data, VIUPD again ranks first with R2 = 0.817 1, followed by MCARI/OSAVI (R2 = 0.658 6), while NDVI and TVI show very low values with R2 less than 0.2. It was demonstrated that VIUPD has the best accuracy and stability to estimate chlorophyll of winter wheat whether using simulated TM data or Hyperion data, which reaffirms that VIUPD is comparatively sensor independent. The chlorophyll estimation accuracy and stability of MCARI/OSAVI also works well, partly because OSAVI could reduce the influence of backgrounds. Two broadband spectral indices NDVI and TVI are weak for the chlorophyll estimation of simulated Hyperion data mainly because of

  12. Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model

    NASA Technical Reports Server (NTRS)

    Goward, Samuel N.; Huemmrich, Karl F.

    1992-01-01

    Relationships are studied between the normalized-difference vegetation index (NDVI) and absorbed photosynthetically active radiation (APAR) in a vegetation canopy. The SAIL model of bidirectional canopy radiative transfer is employed to compare NDVI measurements that are instantaneous with diurnally integrated canopy APAR capacity. The NDVI measurements - taken at solar-zenith angles of more than 60 deg and sensor views of less than 40 deg from nadir - give stable near-linear estimates of diurnal APAR capacity. Discrepancies in the relations between APAR and NDVI are associated with variations in the optical properties of the canopy and with background spectral reflectance. The results are significant for the practical use of these remote sensing techniques but suggest that instantaneous observations can be used to characterize the diurnally integrated APAR in vegetation canopies.

  13. Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

    USGS Publications Warehouse

    Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

    2013-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

  14. 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.

  15. Vegetation index correction to reduce background effects in orchards with high spatial resolution imagery

    NASA Astrophysics Data System (ADS)

    Van Beek, Jonathan; Tits, Laurent; Somers, Ben; Deckers, Tom; Janssens, Pieter; Coppin, Pol

    2014-10-01

    High spatial resolution satellite imagery provides an alternative for time consuming and labor intensive in situ measurements of biophysical variables, such as chlorophyll and water content. However, despite the high spatial resolution of current satellite sensors, mixtures of canopies and backgrounds will be present, hampering the estimation of biophysical variables. Traditional correction methodologies use spectral differences between canopies and backgrounds, but fail with spectrally similar canopies and backgrounds. In this study, the lack of a generic solution to reduce background effects is tackled. Through synthetic imagery, the mixture problem was demonstrated with regards to the estimation of biophysical variables. A correction method was proposed, rescaling vegetation indices based on the canopy cover fraction. Furthermore, the proposed method was compared to traditional background correction methodologies (i.e. soil-adjusted vegetation indices and signal unmixing) for different background scenarios. The results of a soil background scenario showed the inability of soil-adjusted vegetation indices to reduce background admixture effects, while signal unmixing and the proposed method removed background influences for chlorophyll (ΔR2 = ~0.3; ΔRMSE = ~1.6 μg/cm2) and water (ΔR2 = ~0.3; ΔRMSE = ~0.5 mg/cm2) related vegetation indices. For the weed background scenario, signal unmixing was unable to remove the background influences for chlorophyll content (ΔR2 = -0.1; ΔRMSE = -0.6 μg/cm 2 ), while the proposed correction method reduced background effects (ΔR2= 0.1; ΔRMSE = 0.4 μg/cm2). Overall, the proposed vegetation index correction method reduced the background influence irrespective of background type, making useful comparison between management blocks possible.

  16. Analysis of the dynamics of African vegetation using the normalized difference vegetation index

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

    Images at a resolution of 8 km are currently being generated for the whole of Africa, displaying the normalized difference vegetation index (NDVI). These images have undergone a process of temporal compositing to reduce the effects of cloud cover and atmospheric variation. When the NDVI is plotted against time, different cover types are shown to have characteristic profiles corresponding closely with their phenology. The resultant pattern of NDVI values displayed on the images is analyzed in terms of the cover types present and local variations in rainfall. Comparison between images for 1983 and 1984 overall showed considerable similarities, but significant differences were observed in the northward extent of the greening wave in the Sahel, the greening up of the Kalahari Desert and East African communities. It is concluded that vegetation monitoring using NDVI images needs to be associated with scene stratification according to cover type.

  17. Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher

  18. An efficient unsupervised index based approach for mapping urban vegetation from IKONOS imagery

    NASA Astrophysics Data System (ADS)

    Anchang, Julius Y.; Ananga, Erick O.; Pu, Ruiliang

    2016-08-01

    Despite the increased availability of high resolution satellite image data, their operational use for mapping urban land cover in Sub-Saharan Africa continues to be limited by lack of computational resources and technical expertise. As such, there is need for simple and efficient image classification techniques. Using Bamenda in North West Cameroon as a test case, we investigated two completely unsupervised pixel based approaches to extract tree/shrub (TS) and ground vegetation (GV) cover from an IKONOS derived soil adjusted vegetation index. These included: (1) a simple Jenks Natural Breaks classification and (2) a two-step technique that combined the Jenks algorithm with agglomerative hierarchical clustering. Both techniques were compared with each other and with a non-linear support vector machine (SVM) for classification performance. While overall classification accuracy was generally high for all techniques (>90%), One-Way Analysis of Variance tests revealed the two step technique to outperform the simple Jenks classification in terms of predicting the GV class. It also outperformed the SVM in predicting the TS class. We conclude that the unsupervised methods are technically as good and practically superior for efficient urban vegetation mapping in budget and technically constrained regions such as Sub-Saharan Africa.

  19. Predictability of leaf area index using vegetation indices from multiangular CHRIS/PROBA data over eastern China

    NASA Astrophysics Data System (ADS)

    Gu, Zhujun; Sanchez-Azofeifa, G. Arturo; Feng, Jilu; Cao, Sen

    2015-01-01

    This study analyzed the predictability of leaf area index (LAI) to the variation of vegetation type, observation angle, and vegetation index (VI). The analysis was conducted by using the R2 of the LAI-VI models between in situ measured LAIs and VIs derived from CHRIS/PROBA data. The results show that the discrepancy of vegetation type mostly influences the LAI-VI models. The predictability of LAI to the variation of both vegetation type and index demonstrates the differences of oblique/vertical and backward/forward observations, and backward series are greater than the forward. The predictabilities of LAI to the variation of observation angle are greatest for the soil-adjusted VIs and least for the traditional ratio-based indices. Multivariable linear modeling with all VIs from all five angles yields acceptable accuracy except for the sparse shrub. The backward less-oblique observation (-36 deg) is the only angle chosen in the modeling for grass, shrub, and broad leaf forest, while the nadir view performs best for forests with coniferous trees. These results provide a reference to multiangular LAI estimation for different vegetation communities. VIs accounting for angular soil effects require further investigation in the future.

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

    PubMed

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

    2011-02-01

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

  1. Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery

    NASA Technical Reports Server (NTRS)

    Huete, A. R.; Tucker, C. J.

    1991-01-01

    The effects of soil optical properties on vegetation index imagery are analyzed with ground-based spectral measurements and both simulated and actual AVHRR data from the NOAA satellites. Soil effects on vegetation indices were divided into primary variations associated with the brightness of bare soils, secondary variations attributed to 'color' differences among bare soils, and soil-vegetation spectral mixing. Primary variations were attributed to shifts in the soil line owing to atmosphere or soil composition. Secondary soil variance was responsible for the Saharan desert 'artefact' areas of increased vegetation index response in AVHRR imagery.

  2. Modulation Index Adjustment for Recovery of Pure Wavelength Modulation Spectroscopy Second Harmonic Signal Waveforms

    PubMed Central

    Wei, Wei; Chang, Jun; Wang, Qiang; Qin, Zengguang

    2017-01-01

    A new technique of modulation index adjustment for pure wavelength modulation spectroscopy second harmonic signal waveforms recovery is presented. As the modulation index is a key parameter in determining the exact form of the signals generated by the technique of wavelength modulation spectroscopy, the method of modulation index adjustment is applied to recover the second harmonic signal with wavelength modulation spectroscopy. By comparing the measured profile with the theoretical profile by calculation, the relationship between the modulation index and average quantities of the scanning wavelength can be obtained. Furthermore, when the relationship is applied in the experimental setup by point-by-point modulation index modification for gas detection, the results show good agreement with the theoretical profile and signal waveform distortion (such as the amplitude modulation effect caused by diode laser) can be suppressed. Besides, the method of modulation index adjustment can be used in many other aspects which involve profile improvement. In practical applications, when the amplitude modulation effect can be neglected and the stability of the detection system is limited by the sampling rate of analog-to-digital, modulation index adjustment can be used to improve detection into softer inflection points and solve the insufficient sampling problem. As a result, measurement stability is improved by 40%. PMID:28098842

  3. Adjusted Age-Adjusted Charlson Comorbidity Index Score as a Risk Measure of Perioperative Mortality before Cancer Surgery

    PubMed Central

    Chang, Chun-Ming; Yin, Wen-Yao; Wei, Chang-Kao; Wu, Chin-Chia; Su, Yu-Chieh; Yu, Chia-Hui; Lee, Ching-Chih

    2016-01-01

    Background Identification of patients at risk of death from cancer surgery should aid in preoperative preparation. The purpose of this study is to assess and adjust the age-adjusted Charlson comorbidity index (ACCI) to identify cancer patients with increased risk of perioperative mortality. Methods We identified 156,151 patients undergoing surgery for one of the ten common cancers between 2007 and 2011 in the Taiwan National Health Insurance Research Database. Half of the patients were randomly selected, and a multivariate logistic regression analysis was used to develop an adjusted-ACCI score for estimating the risk of 90-day mortality by variables from the original ACCI. The score was validated. The association between the score and perioperative mortality was analyzed. Results The adjusted-ACCI score yield a better discrimination on mortality after cancer surgery than the original ACCI score, with c-statics of 0.75 versus 0.71. Over 80 years of age, 70–80 years, and renal disease had the strongest impact on mortality, hazard ratios 8.40, 3.63, and 3.09 (P < 0.001), respectively. The overall 90-day mortality rates in the entire cohort varied from 0.9%, 2.9%, 7.0%, and 13.2% in four risk groups stratifying by the adjusted-ACCI score; the adjusted hazard ratio for score 4–7, 8–11, and ≥ 12 was 2.84, 6.07, and 11.17 (P < 0.001), respectively, in 90-day mortality compared to score 0–3. Conclusions The adjusted-ACCI score helps to identify patients with a higher risk of 90-day mortality after cancer surgery. It might be particularly helpful for preoperative evaluation of patients over 80 years of age. PMID:26848761

  4. 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.

  5. Comparisons of MODIS vegetation index products with biophysical and flux tower measurements

    NASA Astrophysics Data System (ADS)

    Sirikul, Natthanich

    Vegetation indices (VI) play an important role in studies of global climate and biogeochemical cycles, and are also positively related to many biophysical parameters and satellite products, such as leaf area index (LAI), gross primary production (GPP), land surface water index (LSWI) and land surface temperature (LST). In this study we found that VI's had strong relationships with some biophysical products, such as gross primary production, yet were less well correlated with biophysical structural parameters, such as leaf area index. The relationships between MODIS VI's and biophysical field measured LAI showed poor correlation at semi-arid land and broadleaf forest land cover type whereas cropland showed stronger correlations than the other vegetation types. In addition, the relationship between the enhanced vegetation index (EVI)-LAI and normalized difference vegetation index (NDVI)-LAI did not show significant differences. Comparisons of the relationships between the EVI and NDVI with tower-measured GPP from 11 flux towers in North America, showed that MODIS EVI had much stronger relationships with tower-GPP than did NDVI, and EVI was better correlated with the seasonal dynamics of GPP than was NDVI. In addition, there were no significant differences among the 1x1, 3x3 and 7x7 pixel sample sizes. The comparisons of VIs from the 3 MODIS products from which VI's are generated (Standard VI (MOD13)), Nadir Adjusted Surface Reflectance (NBAR (MOD43)), and Surface Reflectance (MOD09)), showed that MODIS NBAR-EVI (MOD43) was best correlated with GPP compared with the other VI products. In addition, the MODIS VI - tower GPP relationships were significantly improved using NBAR-EVI over the more complex canopy structures, such as the broadleaf and needleleaf forests. The relationship of tower-GPP with other MODIS products would be useful in more thorough characterization of some land cover types in which the VI's have encountered problems. The land surface temperature

  6. Assessment of regional biomass-soil relationships using vegetation indexes

    NASA Technical Reports Server (NTRS)

    Lozano-Garcia, D. Fabian; Fernandez, R. Norberto; Johannsen, Chris J.

    1991-01-01

    The development of photosynthetic active biomass in different ecological conditions, as indicated by normalized difference vegetation indices (NDVIs) is compared by performing a stratified sampling (based on soil assocations) on data acquired over Indiana. Data from the NOAA-10 AVHRR were collected for the 1987 and 1988 growing seasons. An NDVI transformation was performed using the two optical bands of the sensor (0.58-0.68 microns and 0.72-1.10 microns). The NDVI is related to the amount of active photosynthetic biomass present on the ground. Samples of NDVI values over 45 fields representing eight soil associations throughout Indiana were collected to assess the effect of soil conditions and acquisition date on the spectral response of the vegetation, as shown by the NDVIs. Statistical analysis of results indicate that land-cover types (forest, forest/pasture, and crops), soil texture, and soil water-holding capacity have an important effect on vegetation biomass changes as measured by AVHRR data. Acquisition dates should be selected with condideration of the phenological stages of vegetation. Sampling of AVHRR data over extended areas should be stratified according to physiographic units rather than man-made boundaries. This will provide more homogeneous samples for statistical analysis.

  7. Estimation of leaf area index using an angular vegetation index based on in situ measurements and CHRIS/PROBA data

    NASA Astrophysics Data System (ADS)

    Wang, Lijuan; Zhang, Guimin; Lin, Hui; Liang, Liang; Niu, Zheng

    2016-06-01

    The Normalized Difference Vegetation Index (NDVI) is widely used for Leaf Area Index (LAI) estimation. It is well documented that the NDVI is extremely subject to the saturation problem when LAI reaches a high value. A new multi-angular vegetation index, the Hotspot-darkspot Difference Vegetation Index (HDVI) is proposed to estimate the high density LAI. The HDVI, defined as the difference between the hot and dark spot NDVI, relative to the dark spot NDVI, was proposed based on the Analytical two-layer Canopy Reflectance Model (ACRM) model outputs. This index is validated using both in situ experimental data in wheat and data from the multi-angular optical Compact High-Resolution Imaging Spectrometer (CHRIS) satellite. Both indices, the Hotspot-Darkspot Index (HDS) and the NDVI were also selected to analyze the relationship with LAI, and were compared with new index HDVI. The results show that HDVI is an appropriate proxy of LAI with higher determination coefficients (R2) for both the data from the in situ experiment (R2=0.7342, RMSE=0.0205) and the CHRIS data (R2=0.7749, RMSE=0.1013). Our results demonstrate that HDVI can make better the occurrence of saturation limits with the information of multi-angular observation, and is more appropriate for estimating LAI than either HDS or NDVI at high LAI values. Although the new index needs further evaluation, it also has the potential under the condition of dense canopies. It provides the effective improvement to the NDVI and other vegetation indices that are based on the red and NIR spectral bands.

  8. Evaluating drought in the United States using the emissivity difference vegetation index

    NASA Astrophysics Data System (ADS)

    Hirani, Hanisha K.

    As monitoring vegetation and crops becomes increasingly important due to climate change, there arises the need for a monitoring scheme that places more weight on water availability as an indication of vegetation health and vitality. The Emissivity Difference Vegetation Index (EDVI) is the first step towards that type of monitoring scheme. With the potential for diurnal studies, there are applications towards agriculture monitoring, wildfire monitoring, and much more. EDVI is a synergetic product retrieved from microwave, visible, and infrared satellite measurements, as well as reanalysis. Since microwave measurements are more sensitive to vegetation water content, EDVI has the potential to capture intrinsic changes in vegetation. A new drought index is developed from EDVI, the Emissivity Vegetation Condition Index (EVCI). The high temporal sampling of EVCI will make it one of the more dynamic attempts to measure and investigate drought impacts on vegetation and crops on short-term scales. This new drought index will be compared to presently operational drought indices including the Palmer drought indices, the Vegetation Condition Index (VCI), and the Vegetation Health Index (VHI) for the period between 2009-2011 in the United States. The focus will be on improving the methodology of the EDVI retrieval and then examining two periods of identified drought, one in the Southern Great Plains in 2011, and one short-term drought in the Great Lakes region in 2010. The results indicate an agreement between ECVI and precipitation, and the drought episodes in 2010 and 2011 are resolved by EVCI. With a dataset beyond the three years used for this study it would be possible to correct more accurately for climatology.

  9. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    NASA Astrophysics Data System (ADS)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  10. What's Happened to the Price of College? Quality-Adjusted Net Price Indexes for Four Year Colleges

    ERIC Educational Resources Information Center

    Schwartz, Amy Ellen; Scafidi, Benjamin

    2004-01-01

    Hedonic models of the price of college to construct quality-adjusted net price indexes for U.S. four-year colleges were estimated. A 22 percent decline in the estimated price index is reported by adjusting for financial aid, while quality adjusting results lead to a smaller decline, for academic years 1990-91 to 1994-95.

  11. Vegetation Phenology and Vegetation Index Products from Multiple Long Term Satellite Data Records

    NASA Astrophysics Data System (ADS)

    Didan, K.; van Leeuwen, W.; Miura, T.; Friedl, M.; Zhang, X.; Czapla-Myers, J.; Jenkerson, C. B.; Maiersperger, T. K.

    2008-12-01

    Phenology is the expression of the seasonal cycle of all biotic processes. It is the pulse of our planet, and is an essential and critical component of environmental science influencing biodiversity, species interactions, their ecological functioning, and their effects on fluxes of water, energy, and biogeochemical elements at various scales. Changes in phenology depict an integrated response to environmental change and provide valuable information for global change research, land degradation studies, integrated pest and invasive species management, drought monitoring, wildfire risk assessment, and agricultural production. In this NASA Making Earth System data records for Use in Research Environments (NASA-MEaSUREs) project our multi-institution team of investigators plans to generate a seamless and consistent sensor independent Earth System Data Record and Climate Data Record (ESDR/CDR) quality measures of landscape phenology and vegetation index (VI), by fusing measurements from different satellite missions and sensors. We plan to use the AVHRR, MODIS and VIIRS daily surface reflectance products and design sensor independent algorithms that can be applied to these multi-sensor data sets. Our project aims at generating, documenting, and delivering 30+ years of consistent and well characterized ESDR/CDR quality daily measurements of land surface VI and annual phenology parameters at a climate modeling grid resolution (CMG, 0.05 deg). In collaboration with the newly established USA national phenology network (USA-NPN), we plan to correlate these remote sensing based measurements of phenology and VI with ground observations. We aim at evaluating the consistency and accuracy of these products by comparing them with in situ growing season phenology observations over different biomes, latitudinal and elevational gradients. We plan to distribute these products through the USGS EROS center and support them via a web based interactive visualization system. We will enlist

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  13. 5 CFR 591.224 - How does OPM adjust price indexes between surveys?

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false How does OPM adjust price indexes between surveys? 591.224 Section 591.224 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas...

  14. 5 CFR 591.224 - How does OPM adjust price indexes between surveys?

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false How does OPM adjust price indexes between surveys? 591.224 Section 591.224 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas...

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

    USGS Publications Warehouse

    Stow, D.; Daeschner, S.; Hope, A.; Douglas, D.; Petersen, A.; Myneni, R.; 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  17. The oslo health study: a dietary index estimating frequent intake of soft drinks and rare intake of fruit and vegetables is negatively associated with bone mineral density.

    PubMed

    Høstmark, Arne Torbjørn; Søgaard, Anne Johanne; Alvær, Kari; Meyer, Haakon E

    2011-01-01

    Background. Since nutritional factors may affect bone mineral density (BMD), we have investigated whether BMD is associated with an index estimating the intake of soft drinks, fruits, and vegetables. Methods. BMD was measured in distal forearm in a subsample of the population-based Oslo Health Study. 2126 subjects had both valid BMD measurements and answered all the questions required for calculating a Dietary Index = the sum of intake estimates of colas and non-cola beverages divided by the sum of intake estimates of fruits and vegetables. We did linear regression analyses to study whether the Dietary Index and the single food items included in the index were associated with BMD. Results. There was a consistent negative association between the Dietary Index and forearm BMD. Among the single index components, colas and non-cola soft drinks were negatively associated with BMD. The negative association between the Dietary Index and BMD prevailed after adjusting for gender, age, and body mass index, length of education, smoking, alcohol intake, and physical activity. Conclusion. An index reflecting frequent intake of soft drinks and rare intake of fruit and vegetables was inversely related to distal forearm bone mineral density.

  18. The Oslo Health Study: A Dietary Index Estimating Frequent Intake of Soft Drinks and Rare Intake of Fruit and Vegetables Is Negatively Associated with Bone Mineral Density

    PubMed Central

    Høstmark, Arne Torbjørn; Søgaard, Anne Johanne; Alvær, Kari; Meyer, Haakon E.

    2011-01-01

    Background. Since nutritional factors may affect bone mineral density (BMD), we have investigated whether BMD is associated with an index estimating the intake of soft drinks, fruits, and vegetables. Methods. BMD was measured in distal forearm in a subsample of the population-based Oslo Health Study. 2126 subjects had both valid BMD measurements and answered all the questions required for calculating a Dietary Index = the sum of intake estimates of colas and non-cola beverages divided by the sum of intake estimates of fruits and vegetables. We did linear regression analyses to study whether the Dietary Index and the single food items included in the index were associated with BMD. Results. There was a consistent negative association between the Dietary Index and forearm BMD. Among the single index components, colas and non-cola soft drinks were negatively associated with BMD. The negative association between the Dietary Index and BMD prevailed after adjusting for gender, age, and body mass index, length of education, smoking, alcohol intake, and physical activity. Conclusion. An index reflecting frequent intake of soft drinks and rare intake of fruit and vegetables was inversely related to distal forearm bone mineral density. PMID:21772969

  19. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data

    USGS Publications Warehouse

    Gallo, K.; Ji, L.; Reed, B.; Eidenshink, J.; Dwyer, J.

    2005-01-01

    The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 and NOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. ?? 2005 Elsevier Inc. All rights reserved.

  20. Consistency of vegetation index seasonality across the Amazon rainforest

    NASA Astrophysics Data System (ADS)

    Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jérôme; Mõttus, Matti; Aragão, Luiz E. O. C.; Shimabukuro, Yosio

    2016-10-01

    Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

    The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in Landsat MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS5 and MSS6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation. Previously announced in STAR as N83-14567

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  3. Implied adjusted volatility functions: Empirical evidence from Australian index option market

    NASA Astrophysics Data System (ADS)

    Harun, Hanani Farhah; Hafizah, Mimi

    2015-02-01

    This study aims to investigate the implied adjusted volatility functions using the different Leland option pricing models and to assess whether the use of the specified implied adjusted volatility function can lead to an improvement in option valuation accuracy. The implied adjusted volatility is investigated in the context of Standard and Poor/Australian Stock Exchange (S&P/ASX) 200 index options over the course of 2001-2010, which covers the global financial crisis in the mid-2007 until the end of 2008. Both in- and out-of-sample resulted in approximately similar pricing error along the different Leland models. Results indicate that symmetric and asymmetric models of both moneyness ratio and logarithmic transformation of moneyness provide the overall best result in both during and post-crisis periods. We find that in the different period of interval (pre-, during and post-crisis) is subject to a different implied adjusted volatility function which best explains the index options. Hence, it is tremendously important to identify the intervals beforehand in investigating the implied adjusted volatility function.

  4. Growing Degree Vegetation Production Index (GDVPI): A Novel and Data-Driven Approach to Delimit Season Cycles

    NASA Astrophysics Data System (ADS)

    Graham, W. D.; Spruce, J.; Ross, K. W.; Gasser, J.; Grulke, N.

    2014-12-01

    Growing Degree Vegetation Production Index (GDVPI) is a parametric approach to delimiting vegetation seasonal growth and decline cycles using incremental growing degree days (GDD), and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 8-day composite cumulative integral data. We obtain a specific location's daily minimum and maximum temperatures from the nearest National Oceanic and Atmospheric Administration (NOAA) weather stations posted on the National Climate Data Center (NCDC) Climate Data Online (CDO) archive and compute GDD. The date range for this study is January 1, 2000 through December 31, 2012. We employ a novel process, a repeating logistic product (RLP), to compensate for short-term weather variability and data drops from the recording stations and fit a curve to the median daily GDD values, adjusting for asymmetry, amplitude, and phase shift that minimize the sum of squared errors when comparing the observed and predicted GDD. The resulting curve, here referred to as the surrogate GDD, is the time-temperature phasing parameter used to convert Cartesian NDVI values into polar coordinate pairs, multiplying the NDVI values as the radial by the cosine and sine of the surrogate GDD as the angular. Depending on the vegetation type and the original NDVI curve, the polar NDVI curve may be nearly circular, kidney-shaped, or pear-shaped in the case of conifers, deciduous, or agriculture, respectively. We examine the points of tangency about the polar coordinate NDVI curve, identifying values of 1, 0, -1, or infinity, as each of these represent natural inflection points. Lines connecting the origin to each tangent point illustrate and quantify the parametrically segmentation of the growing season based on the GDD and NDVI ostensible dependency. Furthermore, the area contained by each segment represents the apparent vegetation production. A particular benefit is that the inflection points are determined

  5. Use of a wetland index to evaluate changes in riparian vegetation after livestock exclusion

    USGS Publications Warehouse

    Coles-Ritchie, M. C.; Roberts, D.W.; Kershner, J.L.; Henderson, R.C.

    2007-01-01

    A method was developed to characterize ecological integrity of riparian sites based on the abundance of hydric species. This wetland index can be calculated with species data, or with community type data as performed here. Classified riparian community types were used to describe vegetation at 14 livestock exclosures and adjacent grazed areas. Community type wetland index values were generated and used to calculate site wetland index values. It was hypothesized that removal of livestock would result in higher wetland index values because of release from herbivory and decreased physical disturbance of vegetation, streambanks, and soil. The wetland index for exclosures was about 12% higher than grazed sites; differences were statistically significant (p < 0.01) based on paired t-tests. The increase in hydric vegetation after livestock exclusion may have contributed to the greater bank stability (p = 0.002) and smaller width-to-depth ratio (p = 0.005) in exclosures. Challenges were encountered in using community types to describe and compare site vegetation, which could be avoided with species data collection. The wetland index can be a tool to monitor sites over time, compare sites with similar environments, or compare sites for which environmental differences can be accounted.

  6. Statistical analysis of land surface temperature-vegetation indexes relationship through thermal remote sensing.

    PubMed

    Kumar, Deepak; Shekhar, Sulochana

    2015-11-01

    Vegetation coverage has a significant influence on the land surface temperature (LST) distribution. In the field of urban heat islands (UHIs) based on remote sensing, vegetation indexes are widely used to estimate the LST-vegetation relationship. This paper devises two objectives. The first analyzes the correlation between vegetation parameters/indicators and LST. The subsequent computes the occurrence of vegetation parameter, which defines the distribution of LST (for quantitative analysis of urban heat island) in Kalaburagi (formerly Gulbarga) City. However, estimation work has been done on the valuation of the relationship between different vegetation indexes and LST. In addition to the correlation between LST and the normalized difference vegetation index (NDVI), the normalized difference build-up index (NDBI) is attempted to explore the impacts of the green land to the build-up land on the urban heat island by calculating the evaluation index of sub-urban areas. The results indicated that the effect of urban heat island in Kalaburagi city is mainly located in the sub-urban areas or Rurban area especially in the South-Eastern and North-Western part of the city. The correlation between LST and NDVI, indicates the negative correlation. The NDVI suggests that the green land can weaken the effect on urban heat island, while we perceived the positive correlation between LST and NDBI, which infers that the built-up land can strengthen the effect of urban heat island in our case study. Although satellite data (e.g., Landsat TM thermal bands data) has been applied to test the distribution of urban heat islands, but the method still needs to be refined with in situ measurements of LST in future studies.

  7. Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

    NASA Astrophysics Data System (ADS)

    Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

    2013-04-01

    Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the

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

    USGS Publications Warehouse

    Gara, Brian D; Stapanian, Martin A.

    2015-01-01

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

  9. Vegetation index methods for estimating evapotranspiration by remote sensing

    USGS Publications Warehouse

    Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.

    2010-01-01

    Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45–0.95, and root mean square errors are in the range of 10–30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates.

  10. The use of a satellite derived vegetation index for assessment of the urban heat island effect

    NASA Technical Reports Server (NTRS)

    Gallo, Kevin P.; Tarpley, J. D.; Mcnab, Alan L.; Karl, Thomas R.; Brown, Jesslyn F.

    1993-01-01

    Satellite derived normalized difference (ND) vegetation index data, based on urban and rural region composed of a variety of land surface environments, are evaluated. These data are linearly related to the difference in observed urban and rural minimum temperatures. It is concluded that the difference in the ND index between urban and rural regions reflects the difference in the surface properties (evaporation and heat storage capacity) of these two environments and urban and rural minimum temperatures (the urban heat island effect).

  11. Quantifying Vegetation Change in Semiarid Environments: Precision and Accuracy of Spectral Mixture Analysis and the Normalized Difference Vegetation Index

    NASA Technical Reports Server (NTRS)

    Elmore, Andrew J.; Mustard, John F.; Manning, Sara J.; Elome, Andrew J.

    2000-01-01

    Because in situ techniques for determining vegetation abundance in semiarid regions are labor intensive, they usually are not feasible for regional analyses. Remotely sensed data provide the large spatial scale necessary, but their precision and accuracy in determining vegetation abundance and its change through time have not been quantitatively determined. In this paper, the precision and accuracy of two techniques, Spectral Mixture Analysis (SMA) and Normalized Difference Vegetation Index (NDVI) applied to Landsat TM data, are assessed quantitatively using high-precision in situ data. In Owens Valley, California we have 6 years of continuous field data (1991-1996) for 33 sites acquired concurrently with six cloudless Landsat TM images. The multitemporal remotely sensed data were coregistered to within 1 pixel, radiometrically intercalibrated using temporally invariante surface features and geolocated to within 30 m. These procedures facilitated the accurate location of field-monitoring sites within the remotely sensed data. Formal uncertainties in the registration, radiometric alignment, and modeling were determined. Results show that SMA absolute percent live cover (%LC) estimates are accurate to within ?4.0%LC and estimates of change in live cover have a precision of +/-3.8%LC. Furthermore, even when applied to areas of low vegetation cover, the SMA approach correctly determined the sense of clump, (i.e., positive or negative) in 87% of the samples. SMA results are superior to NDVI, which, although correlated with live cover, is not a quantitative measure and showed the correct sense of change in only 67%, of the samples.

  12. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  14. Nanomaterials for the cleaning and pH adjustment of vegetable-tanned leather

    NASA Astrophysics Data System (ADS)

    Baglioni, Michele; Bartoletti, Angelica; Bozec, Laurent; Chelazzi, David; Giorgi, Rodorico; Odlyha, Marianne; Pianorsi, Diletta; Poggi, Giovanna; Baglioni, Piero

    2016-02-01

    Leather artifacts in historical collections and archives are often contaminated by physical changes such as soiling, which alter their appearance and readability, and by chemical changes which occur on aging and give rise to excessive proportion of acids that promote hydrolysis of collagen, eventually leading to gelatinization and loss of mechanical properties. However, both cleaning and pH adjustment of vegetable-tanned leather pose a great challenge for conservators, owing to the sensitivity of these materials to the action of solvents, especially water-based formulations and alkaline chemicals. In this study, the cleaning of historical leather samples was optimized by confining an oil-in-water nanostructured fluid in a highly retentive chemical hydrogel, which allows the controlled release of the cleaning fluid on sensitive surfaces. The chemical gel exhibits optimal viscoelasticity, which facilitates its removal after the application without leaving residues on the object. Nanoparticles of calcium hydroxide and lactate, dispersed in 2-propanol, were used to adjust the pH up to the natural value of leather, preventing too high alkalinity which causes swelling of fibers and denaturation of the collagen. The treated samples were characterized using scanning electron microscopy, controlled environment dynamic mechanical analysis, and infrared spectroscopy. The analytical assessment validated the use of tools derived from colloid and materials science for the preservation of collagen-based artifacts.

  15. 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.

  16. The use of a vegetation index for assessment of the urban heat island effect

    NASA Technical Reports Server (NTRS)

    Gallo, K. P.; Mcnab, A. L.; Karl, T. R.; Brown, J. F.; Hood, J. J.; Tarpley, J. D.

    1993-01-01

    A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

  17. Design and Application of a Normal Difference Vegetation Index Portable Sensing Device

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High-precision and low-cost electronic diagnostic devices are needed for monitoring crop nitrogen status and variable rate fertilization. One normalized difference vegetation index portable sensing device was designed in this study based on the peak red wavelength of 650 nm and the peak near-infrare...

  18. Cloud-Vegetation Interaction: Use of Normalized Difference Cloud Index for Estimation of Cloud Optical Thickness

    NASA Technical Reports Server (NTRS)

    Marshak, A.; Knyazikhint, Y.; Davis, A.; Wiscombe, W.; Pilewskie, P.

    1999-01-01

    A new technique to retrieve cloud optical depth for broken clouds above green vegetation using ground-based zenith radiance measurements is developed. By analogy with the Normalized Difference Vegetation Index NDVI), the Normalized Difference Cloud Index (NDCI) is defined as a ratio between the difference and the sum of two zenith radiances measured for two narrow spectral bands in the visible and near-IR regions. The very different spectral behavior of cloud liquid water drops and green vegetation is the key physics behind the NDCI. It provides extra tools to remove the radiative effects of the 3D cloud structure. Numerical calculations based on fractal clouds and real measurements of NDCI and cloud liquid water path confirm the improvements.

  19. Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbance

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    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.

  20. 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

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

    NASA Astrophysics Data System (ADS)

    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

  2. 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

  3. [Construction of vegetation shadow index (SVI) and application effects in four remote sensing images].

    PubMed

    Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Liu, Tao; Gong, Cong-Hong; Tang, Meng-Ya; Xie, Wan-Jun; Li, Zeng-Lu

    2013-12-01

    Taking the images of Landsat TM, ALOS AVNIR-2, CBERS-02B CCD and HJ-1 CCD as the experimental data, for increasing the differences among shaded area, bright area and water further, the present paper construed a novel vegetation index-Shaded Vegetation Index(SVI), which can not only keep the absolute differences among bright area, shaded area and water area in the near-infrared band, but also can enlarge NDVI, eliminate the possible mixes, and change the histogram "skewed" phenomenon of NDVI, so the vegetation index value is closer to normal distribution, and more in line with the filed condition; this new index was applied to the surface features of large difference of the near-infrared radiation characteristics. Verified by accuracy assessment for the bright area, shaded area and water area recognition effects with SVI, it was showed that the overall classification accuracies of these images were up to 98. 89%, 100%, 97.78% and 97.78% respectively, with the overall Kappa statistics of 0.9833, 1, 0.9667, and 0.966 7, indicating that SVI has excellent detection effects for bright area, shaded area and water area; the statistical comparison of sub-images between SVI and NDVI also illustrated the reliability and effectiveness of SVI, which can be applied in the shadow removal for remote sensing images.

  4. Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data.

    PubMed

    Patel, N R; Parida, B R; Venus, V; Saha, S K; Dadhwal, V K

    2012-12-01

    The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from MODIS 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Pradhan, N. R.

    2015-12-01

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

  7. [The study of LAI estimation using a new vegetation index based on CHRIS data].

    PubMed

    Wang, Li-Juan; Niu, Zheng; Hou, Xue-Hui; Gao, Shuai

    2013-04-01

    Leaf area index (LAI) is an important structural parameter of vegetation canopy, the correct estimation of which has been the focus in the remote sensing community. As a kind of hyperspectral and multi-angle remote sensing data with higher resolution (17 m), PROBA/CHRIS has significant application value in LAI inversion. In the present paper, the analytical two-layer canopy reflectance model (ACRM) was used to simulate a series of reflectances with different LAI values. Based on this, a new vegetation index was built and successfully applied to LAI inversion of PROBA/CHRIS image data. Our results indicated that: compared with the spectral index NDVI and multi-angle index HDS, the new index could make better use of spectrum and multi-angle messages and have a better correlation with LAI of the study area; moreover, the correlation coefficient R2 reached up to 0.734 7. And in order to obtain the figure of LAI distribution of the study area, we used the optimal fit equation between LAI and HDVI to estimate LAI, and the accuracy of the RMSE was 0.619 8.

  8. Social Security cost-of-living adjustments and the Consumer Price Index.

    PubMed

    Burdick, Clark; Fisher, Lynn

    2007-01-01

    OASDI benefits are indexed for inflation to protect beneficiaries from the loss of purchasing power implied by inflation. In the absence of such indexing, the purchasing power of Social Security benefits would be eroded as rising prices raise the cost of living. By statute, cost-of-living adjustments (COLAs) for Social Security benefits are calculated using the Bureau of Labor Statistics (BLS) Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Some argue that this index does not accurately reflect the inflation experienced by the elderly population and should be changed to an elderly-specific price index such as the Experimental Consumer Price Index for Americans 62 Years of Age and Older, often referred to as the Consumer Price Index for the Elderly (CPI-E). Others argue that the measure of inflation underlying the COLA is technically biased, causing it to overestimate changes in the cost of living. This argument implies that current COLAs tend to increase, rather than merely maintain, the purchasing power of benefits over time. Potential bias in the CPI as a cost-of-living index arises from a number of sources, including incomplete accounting for the ability of consumers to substitute goods or change purchasing outlets in response to relative price changes. The BLS has constructed a new index called the Chained Consumer Price Index for All Urban Consumers (C-CPI-U) that better accounts for those consumer adjustments. Price indexes are not true cost-of-living indexes, but approximations of cost-of-living indexes (COLI). The Bureau of Labor Statistics (2006a) explains the difference between the two: As it pertains to the CPI, the COLI for the current month is based on the answer to the following question: "What is the cost, at this month ' market prices, of achieving the standard of living actually attained in the base period?" This cost is a hypothetical expenditure-the lowest expenditure level necessary at this month's prices to achieve the

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  10. Comparison of the prevalence index and average wetland values for identification of wetland vegetation

    SciTech Connect

    Zimmerman, R.E.; Shem, L.M.; Gowdy, M.J.; Van Dyke, G.D.; Hackney, C.T.

    1992-07-01

    Prevalence index values (FICWD, 1989) and average wetland values for all species present were compared for three wetland gas pipeline rights-of-way (ROWS) and adjacent natural areas. The similarities in results using these two indicator values suggest that an average wetland value may offer a simpler, less time-consuming method of evaluating the vegetation of a study site as an indication of wetness. Both PIVs and AWVs, are presented for the ROWs and the adjacent natural area at each site.

  11. Comparison of the prevalence index and average wetland values for identification of wetland vegetation

    SciTech Connect

    Zimmerman, R.E.; Shem, L.M.; Gowdy, M.J. ); Van Dyke, G.D. ); Hackney, C.T. )

    1992-01-01

    Prevalence index values (FICWD, 1989) and average wetland values for all species present were compared for three wetland gas pipeline rights-of-way (ROWS) and adjacent natural areas. The similarities in results using these two indicator values suggest that an average wetland value may offer a simpler, less time-consuming method of evaluating the vegetation of a study site as an indication of wetness. Both PIVs and AWVs, are presented for the ROWs and the adjacent natural area at each site.

  12. 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.

  13. Development and characterization of adjustable refractive index scattering epoxy acrylate polymer layers

    NASA Astrophysics Data System (ADS)

    Eiselt, Thomas; Preinfalk, Jan; Gleißner, Uwe; Lemmer, Uli; Hanemann, Thomas

    2016-09-01

    This work presents different polymer diffusing films for optical components. In optical applications it is sometimes important to have a film with an adjusted refractive index, scattering properties and a low surface roughness. These diffusing films can be used to increase the efficiency of optical components like organic light emitting diodes (OLEDs). In this study three different epoxy acrylate mixtures containing Syntholux 291 EA, bisphenol a glycerolate dimethacrylate, Sartomer SR 348 L are characterized and optimized with different additives. The adjustable refractive index of the material is achieved with a chemical doping by 9-vinylcarbazole. Titanium nanoparticles in the mixtures generate light scattering and increase the refractive index additionally. To prevent sedimentation and agglomeration of these nanoparticles, a stabilization agent [2-(2-methoxyethoxy)ethoxy]acetic acid is added to the mixture. Other ingredients are a UV-starter and thermal starter for the radical polymerization. A high power stirrer (ultraturrax) is used to mix and disperse all chemical substances together to a homogenous mixture. The viscosity behavior of the mixtures is an important property for the selection of the production method and gets characterized. After the mixing, the monomer mixture is applied on glass substrates by blade coating or screen printing. To initiate the chain growing (polymerization) the produced films are irradiated for 10 minutes long with UV light (UV LED Spot Hönle, 405 nm). After this step a final post bake from the layers in the oven (150°C, 30 min.) is operated. Light transmission measurements (UV-Vis) of the polymer matrix and roughness measurements complement the characterization.

  14. Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.; Slayback, D. A.; Pinzon, J. E.; Los, S. O.; Myneni, R. B.; Taylor, M. G.

    2001-01-01

    Normalized difference vegetation index data from the polar-orbiting National Oceanic and Atmospheric Administration meteorological satellites from 1982 to 1999 show significant variations in photosynthetic activity and growing season length at latitudes above 35 degrees N. Two distinct periods of increasing plant growth are apparent: 1982-1991 and 1992-1999, separated by a reduction from 1991 to 1992 associated with global cooling resulting from the volcanic eruption of Mt. Pinatubo in June 1991. The average May to September normalized difference vegetation index from 45 degrees N to 75 degrees N increased by 9% from 1982 to 1991, decreased by 5% from 1991 to 1992, and increased by 8% from 1992 to 1999. Variations in the normalized difference vegetation index were associated with variations in the start of the growing season of -5.6, +3.9, and -1.7 days respectively, for the three time periods. Our results support surface temperature increases within the same period at higher northern latitudes where temperature limits plant growth.

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

    PubMed Central

    Fu, Gang; Shen, Zhen Xi

    2016-01-01

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

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

    PubMed

    Fu, Gang; Shen, Zhen Xi

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  18. 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.

  19. [Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

    PubMed

    Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

    2014-11-01

    Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

  20. Aerial image mosaics built using images with vegetation index pre-calculated

    NASA Astrophysics Data System (ADS)

    Rosendo Candido, Leandro; de Castro Jorge, Lúcio André; Luppe, Maximiliam

    2016-10-01

    Precision agriculture (PA) has offered a multitude of benefits to farmers, such as cost reduction, accuracy and speed in decision making. Among the tools that work with PA, the aerial image mosaics have key role in accurate mapping of diseases and pests in crops. A mosaic is the combination of multiple images, creating a new image that covers the property or plots accurately. One of the important analysis for farmers is based on the properties of the reflectance in each range of the electromagnetic spectrum of vegetation. Performing mathematical combinations of the different spectral bands has a better understanding of the spectral response of the vegetation. These combinations are called vegetation index (VI) and are useful for the control of the biomass, water content in leaf, chlorophyll content and others. It is usually calculated VI after the construction of the mosaic, as well the farmer has an accurate analysis of its vegetation. However, building a mosaic of images, it has a high computational cost, taking hours to complete and then apply the VI and to have the first test results. In order to reduce the computational cost of this process, this work aims to present a mosaic of images constructed from images with the VI already pre-calculated providing faster analysis to the farmer, given the fact that applying VI on the image came a this reduction in density image and thus have the gain in computational cost to build the mosaic.

  1. [Estimating canopy water content in wheat based on new vegetation water index].

    PubMed

    Cheng, Xiao-juan; Yang, Gui-jun; Xu, Xin-gang; Chen, Tian-en; Li, Zhen-hai; Feng, Hai-kuan; Wang, Dong

    2014-12-01

    Moisture content is an important indicator for crop water stress condition, timely and effective monitoring crop water content is of great significance for evaluate crop water deficit balance and guide agriculture irrigation. In order to improve the saturated problems of different forms of typical NDWI (Normalized Different Water Index), we tried to introduce EVI (Enhanced Vegetation Index) to build new vegetation water indices (NDWI#) to estimate crop water content. Firstly, PROSAIL model was used to study the saturation sensitivity of NDWI, and NDWI# to canopy water content and LAI (Leaf Area Index). Then, the estimated model and verified model were estimated using the spectral data and moisture data in the field. The result showed that the new indices have significant relationships with canopy water content. In particular, by implementing modified standardized for NDWI1450, NDWI1940, NDWI2500. The result indicated that newly developed indices with visible-infrared and shortwave infrared spectral feature may have greater advantage for estimation winter canopy water content.

  2. Estimation of vegetation parameters such as Leaf Area Index from polarimetric SAR data

    NASA Astrophysics Data System (ADS)

    Hetz, Marina; Blumberg, Dan G.; Rotman, Stanley R.

    2010-05-01

    This work presents the analysis of the capability to use the radar backscatter coefficient in semi-arid zones to estimate the vegetation crown in terms of Leaf Area Index (LAI). The research area is characterized by the presence of a pine forest with shrubs as an underlying vegetation layer (understory), olive trees, natural grove areas and eucalyptus trees. The research area was imaged by an airborne RADAR system in L-band during February 2009. The imagery includes multi-look radar images. All the images were fully polarized i.e., HH, VV, HV polarizations. For this research we used the central azimuth angle (113° ). We measured LAI using the ?T Sun Scan Canopy Analysis System. Verification was done by analytic calculations and digital methods for the leaf's and needle's surface area. In addition, we estimated the radar extinction coefficient of the vegetation volume by comparing point calibration targets (trihedral corner reflectors with 150cm side length) within and without the canopy. The radar extinction in co- polarized images was ~26dB and ~24dB for pines and olives respectively, compared to the same calibration target outside the vegetation. We used smaller trihedral corner reflectors (41cm side length) and covered them with vegetation to measure the correlation between vegetation density, LAI and radar backscatter coefficient for pines and olives under known conditions. An inverse correlation between the radar backscatter coefficient of the trihedral corner reflectors covered by olive branches and the LAI of those branches was observed. The correlation between LAI and the optical transmittance was derived using the Beer-Lambert law. In addition, comparing this law's principle to the principle of the radar backscatter coefficient production, we derived the equation that connects between the radar backscatter coefficient and LAI. After extracting the radar backscatter coefficient of forested areas, all the vegetation parameters were used as inputs for the

  3. Performance of the Enhanced Vegetation Index to Detect Inner-annual Dry Season and Drought Impacts on Amazon Forest Canopies

    NASA Astrophysics Data System (ADS)

    Brede, B.; Verbesselt, J.; Dutrieux, L.; Herold, M.

    2015-04-01

    The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of variations in sun-sensor geometry throughout the year. We aimed to reproduce these results with the Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD43 product suite, which allows modeling the Bidirectional Reflectance Distribution Function (BRDF) and keeping sun-sensor geometry constant. The derived BRDF-adjusted EVI was spatially aggregated over large areas of central Amazon forests. The resulting time series of EVI spanning the 2000-2013 period contained distinct seasonal patterns with peak values at the onset of the dry season, but also followed the same pattern of sun geometry expressed as Solar Zenith Angle (SZA). Additionally, we assessed EVI's sensitivity to precipitation anomalies. For that we compared BRDF-adjusted EVI dry season anomalies to two drought indices (Maximum Cumulative Water Deficit, Standardized Precipitation Index). This analysis covered the whole of Amazonia and data from the years 2000 to 2013. The results showed no meaningful connection between EVI anomalies and drought. This is in contrast to other studies that investigate the drought impact on EVI and forest photosynthetic capacity. The results from both sub-analyses question the predictive power of EVI for large scale assessments of forest ecosystem functioning in Amazonia. Based on the presented results, we recommend a careful evaluation of the EVI for applications in tropical forests, including rigorous validation supported by ground plots.

  4. 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.

  5. 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

  6. Preliminary vegetation index products from Suomi NPP VIIRS illuminate the California drought

    NASA Astrophysics Data System (ADS)

    Dungan, J. L.; Ganguly, S.; Melton, F. S.; Shupe, J. W.; Nemani, R. R.

    2014-12-01

    The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite has been collecting data for almost three years. NOAA and NASA have been collaborating to validate numerous VIIRS data products capturing atmospheric, land and ocean parameters. For vegetation monitoring, standard VIIRS products currently include a top-of-canopy Enhanced Vegetation Index (EVI), thereby providing an opportunity to observe the recent land surface expression of drought conditions in the state of California as well as creating the potential for modeling gross primary productivity (GPP), evapotranspiration (ET), and other carbon- and water- related variables. We mapped and compared 16-day composite VIIRS EVIs over California from January 2012 to 2014 with equivalent MODIS products from the Aqua satellite (the MYD13 product). Relative to MODIS EVI, VIIRS EVI showed a bias of less than 7% (larger values than MODIS) and a precision of 0.50 to 0.85%. The remaining small proportion of large errors seem to be related to cloud and snow cover. Substantial changes in the EVI time series can be clearly seen for both irrigated and semi-natural land as the recent drought deepened. We also used the VIIRS EVI as input to the Terrestrial Observation and Prediction System (TOPS) model to generate ET and GPP, which illuminate drought effects more specifically. As the VIIRS products become more robust, they will make a valuable addition to the arsenal of satellite sensors capturing synoptic trends in vegetation response to drought conditions.

  7. The normalized difference vegetation index of small Douglas-fir canopies with varying chlorophyll concentrations

    SciTech Connect

    Yoder, B.J.; Waring, R.H. . Dept. of Forest Science)

    1994-07-01

    In an experiment with miniature canopies of 1-m-tall Douglas-fir (Pseudotsuga menziesii) seedlings, the authors modified leaf area index, light absorption capacity, and photosynthetic potential by altering the concentration of chlorophyll in foliage and by controlling the density of seedlings. They measured canopy photosynthesis and light transmission in controlled-environment chambers and then transferred seedlings to a hemispheric illumination system where they measured canopy reflectance. They found that altering the visible band used for computation of a normalized vegetation index substantially changed the correlations between the index and canopy properties. For example, the normalized index was best correlated to light absorption capacity when they used a narrow red band and least correlated when they used a narrow green band. The cause of these differences is chlorophyll. The green regions of reflectance spectra were much more sensitive to changes in chlorophyll concentration compared with the red or near-infrared regions. Increased chlorophyll concentration was also related to increased photosynthetic potential when canopies had been grown under full sunlight. However, they found no statistically significant relationship between leaf chlorophyll concentration and canopy light absorption.

  8. Long-term channel adjustment and geomorphic feature creation by vegetation in a lowland, low energy river

    NASA Astrophysics Data System (ADS)

    Grabowski, Robert; Gurnell, Angela

    2016-04-01

    Physical habitat restoration is increasingly being used to improve the ecological status of rivers. This is particularly true for lowland streams which are perceived to lack sufficient energy to create new features or to flush out fine sediment derived from agricultural and urban sources. However, this study has found that even in low-energy, base-flow dominated chalk streams, physical habitat improvement can happen naturally without direct human intervention. Furthermore this positive change is achieved by components of the river that are often regarded as management problems: in-stream macrophytes (i.e. weed), riparian trees, woody debris, and most importantly fine sediment. This project investigated the long-term changes in channel planform for the River Frome (Dorset, UK) over the last 120 years and the role of aquatic and riparian vegetation in driving this change. Agricultural census data, historical maps, recent aerial images and field observations were analysed within a process-based, hierarchical framework for hydromorphological assessment, developed in the EU FP7 REFORM project, to investigate the source and timing of fine sediment production in the catchment, to quantify the reach-scale geomorphic response, and to identify vegetation-related bedforms that could be responsible for the adjustment. The analysis reveals that the channel has narrowed and become more sinuous in the last 50-60 years. The timing of this planform adjustment correlates with substantial changes in land use and agricultural practices (post-World War II) that are known to increase soil erosion and sediment connectivity. The field observations and recent aerial images suggest that the increased delivery of fine sediment to the channel has been translated into geomorphic adjustment and diversification though the interactions between vegetation, water flow and sediment. Emergent aquatic macrophytes are retaining fine sediment, leading to the development of submerged shelves that aggrade

  9. Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

    NASA Technical Reports Server (NTRS)

    Kustas, W. P.; Schimugge, T. J.; Humes, K. S.; Jackson, T. J.; Parry, R.; Weltz, M. A.; Moran, M. S.

    1993-01-01

    Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experiment Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship. Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These findings indicate that information obtained from optical and microwave data can be used for quantifying the energy balance of semiarid areas. The microwave data can indicate

  10. Relationships between Evaporative Fraction and Remotely Sensed Vegetation Index and Microwave Brightness Temperature for Semiarid Rangelands.

    NASA Astrophysics Data System (ADS)

    Kustas, W. P.; Schmugge, T. J.; Humes, K. S.; Jackson, T. J.; Parry, R.; Weltz, M. A.; Moran, M. S.

    1993-12-01

    Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experimental Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during the experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship with a significant correlation (r2 = 0.69). Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. It caused a substantial reduction in the correlation with r2 = 0.40 or only 40% of the variation in EF being explained by TB. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These

  11. Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

    NASA Technical Reports Server (NTRS)

    McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

    2005-01-01

    Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

  12. Mapping paddy biomass with multiple vegetation indexes by using multispectral remotely sensed image

    NASA Astrophysics Data System (ADS)

    Gu, Xiaohe; Wang, Yancang; Song, Xiaoyu; Xu, Xingang

    2016-10-01

    Monitoring dry biomass of crop timely and accurately by remote sensing is crucial to assess crop growth, manage field water-fertilizer and predict yield. The Huaihe River Basin in China was chose as study area to map the spatial distribution of paddy biomass. The study derived 12 vegetation indexes from HJ-CCD image, which were closely related to crop growth. After screening sensitive vegetation index with in-situ samples by correlation analysis, the study developed the inversion model by single variable and multiple variables. The determination coefficient (R2) and root mean square error (RMSE) was used to evaluate the accuracy of models. Results showed that the accuracies of multivariable models were better than these of single-variable models, of which the average R2 reached 0.647 and the average RMSE was 0.059. It indicated that the multi-variable models were input in more information than those of single-variable models, which improved the accuracies of estimating paddy biomass in to a certain degree. The average overall accuracies of multi-variable models were 92.7%, while that of singe-variable models were 87.8%. The model with multiple linear regressions could be used to map the paddy biomass in the study area by using HJ-CCD image.

  13. Detection of Terrestrial Ecosystem Disturbances Using Aqua/MODIS Land Surface Temperature and Enhanced Vegetation Index

    NASA Astrophysics Data System (ADS)

    Mildrexler, D. J.; Zhao, M.; Running, S. W.

    2011-12-01

    Global information on the timing, location and magnitude of large-scale ecosystem disturbance events is needed to reduce significant uncertainty in the global carbon cycle. The MODIS Global Disturbance Index (MGDI) algorithm is designed for systematic, global, disturbance mapping using Aqua/MODIS Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) data. The MGDI uses annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. LST and EVI respond to different biophysical processes and coupling these variables together into a ratio results in a dynamic approach that measures both the energy exchange consequence and the vegetation density changes resulting from disturbance. This robust radiometric relationship is revisited for each individual pixel every year resulting in a consistent methodology that can be generalized globally to provide 1-km resolution information about the effects of major disturbance on woody ecosystems and has been validated across North America. We have now applied the full Aqua/MODIS dataset through 2010 to the MGDI algorithm across woody ecosystems globally and continue to validate the MGDI results by comparison with confirmed, historical disturbance events such as wildfire, hurricanes, insect epidemics, ice storms, and droughts.

  14. Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index

    USGS Publications Warehouse

    Nagler, Pamela L.; Glenn, Edward P.; Nguyen, Uyen; Scott, Russell; Doody, Tania

    2013-01-01

    Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  15. Analysis of a multiyear global vegetation leaf area index data set

    NASA Astrophysics Data System (ADS)

    Buermann, Wolfgang; Wang, Yujie; Dong, Jiarui; Zhou, Liming; Zeng, Xubin; Dickinson, Robert E.; Potter, Christopher S.; Myneni, Ranga B.

    2002-11-01

    The analysis of a global data set of monthly leaf area index (LAI), derived from satellite observations of normalized difference vegetation index (NDVI) for the period July 1981 to September 1994, is discussed in this paper. Validation of this retroactive, coarse resolution (8 km) global multiyear data set is a challenging task because repetitive ground measurements from all representative vegetation types are not available. Therefore the magnitudes and interannual variations in the derived LAI fields were assessed as follows. First, the use of a NDVI-based algorithm, as opposed to a more physically based approach, is estimated to result in relative errors in LAI of about 10-20%, which is comparable to the mean uncertainty of AVHRR NDVI data. Second, the satellite LAI values compared reasonably well to ground measurements from three field campaigns. Third, comparison with an existing multiyear LAI data set showed qualitative agreement with regards to interannual variability, although the LAI values of the earlier data were consistently larger than those derived here. Fourth, interannual variations in LAI were evaluated through correlations with climate data sets, e.g., sea surface temperatures and precipitation in tropical semiarid regions known for ENSO impacts, temperature dependence of vegetation growth, and therefore LAI, in the northern latitudes. The general consistency between these independent data sets imbues confidence in the LAI data set, at least for use in large-scale modeling studies. Finally, improvements in near-surface climate simulation are documented in a companion article when satellite LAI values were used in a global climate model. The data set is available to the community via our Web server (http://cybele.bu.edu).

  16. Use of Radar Vegetation Index (RVI) in Passive Microwave Algorithms for Soil Moisture Estimates

    NASA Astrophysics Data System (ADS)

    Rowlandson, T. L.; Berg, A. A.

    2013-12-01

    The Soil Moisture Active Passive (SMAP) satellite will provide a unique opportunity for the estimation of soil moisture by having simultaneous radar and radiometer measurements available. As with the Soil Moisture and Ocean Salinity (SMOS) satellite, the soil moisture algorithms will need to account for the contribution of vegetation to the brightness temperature. Global maps of vegetation volumetric water content (VWC) are difficult to obtain, and the SMOS mission has opted to estimate the optical depth of standing vegetation by using a relationship between the VWC and the leaf area index (LAI). LAI is estimated from optical remote sensing or through soil-vegetation-atmosphere transfer modeling. During the growing season, the VWC of agricultural crops can increase rapidly, and if cloud cover exists during an optical acquisition, the estimation of LAI may be delayed, resulting in an underestimation of the VWC and overestimation of the soil moisture. Alternatively, the radar vegetation index (RVI) has shown strong correlation and linear relationship with VWC for rice and soybeans. Using the SMAP radar to produce RVI values that are coincident to brightness temperature measurements may eliminate the need for LAI estimates. The SMAP Validation Experiment 2012 (SMAPVEX12) was a cal/val campaign for the SMAP mission held in Manitoba, Canada, during a 6-week period in June and July, 2012. During this campaign, soil moisture measurements were obtained for 55 fields with varying soil texture and vegetation cover. Vegetation was sampled from each field weekly to determine the VWC. Soil moisture measurements were taken coincident to overpasses by an aircraft carrying the Passive and Active L-band System (PALS) instrumentation. The aircraft flew flight lines at both high and low altitudes. The low altitude flight lines provided a footprint size approximately equivalent to the size of the SMAPVEX12 field sites. Of the 55 field sites, the low altitude flight lines provided

  17. Estimation of green leaf area index of crops: Sensitivity of vegetation indices

    NASA Astrophysics Data System (ADS)

    Nguy-Robertson, A. L.; Gitelson, A. A.; Peng, Y.; Vina, A.; Arkebauer, T. J.; Rundquist, D.

    2011-12-01

    Green leaf area index (gLAI) is an important biophysical characteristic used in climate, ecological, and crop yield models. There is a need for a rapid and accurate estimation of gLAI on a global scale. Traditionally used vegetation indices (VIs) have shown to saturate at moderate-to-high gLAI (e.g. NDVI) or are less sensitive to gLAI at low-to-moderate values of gLAI. The goal of this study was to determine the best suitable VIs for use in a combined vegetation index for estimating gLAI in crops in the entire wide dynamic range of gLAI. The study area consisted of three fields in eastern Nebraska, USA under different management conditions for the years 2001-2008 for a total of 24 field-years. The dynamic range of maize was 0-6.5 m2/m2 and soybean was 0-5.5 m2/m2. NDVI-like indices were the most sensitive to gLAI below 3 m2/m2 while Simple Ratio (SR) and the Chlorophyll Indices (CI) were more sensitive to gLAI above 3 m2/m2. MTCI was the only VI that was equally sensitive to gLAI in the entire dynamic range; however, it was species-specific. Only Red Edge NDVI and CIred edge were not species-specific. In order to benefit from different sensitivities of the indices to low-to-moderate and moderate-to-high gLAI, this study suggests building relationships using VIs in specific dynamic ranges of maximal sensitivity to gLAI. We suggest using NDVI and Simple Ratio (maize: RMSE = 0.71 m2/m2; soybean: RMSE = 0.53 m2/m2) for MODIS data. We suggest the using non-species-specific VIs, Red Edge NDVI and CIred edge (RMSE = 0.63 m2/m2) for MERIS data. For users which prefer to use a single index, we suggest a scaled combined vegetation index using Red Edge NDVI and CIred edge (RMSE = 0.56 m2/m2); however, this approach reduces the sensitivity of the specific indices in the dynamic range of which they are most sensitive.

  18. 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.

  19. Heat index and adjusted temperature as surrogates for wet bulb globe temperature to screen for occupational heat stress.

    PubMed

    Bernard, Thomas E; Iheanacho, Ivory

    2015-01-01

    Ambient temperature and relative humidity are readily ava-ilable and thus tempting metrics for heat stress assessment. Two methods of using air temperature and relative humidity to create an index are Heat Index and Adjusted Temperature. The purposes of this article are: (1) to examine how well Heat Index and Adjusted Temperature estimated the wet bulb globe temperature (WBGT) index, and (2) to suggest how Heat Index and Adjusted Temperature can be used to screen for heat stress level. Psychrometric relationships were used to estimate values of actual WBGT for conditions of air temperature, relative humidity, and radiant heat at an air speed of 0.5 m/s. A relationship between Heat Index [°F] and WBGT [°C] was described by WBGT = -0.0034 HI(2) + 0.96 HI - 34. At lower Heat Index values, the equation estimated WBGTs that were ± 2 °C-WBGT around the actual value, and to about ± 0.5 °C-WBGT for Heat Index values > 100 °F. A relationship between Adjusted Temperature [°F] and WBGT [°C] was described by WBGT = 0.45 Tadj - 16. The actual WBGT was between 1 °C-WBGT below the estimated value and 1.4 °C-WBGT above. That is, there was a slight bias toward overestimating WBGT from Adjusted Temperature. Heat stress screening tables were constructed for metabolic rates of 180, 300, and 450 W. The screening decisions were divided into four categories: (1) < alert limit, (2) < exposure limit, (3) hourly time-weighted averages (TWAs) of work and recovery, and (4) a caution zone for an exposure > exposure limit at rest. The authors do not recommend using Heat Index or Adjusted Temperature instead of WBGT, but they may be used to screen for circumstances when a more detailed analysis using WBGT is appropriate. A particular weakness is accounting for radiant heat; and neither air speed nor clothing was considered.

  20. 75 FR 49411 - Consumer Price Index Adjustments of Oil Pollution Act of 1990 Limits of Liability-Vessels and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-13

    ... Number 1625-0046 entitled ``Financial Responsibility for Water Pollution (Vessels).'' The approval for... SECURITY Coast Guard 33 CFR Part 138 RIN 1625-AB25 Consumer Price Index Adjustments of Oil Pollution Act of...; information collection approval. SUMMARY: On July 1, 2009, the Coast Guard amended the Oil Pollution Act...

  1. The Occupational Mix Adjustment to the Medicare Hospital Wage Index: Why the Rural Impact Is Less than Expected

    ERIC Educational Resources Information Center

    Reiter, Kristin L.; Slifkin, Rebecca; Holmes, George M.

    2008-01-01

    Context: Rural hospitals are heavily dependent on Medicare for their long-term financial solvency. A recent change to Medicare prospective payment system reimbursement--the occupational mix adjustment (OMA) to the wage index--has attracted a great deal of attention in rural policy circles. Purpose: This paper explores variation in the OMA across…

  2. Development and evaluation of a modis vegetation index compositing algorithm for long-term climate studies

    NASA Astrophysics Data System (ADS)

    Solano Barajas, Ramon

    The acquisition of remote sensing data having an investigated quality level constitutes an important step to advance our understanding of the vegetation response to environmental factors. Spaceborne sensors introduce additional challenges that should be addressed to assure that derived findings are based on real phenomena, and not biased or misguided by instrument features or processing artifacts. As a consequence, updates to incorporate new advances and user requirements are regularly found on most cutting edge systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) system. In this dissertation, the objective was to design, characterize and assess any possible departure from current values, a MODIS vegetation index (VI) algorithm for restoring the continuity 16-day 1-km product, based on the new 8-day 500-m MODIS surface reflectance (SR) product scheduled for the forthcoming MODIS Collection 6 (C6). Additionally, the impact of increasing the time resolution (by reducing the compositing period) from 16 to 8 days for the future basic MODIS C6 VI product was also assessed. The performance of the proposed algorithm was evaluated using high quality reference data and known biophysical relationships at several spatial and temporal scales. Firstly, it was evaluated using data from the AERONET-based Surface Reflectance Validation Network (ASRVN), FLUXNET-derived ecosystem gross primary productivity (GPP) and an analysis of the seasonality parameters derived from current Collection 5 (C5) and proxy C6 VI collections. The performance of the 8-day VI version was evaluated and contrasted with current 16-day using the reported correlation of the Enhanced Vegetation Index (EVI) with the GPP derived from CO2 flux measurements. Secondly, we performed an analysis at spatial level using entire images (or "tiles") to assess the Bidirectional Reflectance Distribution Function (BRDF) effects on the VI product, as these can cause biases on the SR and VIs from scanning

  3. 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.

  4. Quality-Adjusted Life Years Lost to Road Crash Injury: Updating the Injury Impairment Index

    PubMed Central

    Spicer, Rebecca S.; Miller, Ted R.; Hendrie, Delia; Blincoe, Lawrence J.

    2011-01-01

    The Injury Impairment Index (III) has long been used internationally to estimate the quality-adjusted life year (QALY) losses associated with crash injuries. The III has major limitations, notably its lack of detailed validation, but it is widely used and estimates from it are regularly published. It is based on physician estimates of typical impairment on 6 dimensions of functioning (cognitive, mobility, bending/grasping/lifting, sensory, pain and cosmetic), supplemented with data on work-related disability. This paper reports on a literature synthesis used to update the III scoring algorithm that converts impairment levels by dimension into a combined QALY loss score. An extensive international literature search identified 13 health status scales, some of them with multiple scorings. From the scorings, we extracted utility scores for each level of each dimension of the III. We also searched for direct utility estimates for III dimension endpoints (e.g., blindness, deafness). Median and inter-quartile ranges were computed by scale point to represent the uncertainty range of preference weights within each III dimension and level. Average QALY losses per injury by MAIS were computed using the updated preference weight ranges applied to 2000–2006 U.S. crash data. The updated QALY loss estimates are lower than those computed with the QALY weights developed in 1990. This paper’s tables of estimated average QALY losses by MAIS, injury type, and body region injured can be applied to future and existing injury data in order to estimate the impact of injury on quality of life and measure health status. PMID:22105411

  5. 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.

  6. Monitoring Thermal Status of Ecosystems with MODIS Land-Surface Temperature and Vegetation Index Products

    NASA Technical Reports Server (NTRS)

    Wan, Zhengming

    2002-01-01

    The global land-surface temperature (LST) and normalized difference vegetation index (NDVI) products retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data in 2001 were used in this study. The yearly peak values of NDVI data at 5km grids were used to define six NDVI peak zones from -0.2 to 1 in steps of 0.2, and the monthly NDVI values at each grid were sorted in decreasing order, resulting in 12 layers of NDVI images for each of the NDVI peak zones. The mean and standard deviation of daytime LSTs and day-night LST differences at the grids corresponding to the first layer of NDVI images characterize the thermal status of terrestrial ecosystems in the NDVI peak zones. For the ecosystems in the 0.8-1 NDVI peak zone, daytime LSTs distribute from 0-35 C and day-night LST differences distribute from -2 to 22 C. The daytime LSTs and day-night LST differences corresponding to the remaining layers of NDVI images show that the growth of vegetation is limited at low and high LSTs. LSTs and NDVI may be used to monitor photosynthetic activity and drought, as shown in their applications to a flood-irrigated grassland in California and an unirrigated grassland in Nevada.

  7. VIP Data Explorer: A Tool for Exploring 30 years of Vegetation Index and Phenology Observations

    NASA Astrophysics Data System (ADS)

    Barreto-munoz, A.; Didan, K.; Rivera-Camacho, J.; Yitayew, M.; Miura, T.; Tsend-Ayush, J.

    2011-12-01

    Continuous acquisition of global satellite imagery over the years has contributed to the creation of long term data records from AVHRR, MODIS, TM, SPOT-VGT and other sensors. These records account for 30+ years, as these archives grow, they become invaluable tools for environmental, resources management, and climate studies dealing with trends and changes from local, regional to global scale. In this project, the Vegetation Index and Phenology Lab (VIPLab) is processing 30 years of daily global surface reflectance data into an Earth Science Data Record of Vegetation Index and Phenology metrics. Data from AVHRR (N07,N09,N11 and N14) and MODIS (AQUA and TERRA collection 5) for the periods 1981-1999 and 2000-2010, at CMG resolution were processed into one seamless and sensor independent data record using various filtering, continuity and gap filling techniques (Tsend-Ayush et al., AGU 2011, Rivera-Camacho et al, AGU 2011). An interactive online tool (VIP Data Explorer) was developed to support the visualization, qualitative and quantitative exploration, distribution, and documentation of these records using a simple web 2.0 interface. The VIP Data explorer (http://vip.arizona.edu/viplab_data_explorer) can display any combination of multi temporal and multi source data, enable the quickly exploration and cross comparison of the various levels of processing of this data. It uses the Google Earth (GE) model and was developed using the GE API for images rendering, manipulation and geolocation. These ESDRs records can be quickly animated in this environment and explored for visual trends and anomalies detection. Additionally the tool enables extracting and visualizing any land pixel time series while showing the different levels of processing it went through. User can explore this ESDR database within this data explorer GUI environment, and any desired data can be placed into a dynamic "cart" to be ordered and downloaded later. More functionalities are planned and will be

  8. Error correction of the Normalized Difference Vegetation Index and Brightness Temperature calculated from the AVHRR observations

    NASA Astrophysics Data System (ADS)

    Rahman, Mohammed Zahidur

    This thesis investigates Normalized Difference Vegetation Index (NDVI) and Brightness Temperature (BT) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data during 1982-2003. This data was collected from five NOAA series satellites. We have proposed to apply Empirical distribution function (EDF) to improve the stability of the NDVI and BT data derived from the AVHRR sensor on NOAA polar orbiting satellite. The instability of data results from orbit degradation as well as the circuit drifts over the life or a satellite. Degradation of NDVI and BT over time and shifts of NDVI and BT between the satellites was estimated China data set, for it includes a wide variety or different ecosystems represented globally. It was found that data for the years 1988, 1992, 1993, 1994, 1995 and 2000 are not stable enough compared to other years because of satellite orbit drift, AVHRR sensor degradation, and also Mt Pinatubo volcanic eruption in 1992. We assume data from NOAA-7(1982, 1983), NOAA-9 (1985, 1986), NOAA-11(1989, 1990), NOAA-14(1996, 1997), and NOAA-16 (2001, 2002) to be standard because theses satellite's equator crossing time falls between 1330 and 1500. Data from this particular period of the day maximized the value of coefficients. The crux of the proposed correction procedure consists of dividing standard year's data sets into two subsets. The subset 1(standard data correction sets) is used for correcting unstable years and then corrected data for this years compared with the standard data in the subset 2 (standard data validation sets). In this dissertation, we apply EDF to correct this deficiency of data for the affected years. We normalize or correct data by the method of empirical distribution functions compared with the standard. Using these normalized values, we estimate new NDVI and BT time series which provides NDVI and BT data for these years that match in subset 2 that is used for data validation.

  9. 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.

  10. Global assessment of Vegetation Index and Phenology Lab (VIP) and Global Inventory Modeling and Mapping Studies (GIMMS) version 3 products

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Okuto, E.; Kang, Y.; Opiyo, E.; Ahmed, M.

    2015-06-01

    Earth observation based long-term global vegetation index products are used by scientists from a wide range of disciplines concerned with global change. Inter-comparison studies are commonly performed to keep the user community informed on the consistency and accuracy of such records as they evolve. In this study, we compared two new records: (1) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index Version 3 (NDVI3g) and (2) Vegetation Index and Phenology Lab (VIP) Version 3 NDVI (NDVI3v) and Enhanced Vegetation Index 2 (EVI3v). We evaluated the two records via three experiments that addressed the primary use of such records in global change research: (1) prediction of the Leaf Area Index (LAI) used in light-use efficiency modeling, (2) estimation of vegetation climatology in Soil-Vegetation-Atmosphere Transfer models, and (3) trend analysis of the magnitude and phenology of vegetation productivity. Experiment one, unlike previous inter-comparison studies, was performed with a unique Landsat 30 m spatial resolution and in situ LAI database for major crop types on five continents. Overall, the two records showed a high level of agreement both in direction and magnitude on a monthly basis, though VIP values were higher and more variable and showed lower correlations and higher error with in situ LAI. The records were most consistent at northern latitudes during the primary growing season and southern latitudes and the tropics throughout much of the year, while the records were less consistent at northern latitudes during green-up and senescence and in the great deserts of the world throughout much of the year. The two records were also highly consistent in terms of trend direction/magnitude, showing a 30+ year increase (decrease) in NDVI over much of the globe (tropical rainforests). The two records were less consistent in terms of timing due to the poor correlation of the records during start and end of growing season.

  11. Initial adjustments within a new river channel: Interactions between fluvial processes, colonizing vegetation, and bank profile development.

    PubMed

    Gurnell, Angela M; Morrissey, Ian P; Boitsidis, Angela J; Bark, Tony; Clifford, Nicholas J; Petts, Geoffrey E; Thompson, Kenneth

    2006-10-01

    A conceptual model of the morphological development of the riparian margins of newly cut river channels is presented, suggesting early feedbacks between vegetation growth and bank form. To test the model, observations of long and cross profiles, bank sediment and seed deposition, and bank vegetation development were collected over the first 2 years of river flows through a reach of the River Cole, West Midlands, UK. The newly created channel had a sinuous planform and varying asymmetric trapezoidal cross section in sympathy with the planform. No imposed bedforms or bank reseeding were included in the design. Over the 2 years, development of bedforms was rapid, with bed sediment sorting and bank profile adjustment occurring more steadily and progressively. Six classes of bank profile were identified by the end of the study period, illustrating close associations with sediment aggradation, vegetation colonization, and growth patterns. Vegetation colonization of the banks was seeded predominantly from local sources during the summer and from hydrochory (transport by the river) during the winter. Colonizing vegetation on the riverbanks appeared to act as a significant propagule source by the second summer and as an increasingly important roughness element, trapping both propagules and sediment, within the second year and providing early feedback into bank evolution. As a result, the time required for riparian margin development in the conceptual model was found to be considerably longer than observed in the study river. In addition, the role of surface wash/bank failure in modifying the bank profile and transporting seeds onto the upper bank face during the first year of bank development was found to be important in initiating rapid bank vegetation colonization and surface stabilization. This set of processes had not been incorporated in the initial conceptual model. In relation to channel restoration, this research illustrates that in small temperate rivers of modest

  12. [New vegetation index fusing visible-infrared and shortwave infrared spectral feature for winter wheat LAI retrieval].

    PubMed

    Li, Xin-chuan; Bao, Yan-song; Xu, Xin-gang; Jin, Xiu-liang; Zhang, Jing-cheng; Song, Xiao-yu

    2013-09-01

    Considering the great relationships between shortwave infrared (SWIR) and leaf area index (LAI), innovative indices based on water vegetation indices and visible-infrared vegetation indices were presented. In the present work, PROSAIL model was used to study the saturation sensitivity of new vegetation indices to LAI. The estimate models about LAI of winter wheat were built on the basis of the experiment data in 2009 acting as train sample and their precisions were evaluated and tested on the basis of the experiment data in 2008. Ten visible-infrared vegetation indices and five water vegetation indices were used to construct new indices. The result showed that newly developed indices have significant relationships with LAI by numerical simulations and in-situ measurements. In particular, by implementing modified standardized LAI Determining Index (sLAIDI *), all new indices were neither sensitive to water variations nor affected by saturation at high LAI levels. The evaluation models could improve prediction accuracy and have well reliability for LAI retrieval. The result indicated that visible-infrared vegetation indices combined with water index have greater advantage for LAI estimation.

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

    NASA Astrophysics Data System (ADS)

    Los, S. O.

    2015-06-01

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

  14. Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale.

    PubMed

    Xu, Chi; Li, Yutong; Hu, Jian; Yang, Xuejiao; Sheng, Sheng; Liu, Maosong

    2012-03-01

    Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.

  15. Version 4 of the Vegetation Index and Phenology Earth Science Data Records

    NASA Astrophysics Data System (ADS)

    Barreto-munoz, A.; Didan, K.; Miura, T.; Tsend-Ayush, J.

    2014-12-01

    This is the culmination of a 6-year effort to create a seamless multi-sensor data record about vegetation dynamic from different synoptic imagers. In this work we devised a set of sophisticated science algorithms to combine these disparate data records into an unique and single dataset. To address the cross sensor continuity problem, several published methods were tested. These methods ranged from a single global linear transfer equation (V1), to a land cover based approach (V2, V3), and to a complex hybrid method that looks at the behavior of each pixel separately and considers the impact of vegetation seasonality by adjusting the continuity by the vegetation dynamic of each phase of the growing season (V4). Because of the 1999 break between AVHRR and MODIS we considered SPOT-VGT data in bridging the two sensors using the periods of overlap. However, we found that due to the lack of an efficient cloud algorithm and accurate QA data in SPOT-VGT the method performed rather poorly. In V4 we matched the AVHRR and MODIS medium term average single pixel temporal profile and created spatially explicit transfer equations. This approach was far superior to all other methods and was adopted in our V4 reprocessing effort. Furthermore, the issue of data filtering was found to be critical to the overall approach. The stricter the data filtering the better the performance of the continuity algorithm. Filtering lead to spatial gaps that were addressed using a simple linear interpolation algorithm, in case of long temporal gaps we used a long term average substitution technique. All data were assigned per pixel quality information that captured the input quality and processing performance. This filtering, continuity, and gap filling package was applied to a 30+ year record of daily global observations from the LTDR-V4 AVHRR (1981-1999) and MODIS C5 (2000-2013) to generate records of NDVI, EVI2, and phenology metrics at CMG resolution. Version V4 of these records are available at

  16. 77 FR 9925 - Price Index Adjustments for Expenditure Limitations and Lobbyist Bundling Disclosure Threshold

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-21

    ... From the Federal Register Online via the Government Publishing Office FEDERAL ELECTION COMMISSION...: Federal Election Commission. ACTION: Notice of adjustments to expenditure limitations and lobbyist bundling disclosure threshold. SUMMARY: As mandated by provisions of the Federal Election Campaign Act...

  17. Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

    USGS Publications Warehouse

    Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.

    2011-01-01

    Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

  18. Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

    SciTech Connect

    Kustas, W.P.; Schimugge, T.J.; Humes, K.S.; Jackson, T.J.; Parry, R.; Weltz, M.A.; Moran, M.S. ||

    1993-12-01

    Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experiment Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship. Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions.

  19. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    NASA Astrophysics Data System (ADS)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

  20. Predicting maize yield in Zimbabwe using dry dekads derived from remotely sensed Vegetation Condition Index

    NASA Astrophysics Data System (ADS)

    Kuri, Farai; Murwira, Amon; Murwira, Karin S.; Masocha, Mhosisi

    2014-12-01

    Maize is a key crop contributing to food security in Southern Africa yet accurate estimates of maize yield prior to harvesting are scarce. Timely and accurate estimates of maize production are essential for ensuring food security by enabling actionable mitigation strategies and policies for prevention of food shortages. In this study, we regressed the number of dry dekads derived from VCI against official ground-based maize yield estimates to generate simple linear regression models for predicting maize yield throughout Zimbabwe over four seasons (2009-10, 2010-11, 2011-12, and 2012-13). The VCI was computed using Normalized Difference Vegetation Index (NDVI) time series dataset from the SPOT VEGETATION sensor for the period 1998-2013. A significant negative linear relationship between number of dry dekads and maize yield was observed in each season. The variation in yield explained by the models ranged from 75% to 90%. The models were evaluated with official ground-based yield data that was not used to generate the models. There is a close match between the predicted yield and the official yield statistics with an error of 33%. The observed consistency in the negative relationship between number of dry dekads and ground-based estimates of maize yield as well as the high explanatory power of the regression models suggest that VCI-derived dry dekads could be used to predict maize yield before the end of the season thereby making it possible to plan strategies for dealing with food deficits or surpluses on time.

  1. Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity

    NASA Technical Reports Server (NTRS)

    Roy, D. P.; Kovalskyy, V.; Zhang, H. K.; Vermote, E. F.; Yan, L.; Kumar, S. S.; Egorov, A.

    2016-01-01

    At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM+). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat- 8 OLI and Landsat-7 ETM+ provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30m corresponding sensor observations extracted from 6,317 Landsat-7 ETM+ and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM+ TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands

  2. Marsh collapse thresholds for coastal Louisiana estimated using elevation and vegetation index data

    USGS Publications Warehouse

    Couvillion, Brady R.; Beck, Holly

    2013-01-01

    Forecasting marsh collapse in coastal Louisiana as a result of changes in sea-level rise, subsidence, and accretion deficits necessitates an understanding of thresholds beyond which inundation stress impedes marsh survival. The variability in thresholds at which different marsh types cease to occur (i.e., marsh collapse) is not well understood. We utilized remotely sensed imagery, field data, and elevation data to help gain insight into the relationships between vegetation health and inundation. A Normalized Difference Vegetation Index (NDVI) dataset was calculated using remotely sensed data at peak biomass (August) and used as a proxy for vegetation health and productivity. Statistics were calculated for NDVI values by marsh type for intermediate, brackish, and saline marsh in coastal Louisiana. Marsh-type specific NDVI values of 1.5 and 2 standard deviations below the mean were used as upper and lower limits to identify conditions indicative of collapse. As marshes seldom occur beyond these values, they are believed to represent a range within which marsh collapse is likely to occur. Inundation depth was selected as the primary candidate for evaluation of marsh collapse thresholds. Elevation relative to mean water level (MWL) was calculated by subtracting MWL from an elevation dataset compiled from multiple data types including light detection and ranging (lidar) and bathymetry. A polynomial cubic regression was used to examine a random subset of pixels to determine the relationship between elevation (relative to MWL) and NDVI. The marsh collapse uncertainty range values were found by locating the intercept of the regression line with the 1.5 and 2 standard deviations below the mean NDVI value for each marsh type. Results indicate marsh collapse uncertainty ranges of 30.7–35.8 cm below MWL for intermediate marsh, 20–25.6 cm below MWL for brackish marsh, and 16.9–23.5 cm below MWL for saline marsh. These values are thought to represent the ranges of

  3. [Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

    PubMed

    Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

    2015-03-01

    Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient

  4. [A novel vegetation index (MPRI) of corn canopy by vehicle-borne dynamic prediction].

    PubMed

    Li, Shu-qiang; Li, Min-zan; Sun, Hong

    2014-06-01

    Ground-based remote sensing system is a significant way to understand the growth of corn and provide accurate and scientific data for precision agriculture. The vehicle-borne system is one of the most important tools for corn canopy monitoring. However, the vehicle-borne growth monitoring system cannot maintain steady operations due to the row spacing of corn. The reflectance of corn canopy, which was used to construct the model for the chlorophyll content, was disturbed by the reflectance of soil background. The background interference with the reflectance could not be removed effectively, which would result in a deviation in the growth monitoring. In order to overcome this problem, a novel vegetation index named MPRI was developed in the present paper. The tests were carried out by the vehicle-borne system on the cornfield. The sensors which configured the vehicle-borne system had 4 bands, being respectively 550, 650, 766 and 850 nm. It would obtain the spectral data while the vehicle moved along the row direction. The sampling rate was about 1 point per second. The GPS receiver obtained the location information at the same rate. MPRI was made up by the reflectance ratio of 660 and 550 nm. It was very effective to analyze the information about the reflectance of the canopy. The results of experiments showed that the MPRI of soil was the positive value and the MPRI of canopy was the negative value. So it is easier to distinguish the spectral information about soil and corn canopy by MPRI. The results indicated that: it had satisfactory forecasting accuracy for the chlorophyll content by using the MPRI on the moving monitoring. The R2 of the prediction model was about 0.72. The R2 Of the model of NDVI, which was used to represent the chlorophyll content, was only 0.24. It indicates that MPRI had good measurement results for the dynamic measurement process. It provided the novel measurement way to get the canopy reflectance spectra and the better vegetation index to

  5. Estimating Sahelian and East African soil moisture using the Normalized Difference Vegetation Index

    NASA Astrophysics Data System (ADS)

    McNally, A.; Funk, C.; Husak, G. J.; Michaelsen, J.; Cappelaere, B.; Demarty, J.; Pellarin, T.; Young, T. P.; Caylor, K. K.; Riginos, C.; Veblen, K. E.

    2013-06-01

    Rainfall gauge networks in Sub-Saharan Africa are inadequate for assessing Sahelian agricultural drought, hence satellite-based estimates of precipitation and vegetation indices such as the Normalized Difference Vegetation Index (NDVI) provide the main source of information for early warning systems. While it is common practice to translate precipitation into estimates of soil moisture, it is difficult to quantitatively compare precipitation and soil moisture estimates with variations in NDVI. In the context of agricultural drought early warning, this study quantitatively compares rainfall, soil moisture and NDVI using a simple statistical model to translate NDVI values into estimates of soil moisture. The model was calibrated using in-situ soil moisture observations from southwest Niger, and then used to estimate root zone soil moisture across the African Sahel from 2001-2012. We then used these NDVI-soil moisture estimates (NSM) to quantify agricultural drought, and compared our results with a precipitation-based estimate of soil moisture (the Antecedent Precipitation Index, API), calibrated to the same in-situ soil moisture observations. We also used in-situ soil moisture observations in Mali and Kenya to assess performance in other water-limited locations in sub Saharan Africa. The separate estimates of soil moisture were highly correlated across the semi-arid, West and Central African Sahel, where annual rainfall exhibits a uni-modal regime. We also found that seasonal API and NDVI-soil moisture showed high rank correlation with a crop water balance model, capturing known agricultural drought years in Niger, indicating that this new estimate of soil moisture can contribute to operational drought monitoring. In-situ soil moisture observations from Kenya highlighted how the rainfall-driven API needs to be recalibrated in locations with multiple rainy seasons (e.g., Ethiopia, Kenya, and Somalia). Our soil moisture estimates from NDVI, on the other hand, performed

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS.

    PubMed

    Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

    2017-02-01

    Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June-August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations (r (2) = 0.62-0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ∼30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

  8. Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

    NASA Astrophysics Data System (ADS)

    Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

    2017-02-01

    Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June-August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations ( r 2 = 0.62-0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % ( D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ˜30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

  9. [Kriging analysis of vegetation index depression in peak cluster karst area].

    PubMed

    Yang, Qi-Yong; Jiang, Zhong-Cheng; Ma, Zu-Lu; Cao, Jian-Hua; Luo, Wei-Qun; Li, Wen-Jun; Duan, Xiao-Fang

    2012-04-01

    In order to master the spatial variability of the normal different vegetation index (NDVI) of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area, NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area, in Pingguo County, Guangxi applying image processing software, ENVI. The spatial variability of NDVI was analyzed applying geostatistical method, and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25 degrees of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25 degrees. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.

  10. Assessment of Iranian Agroclimatological Zone Classification by Using TVDI (Temperature Vegetation Dryness Index)

    NASA Astrophysics Data System (ADS)

    Asadi, Ebrahim; Lopez-Baeza, Ernesto; Coll Pajaron, M. Amparo; Kouzehgaran, Saeedeh; Haghighat, Masoud

    2016-07-01

    Agricultural zoning is an important tool for authorities to plan and decide about development of the agricultural sector, environmental sustainability issues and plan and provide irrigation and rural infrastructures. Previous different methods have suggested the definition of agroclimatological zones in big areas in Iran, but most of them are not easy to be validated or there are not clear criteria to evaluate whether the zones are correctly defined or not. The current {it Iranian Meteorological Organisation} classification is composed of six significant agroclimatological zones defined using the fundamental climate elements of temperature and precipitation obtained from 30 years data from 180 synoptic stations interpolated using regression kriging methods. Elevation was derived from SRTM (Shuttle Radar Topography Mission) digital elevation model of 90 m resolution. In this paper we assess the homogeneity of each of these conventionally defined agroclimatological zones using {bf TVDI (Temperature Vegetation Dryness Index)} values obtained from MODIS land surface temperature and NDVI operational products of the last three years between 2013 and 2015.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  13. An investigation on controlling operation indexes of the hydrocyclone by adjusting its installation angle

    SciTech Connect

    Chen Bingchen; Zhang Jian; Liu Jiaxiang

    1995-12-31

    The influence of various installation angles of hydrocyclone on its operation indexes was investigated, and the correspondent mathematical models were established in this paper. The models developed in this paper can be used to the optimizing control of hydrocyclone and make the hydrocyclone as a particle size sensor.

  14. [Effects of vegetation cover and normalized difference moisture index on thermal landscape pattern: a case study of Guangzhou, South China].

    PubMed

    Wang, Gang; Guan, Dong-Sheng

    2012-09-01

    By using Landsat-5 TM images, the land surface temperature (LST), vegetation cover, and normalized difference moisture index (NDMI) in different areas of Guangzhou were extracted, and the effects of vegetation cover and NDMI on the land surface temperature of the City were studied, based on the landscape ecological methodologies. There existed good linear correlations among the vegetation cover, land surface temperature, and NDMI, but the correlation coefficients for any two of the three items differed obviously with different areas. If the vegetation cover in different areas of Guangzhou was improved to the same level, urban center had the best cooling effect, followed by the suburbs in the north edge of urban center. The forest parks in different areas of the City also had different cooling effect on the surrounding environment. The difference of the average temperature between the 960-1080 m buffer zone and the inner park were 4.69 degrees C in Baiyun Mountain, 1.27 degrees C in Mazaishan, and 0.41 degrees C in Liuxihe. High vegetation cover could increase the thermal landscape heterogeneity and the aggregation among different landscapes, and promote the energy exchange between the lower temperature patches and higher temperature patches, playing an important role in controlling hot island effect. NDMI and vegetation cover had the same effects on the formation of thermal landscape pattern.

  15. Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables

    USGS Publications Warehouse

    Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.

    2015-01-01

    Switchgrass is being evaluated as a potential feedstock source for cellulosic biofuels and is being cultivated in several regions of the United States. The recent availability of switchgrass land cover maps derived from the National Agricultural Statistics Service cropland data layer for the conterminous United States provides an opportunity to assess the environmental conditions of switchgrass over large areas and across different geographic locations. The main goal of this study is to develop a data-driven multiple regression switchgrass productivity model and identify the optimal climate and environment conditions for the highly productive switchgrass in the Great Plains (GP). Environmental and climate variables used in the study include elevation, soil organic carbon, available water capacity, climate, and seasonal weather. Satellite-derived growing season averaged Normalized Difference Vegetation Index (GSN) was used as a proxy for switchgrass productivity. Multiple regression analyses indicate that there are strong correlations between site environmental variables and switchgrass productivity (r = 0.95). Sufficient precipitation and suitable temperature during the growing season (i.e., not too hot or too cold) are favorable for switchgrass growth. Elevation and soil characteristics (e.g., soil available water capacity) are also an important factor impacting switchgrass productivity. An anticipated switchgrass biomass productivity map for the entire GP based on site environmental and climate conditions and switchgrass productivity model was generated. Highly productive switchgrass areas are mainly located in the eastern part of the GP. Results from this study can help land managers and biofuel plant investors better understand the general environmental and climate conditions influencing switchgrass growth and make optimal land use decisions regarding switchgrass development in the GP.

  16. Rural cases of equine West Nile virus encephalomyelitis and the normalized difference vegetation index

    USGS Publications Warehouse

    Ward, M.P.; Ramsay, B.H.; Gallo, K.

    2005-01-01

    Data from an outbreak (August to October, 2002) of West Nile virus (WNV) encephalomyelitis in a population of horses located in northern Indiana was scanned for clusters in time and space. One significant (p = 0.04) cluster of case premises was detected, occurring between September 4 and 10 in the south-west part of the study area (85.70??N, 45.50??W). It included 10 case premises (3.67 case premises expected) within a radius of 2264 m. Image data were acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard a National Oceanic and Atmospheric Administration polar-orbiting satellite. The Normalized Difference Vegetation Index (NDVI) was calculated from visible and near-infrared data of daily observations, which were composited to produce a weekly-1km2 resolution raster image product. During the epidemic, a significant (p<0.01) decrease (0.025 per week) in estimated NDVI was observed at all case and control premise sites. The median estimated NDVI (0.659) for case premises within the cluster identified was significantly (p<0.01) greater than the median estimated NDVI for other case (0.571) and control (0.596) premises during the same period. The difference in median estimated NDVI for case premises within this cluster, compared to cases not included in this cluster, was greatest (5.3% and 5.1%, respectively) at 1 and 5 weeks preceding occurrence of the cluster. The NDVI may be useful for identifying foci of WNV transmission. ?? Mary Ann Liebert, Inc.

  17. Forested floristic quality index: An assessment tool for forested wetland habitats using the quality and quantity of woody vegetation at Coastwide Reference Monitoring System (CRMS) vegetation monitoring stations

    USGS Publications Warehouse

    Wood, William B.; Shaffer, Gary P.; Visser, Jenneke M.; Krauss, Ken W.; Piazza, Sarai C.; Sharp, Leigh Anne; Cretini, Kari F.

    2017-02-08

    The U.S. Geological Survey, in cooperation with the Coastal Protection and Restoration Authority of Louisiana and the Coastal Wetlands Planning, Protection and Restoration Act, developed the Forested Floristic Quality Index (FFQI) for the Coastwide Reference Monitoring System (CRMS). The FFQI will help evaluate forested wetland sites on a continuum from severely degraded to healthy and will assist in defining areas where forested wetland restoration can be successful by projecting the trajectories of change. At each CRMS forested wetland site there are stations for quantifying the overstory, understory, and herbaceous vegetation layers. Rapidly responding overstory canopy cover and herbaceous layer composition are measured annually, while gradually changing overstory basal area and species composition are collected on a 3-year cycle.A CRMS analytical team has tailored these data into an index much like the Floristic Quality Index (FQI) currently used for herbaceous marsh and for the herbaceous layer of the swamp vegetation. The core of the FFQI uses basal area by species to assess the quality and quantity of the overstory at each of three stations within each CRMS forested wetland site. Trees that are considered by experts to be higher quality swamp species like Taxodium distichum (bald cypress) and Nyssa aquatica (water tupelo) are scored higher than tree species like Triadica sebifera (Chinese tallow) and Salix nigra (black willow) that are indicators of recent disturbance. This base FFQI is further enhanced by the percent canopy cover in the overstory and the presence of indicator species at the forest floor. This systemic approach attempts to differentiate between locations with similar basal areas that are on different ecosystem trajectories. Because of these varying states of habitat degradation, paired use of the FQI and the FFQI is useful to interpret the vegetative data in transitional locations. There is often an inverse relation between the health of the

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  19. 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.

  20. Global assessment of Vegetation Index and Phenology Lab (VIP) and Global Inventory Modeling and Mapping Studies (GIMMS) version 3 products

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Okuto, E.; Kang, Y.; Opiyo, E.; Ahmed, M.

    2016-02-01

    Earth observation-based long-term global vegetation index products are used by scientists from a wide range of disciplines concerned with global change. Inter-comparison studies are commonly performed to keep the user community informed on the consistency and accuracy of such records as they evolve. In this study, we compared two new records: (1) Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index version 3 (NDVI3g) and (2) Vegetation Index and Phenology Lab (VIP) version 3 NDVI (NDVI3v) and enhanced vegetation index 2 (EVI3v). We evaluated the two records via three experiments that addressed the primary use of such records in global change research: (1) leaf area index (LAI), (2) vegetation climatology, and (3) trend analysis of the magnitude and timing of vegetation productivity. Unlike previous global studies, a unique Landsat 30 m spatial resolution and in situ LAI database for major crop types on five continents was used to evaluate the performance of not only NDVI3g and NDVI3v but also EVI3v. The performance of NDVI3v and EVI3v was worse than NDVI3g using the in situ data, which was attributed to the fusion of GIMMS and MODIS data in the VIP record. EVI3v has the potential to contribute biophysical information beyond NDVI3g and NDVI3v to global change studies, but we caution its use due to the poor performance of EVI3v in this study. Overall, the records were most consistent at northern latitudes during the primary growing season and southern latitudes and the tropics throughout much of the year, while the records were less consistent at northern latitudes during green-up and senescence, and in the great deserts of the world throughout much of the year. These patterns led to general agreement (disagreement) between trends in the magnitude (timing) of NDVI over the study period. Bias in inter-calibration of the VIP record at northernmost latitudes was suspected to contribute most to these discrepancies.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  2. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  4. Central Amazon Forest Enhanced Vegetation Index Seasonality Driven by Strongly Seasonal Leaf Flush

    NASA Astrophysics Data System (ADS)

    Wu, J.; Nelson, B. W.; Lopes, A. P.; Graca, P. M. L. D. A.; Tavares, J. V.; Prohaska, N.; Martins, G.; Saleska, S. R.

    2015-12-01

    We used an RGB camera mounted 50m above an upland forest canopy to quantify leaf phenology during 12 months for 267 upper canopy tree crowns at the Amazon Tall Tower site (59.0005ºW, 2.1433ºS). Daily images under overcast sky were selected and radiometrically intercalibrated to remove any seasonal bias from incoming radiant color balance. Seasonality of crown color was then recovered for each individual crown by plotting its greenness timeline (green chromatic coordinate). We detected rapid large-amplitude positive and negative changes in greenness. Rapid increase was attributed to leaf flush and occurred in 85% of all crowns, with 80% showing a single flush per year. The theory of photoperiod control of equatorial tropical forest leaf phenology predicts two annual peaks of leaf flush, so is not supported. Rapid negative change occurred in 42% of individuals and was caused by massive pre-flush leaf abscission (31% of all trees) or other non-green pre-flushing states (11%). Crown flushing was concentrated in the five driest months (55% of trees) compared to the five wettest months (10%). Enhanced Vegetation Index (EVI) for each of three crown phenostages was obtained from a single high spatial resolution QuickBird satellite image.These phenostages were identified using only the visible bands of QuickBird so they could be related to the same crown stages seen in the RGB tower camera images. Relative frequencies of the three crown level phenostages were monitored with the tower camera, allowing a monthly estimate of landscape-scale EVI. Free of the seasonal effects on orbital sensors from clouds, cloud shadows, aerosols or solar illumination angle and corrected for seasonal change in light quality, the camera- and QuickBird derived EVI served as an independent verification of MODIS EVI seasonality. Camera-based EVI was highly consistent with view- and solar-angle corrected MAIAC-EVI of a 3x3 km footprint centered on the tower (R = 0.95 between the two monthly curves

  5. Vegetation biomass, leaf area index, and NDVI patterns and relationships along two latitudinal transects in arctic tundra

    NASA Astrophysics Data System (ADS)

    Epstein, H. E.; Walker, D. A.; Raynolds, M. K.; Kelley, A. M.; Jia, G.; Ping, C.; Michaelson, G.; Leibman, M. O.; Kaarlejärvi, E.; Khomutov, A.; Kuss, P.; Moskalenko, N.; Orekhov, P.; Matyshak, G.; Forbes, B. C.; Yu, Q.

    2009-12-01

    Analyses of vegetation properties along climatic gradients provide first order approximations as to how vegetation might respond to a temporally dynamic climate. Until recently, no systematic study of tundra vegetation had been conducted along bioclimatic transects that represent the full latitudinal extent of the arctic tundra biome. Since 1999, we have been collecting data on arctic tundra vegetation and soil properties along two such transects, the North American Arctic Transect (NAAT) and the Yamal Arctic Transect (YAT). The NAAT spans the arctic tundra from the Low Arctic of the North Slope of Alaska to the polar desert of Cape Isachsen on Ellef Ringnes Island in the Canadian Archipelago. The Yamal Arctic Transect located in northwest Siberia, Russia, presently ranges from the forest-tundra transition at Nadym to the High Arctic tundra on Belyy Ostrov off the north coast of the Yamal Peninsula. The summer warmth indices (SWI - sum of mean monthly temperatures greater than 0°C) range from approximately 40 °C months to 3 °C months from south to north. For largely zonal sites along these transects, we systematically collected leaf area index (LAI-2000 Plant Canopy Analyzer), normalized difference vegetation index (NDVI - PSII hand-held spectro-radiometer), and vegetation biomass (clip harvests). Site-averaged LAI ranges from 1.08 to 0 along the transects, yet can be highly variable at the landscape scale. Site-averaged NDVI ranges from 0.67 to 0.26 along the transects, and is less variable than LAI at the landscape scale. Total aboveground live biomass ranges from approximately 700 g m-2 to < 50 g m-2 along the NAAT, and from approximately 1100 g m-2 to < 400 g m-2 along the YAT (not including tree biomass at Nadym). LAI and NDVI are highly correlated logarithmically (r = 0.80) for the entire dataset. LAI is significantly related to total aboveground (live plus dead) vascular plant biomass, although there is some variability in the data (r = 0.63). NDVI is

  6. DEVELOPMENT OF AN INDEX OF ALIEN SPECIES INVASIVENESS: AN AID TO ASSESSING RIPARIAN VEGETATION CONDITION

    EPA Science Inventory

    Many riparian areas are invaded by alien plant species that negatively affect native species composition, community dynamics and ecosystem properties. We sampled vegetation along reaches of 31 low order streams in eastern Oregon, and characterized species assemblages at patch an...

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

    PubMed

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

    2002-01-01

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

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

    USGS Publications Warehouse

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

    2002-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  10. Spatio-temporal distribution of vegetation index and its influencing factors—a case study of the Jiaozhou Bay, China

    NASA Astrophysics Data System (ADS)

    Zheng, Yang; Yu, Ge

    2016-10-01

    The coastal zone is an area characterized by intense interaction between land and sea, high sensitivity to regional environmental changes, and concentrated human activities. Little research has investigated vegetation cover changes in coastal zones resulting from climate change and land-use change, with a lack of knowledge about the driving mechanism. Normalized difference vegetation index (NDVI) can be used as an indicator for change of the coastal environment. In this study, we analyzed the interannual changes and spatial distribution of NDVI in the coastal zone around Jiaozhou Bay in Qingdao, a coastal city undergoing rapid urbanization in northeast China. The underlying causes of NDVI variations were discussed in the context of climate change and land-use change. Results showed that the spatio-temporal distribution of NDVI displayed high spatial variability in the study area and showed a typical trend of gradually increasing from coastal to inland regions. The significant increase area of NDVI was mainly found in newly added construction land, extending along the coastline towards the inland. Land vegetation cover demonstrated a certain response relationship to sea-land climate change and land-based activities. The impact of land-based human activities was slightly greater than that of sea-land climate change for land vegetation cover. The results indicate that promoting ecological policies can build an ecological security framework of vegetation suitable for the resource characteristics of coastal cities. The framework will buffer the negative effects of sea-land climate change and land-based human activities on vegetation cover and thereby achieve the balance of regional development and ecological benefits in the coastal zone.

  11. Study of a Vegetation Index Based on HJ CCD Data's top-of-atmosphere reflectance and FPAR Inversion

    NASA Astrophysics Data System (ADS)

    Dong, Taifeng; Wu, Bingfang; Meng, Jihua

    2014-03-01

    The Fraction of Photosynthetically Active Radiation (FPAR)absorbed by plant canopies is a key parameter for monitoring crop condition and estimating crop yield. In general, it is necessary to obtain Top of Canopy (TOC) reflectance from optical remote sensing data in digital number through atmospheric correction procedures before retrieving FPAR. However, there are a few of uncertainties that existe in the process of atmosphere correction and reduced the quality of TOC. This paper presents a vegetation index based on Top-of-Atmosphere (TOA) reflectance derived from HJ-1 CCD satellite for estimating direct crop FPAR. The vegetation index (HJVI) was designed based on the simulated results of a canopy-atmosphere radiative transfer model, including TOA reflectance and corresponded FPAR. The HJVI had taken the advantages of information in the green, the red and the near-infrared spectral domainswith with a aim of reducing the atmospheric effect and enhancing the sensitive to green vegetation. The HJVI was used to estimate soybean FPAR directly and validated using field measurements. The result indicated that the inversion algorithm produced a good relationship between the prediction and measurement (R2 = 0.546, RMSE = 0.083) and the HJVI showed high potential for estimating FPAR based on the HJ-1 TOA reflectance directly.

  12. A survey of drought and Variation of Vegetation by statistical indexes and remote sensing (Case study: Jahad forest in Bandar Abbas)

    NASA Astrophysics Data System (ADS)

    Tamassoki, E.; Soleymani, Z.; Bahrami, F.; Abbasgharemani, H.

    2014-06-01

    The damages of drought as a climatic and creeping phenomenon are very enormous specially in deserts. Necessity of management and conflict with it is clear. In this case vegetation are damaged too, and even are changed faster. This paper describes the process of vegetation changes and surveys it with drought indexes such as statistical and remote sensing indexes and correlation between temperature and relative humidity by Geographical Information System (GIS) and Remote Sensing (RS) in forest park of Bandar Abbas in successive years. At the end the regression and determination-coefficient for showing the importance of droughts survey are computed. Results revealed that the correlation between vegetation and indexes was 0.5. The humidity had maximum correlation and when we close to 2009 the period of droughts increase and time intervals decrease that influence vegetation enormously and cause the more area lost its vegetation.

  13. Relations between productivity, climate, and normalized difference vegetation index in the central Great Plains

    NASA Astrophysics Data System (ADS)

    Wang, Jue

    Understanding the influences of climate on productivity remains a major challenge in landscape ecology. Satellite remote sensing of normalized difference vegetation index (NDVI) provides a useful tool to study landscape patterns, based on generalization of local measurements, and to examine relations between climate and variation in productivity. This dissertation examines temporal and spatial relations between NDVI, productivity, and climatic factors over the course of nine years in the central Great Plains. Two general findings emerge: (1) integrated NDVI is a reliable measure of production, as validated with ground-based productivity measurements; and (2) precipitation is the primary factor that determines spatial and temporal patterns of NDVI. NDVI, integrated over appropriate time intervals, is strongly correlated with ground productivity measurements in forests, grasslands, and croplands. Most tree productivity measurements (tree ring size, tree diameter growth, and seed production) are strongly correlated with NDVI integrated for a period during the early growing season; foliage production is most strongly correlated with NDVI integrated over the entire growing season; and tree height growth corresponds with NDVI integrate during the previous growing season. Similarly, productivity measurements for herbaceous plants (grassland biomass and crop yield) are strongly correlated with NDVI. Within the growing season, the temporal pattern of grassland biomass production covaries with NDVI, with a four-week lag time. Across years, grassland biomass production covaries with NDVI integrated from part to all of the current growing season. Corn and wheat yield are most strongly related to NDVI integrated from late June to early August and from late April to mid-May, respectively. Precipitation strongly influences both temporal and spatial patterns of NDVI, while temperature influences NDVI only during the early and late growing season. In terms of temporal patterns

  14. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments.

    PubMed

    Nikolov, Ned; Zeller, Karl

    2006-06-01

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange.

  15. 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.

  16. Estimating wide-area evapotranspiration at multiple scales using optical vegetation index methods

    NASA Astrophysics Data System (ADS)

    Nagler, P. L.; Glenn, E.; Jarchow, C.; Barreto-munoz, A.; Didan, K.; Nouri, H.; Anderson, S.; Doody, T.

    2015-12-01

    We provide three examples of remotely sensed evapotranspiration (ET) from our research using optical methods at different spatial scales and applied to (i) urban landscapes, (ii) riparian vegetation in Mexico in response to river flows, and (iii) riparian vegetation in Australia in response to different flood frequencies. In the first example, we will compare ground methods for estimating ET by horticultural plants with scaled estimates of ET using both WV2 NDVI imagery and MODIS EVI which were used to determine water requirements of urban gardens in Adelaide, South Australia. In the second example, we will present the impacts of a 2014 environmental flow, released to the Colorado River delta in Mexico, on vegetation greenness and estimated ET using Landsat and MODIS data. Lastly, we will show the results for scaling sap flow transpiration of Red Gum (Eucalyptus camaldulensis) and associated vegetation along the Murrumbidgee River (a tributary of the River Murray) to MODIS-based estimates of evapotranspiration in the wider riparian reaches along the river. These three applications range in spatial scales from a few hectares for urban gardens, to several thousand hectares for the riparian ecosystem in Mexico, to a regional scale of a hundred thousand hectares for the Red Gum forest in Australia. Remote sensing methods can produce accurate estimates of ET across wide temporal and spatial scales, limited mainly by the accuracy of the ground methods by which they are calibrated and validated.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. Satellite-derived leaf-area-index and vegetation maps as input to global carbon cycle models - A hierarchical approach

    NASA Technical Reports Server (NTRS)

    Badhwar, G. D.; Macdonald, R. B.; Mehta, N. C.

    1986-01-01

    A hierarchical procedure for developing a leaf area index (LAI) map of deciduous boreal forests is studied. The collection of spectral reflectance data from the Boundary Waters Canoe area in Minnesota using helicopter-, high-altitude aircraft-, and Landsat-mounted spectral sensors is described. The relationship between LAI and biomass and the reflectance ratio is analyzed. The sensitivity of canopy reflectance in the visible and infrared to the LAI of the canopy for various boreal forest species is evaluated. The data reveal that Landsat data are useful for producing LAI maps of deciduous forest areas and the maps provide data which clarifies the function of vegetation in the global carbon cycle models.

  20. Mean and inter-year variation of growing-season normalized difference vegetation index for the Sahel 1981-1989

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.; Newcomb, W. W.; Los, S. O.; Prince, S. D.

    1991-01-01

    Images are presented that show the mean and coefficient of variation of nine years (1981-1989) of NOAA AVHRR normalized difference vegetation index (NDVI) data for the growing season (July-October) in Africa, north of the equator. The variation in the growing season NDVI is represented by the coefficient of variation image that shows the large variation in the Sahelian growing season between years. It is concluded that these images illustrate some aspects of the perspective being brought to regional and continental scale processes by coarse resolution satellite sensors and the potential of these sensors to provide consistent, long-term datasets.

  1. An approach to compute the C factor for universal soil loss equation using EOS-MODIS vegetation index (VI)

    NASA Astrophysics Data System (ADS)

    Li, Hui; He, Huizhong; Chen, Xiaoling; Zhang, Lihua

    2008-12-01

    C factor, known as cover and management factor in USLE, is one of the most important factors since it represents the combined effects of plant, soil cover and management on erosion, whereas it also most easily changed variables by men for it itself is time-variant and the uncertainty nature. So it's vital to compute C factor properly in order to model erosion effectively. In this paper we attempt to present a new method for calculating C value using Vegetation Index (VI) derived from multi-temporal MODIS imagery, which can estimate C factor in a more scientific way. Based on the theory that C factor is strongly correlated with VI, the average annual C value is estimated by adding the VI value of three growth phases within a year with different weights. Modified Fournier Index (MFI) is employed to determine the weight of each growth phase for the vegetation growth and agricultural activities are significantly influenced by precipitation. The C values generated by the proposed method were compared with that of other method, and the results showed that the results of our method is highly correlated with the others. This study is helpful to extract C value from satellite data in a scientific and efficient way, which in turn could be used to facilitate the prediction of erosion.

  2. A Rapidly Prototyped Vegetation Dryness Index Evaluated for Wildfire Risk Assessment at Stennis Space Center

    NASA Technical Reports Server (NTRS)

    Ross, Kenton; Graham, William; Prados, Don; Spruce, Joseph

    2007-01-01

    MVDI, which effectively involves the differencing of NDMI and NDVI, appears to display increased noise that is consistent with a differencing technique. This effect masks finer variations in vegetation moisture, preventing MVDI from fulfilling the requirement of giving decision makers insight into spatial variation of fire risk. MVDI shows dependencies on land cover and phenology which also argue against its use as a fire risk proxy in an area of diverse and fragmented land covers. The conclusion of the rapid prototyping effort is that MVDI should not be implemented for SSC decision support.

  3. Spectra and vegetation index variations in moss soil crust in different seasons, and in wet and dry conditions

    NASA Astrophysics Data System (ADS)

    Fang, Shibo; Yu, Weiguo; Qi, Yue

    2015-06-01

    Similar to vascular plants, non-vascular plant mosses have different periods of seasonal growth. There has been little research on the spectral variations of moss soil crust (MSC) over different growth periods. Few studies have paid attention to the difference in spectral characteristics between wet MSC that is photosynthesizing and dry MSC in suspended metabolism. The dissimilarity of MSC spectra in wet and dry conditions during different seasons needs further investigation. In this study, the spectral reflectance of wet MSC, dry MSC and the dominant vascular plant (Artemisia) were characterized in situ during the summer (July) and autumn (September). The variations in the normalized difference vegetation index (NDVI), biological soil crust index (BSCI) and CI (crust index) in different seasons and under different soil moisture conditions were also analyzed. It was found that (1) the spectral characteristics of both wet and dry MSCs varied seasonally; (2) the spectral features of wet MSC appear similar to those of the vascular plant, Artemisia, whether in summer or autumn; (3) both in summer and in autumn, much higher NDVI values were acquired for wet than for dry MSC (0.6 ∼ 0.7 vs. 0.3 ∼ 0.4 units), which may lead to misinterpretation of vegetation dynamics in the presence of MSC and with the variations in rainfall occurring in arid and semi-arid zones; and (4) the BSCI and CI values of wet MSC were close to that of Artemisia in both summer and autumn, indicating that BSCI and CI could barely differentiate between the wet MSC and Artemisia.

  4. Use of the Normalized Difference Vegetation Index to Assess Vegetative Nutritive Value in Halophytic Graminoid Habitat across Alaska's Arctic Coastal Plain

    NASA Astrophysics Data System (ADS)

    Hogrefe, K. R.; Ward, D. H.; Budde, M. E.; Ruthrauff, D. R.; Hupp, J. W.

    2015-12-01

    Climate change will likely alter the seasonal nutrient abundance and general distribution of halophytic graminoid (salt marsh) habitat across the Arctic Coastal Plain. Halophytic graminoids are key forage for newly hatched Black Brant, Lesser Snow and Greater White-fronted Geese and the timing and degree of seasonal nutrient abundance in these plants is critical for gosling growth and survival. After 5 years of research (culminating in 2015) under the USGS Alaska Science Center's Changing Arctic Ecosystems Initiative, we found strong relationships between the Normalized Difference Vegetation Index (NDVI) and nutrient abundance (N g/m2) and availability (%N) in halophytic graminoid habitat. The relationships between NDVI and nutrient abundance and availability were strong whether using NDVI derived from high (spectrometer), moderate (WorldView-2 satellite) or low (eMODIS satellite) resolution data. Correlations established and validated at one location were used to predict nutrient abundance using NDVI readings from other locations, allowing interpretation of satellite derived NDVI in terms of nutrient abundance across broad areas of mapped salt marsh habitat. Further, NDVI seasonal timelines were used to predict the timing of peak nutrient availability using the period of most rapid increase in NDVI value. Currently, we are using WorldView-2 imagery to create vegetation maps of the central Arctic coastal zone (~20 km inland) of Alaska, covering approximately 1000 km of coastline, with a focus on identifying all salt marshes. Such maps will enable monitoring programs and allow for modeling to predict spatial and temporal changes in halophytic graminoid habitat and the nutrients available to geese in the early stages of life.

  5. Adherence to a Vegetable-Fruit-Soy Dietary Pattern or the Alternative Healthy Eating Index Is Associated with Lower Hip Fracture Risk among Singapore Chinese12

    PubMed Central

    Dai, Zhaoli; Butler, Lesley M.; van Dam, Rob M.; Ang, Li-Wei; Yuan, Jian-Min; Koh, Woon-Puay

    2014-01-01

    Data on overall dietary pattern and osteoporotic fracture risk from population-based cohorts are limited, especially from Asian populations. This study examined the relation between overall diet and hip fracture risk by using principal components analysis (PCA) to identify dietary pattern specific to the study population and by using the Alternative Healthy Eating Index (AHEI) 2010 to assess dietary quality. The Singapore Chinese Health Study is a prospective population-based cohort that enrolled 63,257 Chinese men and women (including both pre- and postmenopausal women) aged 45–74 y between 1993 and 1998 in Singapore. Habitual diet was assessed by using a validated food-frequency questionnaire. Two dietary patterns, the vegetable-fruit-soy (VFS) pattern and the meat-dim-sum (MDS) pattern, were derived by PCA. Overall dietary quality was assessed according to the AHEI 2010, which was defined a priori for chronic disease prevention. A Cox regression model was applied with adjustment for potential confounders. In both genders, higher scores for the VFS pattern and the AHEI 2010 were associated with lower risk of hip fracture in a dose-dependent manner (all P-trend ≤ 0.008). Compared with the lowest quintile, participants in the highest quintile had a 34% reduction in risk (HR: 0.66; 95% CI: 0.55, 0.78) for the VFS pattern and a 32% reduction in risk (HR: 0.68; 95% CI: 0.58, 0.79) for the AHEI 2010. The MDS pattern score was not associated with hip fracture risk. An Asian diet rich in plant-based foods, namely vegetables, fruit, and legumes such as soy, may reduce the risk of hip fracture. PMID:24572035

  6. Estimates of evapotranspiration for riparian sites (Eucalyptus) in the Lower Murray -Darling Basin using ground validated sap flow and vegetation index scaling techniques

    NASA Astrophysics Data System (ADS)

    Doody, T.; Nagler, P. L.; Glenn, E. P.

    2014-12-01

    Water accounting is becoming critical globally, and balancing consumptive water demands with environmental water requirements is especially difficult in in arid and semi-arid regions. Within the Murray-Darling Basin (MDB) in Australia, riparian water use has not been assessed across broad scales. This study therefore aimed to apply and validate an existing U.S. riparian ecosystem evapotranspiration (ET) algorithm for the MDB river systems to assist water resource managers to quantify environmental water needs over wide ranges of niche conditions. Ground-based sap flow ET was correlated with remotely sensed predictions of ET, to provide a method to scale annual rates of water consumption by riparian vegetation over entire irrigation districts. Sap flux was measured at nine locations on the Murrumbidgee River between July 2011 and June 2012. Remotely sensed ET was calculated using a combination of local meteorological estimates of potential ET (ETo) and rainfall and MODIS Enhanced Vegetation Index (EVI) from selected 250 m resolution pixels. The sap flow data correlated well with MODIS EVI. Sap flow ranged from 0.81 mm/day to 3.60 mm/day and corresponded to a MODIS-based ET range of 1.43 mm/day to 2.42 mm/day. We found that mean ET across sites could be predicted by EVI-ETo methods with a standard error of about 20% across sites, but that ET at any given site could vary much more due to differences in aquifer and soil properties among sites. Water use was within range of that expected. We conclude that our algorithm developed for US arid land crops and riparian plants is applicable to this region of Australia. Future work includes the development of an adjusted algorithm using these sap flow validated results.

  7. Refractive index detection range adjustable liquid-core fiber optic sensor based on surface plasmon resonance and a nano-porous silica coating

    NASA Astrophysics Data System (ADS)

    Chen, Yuzhi; Li, Xuejin; Zhou, Huasheng; Hong, Xueming; Geng, Youfu

    2016-09-01

    A liquid-core fiber optic surface plasmon resonance sensor with an adjustable nano-porous silica coating is first presented in this paper. By adjusting the refractive index of the nano-porous silica coating, the sensor can be used in different refractive index detection ranges. A low refractive index interval of 1.33-1.34 and a high refractive index interval of 1.42-1.44 are taken as examples to be investigated. Results show that our sensor works well in these two intervals by using appropriate nano-porous silica coatings. The highest sensitivities of the low and high refractive index intervals are obtained to be 5840 nm/RIU and 5120 nm/RIU, respectively. In addition, the sensing performances and the working wavelengths can be adjusted to meet different working requirements by changing the refractive index of the nano-porous silica coating. We also take the single mode incidence cases to explain the effects of different single incident light modes on the sensing performances.

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  9. Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring

    NASA Astrophysics Data System (ADS)

    Peng, D.; Hu, Y.; Li, Z.

    2016-05-01

    It is important to detect and quantify deforestation to guide strategic decisions regarding environment, socioeconomic development, and climate change. In the present study, we conducted a field experiment to examine spectral reflectance and vegetation index changes in poplar and locust tree foliage with different leaf area indices over the course of three sunny days, following tree removal from the canopy. The spectral reflectance of foliage from harvested trees was measured using an ASD FieldSpec Prospectroradiometer; synchronous meteorological data were also obtained. We found that reflectance in short-wave infrared and red-edge reflectance was more time sensitive after tree removal than reflectance in other spectral regions, and that the normalized difference water index (NDWI) and the red-edge chlorophyll index (CIRE) were the preferred indicators of these changes from several indices evaluated. Synthesized meteorological environments were found to influence water and chlorophyll contents after tree removal, and this subsequently changed the spectral canopy reflectance. Our results indicate the potential for such tree removal to be detected with NDWI or CIRE from the second day of a deforestation event.

  10. Reciprocal interactions and adjustments between fluvial landforms and vegetation dynamics in river corridors: A review of complementary approaches

    NASA Astrophysics Data System (ADS)

    Corenblit, Dov; Tabacchi, Eric; Steiger, Johannes; Gurnell, Angela M.

    2007-09-01

    Until recently, one-way relationships between flow dynamics, geomorphology and plant ecology were considered dominantly when studying the functioning of river systems, whereby fluvial landforms and hydrogeomorphic processes drive the evolution of riparian plant communities. However, biological communities may significantly control geomorphic processes and have strong impacts on landform dynamics. In order to fully identify the processes linked to river dynamics (changes in time and space of fluvial landforms and associated plant communities), conceptual multidisciplinary progress is clearly needed. To understand the mutual interactions and feedbacks between fluvial landforms and vegetation community dynamics, this paper presents a detailed literature review of fluvial geomorphology, riparian plant ecology and hydraulic engineering knowledge. The historical and recent development of ecological plant succession theory toward the integration of hydrogeomorphic disturbances is discussed as well as the integration of vegetation within geomorphology as a significant landform control factor, incorporating both hydrogeomorphic controls on riparian vegetation dynamics and mechanical impacts of vegetation structures on flow properties and sediment dynamics. Recent progress in ecology, hydraulic engineering and fluvial geomorphology emphasises interdependence between biological and physical forms and processes. Based on this literature review, a 'fluvial biogeomorphic succession' concept is proposed to link fluvial landform and riparian vegetation community evolution within a bi-directional model. The succession of fluvial landforms and associated vegetation communities is composed of four main critical phases that represent a shift in the relative dominance of hydrogeomorphic and ecological processes as a response to biostabilisation and passive bioconstruction processes. The positive feedbacks associated with this shift lead to the development of characteristic

  11. Consumption Frequency of Foods Away from Home Linked with Higher Body Mass Index and Lower Fruit and Vegetable Intake among Adults: A Cross-Sectional Study

    PubMed Central

    Seguin, Rebecca A.; Aggarwal, Anju; Vermeylen, Francoise; Drewnowski, Adam

    2016-01-01

    Introduction. Consumption of foods prepared away from home (FAFH) has grown steadily since the 1970s. We examined the relationship between FAFH and body mass index (BMI) and fruit and vegetable (FV) consumption. Methods. Frequency of FAFH, daily FV intake, height and weight, and sociodemographic data were collected using a telephone survey in 2008-2009. Participants included a representative sample of 2,001 adult men and women (mean age 54 ± 15 years) residing in King County, WA, with an analytical sample of 1,570. Frequency of FAFH was categorized as 0-1, 2–4, or 5+ times per week. BMI was calculated from self-reported height and weight. We examined the relationship between FAFH with FV consumption and BMI using multivariate models. Results. Higher frequency of FAFH was associated with higher BMI, after adjusting for age, income, education, race, smoking, marital status, and physical activity (women: p = 0.001; men: p = 0.003). There was a negative association between frequency of FAFH and FV consumption. FAFH frequency was significantly (p < 0.001) higher among males than females (43.1% versus 54.0% eating out 0-1 meal per week, resp.). Females reported eating significantly (p < 0.001) more FV than males. Conclusion. Among adults, higher frequency of FAFH was related to higher BMI and less FV consumption. PMID:26925111

  12. The sensitivity based estimation of leaf area index from spectral vegetation indices

    NASA Astrophysics Data System (ADS)

    Gonsamo, Alemu; Pellikka, Petri

    2012-06-01

    The performances of seven spectral vegetation indices (SVIs) were investigated for their sensitivity to a varying range of LAI. The evaluation was carried out for a dataset collected using SPOT 5 HRG 10 m imagery and simulated spectra using PROSPECT + SAIL reflectance models with varying soil reflectance backgrounds. The aim was to evaluate the applicability of multiple SVIs for LAI mapping based on the sensitivity analysis. The main sensitivity function was the first derivative of the regression function divided by the standard errors of the SVIs. In addition, the sensitivity of individual band and SVI with LAI was carried out using the ordinary least squares regressions. A new SVI, reduced infrared simple ratio (RISR) was developed based on an empirical red modification to infrared simple ratio (ISR) SVI. The new SVI was demonstrated which has significantly reduced the effect of soil background reflectance while maintaining high sensitivity to a wide range of LAI.

  13. Analytical Derivation of the Vegetation Optical Depth from the Microwave Polarization Difference Index

    NASA Technical Reports Server (NTRS)

    Meesters, Antoon G. C. A.; DeJeu, Richard A. M.; Owe, Manfred

    2006-01-01

    A numerical solution for the canopy optical depth in an existing microwave-based land surface parameter retrieval model is presented. The optical depth is derived from the microwave polarization difference index and the dielectric constant of the soil. The original procedure used an approximation in the form of a logarithmic decay function to define this relationship, and was derived through a series of lengthy polynomials. These polynomials had to be recalculated when the scattering albedo or antenna incidence angle changes. The new procedure is computationally more efficient and accurate.

  14. Land Surface Temperature Retrieval in Wetlands Using Normalized Difference Vegetation Index-Emissivity Estimation and ASTER Emissivity Product

    NASA Astrophysics Data System (ADS)

    Muro, Javier; Heinmann, Sascha; Strauch, Adrian; Menz, Gunter

    2016-08-01

    Land Surface Temperature (LST) has the potential to act as a continuous indicator of the ecological status of wetlands. Accurate emissivity values are required in order to calculate precise LST. We test two emissivity retrieval methods and their influence on LST calculated from a Landsat 7 image of a highly dynamic wetland in Southern Spain. LST calculated using NDVI (Normalized Difference Vegetation Index) threshold estimations and the ASTER emissivity product are compared. The results show differences of around 0-1 K for most land covers, and up to 3 K for areas of bare soil when Landsat and ASTER images have the same acquisition date. Tests using Landsat and ASTER images from different seasons do not show greater differences between both LSTs. This has important implications for automated LST retrieval methods, such as the one planed by the USGS using Landsat and ASTER emissivity products.

  15. Classifying cropping area of middle Heihe River Basin in China using multitemporal Normalized Difference Vegetation Index data

    NASA Astrophysics Data System (ADS)

    Han, Huibang; Ma, Mingguo; Wang, Xufeng; Ma, Shoucun

    2014-01-01

    Accurate information regarding the structure of crops is critical for the improvement and optimization of land surface models. Multitemporal remote sensing imagery is more effective to determine the crop structure than the single-temporal images because they contain phenological information. Crop structure was extracted based on time series of moderate-resolution imaging spectroradiometer (MODIS) data in the middle Heihe River Basin. A time series of Normalized Difference Vegetation Index (NDVI) data with a 3-day temporal resolution was composed based on daily MODIS reflectance products (MOD 09) from January to December 2011. A total of 120 scenes of composited imagery were integrated into an image data cube of NDVI time series, which was used to extract crop structure for the study area. The spectral curves of corn, wheat, rape, vegetables, and other crops are based on both in situ measurements and visual interpretation. The major crop types were classified by using the adaptive boosting (Adaboost) and support vector machine (SVM) algorithms. The results show that the classification accuracy of Adaboost and SVM was 86.01% and 70.28%, respectively, with Kappa coefficients of 0.8351 and 0.6438, respectively. Summarizing the classification methods used in this study effectively characterize the spatial distribution of the main crops.

  16. Assessing mining impacts utilizing a Landsat derived vegetation moisture index to characterize impacts of longwall subsidence on forest ecosystems

    NASA Astrophysics Data System (ADS)

    Pfeil-McCullough, E. K.; Bain, D.

    2015-12-01

    Subsidence from longwall coal mining impacts the surface and sub-surface hydrology in overlying areas. During longwall mining, coal is completely removed in large rectangular panels and the overlying rock collapses into the void. Though the hydrologic impacts of longwall mine subsidence on overlying vegetation have been studied in more arid systems, in humid-temperate regions these effects are not well understood. In particular, it is not clear how longwall mining will impact water availability to forests. To explore potential impacts, a geospatial analysis of tree canopy water content using Landsat satellite imagery of southwestern Pennsylvania was carried out. The normalized difference moisture index (NDMI) derived from Landsat imagery was applied to expose patterns of vegetation water stress, which were then compared across a temporal gradient of mined panels. NDMI values associated with panels from 2000 through 2014 were assessed within September 2014 Landsat NDMI imagery and compared to a population of pixels un-impacted by mining. This study elucidates mining impacts to forest canopies and the landscape features driving patterns of tree canopy moisture content in southwestern, PA.

  17. Seasonality of Rotavirus in South Asia: A Meta-Analysis Approach Assessing Associations with Temperature, Precipitation, and Vegetation Index

    PubMed Central

    Jagai, Jyotsna S.; Sarkar, Rajiv; Castronovo, Denise; Kattula, Deepthi; McEntee, Jesse; Ward, Honorine; Kang, Gagandeep; Naumova, Elena N.

    2012-01-01

    Background Rotavirus infection causes a significant proportion of diarrhea in infants and young children worldwide leading to dehydration, hospitalization, and in some cases death. Rotavirus infection represents a significant burden of disease in developing countries, such as those in South Asia. Methods We conducted a meta-analysis to examine how patterns of rotavirus infection relate to temperature and precipitation in South Asia. Monthly rotavirus data were abstracted from 39 published epidemiological studies and related to monthly aggregated ambient temperature and cumulative precipitation for each study location using linear mixed-effects models. We also considered associations with vegetation index, gathered from remote sensing data. Finally, we assessed whether the relationship varied in tropical climates and humid mid-latitude climates. Results Overall, as well as in tropical and humid mid-latitude climates, low temperature and precipitation levels are significant predictors of an increased rate of rotaviral diarrhea. A 1°C decrease in monthly ambient temperature and a decrease of 10 mm in precipitation are associated with 1.3% and 0.3% increase above the annual level in rotavirus infections, respectively. When assessing lagged relationships, temperature and precipitation in the previous month remained significant predictors and the association with temperature was stronger in the tropical climate. The same association was seen for vegetation index; a seasonal decline of 0.1 units results in a 3.8% increase in rate of rotavirus. Conclusions In South Asia the highest rate of rotavirus was seen in the colder, drier months. Meteorological characteristics can be used to better focus and target public health prevention programs. PMID:22693594

  18. Mapping rice cropping systems using Landsat-derived Renormalized Index of Normalized Difference Vegetation Index (RNDVI) in the Poyang Lake Region, China

    NASA Astrophysics Data System (ADS)

    Li, Peng; Jiang, Luguang; Feng, Zhiming; Sheldon, Sage; Xiao, Xiangming

    2016-06-01

    Mapping rice cropping systems with optical imagery in multiple cropping regions is challenging due to cloud contamination and data availability; development of a phenology-based algorithm with a reduced data demand is essential. In this study, the Landsat-derived Renormalized Index of Normalized Difference Vegetation Index (RNDVI) was proposed based on two temporal windows in which the NDVI values of single and early (or late) rice display inverse changes, and then applied to discriminate rice cropping systems. The Poyang Lake Region (PLR), characterized by a typical cropping system of single cropping rice (SCR, or single rice) and double cropping rice (DCR, including early rice and late rice), was selected as a testing area. The results showed that NDVI data derived from Landsat time-series at eight to sixteen days captures the temporal development of paddy rice. There are two key phenological stages during the overlapping growth period in which the NDVI values of SCR and DCR change inversely, namely the ripening phase of early rice and the growing phase of single rice as well as the ripening stage of single rice and the growing stage of late rice. NDVI derived from scenes in two temporal windows, specifically early August and early October, was used to construct the RNDVI for discriminating rice cropping systems in the polder area of the PLR, China. Comparison with ground truth data indicates high classification accuracy. The RNDVI approach highlights the inverse variations of NDVI values due to the difference of rice growth between two temporal windows. This makes the discrimination of rice cropping systems straightforward as it only needs to distinguish whether the candidate rice type is in the period of growth (RNDVI<0) or senescence (RNDVI>0).

  19. Trends in the normalized difference vegetation index (NDVI) associated with urban development in arctic and subarctic Western Siberia

    NASA Astrophysics Data System (ADS)

    Outten, S.; Miles, V.; Ezau, I.

    2015-12-01

    Changes in normalized difference vegetation index (NDVI) in the high Arctic have been reliably documented, with widespread "greening" (increase in NDVI), specifically along the northern rim of Eurasia and Alaska. Whereas in West Siberia south of 65N, widespread "browning" (decrease in NDVI) has been noted, although the causes remain largely unclear. In this study we report results of statistical analysis of the spatial and temporal changes in NDVI around 28 major urban areas in the arctic and subarctic Western Siberia. Exploration and exploitation of oil and gas reserves has led to rapid industrialization and urban development in the region. This development has significant impact on the environment and particularly in the vegetation cover in and around the urbanized areas. The analysis is based on 15 years (2000-2014) of high-resolution (250 m) Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired for summer months (June through August) over the entire arctic and subarctic Western Siberian region. The analysis shows that the NDVI background trends are generally in agreement with the trends reported in previous coarse-resolution NDVI studies. Our study reveals greening over the arctic (tundra and tundra-forest) part of the region. Simultaneously, the southern (boreal taiga forest) part is browning, with the more densely vegetation areas or areas with highest NDVI, particularly along Ob River showing strong negative trend. The unexpected and interesting finding of the study is statistically robust indication of the accelerated increase of NDVI ("greening") in the older urban areas. Many Siberian cities become greener even against the decrease in the NDVI background. Moreover, interannual variations of urban NDVI are not coherent with the NDVI background variability. We also find that in tundra zones, NDVI values are higher in a 5-10 km buffer zone around the city edge than in rural areas (40 km distance from the city edge), and in taiga in a 5-10 km

  20. Empirical Relationship Between Leaf Biomass of Red Pine Forests and Enhanced Vegetation Index in South Korea Using LANDSAT-5 TM

    NASA Astrophysics Data System (ADS)

    Gusso, A.; Lee, J.; Son, Y.; Son, Y. M.

    2016-06-01

    Research on forest carbon (C) dynamics has been undertaken due to the importance of forest ecosystems in national C inventories. Currently, the C sequestration of South Korean forests surpasses that of other countries. In South Korea, Pinus densiflora (red pine) is the most abundant tree species. Thus, understanding the growth rate and biomass evolution of red pine forest in South Korea is important for estimating the forest C dynamics. In this paper, we derived empirical relationship between foliage biomass and the no blue band enhanced vegetation index (EVI-2) profile using both field work and multi-temporal Landsat-5 TM remote sensing data to estimate the productivity of forest biomass in South Korea. Our analysis combined a set of 84 Landsat-5 TM images from 28 different dates between 1986 and 2008 to study red pine forest development over time. Field data were collected from 30 plots (0.04 ha) that were irregularly distributed over South Korea. Individual trees were harvested by destructive sampling, and the age of trees were determined by the number of tree rings. The results are realistic (R2&thinsp=&thinsp0.81, p < 0.01) and suggest that the EVI-2 index is able to adequately represent the development profile of foliage biomass in red pine forest growth.

  1. Comparison of sap flux, moisture flux tower and MODIS enhanced vegetation index methods for estimating riparian evapotranspiration

    USGS Publications Warehouse

    Nagler, Pamela L.; Glenn, Edward P.; Morino, Kiyomi; Neale, Christopher M.U; Cosh, Michael H.

    2010-01-01

    Riparian evapotranspiration (ET) was measured on a salt cedar (Tamarix spp.) dominated river terrace on the Lower Colorado River from 2007 to 2009 using tissue-heat-balance sap flux sensors at six sites representing very dense, medium dense, and sparse stands of plants. Salt cedar ET varied markedly across sites, and sap flux sensors showed that plants were subject to various degrees of stress, detected as mid-day depression of transpiration and stomatal conductance. Sap flux results were scaled from the leaf level of measurement to the stand level by measuring plant-specific leaf area index and fractional ground cover at each site. Results were compared to Bowen ratio moisture tower data available for three of the sites. Sap flux sensors and flux tower results ranked the sites the same and had similar estimates of ET. A regression equation, relating measured ET of salt cedar and other riparian plants and crops on the Lower Colorado River to the Enhanced Vegetation Index from the MODIS sensor on the Terra satellite and reference crop ET measured at meteorological stations, was able to predict actual ET with an accuracy or uncertainty of about 20%, despite between-site differences for salt cedar. Peak summer salt cedar ET averaged about 6 mm d-1 across sites and methods of measurement.

  2. Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index.

    PubMed

    Cronin, Robert M; Field, Julie R; Bradford, Yuki; Shaffer, Christian M; Carroll, Robert J; Mosley, Jonathan D; Bastarache, Lisa; Edwards, Todd L; Hebbring, Scott J; Lin, Simon; Hindorff, Lucia A; Crane, Paul K; Pendergrass, Sarah A; Ritchie, Marylyn D; Crawford, Dana C; Pathak, Jyotishman; Bielinski, Suzette J; Carrell, David S; Crosslin, David R; Ledbetter, David H; Carey, David J; Tromp, Gerard; Williams, Marc S; Larson, Eric B; Jarvik, Gail P; Peissig, Peggy L; Brilliant, Murray H; McCarty, Catherine A; Chute, Christopher G; Kullo, Iftikhar J; Bottinger, Erwin; Chisholm, Rex; Smith, Maureen E; Roden, Dan M; Denny, Joshua C

    2014-01-01

    Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record (EHR)-based PheWAS to explore pleiotropy of genetic variants in the fat mass and obesity associated gene (FTO), some of which have been previously associated with obesity and type 2 diabetes (T2D). We used a population of 10,487 individuals of European ancestry with genome-wide genotyping from the Electronic Medical Records and Genomics (eMERGE) Network and another population of 13,711 individuals of European ancestry from the BioVU DNA biobank at Vanderbilt genotyped using Illumina HumanExome BeadChip. A meta-analysis of the two study populations replicated the well-described associations between FTO variants and obesity (odds ratio [OR] = 1.25, 95% Confidence Interval = 1.11-1.24, p = 2.10 × 10(-9)) and FTO variants and T2D (OR = 1.14, 95% CI = 1.08-1.21, p = 2.34 × 10(-6)). The meta-analysis also demonstrated that FTO variant rs8050136 was significantly associated with sleep apnea (OR = 1.14, 95% CI = 1.07-1.22, p = 3.33 × 10(-5)); however, the association was attenuated after adjustment for body mass index (BMI). Novel phenotype associations with obesity-associated FTO variants included fibrocystic breast disease (rs9941349, OR = 0.81, 95% CI = 0.74-0.91, p = 5.41 × 10(-5)) and trends toward associations with non-alcoholic liver disease and gram-positive bacterial infections. FTO variants not associated with obesity demonstrated other potential disease associations including non-inflammatory disorders of the cervix and chronic periodontitis. These results suggest that genetic variants in FTO may have pleiotropic associations, some of which are not mediated by obesity.

  3. Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

    NASA Technical Reports Server (NTRS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-01-01

    Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  4. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  5. An index of unhealthy lifestyle is associated with coronary heart disease mortality rates for small areas in England after adjustment for deprivation.

    PubMed

    Scarborough, P; Allender, S; Rayner, M; Goldacre, M

    2011-03-01

    Indices of socio-economic deprivation are often used as a proxy for differences in the health behaviours of populations within small areas, but these indices are a measure of the economic environment rather than the health environment. Sets of synthetic estimates of the ward-level prevalence of low fruit and vegetable consumption, obesity, raised blood pressure, raised cholesterol and smoking were combined to develop an index of unhealthy lifestyle. Multi-level regression models showed that this index described about 50% of the large-scale geographic variation in CHD mortality rates in England, and substantially adds to the ability of an index of deprivation to explain geographic variations in CHD mortality rates.

  6. Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

    NASA Astrophysics Data System (ADS)

    Matin, M. A.; Bourque, C. P.-A.

    2015-08-01

    This study associates the dynamics of enhanced vegetation index in lowland desert oases to the recycling of water in two endorheic (hydrologically closed) river basins in Gansu Province, north-west China, along a gradient of elevation zones and land cover types. Each river basin was subdivided into four elevation zones representative of (i) oasis plains and foothills, and (ii) low-, (iii) mid-, and (iv) high-mountain elevations. Comparison of monthly vegetation phenology with precipitation and snowmelt dynamics within the same basins over a 10-year period (2000-2009) suggested that the onset of the precipitation season (cumulative % precipitation > 7-8 %) in the mountains, typically in late April to early May, was triggered by the greening of vegetation and increased production of water vapour at the base of the mountains. Seasonal evolution of in-mountain precipitation correlated fairly well with the temporal variation in oasis-vegetation coverage and phenology characterised by monthly enhanced vegetation index, yielding coefficients of determination of 0.65 and 0.85 for the two basins. Convergent cross-mapping of related time series indicated bi-directional causality (feedback) between the two variables. Comparisons between same-zone monthly precipitation amounts and enhanced vegetation index provided weaker correlations. Start of the growing season in the oases was shown to coincide with favourable spring warming and discharge of meltwater from low- to mid-elevations of the Qilian Mountains (zones 1 and 2) in mid-to-late March. In terms of plant requirement for water, mid-seasonal development of oasis vegetation was seen to be controlled to a greater extent by the production of rain in the mountains. Comparison of water volumes associated with in-basin production of rainfall and snowmelt with that associated with evaporation seemed to suggest that about 90 % of the available liquid water (i.e. mostly in the form of direct rainfall and snowmelt in the mountains

  7. Correlation of meteorological parameters and remotely sensed normalized difference vegetation index (NDVI) with cotton leaf curl virus (CLCV) in Multan

    NASA Astrophysics Data System (ADS)

    Ahmed, A.; Akhtar, A.; Khalid, B.; Shamim, A.

    2013-06-01

    Climate change and weather has a profound effect on the spread of Cotton Leaf Curl Virus (CLCV) which is transmitted by whitefly. Climate change is altering temperature and precipitation patterns, resulting in the shift of some insect/pest from small population to large population thus effecting crops yield. To find out the relationship between the weather conditions, outburst of CLCV and changes in Normalized Difference Vegetation Index (NDVI) values due to the outburst of CLCV, a study was carried out for tehsil Multan. Data was acquired for the months of June, July, August and September for the year 2010. Regression analysis between CLCV and meteorological conditions as well as between CLCV and NDVI was performed. Meteorological parameters included temperature, humidity, precipitation, cloud cover, wind direction, pan evaporation and sunshine hours. NDVI values were calculated from SPOT satellite imagery (1km) using ArcMap10 and WinDisp v5.1. Correlation coefficients obtained in most of the cases were acceptable however the significance F and P-value were higher than their critical value at 95% level of significance. Therefore significant correlation was found only between CLCV and temperature and between CLCV and PAN evaporation during the month of July.

  8. Online Measurement of Soil Organic Carbon as Correlated with Wheat Normalised Difference Vegetation Index in a Vertisol Field

    PubMed Central

    Tekin, Yücel; Ulusoy, Yahya; Tümsavaş, Zeynal; Mouazen, Abdul M.

    2014-01-01

    This study explores the potential of visible and near infrared (vis-NIR) spectroscopy for online measurement of soil organic carbon (SOC). It also attempts to explore correlations and similarities between the spatial distribution of SOC and normalized differential vegetation index (NDVI) of a wheat crop. The online measurement was carried out in a clay vertisol field covering 10 ha of area in Karacabey, Bursa, Turkey. Kappa statistics were carried out between different SOC and NDVI data to investigate potential similarities. Calibration model of SOC in full cross-validationresulted in a good accuracy (R2 = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81). The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R2 = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R2 = 0.60, RMSEP = 0.20%, and RPD = 1.41). Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map. PMID:25097882

  9. Online measurement of soil organic carbon as correlated with wheat normalised difference vegetation index in a vertisol field.

    PubMed

    Tekin, Yücel; Ulusoy, Yahya; Tümsavaş, Zeynal; Mouazen, Abdul M

    2014-01-01

    This study explores the potential of visible and near infrared (vis-NIR) spectroscopy for online measurement of soil organic carbon (SOC). It also attempts to explore correlations and similarities between the spatial distribution of SOC and normalized differential vegetation index (NDVI) of a wheat crop. The online measurement was carried out in a clay vertisol field covering 10 ha of area in Karacabey, Bursa, Turkey. Kappa statistics were carried out between different SOC and NDVI data to investigate potential similarities. Calibration model of SOC in full cross-validation resulted in a good accuracy (R (2) = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81). The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R (2) = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R (2) = 0.60, RMSEP = 0.20%, and RPD = 1.41). Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map.

  10. Evaluation of the relation between evapotranspiration and normalized difference vegetation index for downscaling the simplified surface energy balance model

    USGS Publications Warehouse

    Haynes, Jonathan V.; Senay, Gabriel B.

    2012-01-01

    The Simplified Surface Energy Balance (SSEB) model uses satellite imagery to estimate actual evapotranspiration (ETa) at 1-kilometer resolution. SSEB ETa is useful for estimating irrigation water use; however, resolution limitations restrict its use to regional scale applications. The U.S. Geological Survey investigated the downscaling potential of SSEB ETa from 1 kilometer to 250 meters by correlating ETa with the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer instrument (MODIS). Correlations were studied in three arid to semiarid irrigated landscapes of the Western United States (Escalante Valley near Enterprise, Utah; Palo Verde Valley near Blythe, California; and part of the Columbia Plateau near Quincy, Washington) during several periods from 2002 to 2008. Irrigation season ETa-NDVI correlations were lower than expected, ranging from R2 of 0.20 to 0.61 because of an eastward 2–3 kilometer shift in ETadata. The shift is due to a similar shift identified in the land-surface temperature (LST) data from the MODIS Terra satellite, which is used in the SSEB model. Further study is needed to delineate the Terra LST shift, its effect on SSEB ETa, and the relation between ETa and NDVI.

  11. [Estimation of vegetation water content from Landsat 8 OLI data].

    PubMed

    Zheng, Xing-ming; Ding, Yan-ling; Zhao, Kai; Jiang, Tao; Li, Xiao-feng; Zhang, Shi-yi; Li, Yang-yang; Wu, Li-li; Sun, Jian; Ren, Jian-hua; Zhang, Xuan-xuan

    2014-12-01

    The present paper aims to analyze the capabilities and limitations for retrieving vegetation water content from Landsat8 OLI (Operational Land Imager) sensor-new generation of earth observation program. First, the effect of soil background on canopy reflectance and the sensitive band to vegetation water content were analyzed based on simulated dataset from ProSail model. Then, based on vegetation water indices from Landsat8 OLI and field vegetation water content during June 1 2013 to August 14 2013, the best vegetation water index for estimating vegetation water content was found through comparing 12 different indices. The results show that: (1) red, near infrared and two shortwave infrared bands of OLI sensor are sensitive to the change in vegetation water content, and near infrared band is the most sensitive one; (2) At low vegetation coverage, solar radiation reflected by soil background will reach to spectral sensor and influence the relationship between vegetation water index and vegetation water content, and simulation results from ProSail model also show that soil background reflectance has a significant impact on vegetation canopy reflectance in both wet and dry soil conditions, so the optimized soil adjusted vegetation index (OSAVI) was used in this paper to remove the effect of soil background on vegetation water index and improve its relationship with vegetation water content; (3) for the 12 vegetation water indices, the relationship between MSI2 and vegetation water content is the best with the R-square of 0.948 and the average error of vegetation water content is 0.52 kg · m(-2); (4) it is difficult to estimate vegetation water content from vegetation water indices when vegetation water content is larger than 2 kg · m(-2) due to spectral saturation of these indices.

  12. The Oslo Health Study: a Dietary Index estimating high intake of soft drinks and low intake of fruits and vegetables was positively associated with components of the metabolic syndrome.

    PubMed

    Høstmark, Arne Torbjørn

    2010-12-01

    A previous finding that soft drink intake is associated with increased serum triglycerides and decreased high-density-lipoprotein (HDL) cholesterol, both components of the metabolic syndrome (MetS), raises the question of whether other aspects of an unhealthy diet might be associated with MetS. Main MetS requirements are central obesity and 2 of the following: increased triglycerides, low HDL, increased systolic or diastolic blood pressure, and elevated fasting blood glucose. Of the 18 770 participants in the Oslo Health Study, there were 13 170 respondents (5997 men and 7173 women) with data on MetS factors (except fasting glucose) and on the components used to determine the Dietary Index score (calculated as the intake estimate of soft drinks divided by the sum of intake estimates of fruits and vegetables). MetSRisk was calculated as the sum of arbitrarily weighted factors positively associated with MetS divided by HDL cholesterol. Using regression analyses, the association of the Dietary Index with MetSRisk, with the number of MetS requirements present, and with the complete MetS was studied. In young, middle-aged, and senior men and women, there was, in general, a positive association (p < 0.001) between the Dietary Index and the MetS estimates, which persisted in regression models adjusted for sex, age, time since the last meal, intake of cheese, intake of fatty fish, intake of coffee, intake of alcohol, smoking, physical activity, education, and birthplace. Thus, an index reflecting a high intake of soft drinks and a low intake of fruit and vegetables was positively and independently associated with aspects of MetS.

  13. 5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas Cost-Of-Living Allowances § 591.228 How does OPM convert the price index...

  14. 5 CFR 591.228 - How does OPM convert the price index plus adjustment factor to a COLA rate?

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas Cost-Of-Living Allowances § 591.228 How does OPM convert the price index...

  15. 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.

  16. Application of vegetation isoline equations for simultaneous retrieval of leaf area index and leaf chlorophyll content using reflectance of red edge band

    NASA Astrophysics Data System (ADS)

    Okuda, Kakuya; Taniguchi, Kenta; Miura, Munenori; Obata, Kenta; Yoshioka, Hiroki

    2016-09-01

    The remotely sensed reflectance spectra of vegetated surfaces contain information relating to the leaf area index (LAI) and the chlorophyll-a and -b concentrations (Cab) in a leaf. Difficulties associated with the retrieval of these two biophysical parameters from a single reflectance spectrum arise mainly from the choice of a suitable set of observation wavelengths and the development of a retrieval algorithm. Efforts have been applied toward the development of new algorithms, such as the numerical inversion of radiative transfer models, in addition to the development of simple approaches based on the spectral vegetation indices. This study explored a different approach: An equation describing band-to-band relationships (vegetation isoline equation) was used to retrieve the LAI and Cab simultaneously from a reflectance spectrum. The algorithm used three bands, including the red edge region, and an optimization cost function was constructed from two vegetation isoline equations in the red-NIR and red edge-NIR reflectance subspaces. A series of numerical experiments was conducted using the PROSPECT model to explore the numerical challenges associated with the use of the vegetation isoline equation during the parameter retrieval of the LAI and Cab. Overall, our results indicated the existence of a global minimum (and no local minima) over a wide swath of the LAI-Cab parameter subspace in most simulation cases. These results suggested that the use of the vegetation isoline equation in the simultaneous retrieval of the LAI and the Cab provides a viable alternative to the spectral vegetation index algorithms and the direct inversion of the canopy radiative transfer models.

  17. Normalized Difference Vegetation Index as a Tool for Wheat Yield Estimation: A Case Study from Faisalabad, Pakistan

    PubMed Central

    Sultana, Syeda Refat; Ali, Amjed; Ahmad, Ashfaq; Mubeen, Muhammad; Zia-Ul-Haq, M.; Ahmad, Shakeel; Ercisli, Sezai; Jaafar, Hawa Z. E.

    2014-01-01

    For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI) is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF) during the two years 2008-09 and 2009-10. For recording the value of NDVI, Green seeker (Handheld-505) was used. Split plot design was used as experimental model in, keeping four nitrogen rates (N1 = 0 kg ha−1, N2 = 55 kg ha−1, N3 = 110 kg ha−1, and N4 = 220 kg ha−1) in main plots and ten wheat cultivars (Bakkhar-2001, Chakwal-50, Chakwal-97, Faisalabad-2008, GA-2002, Inqlab-91, Lasani-2008, Miraj-2008, Sahar-2006, and Shafaq-2006) in subplots with four replications. Impact of nitrogen and difference between cultivars were forecasted through NDVI. The results suggested that nitrogen treatment N4 (220 kg ha−1) and cultivar Faisalabad-2008 gave maximum NDVI value (0.85) at grain filling stage among all treatments. The correlation among NDVI at booting, grain filling, and maturity stages with grain yield was positive (R2 = 0.90; R2 = 0.90; R2 = 0.95), respectively. So, booting, grain filling, and maturity can be good depictive stages during mid and later growth stages of wheat crop under agroclimatic conditions of Faisalabad and under similar other wheat growing environments in the country. PMID:25045744

  18. Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation.

    PubMed

    Zajac, Zuzanna; Stith, Bradley; Bowling, Andrea C; Langtimm, Catherine A; Swain, Eric D

    2015-07-01

    Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

  19. Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology.

    PubMed

    Lopes, Marta S; Reynolds, Matthew P

    2012-06-01

    The green area displayed by a crop is a good indicator of its photosynthetic capacity, while chlorophyll retention or 'stay-green' is regarded as a key indicator of stress adaptation. Remote-sensing methods were tested to estimate these parameters in diverse wheat genotypes under different growing conditions. Two wheat populations (a diverse set of 294 advanced lines and a recombinant inbred line population of 169 sister lines derived from the cross between Seri and Babax) were grown in Mexico under three environments: drought, heat, and heat combined with drought. In the two populations studied here, a moderate heritable expression of stay-green was found-when the normalized difference vegetation index (NDVI) at physiological maturity was estimated using the regression of NDVI over time from the mid-stages of grain-filling to physiological maturity-and for the rate of senescence during the same period. Under heat and heat combined with drought environments, stay-green calculated as NDVI at physiological maturity and the rate of senescence, showed positive and negative correlations with yield, respectively. Moreover, stay-green calculated as an estimation of NDVI at physiological maturity and the rate of senescence regressed on degree days give an independent measurement of stay-green without the confounding effect of phenology. On average, in both populations under heat and heat combined with drought environments CTgf and stay-green variables accounted for around 30% of yield variability in multiple regression analysis. It is concluded that stay-green traits may provide cumulative effects, together with other traits, to improve adaptation under stress further.

  20. Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

    USGS Publications Warehouse

    Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

    2015-01-01

    Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

  1. Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

    PubMed Central

    Zajac, Zuzanna; Stith, Bradley; Bowling, Andrea C; Langtimm, Catherine A; Swain, Eric D

    2015-01-01

    Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust

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

    NASA Technical Reports Server (NTRS)

    Frouin, Robert

    1993-01-01

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

  3. Use of vegetation index and surface temperature to estimate soil moisture in a semi-arid catchment in Brazil with limited monitoring

    NASA Astrophysics Data System (ADS)

    Rebello, V. P. A.; Cunha, T. M.; Rotunno Filho, O. C.; Barbosa, M. C.; Franklin, M. R.; Lakshmi, V.

    2014-12-01

    During the last two decades, there have been numerous studies using remote sensing to study catchment energy and water balance. A well-known example is the combination of surface temperature (Ts) and the normalized difference vegetation index (NDVI), which can provide information on vegetation and moisture conditions at the land surface. Since the soil moisture is a key variable in hydrological modeling, this information is potentially useful in large watersheds and remote areas in developing countries, where little infrastructure and few resources still make continuous in-situ monitoring of environmental variables a difficult task, as well as in semi arid areas, where the lack of water may represent an obstacle to the regional economic and sustainable development. The basic methodology is to calculate soil moisture indexes by the scatter plots of NDVI and Ts and to analyze the Ts/NDVI slope, in order to estimate temporal patterns of soil moisture. We will utilize the standard vegetation index and surface temperature products from MODIS and NOAA - AVHRR, and the results will be compared with soil moisture derived from a hydrological model (Soil Moisture Accounting Procedure). This work will focus on a 18200 km² semi-arid catchment in Northeastern Brazil.

  4. Using MODIS Normalized Difference Vegetation Index to monitor seasonal and inter-annual dynamics of wetland vegetation in the Great Artesian Basin: a baseline for assessment of future changes in a unique ecosystem

    NASA Astrophysics Data System (ADS)

    Petus, C.; Lewis, M.; White, D.

    2012-07-01

    The Great Artesian Basin mound springs (Australia) are unique wetland ecosystems of great significance. However, these unique ecosystems are endangered by anthropogenic water extraction. Relationships have been established between the vegetated wetland area and the discharge associated with individual springs, providing a potential means of monitoring groundwater flow using measurements of wetland area. Previous studies using this relationship to monitor Great Artesian Basin springs have used aerial photography or high resolution satellite images, giving sporadic temporal information. These "snapshot " studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study, the potential of medium resolution MODIS Normalized Difference Vegetation Index data for studying the long-term and high frequency temporal dynamics of wetland vegetation at the Dalhousie Spring Complex of the GAB is tested. Photosynthetic activity within Dalhousie wetlands could be differentiated from surrounding land responses. The study showed good correlation between wetland vegetated area and groundwater flow, but also the important influence of natural species phenologies, rainfall, and human activity on the observed seasonal and inter-annual vegetation dynamic. Declining trends in the extent of wetland areas were observed over the 2000- 2009 period followed by a return of wetland vegetation since 2010. This study underlined the need to continue long-term medium resolution satellite studies of the Great Artesian Basin as these data provide a good understanding of variability within the wetlands, give temporal context for less frequent studies and a strong baseline for assessment of future changes.

  5. 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.

  6. A Vegetation Index qualifying pasture edges is related to Ixodes ricinus density and to Babesia divergens seroprevalence in dairy cattle herds.

    PubMed

    Agoulon, Albert; Malandrin, Laurence; Lepigeon, Florent; Vénisse, Maxime; Bonnet, Sarah; Becker, Claire A M; Hoch, Thierry; Bastian, Suzanne; Plantard, Olivier; Beaudeau, François

    2012-04-30

    Babesia divergens, transmitted by the tick Ixodes ricinus, is the main agent of bovine piroplasmosis in France. This Apicomplexa often is present in asymptomatic carriers; however, clinical cases are rare. While numerous factors are known to influence tick density, no risk factor of contact with B. divergens has been identified for cattle. Our study aimed to explore whether a Vegetation Index could serve as an indirect indicator of within-herd B. divergens seroprevalence. In February 2007, blood samples were taken from all of the cows in 19 dairy cattle herds in Western France and IFAT serology was performed individually to measure B. divergens seroprevalence. The following spring, I. ricinus nymphs were collected by drag sampling along transects on the vegetation of each farm's pasture perimeters. Tick density was related significantly to a Vegetation Index (V.I., ranging from 1 to 5) that took into account the abundance of trees and bushes on the edge of pastures: most ticks (57%) were found in transects with the highest V.I. (covering 15% of the explored surface in the study area). At the farm level, the proportion of transects presenting I. ricinus nymphs was significantly related to B. divergens seroprevalence: the farms with more than 15% of transects with I. ricinus had a significantly higher risk of high seroprevalence. The proportion of pasture perimeters where the V.I.=5 also was significantly related to B. divergens seroprevalence: the farms where more than 20% of transects had a V.I.=5 had a significantly higher risk of high seroprevalence. Given that the Vegetation Index is a steady indicator of the potential I. ricinus density in the biotope, we recommend that the risk of high B. divergens seroprevalence in cows be evaluated using this tool rather than drag samplings.

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

    PubMed

    Ren, Shilong; Chen, Xiaoqiu; An, Shuai

    2017-04-01

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

  8. Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index: An assessment tool for marsh habitat focused on the three-dimensional structure at CRMS vegetation monitoring stations

    USGS Publications Warehouse

    Wood, William B.; Visser, Jenneke M.; Piazza, Sarai C.; Sharp, Leigh A.; Hundy, Laura C.; McGinnis, Tommy E.

    2015-12-04

    The VV and VVI will be used to establish trends, to make comparisons, and to evaluate restoration projects. Assessments that rely on the VVI will be included in appropriate Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) project reports and analyses. Implementation of the VVI will give coastal managers a new tool to design, implement, and monitor coastal restoration projects. A yearly trajectory of site, project, basin, and coastwide VVI will be posted on the CRMS Web site as data are collected. The primary purpose of the tool is to assess CWPPRA restoration project effectiveness, but it will also be useful in identifying areas in need of restoration and in coastwide vegetation assessments.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  11. Estimates of phytomass and net primary productivity in terrestrial ecosystems of the former Soviet Union identified by classified Global Vegetation Index

    SciTech Connect

    Gaston, G.G.; Kolchugina, T.P.

    1995-12-01

    Forty-two regions with similar vegetation and landcover were identified in the former Soviet Union (FSU) by classifying Global Vegetation Index (GVI) images. Image classes were described in terms of vegetation and landcover. Image classes appear to provide more accurate and precise descriptions for most ecosystems when compared to general thematic maps. The area of forest lands were estimated at 1,330 Mha and the actual area of forest ecosystems at 875 Mha. Arable lands were estimated to be 211 Mha. The area of the tundra biome was estimated at 261 Mha. The areas of the forest-tundra/dwarf forest, taiga, mixed-deciduous forest and forest-steppe biomes were estimated t 153, 882, 196, and 144 Mha, respectively. The areas of desert-semidesert biome and arable land with irrigated land and meadows, were estimated at 126 and 237 Mha, respectively. Vegetation and landcover types were associated with the Bazilevich database of phytomass and NPP for vegetation in the FSU. The phytomass in the FSU was estimated at 97.1 Gt C, with 86.8 in forest vegetation, 9.7 in natural non-forest and 0.6 Gt C in arable lands. The NPP was estimated at 8.6 Gt C/yr, with 3.2, 4.8, and 0.6 Gt C/yr of forest, natural non-forest, and arable ecosystems, respectively. The phytomass estimates for forests were greater than previous assessments which considered the age-class distribution of forest stands in the FSU. The NPP of natural ecosystems estimated in this study was 23% greater than previous estimates which used thematic maps to identify ecosystems. 47 refs., 4 figs., 2 tabs.

  12. Osmotic adjustment and the growth response of seven vegetable crops following water-deficit stress. [Phaseolus vulgaris L. ; Beta vulgaris L. ; Abelmoschus esculentus; Pisum sativum L. ; Capsicum annuum L. ; Spinacia oleracea L. ; Lycopersicon esculentum Mill

    SciTech Connect

    Wullschleger, S.D. ); Oosterhuis, D.M. )

    1991-09-01

    Growth-chamber studies were conducted to examine the ability of seven vegetable crops- Blue Lake beam (Phaseolus vulgaris L.) Detroit Dark Red beet (Beta vulgaris L.) Burgundy okra (Abelmoschus esculentus) (Moench), Little Marvel pea (Pisum sativum L), California Wonder bell pepper (Capsicum annuum L), New Zealand spinach (Spinacia oleracea L), and Beefsteak tomato (Lycopersicon esculentum Mill.) - to adjust osmotically in response to water-deficit stress. Water stress was imposed by withholding water for 3 days, and the adjustment of leaf and root osmotic potentials upon relief of the stress and rehydration were monitored with thermocouple psychrometers. Despite similar reductions in leaf water potential and stomatal conductance among the species studied reductions in lead water potential an stomatal conductance among the species, crop-specific differences were observed in leak and root osmotic adjustment. Leaf osmotic adjustment was observed for bean, pepper, and tomato following water-deficit stress. Root osmotic adjustment was significant in bean, okra, pea and tomato. Furthermore, differences in leaf and root osmotic adjustment were also observed among five tomato cultivars. Leaf osmotic adjustment was not associated with the maintenance of leaf growth following water-deficit stress, since leaf expansion of water-stressed bean and pepper, two species capable of osmotic adjustment, was similar to that of spinach, which exhibited no leaf osmotic adjustment.

  13. Extending the normalized difference vegetation index (NDVI) to short-wave infrared radiation (SWIR) (1- to 2.5-μm)

    NASA Astrophysics Data System (ADS)

    Mayer, Rulon R.; Scribner, Dean A.

    2002-11-01

    There is increasing interest in using wide-area standoff airborne hyperspectral sensors to detect potential targets at large oblique viewing angles. Under such conditions, the intervening atmosphere between the targets and the imager can attenuate and alter the detected signal. To help compensate for the reduced signal for long range viewing, recent efforts have focused on using hyperspectral sensors to collect imagery derived from short wave radiation SWIR (1-2.5 μm) rather than the more standard visible-near infrared radiation Vis-NIR (0.4-1.0 μm). However, unlike imagery collected using Vis-NIR, there is currently a relative dearth of analytical and classification algorithms that only use SWIR. To enhance the ability to detect spectral features confined to the SWIR regime, this study has examined extracting vegetation features in the SWIR. Visible-near infrared hyperspectral imagery has successfully extracted vegetation within a scene through computation of the normalized difference vegetation index (NDVI). The Visible NDVI computes a normalized difference of two bands corresponding to the chlorophyll absorption (0.67 μm) and IR edge (0.80 μm). This work extended and examined schemes for extracting vegetation within SWIR imagery. Specifically, this study examined the HYDICE data collect (0.4-2.5 μm) and the visible NDVI was used as the standard for determining the vegetation within the scene. A SWIR derived NDVI was generated using pairs of SWIR bands (1.08, 1.46 μm), (1.08, 1.57 μm), (1.08, 1.66 μm), and (1,08, 2.18 μm). All SWIR paired bands exhibited large (> 0.92) correlation coefficients with the Vis-NIR NDVI. Vis-NIR NDVI preferentially detects the greenest vegetation but the SWIR NDVI tends to favor vegetation residing in shadows. Water has large SWIR NDVI but has low reflectance throughout the SWIR. By setting a threshold, water can be eliminated from consideration and only vegetation is detected. In addition, minimizing the mean squared error

  14. The environmental vegetation index: A tool potentially useful for arid land management. [Texas and Mexico, plant growth stress due to water deficits

    NASA Technical Reports Server (NTRS)

    Gray, T. I., Jr.; Mccrary, D. G. (Principal Investigator)

    1981-01-01

    The NOAA-6 AVHRR data sets acquired over South Texas and Mexico during the spring of 1980 and after Hurricane Allen passed inland are analyzed. These data were processed to produce the Gray-McCrary Index (GMI's) for each pixel location over the selected area, which area contained rangeland and cropland, both irrigated and nonirrigated. The variations in the GMI's appear to reflect well the availability of water for vegetation. The GMI area maps are shown to delineate and to aid in defining the duration of drought; suggesting the possibility that time changes over a selected area could be useful for irrigation management.

  15. Age-adjusted charlson comorbidity index score as predictor of prolonged postoperative ileus in patients with colorectal cancer who underwent surgical resection.

    PubMed

    Tian, Yaohua; Xu, Beibei; Yu, Guopei; Li, Yan; Liu, Hui

    2017-02-11

    Comorbidities had considerable effects on the development of postoperative ileus (POI). The primary aim of the present study was to determine the influence of the age-adjusted Charlson comorbidity index (ACCI) score on the risk of prolonged POI in patients with colorectal cancer who underwent surgical resection. Using the electronic Hospitalization Summary Reports, we identified 11,397 patients with colorectal cancer who underwent surgical resection from 2013 through 2015. Logistic regression models were applied to evaluate the effect of the ACCI score on the risk of prolonged POI. The ACCI score had a positive graded association with the risk of prolonged POI in both colon and rectal cancer (P for trend < 0.05). Among patients with rectal cancer, after adjusting for potential confounders, those with an ACCI score of 4-5 had a 108% higher risk of prolonged POI than those with an ACCI score of 0-1 (odds ratio [OR], 2.08; 95% confidence interval [CI], 1.09-3.98), and those with an ACCI score of ≥ 6 had a 130% higher risk (OR, 2.30; 95% CI, 1.08-4.89). Among patients with colon cancer, those with an ACCI score of ≥ 6 had a 47% greater risk of prolonged POI than those with an ACCI score of 0-1 (OR, 1.47; 95% CI, 1.07-2.02). These findings suggested that a higher ACCI score was an independent predictor of the development of prolonged POI.

  16. Fat mass and obesity-associated gene rs11642015 polymorphism is significantly associated with prediabetes and type 2 diabetes subsequent to adjustment for body mass index.

    PubMed

    Han, Liyuan; Tang, Linlin; Wang, Changyi; Chen, Zhongwei; Zhang, Tao; Chen, Sihan; Liu, Shengyuan; Peng, Xiaolin; Mai, Yifeng; Duan, Shiwei

    2014-09-01

    The association of the fat mass and obesity-associated gene (FTO) rs11642015 polymorphism with prediabetes, type 2 diabetes and obesity in certain populations has not been previously reported. A population-based study was conducted that included 490 type 2 diabetic, 471 prediabetic and 575 normal subjects. The main outcomes of the study were prediabetes, type 2 diabetes and obesity. Binary logistic regression was performed to estimate the association of FTO rs11642015 with the risk of prediabetes, type 2 diabetes and obesity following adjustment for the corresponding confounders. A meta-analysis was also conducted to evaluate the association between FTO rs11642015 and obesity. FTO rs11642015 was significantly associated with prediabetes in the whole sample under the additive model [odds ratio (OR), 1.50; 95% confidence interval (CI), 1.17-1.93; P=0.002], particularly in females. The polymorphism remained consistently significant following adjustment for age and body mass index (BMI), showing an increased prediabetes risk with an additive effect (OR, 1.55; 95% CI, 1.19-2.01; P=0.001). In addition, a significant association was found for rs11642015 with prediabetes and type 2 diabetes under the dominant model. However, under the stringent Bonferroni's correction there was no evidence of positive associations for FTO rs11642015 with obesity in the whole sample, females or males. Findings of the meta-analysis showed that FTO rs11642015 was not predisposed to obesity. In conclusion, the T allele of FTO rs11642015 is positively associated with an increased risk of prediabetes, even after adjustment for age and BMI, particularly in females. Subjects carrying the CT + TT genotype are predisposed to prediabetes and type 2 diabetes. Therefore, results of the population-based study and follow-up meta-analysis suggested that FTO rs11642015 is not significantly associated with susceptibility to obesity.

  17. Fat mass and obesity-associated gene rs11642015 polymorphism is significantly associated with prediabetes and type 2 diabetes subsequent to adjustment for body mass index

    PubMed Central

    HAN, LIYUAN; TANG, LINLIN; WANG, CHANGYI; CHEN, ZHONGWEI; ZHANG, TAO; CHEN, SIHAN; LIU, SHENGYUAN; PENG, XIAOLIN; MAI, YIFENG; DUAN, SHIWEI

    2014-01-01

    The association of the fat mass and obesity-associated gene (FTO) rs11642015 polymorphism with prediabetes, type 2 diabetes and obesity in certain populations has not been previously reported. A population-based study was conducted that included 490 type 2 diabetic, 471 prediabetic and 575 normal subjects. The main outcomes of the study were prediabetes, type 2 diabetes and obesity. Binary logistic regression was performed to estimate the association of FTO rs11642015 with the risk of prediabetes, type 2 diabetes and obesity following adjustment for the corresponding confounders. A meta-analysis was also conducted to evaluate the association between FTO rs11642015 and obesity. FTO rs11642015 was significantly associated with prediabetes in the whole sample under the additive model [odds ratio (OR), 1.50; 95% confidence interval (CI), 1.17–1.93; P=0.002], particularly in females. The polymorphism remained consistently significant following adjustment for age and body mass index (BMI), showing an increased prediabetes risk with an additive effect (OR, 1.55; 95% CI, 1.19–2.01; P=0.001). In addition, a significant association was found for rs11642015 with prediabetes and type 2 diabetes under the dominant model. However, under the stringent Bonferroni’s correction there was no evidence of positive associations for FTO rs11642015 with obesity in the whole sample, females or males. Findings of the meta-analysis showed that FTO rs11642015 was not predisposed to obesity. In conclusion, the T allele of FTO rs11642015 is positively associated with an increased risk of prediabetes, even after adjustment for age and BMI, particularly in females. Subjects carrying the CT + TT genotype are predisposed to prediabetes and type 2 diabetes. Therefore, results of the population-based study and follow-up meta-analysis suggested that FTO rs11642015 is not significantly associated with susceptibility to obesity. PMID:25054011

  18. Pharmacokinetic evaluation of doxorubicin plasma levels in normal and overweight patients with breast cancer and simulation of dose adjustment by different indexes of body mass.

    PubMed

    Barpe, Deise Raquel; Rosa, Daniela Dornelles; Froehlich, Pedro Eduardo

    2010-11-20

    Although being used for decades in the treatment of several types of cancer, either alone or in association, only a few data about the pharmacokinetics of doxorubicin (DOX) in humans are available. DOX is frequently used in association with other anticancer drugs in the management of breast cancer. Pharmacokinetic data available in the literature show that after i.v. administration DOX follows a two-compartment open model, with a fast distribution phase followed by a very slow elimination phase. The objective of this work is to perform a pilot study in order to verify if the usual dose adjustment based on body surface area (BSA) would be producing the same plasma concentration-time profiles in patients with normal (<25) and above normal (>25) body mass index (BMI). In order to assess the pharmacokinetics of DOX after a short-term i.v. infusion of 60mg/m(2) of BSA, an experimental design using only five plasma samples of each patient was applied. Samples were collected at 0.00, 0.66 (right after the end of infusion), 1.66, 8.66, and 24.66h. DOX pharmacokinetic profiles were evaluated after quantification of DOX using a new HPLC method developed and validated. Pharmacokinetic parameters (AUC(0-24.66) and C(max)) were analyzed by non-compartmental and compartmental approaches. Significant differences (α=0.05) between overweight and normal weight groups were found with respect to AUC and C(max). After adjustment of dose by weight and by BMI, the compartmental model was used to simulate plasma concentrations and new values for C(max) and AUC(0-24.66) were calculated. The new values obtained using both body weight (BW) and BMI were closer to the normal group than those obtained with BSA. According to the simulation, the differences of AUC and C(max) between the overweight group and the group of patients with normal weight were lower when the dose was adjusted by BW and BMI. These results suggest that more studies must be conducted, with more patients, in order to

  19. Seven-year phenological record of the Alaskan ecoregions derived from advanced very high resolution radiometer normalized difference vegetation index data

    USGS Publications Warehouse

    Markon, Carl J.

    2001-01-01

    Seasonal properties of vegetation covering northern boreal and arctic landscapes are considered important as input to numerous climate change studies. In this study, multitemporal phenological characteristics of Alaskan vegetation were studied for the State as a whole, and 19 of 20 ecoregions were studied using seasonally truncated, composited advanced very high resolution radiometer derived normalized difference vegetation index (NDVI) data. Phenological characteristics included four temporal and six greenness metrics derived for each year from 1991 to 1997. Temporal metrics included date of onset of greenness, last day of greenness, date of maximum greenness, and total days of greenness. Greenness metrics consisted of NDVI values recorded during the onset and last day of greenness, maximum greenness, mean greenness for the growing season, and estimated rates of greenup and greendown in the spring and autumn, respectively. Results indicated that over many areas of Alaska there was a trend toward earlier onset of greenness each spring from 1992 to 1997, but the last day of greenness in the autumn was roughly the same. Earlier greenup dates in the spring resulted in a lengthened growing season greenup of up to 20 days in some areas of Alaska from 1992 to 1997. Climate data, however, did not always corroborate these findings. In general, greenness values dropped from 1991 to 1992 and then increased from 1992 to 1997. Values obtained after 1991 may have been affected by atmospheric perturbations owing to the 1991 Mt. Pinatubo eruption and lasting until at least 1997.

  20. Interactions between river stage and wetland vegetation detected with a Seasonality Index derived from LANDSAT images in the Apalachicola delta, Florida

    NASA Astrophysics Data System (ADS)

    la Cecilia, Daniele; Toffolon, Marco; Woodcock, Curtis E.; Fagherazzi, Sergio

    2016-03-01

    The distribution of swamp floodplain vegetation and its evolution in the lower non-tidal reaches of the Apalachicola River, Florida USA, is mapped using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images captured over a period of 29 years. A newly developed seasonality index (SI), the ratio of the NDVI in winter months to the summer months, shows that the hardwood swamp, dominated by bald cypress and water tupelo, is slowly replaced by bottomland hardwood forest. This forest shift is driven by lower water levels in the Apalachicola River in the last 30 years, and predominantly occurs in the transitional area between low floodplains and high river banks. A negative correlation between maximum summer NDVI and water levels in winter suggests the growth of more vigorous vegetation in the vicinity of sloughs during years with low river flow. A negative correlation with SI further indicates that these vegetation patches are possibly replaced by species typical of drier floodplain conditions.

  1. Sixteen years of agricultural drought assessment of the BioBío region in Chile using a 250 m resolution Vegetation Condition Index (VCI)

    NASA Astrophysics Data System (ADS)

    Zambrano, Francisco; Lillo-Saavedra, Mario; Verbist, Koen; Lagos, Octavio

    2016-10-01

    Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBio Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (Nov-Apr) instead of the regular growing season (Sept-Apr), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBio Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250m) with the measured crop yield to identify more detailed individual crop

  2. Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

    NASA Technical Reports Server (NTRS)

    Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

    2006-01-01

    The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

  3. Testing gridded land precipitation data and precipitation and runoff reanalyses (1982-2010) between 45° S and 45° N with normalised difference vegetation index data

    NASA Astrophysics Data System (ADS)

    Los, S. O.

    2015-04-01

    The realistic simulation of key components of the land-surface hydrological cycle - precipitation, runoff, evaporation and transpiration, in general circulation models of the atmosphere - is crucial to assess adverse weather impacts on environment and society. Here, gridded precipitation data from observations and precipitation and runoff fields from reanalyses were tested with satellite derived global vegetation index data for 1982-2010 and latitudes between 45° S and 45° N. Data were obtained from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Monitoring Mission (TRMM; analysed for 1998-2010 only) and precipitation and runoff reanalyses were obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the NASA Global Modelling and Assimilation Office (GMAO). Annual land-surface precipitation was converted to annual potential vegetation net primary productivity (NPP) and was compared to mean annual normalised difference vegetation index (NDVI) data measured by the Advanced Very High Resolution Radiometer (AVHRR; 1982-1999) and Moderate Resolution Imaging Spectroradiometer (MODIS; 2001-2010). The effect of spatial resolution on the agreement between NPP and NDVI was investigated as well. The CRU and TRMM derived NPP agreed most closely with the NDVI data. The GPCP data showed weaker spatial agreement, largely because of their lower spatial resolution, but similar temporal agreement. MERRA Land and ERA Interim precipitation reanalyses showed similar spatial agreement to the GPCP data and good temporal agreement in semi-arid regions of the Americas, Asia, Australia and southern Africa. The NCEP/NCAR reanalysis showed the lowest spatial agreement, which could only in part be explained by its lower spatial resolution. No reanalysis showed realistic interannual precipitation variations

  4. Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

    NASA Astrophysics Data System (ADS)

    Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

    2015-08-01

    Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

  5. Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

    PubMed Central

    Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

    2016-01-01

    Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting. PMID:27667901

  6. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

    USGS Publications Warehouse

    Glenn, E.P.; Neale, C. M. U.; Hunsaker, D.J.; Nagler, P.L.

    2011-01-01

    Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil

  7. The Effect of Physical Exercise on Postural Stability in Sighted Individuals and Those Who Are Visually Impaired: An Analysis Adjusted for Physical Activity and Body Mass Index.

    PubMed

    Sadowska, Dorota; Stemplewski, Rafał; Szeklicki, Robert

    2015-10-01

    The aim of this study was to assess the effect of physical exercise on postural stability in sighted participants and individuals who are visually impaired, adjusted for potential modulatory effects of physical activity level and body mass index (BMI). The study included 23 participants who were severely visually impaired and 23 sighted participants. Postural stability measurements were taken with open eyes (session I) and with closed eyes (session II). During each session, the mean velocity of the center of pressure (COP) displacements was determined using a force plate both before and after physical exercise. During testing with open eyes, the 2 groups did not differ significantly in terms of their postural response to physical exercise. When examined with closed eyes, the individuals who were visually impaired showed markedly greater postexercise increase in mean velocity of the COP displacement in the mediolateral direction. This intergroup difference was likely a consequence of significantly higher preexercise values of posturographic parameters observed in the sighted participants. More pronounced postexercise changes in the postural stability of sighted participants were associated with lower levels of physical activity and higher values of BMI. Further research is needed to explain the character of the abovementioned relationships in individuals who are visually impaired.

  8. Analysis of Vegetation and Atmospheric Correction Indices for Landsat Images

    NASA Technical Reports Server (NTRS)

    Bush, Tasha R.; Desai, M.

    1997-01-01

    Vegetation and Atmospheric Indices are mathematical combinations of remote sensing bands which are useful in distinguishing the various values of the spectral reflectance. In this paper we study how the applications of various atmospherically corrected indices and vegetation indices can aide in retrieving the amount of surface reflectance from a remotely sensed image. Specifically, this paper studies and compares three vegetation indices and one atmospherically resistant index. These indices include the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), the Green Vegetation Index (GVI), and the Atmospherically Resistant Vegetation Index (ARVI), respectively. The algorithms attempt to estimate the optical characteristics of Thematic Mapper (TM) imagery. It will be shown that the NDVI algorithm followed by the ARVI correcting algorithm provided significant improvements in the tonal qualities of the retrieved images. The results are presented on 1987 TM images over the Kennedy Space Center (KSC) and are compared with a set of United States Geological Survey (U.S.G.S) maps.

  9. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    NASA Astrophysics Data System (ADS)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  10. 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.

  11. Monitoring the recovery of Juncus roemerianus marsh burns with the normalized difference vegetation index and Landsat Thematic Mapper data

    USGS Publications Warehouse

    Ramsey, Elijah W.; Sapkota, S.K.; Barnes, F.G.; Nelson, G.A.

    2002-01-01

    Nine atmospherically corrected Landsat Thematic Mapper images were used to generate mean normalized difference vegetation indices (NDVI) at 11 burn sites throughout a coastal Juncus roemerianus marsh in St. Marks National Wildlife Refuge, Florida. Time-since-burn, the time lapse from the date of burn to the date of image collection, was related to variation in mean NDVI over time. Regression analysis showed that NDVI increased for about 300 to 400 days immediately after the burn, overshooting the typical mean NDVI of a nonburned marsh. For about another 500 to 600 days NDVI decreased until reaching a nearly constant NDVI of about 0.40. During the phase of increasing NDVI the ability to predict time-since-burn was within about ??60 days. Within the decreasing phase this dropped to about ??88 days. Examination of each burn site revealed some nonburn related influences on NDVI (e.g., seasonality). Normalization of burn NDVI by site-specific nonburn control NDVI eliminated most influences. However, differential responses at the site-specific level remained related to either storm impacts or secondary burning. At these sites, collateral data helped clarify the abnormal changes in NDVI. Accounting for these abnormalities, site-specific burn recovery trends could be broadly standardized into four general phases: Phase 1-preburn, Phase 2-initial recovery (increasing NDVI), Phase 3-late recovery (decreasing NDVI), and Phase 4-final coalescence (unchanging NDVI). Phase 2 tended to last about 300 to 500 days, Phase 3 an additional 500 to 600 days, and finally reaching Phase 4, 900 to 1,000 days after burn.

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

    SciTech Connect

    Rahilly, P.J.A.; Li, D.; Guo, Q.; Zhu, J.; Ortega, R.; Quinn, N.W.T.; Harmon, T.C.

    2010-01-15

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

  13. Estimating evapotranspiration using remote sensing: A hybrid approach between MODIS derived enhanced vegetation index, Bowen ratio system, and ground based micro-meteorological data

    NASA Astrophysics Data System (ADS)

    Chatterjee, Sumantra

    We investigated water loss by evapotranspiration (ET) from the Palo Verde Irrigation District (PVID) and the Cibola National Wildlife Refuge (CNWR) in southern California bordering the Colorado River collaborating with the United States Bureau of Reclamation (U.S.B.R.). We developed an empirical model to estimate ET for the entire PVID using satellite derived MODIS enhanced vegetation index (EVI), and ground based measurements of solar radiation and vapor pressure. We compared our predictions with U.S.B.R. estimates through statistical cross validation and showed they agree with an error less than 8%. We tested the same model for an alfalfa field inside PVID to check its applicability at a smaller spatial scale. We showed that the same model developed for PVID is the best model for estimating ET for the alfalfa field. We collected data from three Bowen ratio energy balance (BREB) towers installed in the invasive saltcedar (Tamarix spp) dominated riparian zone in the CNWR and a fourth tower in the alfalfa field in PVID. The riparian sites were selected according to different densities of vegetation. We collected data from these sites at various intervals during the period between June 2006 to November 2008. We reduced the errors associated with the Bowen ratio data using statistical procedures taking into account occasional instrument failures and problems inherent in the BREB method. Our results were consistent with vegetation density and estimates from MODIS EVI images. To estimate ET for larger patches of mixed vegetation we modified the crop coefficient equation and represented it in terms of EVI. Using this approach, we scaled the alfalfa field data to the entire PVID and compared the results with U.S.B.R. (2001-2007) estimates. We predicted ET well within the acceptable range established in the literature. We empirically developed ET models for the riparian tower sites to provide accurate point scale ET estimation and scaled for the entire riparian region in

  14. Satellite vegetation index data as a tool to forecast population dynamics of medically important mosquitoes at military installations in the continental United States.

    PubMed

    Britch, Seth C; Linthicum, Kenneth J; Anyamba, Assaf; Tucker, Compton J; Pak, Edwin W; Maloney, Francis A; Cobb, Kristin; Stanwix, Erin; Humphries, Jeri; Spring, Alexandra; Pagac, Benedict; Miller, Melissa

    2008-07-01

    The United States faces many existing and emerging mosquito-borne disease threats, such as West Nile virus and Rift Valley fever. An important component of strategic prevention and control plans for these and other mosquito-borne diseases is forecasting the distribution, timing, and abundance of mosquito vector populations. Populations of many medically important mosquito species are closely tied to climate, and historical climate-population associations may be used to predict future population dynamics. Using 2003-2005 U.S. Army Center for Health Promotion and Preventive Medicine mosquito surveillance data, we looked at populations of several known mosquito vectors of West Nile virus, as well as possible mosquito vectors of Rift Valley fever virus, at continental U.S. military installations. We compared population changes with concurrent patterns for a satellite-derived index of climate (normalized difference vegetation index) and observed instances of population changes appearing to be direct responses to climate. These preliminary findings are important first steps in developing an automated, climate-driven, early warning system to flag regions of the United States at elevated risk of mosquito-borne disease transmission.

  15. Development of a remotely sensing seasonal vegetation-based Palmer Drought Severity Index and its application of global drought monitoring over 1982-2011

    NASA Astrophysics Data System (ADS)

    Yan, Hao; Wang, Shao-Qiang; Lu, Hou-Quan; Yu, Qin; Zhu, Zai-Chun; Myneni, Ranga B.; Liu, Qiang; Shugart, Herman H.

    2014-08-01

    Vegetation effects are currently disregarded in Palmer Drought Severity Index (PDSI), and the sensitivity of PDSI to the choice of potential evaporation (EP) parameterization is often a concern. We developed a revised self-calibrating PDSI model that replaces EP with leaf area index-based total evapotranspiration (ARTS E0). It also included a simple snowmelt module. Using a unique satellite leaf area index data set and climate data, we calculated and compared ARTS E0, three other types of EP (i.e., Thornthwaite EP_Th, Allen EP_Al, and Penman-Monteith EP_PM), and corresponding PDSI values (i.e., PDSI_ARTS, PDSI_Th, PDSI_Al, and PDSI_PM) for the period 1982-2011. The results of PDSI_ARTS, PDSI_Al, and PDSI_PM show that global land became wetter mainly due to increased precipitation and El Niño-Southern Oscillation (ENSO) effect for the period, which confirms the ongoing intensification of global hydrologic cycle with global temperature increase. However, only PDSI_Th gave a trend of global drying, which confirms that PDSI_Th overestimates the global drying in response to global warming; i.e., PDSI values are sensitive to the parameterizations for Ep. Thus, ARTS E0, EP_Al, and EP_PM are preferred to EP_Th in global drought monitoring. In short, global warming affects global drought condition in two opposite ways. One is to contribute to the increases of EP and hence drought; the other is to increase global precipitation that contributes to global wetting. These results suggest that precipitation trend and its interaction with global warming and ENSO should be given much attention to correctly quantify past and future trends of drought.

  16. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

    NASA Astrophysics Data System (ADS)

    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  17. Integrating vegetation index time series and meteorological data to understand the effect of the land use/land cover (LULC) in the climatic seasonality of the Brazilian Cerrado

    NASA Astrophysics Data System (ADS)

    Lins, D. B.; Zullo, J.; Friedel, M. J.

    2013-12-01

    The Cerrado (savanna ecosystem) of São Paulo state (Brazil) represent a complex mosaic of different typologies of uses, actors and biophysical and social restrictions. Originally, 14% of the state of São Paulo area was covered by the diversity of Cerrado phytophysiognomies. Currently, only 1% of this original composition remains fragmented into numerous relicts of biodiversity, mainly concentrated in the central-eastern of the state. A relevant part of the fragments are found in areas of intense coverage change by human activities, whereas the greatest pressure comes from sugar cane cultivation, either by direct replacement of Cerrado vegetation or occupying pasture areas in the fragments edges. As a result, new local level dynamics has been introduced, directly or indirectly, affecting the established of processes in climate systems. In this study, the main goal is analyzing the relationship between the Cerrado landscape changing and the climate dynamics in regional and local areas. The multi-temporal MODIS 250 m Vegetation Index (VI) datasets (period of 2000 to 2012) are integrated with precipitation data of the correspondent period (http://www.agritempo.gov.br/),one of the most important variable of the spatial phytophysiognomies distribution. The integration of meteorological data enable the development of an integrated approach to understand the relationship between climatic seasonality and the changes in the spatial patterns. A procedure to congregated diverse dynamics information is the Self Organizing Map (SOM, Kohonen, 2001), a technique that relies on unsupervised competitive learning (Kohonen and Somervuo 2002) to recognize patterns. In this approach, high-dimensional data are represented on two dimensions, making possible to obtain patterns that takes into account information from different natures. Observed advances will contribute to bring machine-learning techniques as a valid tool to provide improve in land use/land cover (LULC) analyzes at

  18. Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index.

    PubMed

    Löw, Fabian; Waldner, François; Latchininsky, Alexandre; Biradar, Chandrashekhar; Bolkart, Maximilian; Colditz, René R

    2016-12-01

    The Asian Migratory locust (Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km(2) (28% of the observed area) was flagged as potential locust habitat and 5% represents a permanent high risk of locust infestation. Results are instrumental for predicting potential locust outbreaks and developing well-targeted management plans. The method offers positive perspectives for locust management and treatment of infested sites because it is able to deliver risk maps in near real time, with an accuracy of 80% in April-May which coincides with both locust hatching and the first control surveys. Such maps could help in rapid decision-making regarding control interventions against the initial locust congregations, and thus the efficiency of survey teams and the chemical treatments could be increased, thus potentially reducing environmental pollution

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  1. Remote sensing-based vegetation indices for monitoring vegetation change in the semi-arid region of Sudan

    NASA Astrophysics Data System (ADS)

    R. A., Majdaldin; Osunmadewa, B. A.; Csaplovics, E.; Aralova, D.

    2016-10-01

    Land degradation, a phenomenon referring to (drought) in arid, semi-arid and dry sub-humid regions as a result of climatic variations and anthropogenic activities most especially in the semi-arid lands of Sudan, where vast majority of the rural population depend solely on agriculture and pasture for their daily livelihood, the ecological pattern had been greatly influenced thereby leading to loss of vegetation cover coupled with climatic variability and replacement of the natural tree composition with invasive mesquite species. The principal aim of this study is to quantitatively examine the vigour of vegetation in Sudan through different vegetation indices. The assessment was done based on indicators such as soil adjusted vegetation index (SAVI). Cloud free multi-spectral remotely sensed data from LANDSAT imagery for the dry season periods of 1984 and 2009 were used in this study. Results of this study shows conversion of vegetation to other land use type. In general, an increase in area covered by vegetation was observed from the NDVI results of 2009 which is a contrast of that of 1984. The results of the vegetation indices for NDVI in 1984 (vegetated area) showed that about 21% was covered by vegetation while 49% of the area were covered with vegetation in 2009. Similar increase in vegetated area were observed from the result of SAVI. The decrease in vegetation observed in 1984 is as a result of extensive drought period which affects vegetation productivity thereby accelerating expansion of bare surfaces and sand accumulation. Although, increase in vegetated area were observed from the result of this study, this increase has a negative impact as the natural vegetation are degraded due to human induced activities which gradually led to the replacement of the natural vegetation with invasive tree species. The results of the study shows that NDVI perform better than by SAVI.

  2. Functional analysis of Normalized Difference Vegetation Index curves reveals overwinter mule deer survival is driven by both spring and autumn phenology

    PubMed Central

    Hurley, Mark A.; Hebblewhite, Mark; Gaillard, Jean-Michel; Dray, Stéphane; Taylor, Kyle A.; Smith, W. K.; Zager, Pete; Bonenfant, Christophe

    2014-01-01

    Large herbivore populations respond strongly to remotely sensed measures of primary productivity. Whereas most studies in seasonal environments have focused on the effects of spring plant phenology on juvenile survival, recent studies demonstrated that autumn nutrition also plays a crucial role. We tested for both direct and indirect (through body mass) effects of spring and autumn phenology on winter survival of 2315 mule deer fawns across a wide range of environmental conditions in Idaho, USA. We first performed a functional analysis that identified spring and autumn as the key periods for structuring the among-population and among-year variation of primary production (approximated from 1 km Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI)) along the growing season. A path analysis showed that early winter precipitation and direct and indirect effects of spring and autumn NDVI functional components accounted for 45% of observed variation in overwinter survival. The effect size of autumn phenology on body mass was about twice that of spring phenology, while direct effects of phenology on survival were similar between spring and autumn. We demonstrate that the effects of plant phenology vary across ecosystems, and that in semi-arid systems, autumn may be more important than spring for overwinter survival. PMID:24733951

  3. The use of multi-temporal Landsat Normalized Difference Vegetation Index (NDVI) data for mapping fuels in Yosemite National Park, USA

    USGS Publications Warehouse

    Van Wagtendonk, Jan W.; Root, Ralph R.

    2003-01-01

    The objective of this study was to test the applicability of using Normalized Difference Vegetation Index (NDVI) values derived from a temporal sequence of six Landsat Thematic Mapper (TM) scenes to map fuel models for Yosemite National Park, USA. An unsupervised classification algorithm was used to define 30 unique spectral-temporal classes of NDVI values. A combination of graphical, statistical and visual techniques was used to characterize the 30 classes and identify those that responded similarly and could be combined into fuel models. The final classification of fuel models included six different types: short annual and perennial grasses, tall perennial grasses, medium brush and evergreen hardwoods, short-needled conifers with no heavy fuels, long-needled conifers and deciduous hardwoods, and short-needled conifers with a component of heavy fuels. The NDVI, when analysed over a season of phenologically distinct periods along with ancillary data, can elicit information necessary to distinguish fuel model types. Fuels information derived from remote sensors has proven to be useful for initial classification of fuels and has been applied to fire management situations on the ground.

  4. Support vector data description model to map urban extent from National Polar-Orbiting Partnership Satellite-Visible Infrared Imaging Radiometer Suite nightlights and normalized difference vegetation index

    NASA Astrophysics Data System (ADS)

    Zhang, Jinshui; Zhou, Zhongwei; Shuai, Guanyuan; Liu, Hongli

    2016-04-01

    We explored a one-class classifier, the support vector data description (SVDD), using the Suomi National Polar-Orbiting Partnership Satellite-Visible Infrared Imaging Radiometer Suite and normalized difference vegetation index to map the urban extent, which was tested in the Beijing and Tianjin city group area. The urban edge-pixels were selected as training samples for SVDD based on a profile-based sampling method combining nighttime light value histograms. The results showed that the overall accuracy of SVDD was similar to the support vector machine (SVM) model. However, kappa coefficients of SVDD for highly developed cities were superior to SVM, as producer and user accuracies of SVDD were almost equal to show high agreement of urban and nonurban areas. For metropolitan areas, such as Beijing and Tianjin, the urban extent generated by SVDD is closer to the reference data. The R2 between the quantity of SVDD-estimated urban extent and population, 0.86, was higher than that obtained from SVM, 0.76, indicating that the estimated urban extent from the SVDD is more efficient for understanding the population development. The SVDD was further applied for three other representative metropolitans in China: Shanghai, Guangzhou, and Shenzhen to validate the SVDD's performance, and similar results were achieved. The success of the SVDD-based urban extent extraction improves our ability to map urban extent at regional and national scales.

  5. Crop Species Recognition and Discrimination Paddy-Rice from Reaped-Fields by the Radar Vegetation Index (rvi) of ALOS-2/PALSAR2

    NASA Astrophysics Data System (ADS)

    Yamada, Y.

    2016-06-01

    The Japanese ALOS-2 satellite was launched on May 24th, 2014. It has the L-band SAR, PALSAR-2. Kim,Y. and van Zyl, J.J. proposed a kind of Radar Vegetation Index (RVI) as RVI = 8 * σ0hv / (σ0hh + σ0vv + 2* σ0hv) by L-band full-polarimetric radar data. Kim, Y. and Jackson, T.J., et al. applied the equation into rice and soybean by multi-frequency polarimetric scatterometer above 4.16 meters from the ground. Their report showed the L-band was the most promising wave length for estimating LAI and NDVI from RVI. The author tried to apply the analysis to the actual paddy field areas, both Inashiki region and Miyagi region in the eastern main island, "Honshu", areas of Japan by ALOS-2/PALSAR-2 full-polarimetry data in the summer season, the main crop growing time, of 2015. Judging from conventional methods, it will be possible to discriminate paddy rice growing fields from reaped fields or the other crops growing fields by the PALSAR-2 data. But the RVI value is vaguely related to such land use or biomass at the present preliminary experiment. The continuous research by the additional PALSAR-2 full-polarimetry data should be desired.

  6. The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

    NASA Technical Reports Server (NTRS)

    Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

    2015-01-01

    We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

  7. Functional analysis of normalized difference vegetation index curves reveals overwinter mule deer survival is driven by both spring and autumn phenology.

    PubMed

    Hurley, Mark A; Hebblewhite, Mark; Gaillard, Jean-Michel; Dray, Stéphane; Taylor, Kyle A; Smith, W K; Zager, Pete; Bonenfant, Christophe

    2014-01-01

    Large herbivore populations respond strongly to remotely sensed measures of primary productivity. Whereas most studies in seasonal environments have focused on the effects of spring plant phenology on juvenile survival, recent studies demonstrated that autumn nutrition also plays a crucial role. We tested for both direct and indirect (through body mass) effects of spring and autumn phenology on winter survival of 2315 mule deer fawns across a wide range of environmental conditions in Idaho, USA. We first performed a functional analysis that identified spring and autumn as the key periods for structuring the among-population and among-year variation of primary production (approximated from 1 km Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI)) along the growing season. A path analysis showed that early winter precipitation and direct and indirect effects of spring and autumn NDVI functional components accounted for 45% of observed variation in overwinter survival. The effect size of autumn phenology on body mass was about twice that of spring phenology, while direct effects of phenology on survival were similar between spring and autumn. We demonstrate that the effects of plant phenology vary across ecosystems, and that in semi-arid systems, autumn may be more important than spring for overwinter survival.

  8. 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.

  9. Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana

    PubMed Central

    Hanschen, Franziska S.; Klopsch, Rebecca; Oliviero, Teresa; Schreiner, Monika; Verkerk, Ruud; Dekker, Matthijs

    2017-01-01

    Consumption of glucosinolate-rich Brassicales vegetables is associated with a decreased risk of cancer with enzymatic hydrolysis of glucosinolates playing a key role. However, formation of health-promoting isothiocyanates is inhibited by the epithiospecifier protein in favour of nitriles and epithionitriles. Domestic processing conditions, such as changes in pH value, temperature or dilution, might also affect isothiocyanate formation. Therefore, the influences of these three factors were evaluated in accessions of Brassica rapa, Brassica oleracea, and Arabidopsis thaliana. Mathematical modelling was performed to determine optimal isothiocyanate formation conditions and to obtain knowledge on the kinetics of the reactions. At 22 °C and endogenous plant pH, nearly all investigated plants formed nitriles and epithionitriles instead of health-promoting isothiocyanates. Response surface models, however, clearly demonstrated that upon change in pH to domestic acidic (pH 4) or basic pH values (pH 8), isothiocyanate formation considerably increases. While temperature also affects this process, the pH value has the greatest impact. Further, a kinetic model showed that isothiocyanate formation strongly increases due to dilution. Finally, the results show that isothiocyanate intake can be strongly increased by optimizing the conditions of preparation of Brassicales vegetables. PMID:28094342

  10. Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana

    NASA Astrophysics Data System (ADS)

    Hanschen, Franziska S.; Klopsch, Rebecca; Oliviero, Teresa; Schreiner, Monika; Verkerk, Ruud; Dekker, Matthijs

    2017-01-01

    Consumption of glucosinolate-rich Brassicales vegetables is associated with a decreased risk of cancer with enzymatic hydrolysis of glucosinolates playing a key role. However, formation of health-promoting isothiocyanates is inhibited by the epithiospecifier protein in favour of nitriles and epithionitriles. Domestic processing conditions, such as changes in pH value, temperature or dilution, might also affect isothiocyanate formation. Therefore, the influences of these three factors were evaluated in accessions of Brassica rapa, Brassica oleracea, and Arabidopsis thaliana. Mathematical modelling was performed to determine optimal isothiocyanate formation conditions and to obtain knowledge on the kinetics of the reactions. At 22 °C and endogenous plant pH, nearly all investigated plants formed nitriles and epithionitriles instead of health-promoting isothiocyanates. Response surface models, however, clearly demonstrated that upon change in pH to domestic acidic (pH 4) or basic pH values (pH 8), isothiocyanate formation considerably increases. While temperature also affects this process, the pH value has the greatest impact. Further, a kinetic model showed that isothiocyanate formation strongly increases due to dilution. Finally, the results show that isothiocyanate intake can be strongly increased by optimizing the conditions of preparation of Brassicales vegetables.

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

    PubMed Central

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

    2015-01-01

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

  12. Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale.

    PubMed

    Bro-Jørgensen, Jakob; Brown, Molly E; Pettorelli, Nathalie

    2008-11-01

    Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors.

  13. The relationship of hyper-spectral vegetation indices with leaf area index (LAI) over the growth cycle of wheat and chickpea at 3 nm spectral resolution

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.

    2006-01-01

    Hyperspectral ratio and normalized difference vegetation indices were computed from the 3 nm bandwidth ground-based spectral data taken in 400-950 nm wave length region over the crop growth cycle (CGC) of wheat and chickpea. Synthesized broad band Landsat TM-RVI, TM-NDVI and TM-SAVI were also computed using this narrow bandwidth spectral observations. Regression analysis was carried out for these indices with leaf area index (LAI) for wheat and chickpea over CGC and the r2 values were found poor in 0.2-0.53 range for wheat and in 0.41-0.82 range for chickpea. Significant relationship with LAI were found for wheat ( r2 in 0.86-0.97 range) when growth and decline phases were analyzed independently. Here, r2 values for chickpea were less than that for wheat. The high difference in rate of change of slope for hRVI is a good discriminator for high ET (wheat) and low ET (chickpea) crops. To find out the potential hyperspectral ratios and normalized difference indices that could provide strong relationship with LAI, a correlation-based analysis was carried out for LAI with all the possible combinations of ratios and normalized difference indices in 400-950 nm region (at 3 nm spectral interval) independently for growth and decline phases of LAI and found that in addition to traditional near-IR and red pairs, the pairs within near-IR, near-IR and visible extending to near-IR were also significantly related to LAI.

  14. Multi-Temporal Crop Surface Models Combined with the RGB Vegetation Index from Uav-Based Images for Forage Monitoring in Grassland

    NASA Astrophysics Data System (ADS)

    Possoch, M.; Bieker, S.; Hoffmeister, D.; Bolten, A.; Schellberg, J.; Bareth, G.

    2016-06-01

    Remote sensing of crop biomass is important in regard to precision agriculture, which aims to improve nutrient use efficiency and to develop better stress and disease management. In this study, multi-temporal crop surface models (CSMs) were generated from UAV-based dense imaging in order to derive plant height distribution and to determine forage mass. The low-cost UAV-based RGB imaging was carried out in a grassland experiment at the University of Bonn, Germany, in summer 2015. The test site comprised three consecutive growths including six different nitrogen fertilizer levels and three replicates, in sum 324 plots with a size of 1.5×1.5 m. Each growth consisted of six harvesting dates. RGB-images and biomass samples were taken at twelve dates nearly biweekly within two growths between June and September 2015. Images were taken with a DJI Phantom 2 in combination of a 2D Zenmuse gimbal and a GoPro Hero 3 (black edition). Overlapping images were captured in 13 to 16 m and overview images in approximately 60 m height at 2 frames per second. The RGB vegetation index (RGBVI) was calculated as the normalized difference of the squared green reflectance and the product of blue and red reflectance from the non-calibrated images. The post processing was done with Agisoft PhotoScan Professional (SfM-based) and Esri ArcGIS. 14 ground control points (GCPs) were located in the field, distinguished by 30 cm × 30 cm markers and measured with a RTK-GPS (HiPer Pro Topcon) with 0.01 m horizontal and vertical precision. The errors of the spatial resolution in x-, y-, z-direction were in a scale of 3-4 cm. From each survey, also one distortion corrected image was georeferenced by the same GCPs and used for the RGBVI calculation. The results have been used to analyse and evaluate the relationship between estimated plant height derived with this low-cost UAV-system and forage mass. Results indicate that the plant height seems to be a suitable indicator for forage mass. There is a

  15. Investigation of environmental change pattern in Japan. Investigation of the ecological environment index from observation of the regional vegetation cover and their growing condition

    NASA Technical Reports Server (NTRS)

    Maruyasu, T. (Principal Investigator); Nakajima, I.

    1977-01-01

    The author has identified the following significant results. Practical use of recognition results of LANDSAT data as the base map of the field survey or the retouching work of vegetation and land use has the effective benefit to cut down the cost, labor, and time lower than 10% of a conventional method. Correct and detailed vegetation maps were prepared using combined interpretation of repetition of data of different seasons at warm and temperate forested areas.

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

    PubMed

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

    2014-03-01

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

  17. [Estimation models of vegetation fractional coverage (VFC) based on remote sensing image at different radiometric correction levels].

    PubMed

    Gu, Zhu-Jun; Zeng, Zhi-Yuan; Shi, Xue-Zheng; Yu, Dong-Sheng; Zheng, Wei; Zhang, Zhen-Long; Hu, Zi-Fu

    2008-06-01

    The images of post atmospheric correction reflectance (PAC), top of atmosphere reflectance (TOA), and digital number (DN) of a SPOT5 HRG remote sensing image of Nanjing, China were used to derive four vegetation indices (VIs), i. e., normalized difference vegetation index (NDVI), transformed vegetation index (TVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI), and 36 VI-VFC relationship models were established based on these VIs and the VFC data obtained from ground measurement. The results showed that among the models established, the cubic polynomial models based on NDVI and TVI from PAC were the best, followed by those based on SAVI and MSAVI from DN, with the accuracy being slightly higher than that of the former two models when VFC > 0.8. The accuracy of these four models was higher in middle-densely vegetated areas (VFC = 0.4-0.8) than in sparsely vegetated areas (VFC = 0-0.4). All the established models could be used in other places via the introduction of calibration models. In VI-VFC modeling, using VIs derived from different radiometric correction levels of remote sensing image could help mining valuable information from remote sensing image, and thus, improving the accuracy of VFC estimation.

  18. Vegetation against dune mobility.

    PubMed

    Durán, Orencio; Herrmann, Hans J

    2006-11-03

    Vegetation is the most common and most reliable stabilizer of loose soil or sand. This ancient technique is for the first time cast into a set of equations of motion describing the competition between aeolian sand transport and vegetation growth. Our set of equations is then applied to study quantitatively the transition between barchans and parabolic dunes driven by the dimensionless fixation index theta which is the ratio between the dune characteristic erosion rate and vegetation growth velocity. We find a fixation index theta(c) below which the dunes are stabilized, characterized by scaling laws.

  19. Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

    USGS Publications Warehouse

    Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

    2016-01-01

    We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

  20. NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA

    USGS Publications Warehouse

    Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.; Phuyal, Khem P.; Ji, Lei

    2013-01-01

    In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVIsat_adjust) based on RVI was developed. A 10-year (2000–2009) NDVIsat_adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CPnon_sat_adjust, CPsat_adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CPsat_adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CPnon_sat_adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CPsat_adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.

  1. A refractive index-matched facility for fluid-structure interaction studies of pulsatile and oscillating flow in elastic vessels of adjustable compliance

    NASA Astrophysics Data System (ADS)

    Burgmann, S.; Große, S.; Schröder, W.; Roggenkamp, J.; Jansen, S.; Gräf, F.; Büsen, M.

    2009-10-01

    The flow field in the respiratory and vascular system is known to be influenced by the flexibility of the walls. However, up to now, most of the experimental biofluidic investigations have been performed in rigid models due to the complexity and necessity of optical access. In this paper, a facility and measurement techniques for studying oscillating and pulsatile flow in elastic vessels will be described. The investigated vessel models have been adapted such that fluid-mechanical and structure-mechanical characteristics represent realistic blood flows in medium blood vessels. That is, characteristic parameters, i.e., the Reynolds and Womersley number, as well as mechanical properties of the flexible wall, i.e., the Young’s modulus and the material compliance, have been chosen to reasonably represent realistic flow conditions. First, a method to manufacture elastic models, which mimic the structure-mechanical properties of vascular vessels is described. The models possess a tunable compliance and are made of transparent polydimethylsiloxane. Second, the experimental setup of the flow facility will be elucidated. The flow facility allows to mimic pulsatile flow at physiologically relevant Reynolds and Womersley numbers. The precise form of the flow cycle can individually be controlled. Water/glycerine is used as flow medium for refractive index matching particle image velocimetry (PIV) measurements. The PIV recordings not only allow to assess the mean cross-sectional flow field but also further enable to simultaneously detect the movement of the flexible wall. Additionally, the local wall-shear stress can be obtained from the single-pixel line resolved near-wall flow field. To confirm the flow conditions of the oscillatory laminar flow inside the flow facility and to evaluate the ability to assess the flow field, measurements in a straight, uniform diameter, rigid Plexiglas pipe under identical conditions to those of the oscillating flow in the flexible vessel

  2. Retrospective analysis of age-adjusted body mass index among pre-pregnant women in the Lithuanian urban area during three decades

    PubMed Central

    Francaite-Daugeliene, Migle; Petrenko, Vladimiras; Baliutaviciene, Dalia; Velickiene, Dzilda

    2016-01-01

    Background The prevalence of maternal obesity at the beginning of pregnancy is increasing. However, there are some studies reporting the stabilisation of obesity epidemic or even the downward trend in the general population. Objective To determine the prevalence of overweight and obesity in Lithuanian pre-pregnant women during 3 decades. Methods This observational retrospective study included a sample of 2827, women aged 18–44 years who gave birth in 1987–1989, 1996–1997 and 2007–2010: 861 (30.5%), 995 (35.2%) and 971 (34.3%), respectively. All women were divided into groups by body mass index (BMI) calculated from self-reported weight and height, and age reported during the first antenatal visit. Quantitative parametric variables were expressed as mean and SD; qualitative variables, as absolute numbers (n) and percentage (%). For parametric data, analysis of variance (ANOVA) was used. Differences were considered statistically significant at p<0.05. Results The prevalence of overweight and obesity among women aged 18–24 years decreased from 20.9% in 1987–1989 to 9.5% in 1996–1997 but increased to 15.7% in 2007–2010; among women aged 25–34 years, decreased from 35.5% in 1987–1989 to 23% in 1996–1997 and to 22.4% in 2007–2010; and among women aged 35–44 years decreased from 64.9% in 1987–1989 to 34% in 1996–1997 but increased to 45.3% in 2007–2010. BMI increased with an increasing age (r=0.254, p<0.05). Analysis by separate periods (1987–1989, 1996–1997 and 2007–2010) revealed a positive correlation between BMI and age at the first antenatal visit in all periods (r=0.325, p<0.01; r=0.266, p<0.01; and r=0.210, p<0.01, respectively). Conclusions The prevalence of overweight and obesity among pre-pregnant women tended to decrease in the Lithuanian urban area during 3 decades. A slight increase in overweight and obesity documented in 2007–2010 compared with 1996–1997 most likely was caused by older maternal age. PMID

  3. A MODIS-based begetation index climatology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. 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

    samples vary with the outcomes of the bionomic properties of the mosquito species themselves, such as flight range, quality and avail- ability of...Surveillance Data Mosquito Species Aedes atbopictux Aedes ve.xans Anopheles crucians CoquiHemdiii perturbans Culi seta melanura Cule.x erythrothorax Culex...ponds Heavily vegetated bodies of water Tree holes and swamp.s Cattail marshes and ponds Stagnant water pools Fresh or foul water pools Salt marshes Tree

  5. Evaluating the Use of the Case Mix Index for Risk Adjustment of Healthcare-Associated Infection Data: An Illustration using Clostridium difficile Infection Data from the National Healthcare Safety Network.

    PubMed

    Thompson, Nicola D; Edwards, Jonathan R; Dudeck, Margaret A; Fridkin, Scott K; Magill, Shelley S

    2016-01-01

    BACKGROUND Case mix index (CMI) has been used as a facility-level indicator of patient disease severity. We sought to evaluate the potential for CMI to be used for risk adjustment of National Healthcare Safety Network (NHSN) healthcare-associated infection (HAI) data. METHODS NHSN facility-wide laboratory-identified Clostridium difficile infection event data from 2012 were merged with the fiscal year 2012 Inpatient Prospective Payment System (IPPS) Impact file by CMS certification number (CCN) to obtain a CMI value for hospitals reporting to NHSN. Negative binomial regression was used to evaluate whether CMI was significantly associated with healthcare facility-onset (HO) CDI in univariate and multivariate analysis. RESULTS Among 1,468 acute care hospitals reporting CDI data to NHSN in 2012, 1,429 matched by CCN to a CMI value in the Impact file. CMI (median, 1.49; interquartile range, 1.36-1.66) was a significant predictor of HO CDI in univariate analysis (P<.0001). After controlling for community onset CDI prevalence rate, medical school affiliation, hospital size, and CDI test type use, CMI remained highly significant (P<.0001), with an increase of 0.1 point in CMI associated with a 3.4% increase in the HO CDI incidence rate. CONCLUSIONS CMI was a significant predictor of NHSN HO CDI incidence. Additional work to explore the feasibility of using CMI for risk adjustment of NHSN data is necessary. Infect. Control Hosp. Epidemiol. 2015;37(1):19-25.

  6. Chiropractic Adjustment

    MedlinePlus

    ... structural alignment and improve your body's physical function. Low back pain, neck pain and headache are the most common ... treated. Chiropractic adjustment can be effective in treating low back pain, although much of the research done shows only ...

  7. Adjustment disorder

    MedlinePlus

    ... from other people Skipped heartbeats and other physical complaints Trembling or twitching To have adjustment disorder, you ... ADAM Health Solutions. About MedlinePlus Site Map FAQs Customer Support Get email updates Subscribe to RSS Follow ...

  8. Exploring the Relationship Between Water Flux and Vegetation Water Status Using Time Series Data of Evapotranspiration and Modis Vegetation Indices

    NASA Astrophysics Data System (ADS)

    Cheng, T.; Riaño, D.; Ustin, S.

    2012-12-01

    In agricultural practices, evapotranspiration (ET) data obtained from weather stations or flux towers are used to monitor crop water use and schedule irrigation over the growing season. Recent advances in remote sensing have shown that satellite data (e.g., MODIS) can be used to quantify the amount of water held in vegetation canopies. However, the relationship between how much water has been used through the ET process and how much water is maintained in vegetation canopies remains unclear. This study aimed to investigate how vegetation canopy water content is related to ET for almond orchards in the southern San Joaquin Valley of California. MODIS Nadir BRDF-Adjusted Reflectance 8-day 500 m data for the growing season of 2011 (March ~ November of 2011) were used to derive a number of vegetation indices as spectral indicators of canopy water content, including the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Infrared Index using MODIS Band 6 (NDII) and the Normalized Difference Infrared Index using MODIS Band 7 (NDII7). These times series of MODIS indices were then compared to flux tower-based ET measurements temporally integrated from half-hourly to 8 days for the same time period. Our results showed all vegetation indices could account for more than 70% of variation in the ET data and the two infrared indices (NDII and NDII7) explained more than the other three indices. The relationships between vegetation indices and ET were generally positive and rate of ET change increased while the water content in almond canopies increased. The seasonal trajectory of ET could be fitted by a Gaussian function, with the ET peaking at day of year (DOY) 179. All vegetation indices exhibited broader peaking periods than ET due to insensitivity of spectral signals to fully developed canopies. The Gaussian function fitted to the NDII trajectory had the peaking day closest

  9. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn. Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation. VIs for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these VIs produced from the two satellite systems with different spatial and spectral resolution was made for each growth stage of the crops and their results were analyzed in order to examine their correlation. Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.

  10. White Light Emission from Vegetable Extracts.

    PubMed

    Singh, Vikram; Mishra, Ashok K

    2015-06-17

    A mixture of extracts from two common vegetables, red pomegranate and turmeric, when photoexcited at 380 nm, produced almost pure white light emission (WLE) with Commission Internationale d'Eclairage (CIE) chromaticity index (0.35, 0.33) in acidic ethanol. It was also possible to obtain WLE in polyvinyl alcohol film (0.32, 0.25), and in gelatin gel (0.26, 0.33) using the same extract mixture. The colour temperature of the WLE was conveniently tunable by simply adjusting the concentrations of the component emitters. The primary emitting pigments responsible for contributing to WLE were polyphenols and anthocyanins from pomegranate, and curcumin from turmeric. It was observed that a cascade of Forster resonance energy transfer involving polyphenolics, curcumin and anthocyanins played a crucial role in obtaining a CIE index close to pure white light. The optimized methods of extraction of the two primary emitting pigments from their corresponding plant sources are simple, cheap and fairly green.

  11. 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.

  12. Relationships of body mass index with serum carotenoids, tocopherols and retinol at steady-state and in response to a carotenoid-rich vegetable diet intervention in Filipino schoolchildren.

    PubMed

    Ribaya-Mercado, Judy D; Maramag, Cherry C; Tengco, Lorena W; Blumberg, Jeffrey B; Solon, Florentino S

    2008-04-01

    In marginally nourished children, information is scarce regarding the circulating concentrations of carotenoids and tocopherols, and physiological factors influencing their circulating levels. We determined the serum concentrations of carotenoids, tocopherols and retinol at steady state and in response to a 9-week vegetable diet intervention in 9-12-year-old girls (n=54) and boys (n=65) in rural Philippines. We determined cross-sectional relationships of BMI (body mass index) with serum micronutrient levels, and whether BMI is a determinant of serum carotenoid responses to the ingestion of carotenoid-rich vegetables. We measured dietary nutrient intakes and assessed inflammation by measurement of serum C-reactive protein levels. The children had low serum concentrations of carotenoids, tocopherols and retinol as compared with published values for similar-aged children in the U.S.A. The low serum retinol levels can be ascribed to inadequate diets and were not the result of confounding due to inflammation. Significant inverse correlations of BMI and serum all-trans-beta-carotene, 13-cis-beta-carotene, alpha-carotene, lutein, zeaxanthin and alpha-tocopherol (but not beta-cryptoxanthin, lycopene and retinol) were observed among girls at baseline. The dietary intervention markedly enhanced the serum concentrations of all carotenoids. Changes in serum all-trans-beta-carotene and alpha-carotene (but not changes in lutein, zeaxanthin and beta-cryptoxanthin) in response to the dietary intervention were inversely associated with BMI in girls and boys. Thus, in Filipino school-aged children, BMI is inversely related to the steady-state serum concentrations of certain carotenoids and vitamin E, but not vitamin A, and is a determinant of serum beta- and alpha-carotene responses, but not xanthophyll responses, to the ingestion of carotenoid-rich vegetable meals.

  13. Comparison of Hybrid Classifiers for Crop Classification Using Normalized Difference Vegetation Index Time Series: A Case Study for Major Crops in North Xinjiang, China.

    PubMed

    Hao, Pengyu; Wang, Li; Niu, Zheng

    2015-01-01

    A range of single classifiers have been proposed to classify crop types using time series vegetation indices, and hybrid classifiers are used to improve discriminatory power. Traditional fusion rules use the product of multi-single classifiers, but that strategy cannot integrate the classification output of machine learning classifiers. In this research, the performance of two hybrid strategies, multiple voting (M-voting) and probabilistic fusion (P-fusion), for crop classification using NDVI time series were tested with different training sample sizes at both pixel and object levels, and two representative counties in north Xinjiang were selected as study area. The single classifiers employed in this research included Random Forest (RF), Support Vector Machine (SVM), and See 5 (C 5.0). The results indicated that classification performance improved (increased the mean overall accuracy by 5%~10%, and reduced standard deviation of overall accuracy by around 1%) substantially with the training sample number, and when the training sample size was small (50 or 100 training samples), hybrid classifiers substantially outperformed single classifiers with higher mean overall accuracy (1%~2%). However, when abundant training samples (4,000) were employed, single classifiers could achieve good classification accuracy, and all classifiers obtained similar performances. Additionally, although object-based classification did not improve accuracy, it resulted in greater visual appeal, especially in study areas with a heterogeneous cropping pattern.

  14. Comparison of Hybrid Classifiers for Crop Classification Using Normalized Difference Vegetation Index Time Series: A Case Study for Major Crops in North Xinjiang, China

    PubMed Central

    Hao, Pengyu; Wang, Li; Niu, Zheng

    2015-01-01

    A range of single classifiers have been proposed to classify crop types using time series vegetation indices, and hybrid classifiers are used to improve discriminatory power. Traditional fusion rules use the product of multi-single classifiers, but that strategy cannot integrate the classification output of machine learning classifiers. In this research, the performance of two hybrid strategies, multiple voting (M-voting) and probabilistic fusion (P-fusion), for crop classification using NDVI time series were tested with different training sample sizes at both pixel and object levels, and two representative counties in north Xinjiang were selected as study area. The single classifiers employed in this research included Random Forest (RF), Support Vector Machine (SVM), and See 5 (C 5.0). The results indicated that classification performance improved (increased the mean overall accuracy by 5%~10%, and reduced standard deviation of overall accuracy by around 1%) substantially with the training sample number, and when the training sample size was small (50 or 100 training samples), hybrid classifiers substantially outperformed single classifiers with higher mean overall accuracy (1%~2%). However, when abundant training samples (4,000) were employed, single classifiers could achieve good classification accuracy, and all classifiers obtained similar performances. Additionally, although object-based classification did not improve accuracy, it resulted in greater visual appeal, especially in study areas with a heterogeneous cropping pattern. PMID:26360597

  15. Long-term follow-up of tandem high-dose therapy with autologous stem cell support for adults with high-risk age-adjusted international prognostic index aggressive non-Hodgkin Lymphomas: a GOELAMS pilot study.

    PubMed

    Monjanel, Hélène; Deconinck, Eric; Perrodeau, Elodie; Gastinne, Thomas; Delwail, Vincent; Moreau, Anne; François, Sylvie; Berthou, Christian; Gyan, Emmanuel; Milpied, Noël

    2011-06-01

    Single high-dose therapy (HDT) followed by autologous peripheral blood stem cell (PBSC) support improves complete response and overall survival (OS) in untreated aggressive non-Hodgkin's lymphoma (NHL). However, patients with a high age-adjusted international prognostic index (aa-IPI equal to 3) still have poor clinical outcome despite high dose intensity regimen. To improve complete response in this subgroup, the French Groupe Ouest-Est des Leucémies et Autres Maladies du Sang (GOELAMS) conducted a pilot phase II trial (073) evaluating tandem HDT with PBSC support in a series of 45 patients with aa-IPI equal to 3 untreated aggressive non-Hodgkin's lymphoma. After induction with an anthracyclin-containing regimen, responders underwent tandem HDT conditioned by high-dose mitoxantrone plus cytarabine for the first HDT and total-body irradiation (TBI), carmustine, etoposide, and cyclophosphamide for the second HDT. Thirty-one patients out of 41 evaluable patients completed the program. There were 4 toxic deaths. The complete response rate was 49%. With a median follow-up of 114 months for surviving patients, the OS was 51%, and 19 out of the 22 patients (86%) who reached a complete response are alive and relapse-free. Recent prospective evaluation of quality of life and comorbidities of surviving patients does not reveal long-term toxicities of the procedure. In the era of monoclonal antibodies and response-adapted therapy, the role of tandem HDT still need to be determined.

  16. Comparison of fractional vegetation cover estimations using dimidiate pixel models and look-up table inversions of the PROSAIL model from Landsat 8 OLI data

    NASA Astrophysics Data System (ADS)

    Ding, Yanling; Zhang, Hongyan; Li, Zhenwang; Xin, Xiaoping; Zheng, Xingming; Zhao, Kai

    2016-07-01

    Fractional vegetation cover (FVC) is an important variable for describing the quality and changes of vegetation in terrestrial ecosystems. Dimidiate pixel models and physical models are widely used to estimate FVC. Six dimidiate pixel models based on different vegetation indices (VI) and four look-up table (LUT) methods were compared to estimate FVC from Landsat 8 OLI data. Comparisons with in situ FVC of steppe and corn showed that the model proposed by Baret et al., which is based on the normalized difference vegetation index (NDVI), predicted FVC most accurately followed by Carlson and Ripley's method. Gutman and Ignatov's method overestimated FVC. Modified soil adjusted vegetation index (MSAVI) and the mixture of NDVI and RVI showed potential to replace NDVI in Gutman and Ignatov's model, whereas the difference vegetation index (DVI) performed less well. At low vegetation cover, the LUT using reflectances to constrain the cost function performed better than LUTs using VI to constrain the cost function, whereas at high vegetation cover, the LUT based on NDVI estimated FVC most accurately. The applications of DVI and MSAVI to constrain the cost function also obtained improvement at high vegetation cover. Overall, the accuracies of LUT methods were a little lower than those of dimidiate pixel models.

  17. Shaft adjuster

    DOEpatents

    Harry, H.H.

    1988-03-11

    Abstract and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus. 3 figs.

  18. Shaft adjuster

    DOEpatents

    Harry, Herbert H.

    1989-01-01

    Apparatus and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus.

  19. White vegetables: glycemia and satiety.

    PubMed

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

    2013-05-01

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

  20. Association between flavonoid-rich fruit and vegetable consumption and total serum bilirubin.

    PubMed

    Loprinzi, Paul D; Mahoney, Sara E

    2015-03-01

    Emerging work demonstrates that serum bilirubin is a novel biomarker implicated in cardiovascular and metabolic diseases. However, we have a limited understanding of the influence of flavonoid-rich fruit and vegetable consumption on bilirubin levels, which was the purpose of this study. Data from the 2003 to 2006 National Health and Nutrition Examination survey were used (n = 1783; 18-85 years of age), with analyses performed in 2014. Total serum bilirubin was measured from a blood sample. Using a food frequency questionnaire (FFQ), a flavonoid index variable was created summing the frequency of consumption of flavonoid-rich foods. After adjustments, greater consumption of flavonoid-rich fruits and vegetables was positively associated with bilirubin levels. Our findings suggest an association between flavonoid-rich fruit and vegetable consumption and bilirubin levels. If confirmed by prospective and experimental studies, then regular consumption of flavonoid-rich fruits and vegetables should be promoted to increase levels of bilirubin.

  1. Frequent summer droughts homogenize landscape vegetation patterns at the catchment scale

    NASA Astrophysics Data System (ADS)

    Hwang, T.; Band, L. E.; Miniat, C. F.; Song, C.

    2013-12-01

    Mountain watersheds are primary sources of freshwater, carbon sequestration, and other ecosystem services. There is significant interest in the effects of climate change and variability on the patterns and processes of these services over short to long time scales. Forest ecosystems are sensitive to interannual to long-term hydroclimate variability and they adjust leaf area and duration in response to water or nutrient availability. Therefore, much of the impact of hydroclimate variability and resulting water yield is manifested in vegetation dynamics in space and time since they provide 'a window into the underlying water balance' (Sivapalan, 2005). Landsat TM provides a three-decade multispectral imagery record which enables us to estimate changes in landscape vegetation patterns at fine resolution (30 m) over the period of global warming. We characterize the catchment-scale vegetation patterns with the ';hydrologic vegetation gradient (HVG)' (defined as the gradient of the normalized difference vegetation index (NDVI) along hydrologic flowpaths; Hwang et al., 2012) and the standard deviations of NDVI from historic Landsat TM images at six preserved headwater catchments in Coweeta Hydrologic Laboratory, NC. We also analyze long-term seasonal water balances and low flow patterns from observed hydrologic records. We found that vegetation gradients along hydrologic flowpaths have decreased with hydroclimate change due to the decreases in upslope subsidies. This study shows that forest ecosystems are responding to the variability in hydroclimate regime rather than the mean, especially to drought. This study provides mechanistic understanding of shifts in hydrologic and ecologic regimes in humid mountainous landscapes with hydroclimate change. It also presents the potential to use emergent vegetation patterns in space and time for the inference of long-term hydrologic behavior. Figure 1. Temporal patterns of the hydrologic vegetation gradient and standard deviations

  2. Vegetative response to water availability on the San Carlos Apache Reservation

    USGS Publications Warehouse

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

    2016-01-01

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

  3. Relation of raw and cooked vegetable consumption to blood pressure: the INTERMAP Study

    PubMed Central

    Chan, Q; Stamler, J; Brown, I J; Daviglus, M L; Van Horn, L; Dyer, A R; Oude Griep, L M; Miura, K; Ueshima, H; Zhao, L; Nicholson, J K; Holmes, E; Elliott, P

    2014-01-01

    Inverse associations have been reported of overall vegetable intake to blood pressure (BP); whether such relations prevail for both raw and cooked vegetables has not been examined. Here we report cross-sectional associations of vegetable intakes with BP for 2195 Americans ages 40–59 in the International Study of Macro/Micronutrients and Blood Pressure (INTERMAP) using four standardized multi-pass 24-h dietary recalls and eight BP measurements. Relations to BP of raw and cooked vegetables consumption, and main individual constituents were assessed by multiple linear regression. Intakes of both total raw and total cooked vegetables considered separately were inversely related to BP in multivariate-adjusted models. Estimated average systolic BP differences associated with two s.d. differences in raw vegetable intake (68 g per 1000 kcal) and cooked vegetable intake (92 g per 1000 kcal) were −1.9 mm Hg (95% confidence interval (CI): −3.1, −0.8; P=0.001) and −1.3 mm Hg (95% CI: −2.5, −0.2; P=0.03) without body mass index (BMI) in the full model; −1.3 mm Hg (95% CI: −2.4, −0.2; P=0.02) and −0.9 mm Hg (95% CI: −2.0, 0.2; P=0.1) with additional adjustment for BMI. Among commonly consumed individual raw vegetables, tomatoes, carrots, and scallions related significantly inversely to BP. Among commonly eaten cooked vegetables, tomatoes, peas, celery, and scallions related significantly inversely to BP. PMID:24257514

  4. Tracking Crop Leaf Area Index and Chlorophyll Content Using RapidEye Data in Northern Ontario, Canada

    NASA Astrophysics Data System (ADS)

    Shang, J.; Liu, J.; Ma, B.; Zhao, T.; Kovacs, J. M.; Jiao, X.; Dong, T.; Huffman, T.; Geng, X.; Walters, D.

    2014-12-01

    Information on crop phenological state such as flowering, maturing, drying, senescence, and harvesting is essential for crop production surveillance and yield prediction. Earth Observation data provide an important information source for monitoring crop development at various temporal and spatial scales. In particular, the availability of many high-spatial-resolution space sensors offers a powerful tool for precision farming. This study reports the results of a two-year (2012, 2013) study over spring wheat and canola fields using six different vegetation indices derived from the high-resolution (6.5m) RapidEye optical satellite data in northern Ontario, Canada. The study revealed that for both wheat and canola, significant relationships were observed between the ground-derived leaf area index (LAI) and all 6 vegetation indices tested. For spring wheat, the strongest relationship was found between LAI and the Modified Triangular Vegetation Index 2 (MTVI2), with a coefficient of determination (R2) of 0.95. For canola, a R2 of 0.92 was achieved. Strong relationships were also found between all six vegetation indices and the chlorophyll concentration index (CCI) measured in the fields using a CCM-200 device. The strongest correlation exists between CCI and the ratio of Modified the Chlorophyll Absorption Reflected Index (MCARI) and the Optimized Soil Adjusted Vegetation Index (OSAVI), with an R2 of 0.86. It suggests that RapidEye data can be used to track field-scale crop LAI and monitor crop chlorophyll content.

  5. Monitoring of maize chlorophyll content based on multispectral vegetation indices

    NASA Astrophysics Data System (ADS)

    Sun, Hong; Li, Minzan; Zheng, Lihua; Zhang, Yane; Zhang, Yajing

    2012-11-01

    In order to estimate the nutrient status of maize, the multi-spectral image was used to monitor the chlorophyll content in the field. The experiments were conducted under three different fertilizer treatments (High, Normal and Low). A multispectral CCD camera was used to collect ground-based images of maize canopy in green (G, 520~600nm), red (R, 630~690nm) and near-infrared (NIR, 760~900nm) band. Leaves of maize were randomly sampled to detect the chlorophyll content by UV-Vis spectrophotometer. The images were processed following image preprocessing, canopy segmentation and parameter calculation: Firstly, the median filtering was used to improve the visual contrast of image. Secondly, the leaves of maize canopy were segmented in NIR image. Thirdly, the average gray value (GIA, RIA and NIRIA) and the vegetation indices (DVI, RVI, NDVI, et al.) widely used in remote sensing were calculated. A new vegetation index, combination of normalized difference vegetation index (CNDVI), was developed. After the correlation analysis between image parameter and chlorophyll content, six parameters (GIA, RIA, NIRIA, GRVI, GNDVI and CNDVI) were selected to estimate chlorophyll content at shooting and trumpet stages respectively. The results of MLR predicting models showed that the R2 was 0.88 and the adjust R2 was 0.64 at shooting stage; the R2 was 0.77 and the adjust R2 was 0.31 at trumpet stage. It was indicated that vegetation indices derived from multispectral image could be used to monitor the chlorophyll content. It provided a feasible method for the chlorophyll content detection.

  6. Sea Surface Temperature and Vegetation Index

    NASA Technical Reports Server (NTRS)

    2002-01-01

    This is a composite MODIS image showing the 'green wave' of spring in North America and sea surface temperature in the ocean, collected over an 8-day period during the first week in April 2000. On land, the darker green pixels show where the most green foliage is being produced due to photosynthetic activity. Yellows on land show where there is little or no productivity and red is a boundary zone. In the ocean, orange and yellows show warmer waters and blues show colder values.

  7. Assessment of MSS spectral indexes for monitoring arid rangeland

    NASA Technical Reports Server (NTRS)

    Musick, H. B.

    1983-01-01

    The utility of MSS spectral indexes for monitoring arid rangeland vegetation was tested by determining correlations between spectral indexes and vegetation parameters and by examining retrospective MSS data to determine if vegetation change could be detected and measured using spectral indexes. MSS Band 5, albedo, and the Kauth-Thomas Brightness component appear to be useful for monitoring total vegetation cover. Multiseasonal green vegetation indexes could be used to estimate changes in the shrub/grass ratio. In retrospective monitoring, spectral index change appeared to be offset from true change, indicating that the methods used to standardize data sets for differences in solar elevation and sensor radiometric response were not completely successful.

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

    USGS Publications Warehouse

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

    2016-01-01

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

  9. Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI)

    PubMed Central

    Zhang, Tianhao; Gong, Wei; Wang, Wei; Ji, Yuxi; Zhu, Zhongmin; Huang, Yusi

    2016-01-01

    Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM2.5) is currently quite limited in China. By introducing NO2 and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a fused Aerosol Optical Depth (AOD) product and meteorological parameters could explain approximately 87% of the variability in the corresponding PM2.5 mass concentrations. There existed obvious increase in the estimation accuracy against the original GWR model without NO2 and EVI, where cross-validation R2 increased from 0.77 to 0.87. Both models tended to overestimate when measurement is low and underestimate when high, where the exact boundary value depended greatly on the dependent variable. There was still severe PM2.5 pollution in many residential areas until 2015; however, policy-driven energy conservation and emission reduction not only reduced the severity of PM2.5 pollution but also its spatial range, to a certain extent, from 2014 to 2015. The accuracy of satellite-derived PM2.5 still has limitations for regions with insufficient ground monitoring stations and desert areas. Generally, the use of NO2 and EVI in GWR models could more effectively estimate PM2.5 at the national scale than previous GWR models. The results in this study could provide a reasonable reference for assessing health impacts, and could be used to examine the effectiveness of emission control strategies under implementation in China. PMID:27941628

  10. 78 FR 59093 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-25

    ... quarter. In Railroad Cost Recovery Procedures--Productivity Adjustment, 5 I.C.C. 2d 434 (1989), aff'd sub... require the adjustment of the quarterly index for a measure of productivity. The provisions of 49 U.S.C... a productivity-adjusted RCAF. In Productivity Adjustment--Implementation, 1 S.T.B. 739 (1996),...

  11. 78 FR 70080 - Market Dominant Price Adjustment

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-22

    ... Market Dominant Price Adjustment AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The... market dominant products. The adjustments are scheduled to take effect January 26, 2014. This notice.... Ordering Paragraphs I. Overview A. Index-Based Price Changes for Market Dominant Classes of Mail...

  12. An Unbalance Adjustment Method for Development Indicators

    ERIC Educational Resources Information Center

    Tarabusi, Enrico Casadio; Guarini, Giulio

    2013-01-01

    This paper analyzes some aggregation aspects of the procedure for constructing a composite index on a multidimensional socio-economic phenomenon such as development, the main focus being on the unbalance among individual dimensions. First a theoretical framework is set up for the unbalance adjustment of the index. Then an aggregation function is…

  13. Inflation Adjustments for Defense Acquisition

    DTIC Science & Technology

    2014-10-01

    Harmon Daniel B. Levine Stanley A. Horowitz, Project Leader INSTITUTE FOR DEFENSE ANALYSES 4850 Mark Center Drive Alexandria, Virginia 22311-1882 Approved...T U T E F O R D E F E N S E A N A L Y S E S IDA Document D-5112 Inflation Adjustments for Defense Acquisition Bruce R. Harmon Daniel B. Levine...might do a better job? The focus of the study is on aircraft procurement. By way of terminology , “cost index,” “price index,” and “deflator” are used

  14. Spectral vegetation indices for estimating shrub cover, green phytomass and leaf turnover in a sedge-shrub tundra

    NASA Astrophysics Data System (ADS)

    Kushida, K.; Kim, Y.; Tsuyuzaki, S.; Fukuda, M.

    2008-12-01

    Using field observations, we determined the relationships between spectral indices and the shrub ratio, green phytomass and leaf turnover of a sedge-shrub tundra community in the Arctic National Wildlife Refuge, Alaska, USA. We established a 50-m ~ 50-m plot (69.73°N 143.62°W) located on a floodplain of the refuge. The willow shrub (Salix lanata) and sedge (Carex bigelowii) dominated the plot vegetation. In July to August 2007, we established ten 0.5-m ~ 0.5-m quadrats on both shrub- covered ground (shrub quadrats) and on ground with no shrubs (sedge quadrats). All the shrubs within the shrub quadrats were harvested, and the photosynthetic and non-photosynthetic parts were weighed. Subsequently, the remaining green phytomass was also harvested and weighed. The shrub quadrats were measured spectrally before and after harvesting the shrubs. The sedge quadrats were also measured spectrally. The shrub ratio was more strongly correlated with the normalized difference vegetation index (NDVI, R2 of 0.57) than the normalized difference infrared index (NDII), the soil-adjusted vegetation index (SAVI) or the enhanced vegetation index (EVI). On the other hand, for both green phytomass and leaf turnover, the strongest correlation was with NDII (R2 of 0.63 and 0.79, respectively).

  15. White Light Emission from Vegetable Extracts

    PubMed Central

    Singh, Vikram; Mishra, Ashok K.

    2015-01-01

    A mixture of extracts from two common vegetables, red pomegranate and turmeric, when photoexcited at 380 nm, produced almost pure white light emission (WLE) with Commission Internationale d’Eclairage (CIE) chromaticity index (0.35, 0.33) in acidic ethanol. It was also possible to obtain WLE in polyvinyl alcohol film (0.32, 0.25), and in gelatin gel (0.26, 0.33) using the same extract mixture. The colour temperature of the WLE was conveniently tunable by simply adjusting the concentrations of the component emitters. The primary emitting pigments responsible for contributing to WLE were polyphenols and anthocyanins from pomegranate, and curcumin from turmeric. It was observed that a cascade of Forster resonance energy transfer involving polyphenolics, curcumin and anthocyanins played a crucial role in obtaining a CIE index close to pure white light. The optimized methods of extraction of the two primary emitting pigments from their corresponding plant sources are simple, cheap and fairly green. PMID:26083264

  16. White Light Emission from Vegetable Extracts

    NASA Astrophysics Data System (ADS)

    Singh, Vikram; Mishra, Ashok K.

    2015-06-01

    A mixture of extracts from two common vegetables, red pomegranate and turmeric, when photoexcited at 380 nm, produced almost pure white light emission (WLE) with Commission Internationale d’Eclairage (CIE) chromaticity index (0.35, 0.33) in acidic ethanol. It was also possible to obtain WLE in polyvinyl alcohol film (0.32, 0.25), and in gelatin gel (0.26, 0.33) using the same extract mixture. The colour temperature of the WLE was conveniently tunable by simply adjusting the concentrations of the component emitters. The primary emitting pigments responsible for contributing to WLE were polyphenols and anthocyanins from pomegranate, and curcumin from turmeric. It was observed that a cascade of Forster resonance energy transfer involving polyphenolics, curcumin and anthocyanins played a crucial role in obtaining a CIE index close to pure white light. The optimized methods of extraction of the two primary emitting pigments from their corresponding plant sources are simple, cheap and fairly green.

  17. Urban Vegetation Cover and Vegetation Change in Accra, Ghana: Connection to Housing Quality.

    PubMed

    Stow, Douglas A; Weeks, John R; Toure, Sory; Coulter, Lloyd L; Lippitt, Christopher D; Ashcroft, Eric

    2013-01-01

    The objectives are to (1) quantify, map, and analyze vegetation cover distributions and changes across Accra, Ghana, for 2002 and 2010; and (2) examine the statistical relationship between vegetation cover and a housing quality index (HQI) for 2000 at the neighborhood level. Pixel-level vegetation cover maps derived using threshold classification of 2002 and 2010 QuickBird normalized difference vegetation index images have very high overall accuracies and yield an estimate of 5.9 percent vegetation cover reduction over the study area between 2002 and 2010. A high degree of variance in vegetation cover for individual dates is explained by HQI at the neighborhood level, although minimal covariability between absolute or relative vegetation cover change and HQI for 2000 was observed.

  18. Urban Vegetation Cover and Vegetation Change in Accra, Ghana: Connection to Housing Quality

    PubMed Central

    Stow, Douglas A.; Weeks, John R.; Toure, Sory; Coulter, Lloyd L.; Lippitt, Christopher D.; Ashcroft, Eric

    2013-01-01

    The objectives are to (1) quantify, map, and analyze vegetation cover distributions and changes across Accra, Ghana, for 2002 and 2010; and (2) examine the statistical relationship between vegetation cover and a housing quality index (HQI) for 2000 at the neighborhood level. Pixel-level vegetation cover maps derived using threshold classification of 2002 and 2010 QuickBird normalized difference vegetation index images have very high overall accuracies and yield an estimate of 5.9 percent vegetation cover reduction over the study area between 2002 and 2010. A high degree of variance in vegetation cover for individual dates is explained by HQI at the neighborhood level, although minimal covariability between absolute or relative vegetation cover change and HQI for 2000 was observed. PMID:24293703

  19. Estimating wheat growth with radar vegetation indices

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. 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.

  1. White Vegetables: Glycemia and Satiety12

    PubMed Central

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

    2013-01-01

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

  2. Monitoring vegetation phenology using MODIS

    USGS Publications Warehouse

    Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

    2003-01-01

    Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

  3. Developing a compositing algorithm for retrieval of green vegetation fraction

    NASA Astrophysics Data System (ADS)

    Jiang, Z.; Ju, J.; vargas, M.; Csiszar, I. A.

    2012-12-01

    Real-time weekly global green vegetation fraction (GVF) is needed in the numeric weather, climate and hydrological models. The current NOAA operational GVF product is derived from weekly AVHRR NDVI data, which are composited using the maximum-value compositing (MVC) method. MVC is a widely used technique to remove cloud and atmospheric contamination over land surface by selecting the observation of the maximum NDVI in a compositing period. However, it is well documented that the maximum NDVI is often selected from high sensor zenith angles (SZA), which may introduce error in GVF retrieval. To reduce the composite sensor zenith angles, a view angle adjusted soil-adjusted vegetation index (VA-SAVI), instead of NDVI, is proposed as the criterion of compositing in this study (VA-SAVI=SAVI-C×SZA2, where C is a coefficient). The observation with the maximum VA-SAVI (MVA-SAVI) is selected to represent a compositing period. To evaluate the MVA-SAVI compositing method, global Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua daily surface reflectance data (MYD09GA) in different seasons were composited using the MVA-SAVI method. Composite data were then compared with the 16-day MVC composite data, the MODIS standard 16-day vegetation index (MYD13A1) and 8-day surface reflectance data (MYD09A1). It was found that the mean 16-day composite sensor zenith angle by MVA-SAVI was 13.5°, whereas the mean sensor zenith angles composited by MVC was 39.3°, demonstrated that MVA-SAVI compositing tends to select observations close to the nadir view. MVA-SAVI compositing produced the mean sensor zenith angle 10° and 6° smaller than the MYD13A1 and MYD09A1 data and the mean NDVI (EVI) values 1.4% and 3.2% (4.0% and 3.3%) higher than those the MYD13A1 and MYD09A1 data, respectively. The smaller composited sensor zenith angles and higher vegetation index values suggest that MVA-SAVI compositing is a better compositing method than the MODIS compositing methods and the

  4. 76 FR 16037 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-22

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the second quarter 2011 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  5. 76 FR 59483 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-26

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the fourth quarter 2011 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  6. 77 FR 58910 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-24

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the fourth quarter 2012 rail cost adjustment factor (RCAF) and cost index filed by the Association of American Railroads....

  7. 77 FR 37958 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-25

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the third quarter 2012 rail cost adjustment factor (RCAF) and cost index filed by the Association of...

  8. 77 FR 17121 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-23

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, Department of Transportation. ACTION: Approval of rail cost adjustment factor. ] SUMMARY: The Board has approved the second quarter 2012 rail cost adjustment factor (RCAF) and cost index filed by the...

  9. 78 FR 17764 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-22

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the second quarter 2013 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  10. 76 FR 37191 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-24

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the third quarter 2011 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  11. 75 FR 80895 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-23

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the first quarter 2011 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  12. 78 FR 37660 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-21

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board approves the third quarter 2013 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of American...

  13. 75 FR 58019 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-23

    ... Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board, DOT. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the fourth quarter 2010 Rail Cost Adjustment Factor (RCAF) and cost index filed by the Association of...

  14. 75 FR 35877 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-23

    ... TRANSPORTATION Surface Transportation Board Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the third quarter 2010 rail cost adjustment factor (RCAF) and cost index filed by the Association of...

  15. 76 FR 80448 - Quarterly Rail Cost Adjustment Factor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-23

    ...-No. 5) (2012-1)] Quarterly Rail Cost Adjustment Factor AGENCY: Surface Transportation Board. ACTION: Approval of rail cost adjustment factor. SUMMARY: The Board has approved the first quarter 2012 rail cost adjustment factor (RCAF) and cost index filed by the Association of American Railroads. The first...

  16. Evaluation of a native vegetation masking technique

    NASA Technical Reports Server (NTRS)

    Kinsler, M. C.

    1984-01-01

    A crop masking technique based on Ashburn's vegetative index (AVI) was used to evaluate native vegetation as an indicator of crop moisture condition. A mask of the range areas (native vegetation) was generated for each of thirteen Great Plains LANDSAT MSS sample segments. These masks were compared to the digitized ground truth and accuracies were computed. An analysis of the types of errors indicates a consistency in errors among the segments. The mask represents a simple quick-look technique for evaluating vegetative cover.

  17. Author Indexing.

    ERIC Educational Resources Information Center

    Diodato, Virgil P.

    1981-01-01

    Discusses the effectiveness of using author-supplied indexing to increase subject control in information retrieval, and describes a study which compared author indexing for articles published in "American Mathematical Society" journals to indexing of the same articles by an editor of "Mathematical Reviews." Nine references are…

  18. 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.

  19. Red and photographic infrared linear combinations for monitoring vegetation

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.

    1979-01-01

    The relationships between various linear combinations of red and photographic infrared radiances and vegetation parameters are investigated. In situ spectrometers are used to measure the relationships between linear combinations of red and IR radiances, their ratios and square roots, and biomass, leaf water content and chlorophyll content of a grass canopy in June, September and October. Regression analysis shows red-IR combinations to be more significant than green-red combinations. The IR/red ratio, the square root of the IR/red ratio, the vegetation index (IR-red difference divided by their sum) and the transformed vegetation index (the square root of the vegetation index + 0.5) are found to be sensitive to the amount of photosynthetically active vegetation. The accumulation of dead vegetation over the year is found to have a linearizing effect on the various vegetation measures.

  20. Measurement and comparison of remotely derived leaf area index predictors

    NASA Astrophysics Data System (ADS)

    Jensen, Ryan Russell

    Environmental change occurs in response to both natural and anthropogenic causes. As the world's human population continues to increase, anthropogenic change will also increase. These changes affect the health and vigor of forests throughout the world, including those in north central Florida. Leaf Area Index (LAI), the amount of leaf area per unit ground area, is an important biophysical variable that is directly related to rates of atmospheric gas exchange, biomass partitioning, and productivity. While global and local models that map biophysical parameters are prevalent in the literature, landscape to regional scale models are less common. Therefore, the ability to map and monitor LAI over landscape to regional scale areas is essential for understanding medium scale biophysical properties and how these properties affect biogeochemical cycling, biomass accumulation, and primary productivity. This study develops and verifies several new models to estimate LAI using in situ field measurements throughout north central Florida, Landsat Thematic Mapper remotely sensed imagery, remotely derived vegetation indices, simple and multiple regression, and artificial neural networks (ANNs). This study concludes that while multiple band regression and regression with individual vegetation indices (Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, Simple Ratio, and Greenness Vegetation Index) can estimate LAI, the most accurate way to estimate regional scale LAI is to train an ANN using in situ LAI data and remote sensing brightness values measured from six different portions of the electromagnetic spectrum. The new ANN method of estimating LAI is then applied to two forest ecology studies. The first study analyzes LAI in longleaf pine/turkey oak sandhills as a function of time since last burn. It concludes that in the absence of fire, sandhill LAI increases, and this may be useful for identifying where prescribed burns need to be done. The second study

  1. Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

    NASA Astrophysics Data System (ADS)

    Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

    2014-05-01

    Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the

  2. Radar vegetation indices for estimating the vegetation water content of rice and soybean

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation water content (VWC) is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. In this study, the Radar Vegetation Index (RVI) was evaluated for estimating VWC. Analysis utilized a data set obtained using a ground-bas...

  3. On the evaluation of vegetation resilience in Southern Italy by using satellite VEGETATION, MODIS, TM time series

    NASA Astrophysics Data System (ADS)

    Coluzzi, C.; Didonna, I.

    2009-04-01

    Satellite technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Therefore variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale satellite temporal series ( 1998 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different type of environmenta diturbances (drought, salinity, pollution, etc). Our objective is to characterize quantitatively the resilient effect of vegetation cover at different temporal and

  4. On the evaluation of vegetation resilience in Southern Italy by using VEGETATION, MODIS, TM satellite time series

    NASA Astrophysics Data System (ADS)

    Didonna, I.; Coluzzi, R.

    2009-04-01

    Satellite technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale satellite temporal series ( 2000 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION, MODIS and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different types of environmental diturbances (drought, salinity, pollution, etc). Our objective was to characterize quantitatively the resilient effect of vegetation cover at differen temporal and

  5. Sensitivity analysis for leaf area index (LAI) estimation from CHRIS/PROBA data

    NASA Astrophysics Data System (ADS)

    Cao, Jianjun; Gu, Zhujun; Xu, Jianhua; Duan, Yushan; Liu, Yongmei; Liu, Yongjuan; Li, Dongliang

    2014-09-01

    Sensitivity analyses were conducted for the retrieval of vegetation leaf area index (LAI) from multiangular imageries in this study. Five spectral vegetation indices (VIs) were derived from Compact High Resolution Imaging Spectrometer onboard the Project for On Board Autonomy (CHRIS/PROBA) images, and were related to LAI, acquired from in situ measurement in Jiangxi Province, China, for five vegetation communities. The sensitivity of LAI retrieval to the variation of VIs from different observation angles was evaluated using the ratio of the slope of the best-fit linear VI-LAI model to its root mean squared error. Results show that both the sensitivity and reliability of VI-LAI models are influenced by the heterogeneity of vegetation communities, and that performance of vegetation indices in LAI estimation varies along observation angles. The VI-LAI models are more reliable for tall trees than for low growing shrub-grasses and also for forests with broad leaf trees than for coniferous forest. The greater the tree height and leaf size, the higher the sensitivity. Forests with broad-leaf trees have higher sensitivities, especially at oblique angles, while relatively simple-structured coniferous forests, shrubs, and grasses show similar sensitivities at all angles. The multi-angular soil and/or atmospheric parameter adjustments will hopefully improve the performance of VIs in LAI estimation, which will require further investigation.

  6. Leaf area index retrieval using gap fractions obtained from high resolution satellite data: Comparisons of approaches, scales and atmospheric effects

    NASA Astrophysics Data System (ADS)

    Gonsamo, Alemu

    2010-08-01

    This study is aimed at demonstrating the feasibility of the large scale LAI inversion algorithms using red and near infrared reflectance obtained from high resolution satellite imagery. Radiances in digital counts were obtained in 10 m resolution acquired on cloud free day of August 23, 2007, by the SPOT 5 high resolution geometric (HRG) instrument on mostly temperate hardwood forest located in the Great Lakes - St. Lawrence forest in Southern Quebec. Normalized difference vegetation index (NDVI), scaled difference vegetation index (SDVI) and modified soil-adjusted vegetation index (MSAVI) were applied to calculate gap fractions. LAI was inverted from the gap fraction using the common Beer-Lambert's law of light extinction under forest canopy. The robustness of the algorithm was evaluated using the ground-based LAI measurements and by applying the methods for the independently simulated reflectance data using PROSPECT + SAIL coupled radiative transfer models. Furthermore, the high resolution LAI was compared with MODIS LAI product. The effects of atmospheric corrections and scales were investigated for all of the LAI retrieval methods. NDVI was found to be not suitable index for large scale LAI inversion due to the sensitivity to scale and atmospheric effects. SDVI was virtually scale and atmospheric correction invariant. MSAVI was also scale invariant. Considering all sensitivity analysis, MSAVI performed best followed by SDVI for robust LAI inversion from high resolution imagery.

  7. Global vegetation dynamics - Satellite observations over Asia

    NASA Technical Reports Server (NTRS)

    Malingreau, J.-P.

    1986-01-01

    The weekly global vegetation index (GVI) derived from the NOAA AVHRR instrument has been analyzed for the 1982-1985 period over a wide range of vegetation formations of Asia. Temporal development curves of the index are presented for environments ranging from the desert of central Asia to the tropical forest of Borneo. The paper shows that, despite the coarse resolution of the GVI product, a large set of useful information on ecosystem dynamics and cropping practices can be consistently derived from time series of such data. In addition, it is shown that the impact of the 1982-1983 El Nino Southern Oscillation-related drought can be detected in the GVI data through an analysis of anomalies in the development of selected vegetation formations. The relevance of such analysis for global vegetation monitoring and change detection is then underlined.

  8. Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation

    NASA Astrophysics Data System (ADS)

    Li, Yunqing; Shi, Jiancheng; Zhao, Tianjie

    2015-01-01

    Vegetation optical depth (VOD) and effective vegetation optical depth (EVOD) are key factors for estimating soil moisture and vegetation parameters. Microwave vegetation indices (MVIs, including A and B parameters) have been recently developed for short-vegetation covered surfaces. The MVIs parameter B (MVIs_B) is mainly related to vegetation conditions, which makes it provide a potential way of EVOD retrieval. A theoretical expression deriving EVOD was deduced using MVIs_B from WindSat data. Global patterns of EVOD were analyzed subsequently. It has been shown that EVOD retrieved from MVIs performed a consistent global pattern and seasonal variation with normalized difference vegetation index. Time-series data from the Central Tibetan Plateau Soil Moisture/Temperature Monitoring Network, which is grassland dominated, was selected for temporal analysis. It was found that the temporal EVOD from WindSat MVIs can capture the growth trend of vegetation. Comparisons between EVOD estimations from MVIs and a radiative transfer model were also performed over this network. It was found that EVOD from the two methods exhibited comparable values and similar trends. MVIs_B-derived EVOD can be obtained without any other auxiliary data and has great potential in land-surface parameter retrieval over short-vegetation covered areas.

  9. Gully evolution and geomorphic adjustments of badlands to recent afforestation

    NASA Astrophysics Data System (ADS)

    Ballesteros-Cánovas, Juan Antonio; Stoffel, Markus; Francisco Martín-Duque, Jose; Corona, Christophe; Lucia, Ana; María Bodoque, Jose

    2016-04-01

    Badlands and gullied areas are among the geomorphic environments with the highest erosion rates worldwide, however records on their evolution are very scarce and often limited to presumed initial conditions and the known present state. In this communication, we present a unique and very dense and annual record and outstanding example of erosion processes in a Mediterranean environment in Central Spain, where badland and gullying processes on sandy slopes of a set of mesas have been presumably triggered by quarrying activities since Medieval times. The gully channel evolution here analyzed provides an exceptional example of a larger setting of geomorphic. Besides the analysis of geomorphic adjustments to historical land-use changes induced by historical quarrying and gullying dynamics, we also quantified the impact of current geomorphic adjustments to 20th century afforestation by combining multiproxy such as aerial photography, historical archives, and large dataset of exposed roots to date, quantify, and reconstruct the morphology of a rapidly evolving channel in a gullied catchment. In this analysis, more than 150 exposed roots were analyzed to quantify and report channel incision; widening and gully retreatment rates during the last decades, as well as to quantify sheet erosion on different soil units. Our results suggest that, rather than stabilizing gully evolution, the afforestation carried out during 1960s has played an important role in water-sediment balance and connectivity and would have triggered the initiation of channel incision processes in the 1980s. Therefore, we observe that the channel incision match with a significant increase of the vegetation cover, which leads a significant decrease in sheet erosion rates. Based on our long-term annual gully reconstruction, we observed that sediment delivery does not correlate with the estimated intensity of precipitation (Fourier index). Instead, we observe abrupt morphological changes in the gully are

  10. High Vegetable Fats Intake Is Associated with High Resting Energy Expenditure in Vegetarians.

    PubMed

    Montalcini, Tiziana; De Bonis, Daniele; Ferro, Yvelise; Carè, Ilaria; Mazza, Elisa; Accattato, Francesca; Greco, Marta; Foti, Daniela; Romeo, Stefano; Gulletta, Elio; Pujia, Arturo

    2015-07-17

    It has been demonstrated that a vegetarian diet may be effective in reducing body weight, however, the underlying mechanisms are not entirely clear. We investigated whether there is a difference in resting energy expenditure between 26 vegetarians and 26 non-vegetarians and the correlation between some nutritional factors and inflammatory markers with resting energy expenditure. In this cross-sectional study, vegetarians and non-vegetarians were matched by age, body mass index and gender. All underwent instrumental examinations to assess the difference in body composition, nutrient intake and resting energy expenditure. Biochemical analyses and 12 different cytokines and growth factors were measured as an index of inflammatory state. A higher resting energy expenditure was found in vegetarians than in non-vegetarians (p = 0.008). Furthermore, a higher energy from diet, fibre, vegetable fats intake and interleukin-β (IL-1β) was found between the groups. In the univariate and multivariable analysis, resting energy expenditure was associated with vegetarian diet, free-fat mass and vegetable fats (p < 0.001; Slope in statistic (B) = 4.8; β = 0.42). After adjustment for cytokines, log10 interleukin-10 (IL-10) still correlated with resting energy expenditure (p = 0.02). Resting energy expenditure was positively correlated with a specific component of the vegetarian's diet, i.e., vegetable fats. Furthermore, we showed that IL-10 was positively associated with resting energy expenditure in this population.

  11. High Vegetable Fats Intake Is Associated with High Resting Energy Expenditure in Vegetarians

    PubMed Central

    Montalcini, Tiziana; De Bonis, Daniele; Ferro, Yvelise; Carè, Ilaria; Mazza, Elisa; Accattato, Francesca; Greco, Marta; Foti, Daniela; Romeo, Stefano; Gulletta, Elio; Pujia, Arturo

    2015-01-01

    It has been demonstrated that a vegetarian diet may be effective in reducing body weight, however, the underlying mechanisms are not entirely clear. We investigated whether there is a difference in resting energy expenditure between 26 vegetarians and 26 non-vegetarians and the correlation between some nutritional factors and inflammatory markers with resting energy expenditure. In this cross-sectional study, vegetarians and non-vegetarians were matched by age, body mass index and gender. All underwent instrumental examinations to assess the difference in body composition, nutrient intake and resting energy expenditure. Biochemical analyses and 12 different cytokines and growth factors were measured as an index of inflammatory state. A higher resting energy expenditure was found in vegetarians than in non-vegetarians (p = 0.008). Furthermore, a higher energy from diet, fibre, vegetable fats intake and interleukin-β (IL-1β) was found between the groups. In the univariate and multivariable analysis, resting energy expenditure was associated with vegetarian diet, free-fat mass and vegetable fats (p < 0.001; Slope in statistic (B) = 4.8; β = 0.42). After adjustment for cytokines, log10 interleukin-10 (IL-10) still correlated with resting energy expenditure (p = 0.02). Resting energy expenditure was positively correlated with a specific component of the vegetarian’s diet, i.e., vegetable fats. Furthermore, we showed that IL-10 was positively associated with resting energy expenditure in this population. PMID:26193314

  12. Geographic Portability of the Relationships Between LAI, FPAR, and Spectral Vegetation Reflectance

    NASA Astrophysics Data System (ADS)

    Gibbs, H. K.; Washington-Allen, R. A.; King, A. W.; Sale, M. J.

    2002-05-01

    Accurate spatial prediction of biophysical parameters such as leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) is critical for many modeling and monitoring applications. Traditional methods that derive these parameters from satellite data require time-consuming and expensive ground measurements to establish relationships with spectral vegetation indices (SVI) or to calibrate bidirectional reflectance distribution function (BRDF) models. Consequently, correlations and model calibrations established for one site are frequently transferred to another site. We assess this geographic transfer and develop potential corrections as part of a multi-laboratory Department of Energy project investigating hydrometeorological processes in the Walnut River Watershed in southeast Kansas. We apply LAI-SVI correlations and BRDF model parameterizations developed for the North America Great Plains and the Konza Prairie Long Term Ecological Research sites to the Walnut River Watershed. Advanced Very High Resolution Radiometer biweekly Normalized Difference Vegetation Index (NDVI) composites from 1999 and 2000 and NDVI derived from Landsat Thematic Mapper scenes from 1999, 2000, and 2001 were used to evaluate and improve the geographic transfer to the watershed. Preliminary analysis indicates that simple corrections using site-specific satellite data to adjust model parameters (e.g., NDVI of bare ground) improve predictions of the ported LAI-SVI relationships and BRDF model calibrations.

  13. Prevalent vegetation growth enhancement in urban environment

    PubMed Central

    Zhao, Shuqing; Liu, Shuguang; Zhou, Decheng

    2016-01-01

    Urbanization, a dominant global demographic trend, leads to various changes in environments (e.g., atmospheric CO2 increase, urban heat island). Cities experience global change decades ahead of other systems so that they are natural laboratories for studying responses of other nonurban biological ecosystems to future global change. However, the impacts of urbanization on vegetation growth are not well understood. Here, we developed a general conceptual framework for quantifying the impacts of urbanization on vegetation growth and applied it in 32 Chinese cities. Results indicated that vegetation growth, as surrogated by satellite-observed vegetation index, decreased along urban intensity across all cities. At the same time, vegetation growth was enhanced at 85% of the places along the intensity gradient, and the relative enhancement increased with urban intensity. This growth enhancement offset about 40% of direct loss of vegetation productivity caused by replacing productive vegetated surfaces with nonproductive impervious surfaces. In light of current and previous field studies, we conclude that vegetation growth enhancement is prevalent in urban settings. Urban environments do provide ideal natural laboratories to observe biological responses to environmental changes that are difficult to mimic in manipulative experiments. However, one should be careful in extrapolating the finding to nonurban environments because urban vegetation is usually intensively managed, and attribution of the responses to diverse driving forces will be challenging but must be pursued. PMID:27185955

  14. Prevalent vegetation growth enhancement in urban environment.

    PubMed

    Zhao, Shuqing; Liu, Shuguang; Zhou, Decheng

    2016-05-31

    Urbanization, a dominant global demographic trend, leads to various changes in environments (e.g., atmospheric CO2 increase, urban heat island). Cities experience global change decades ahead of other systems so that they are natural laboratories for studying responses of other nonurban biological ecosystems to future global change. However, the impacts of urbanization on vegetation growth are not well understood. Here, we developed a general conceptual framework for quantifying the impacts of urbanization on vegetation growth and applied it in 32 Chinese cities. Results indicated that vegetation growth, as surrogated by satellite-observed vegetation index, decreased along urban intensity across all cities. At the same time, vegetation growth was enhanced at 85% of the places along the intensity gradient, and the relative enhancement increased with urban intensity. This growth enhancement offset about 40% of direct loss of vegetation productivity caused by replacing productive vegetated surfaces with nonproductive impervious surfaces. In light of current and previous field studies, we conclude that vegetation growth enhancement is prevalent in urban settings. Urban environments do provide ideal natural laboratories to observe biological responses to environmental changes that are difficult to mimic in manipulative experiments. However, one should be careful in extrapolating the finding to nonurban environments because urban vegetation is usually intensively managed, and attribution of the responses to diverse driving forces will be challenging but must be pursued.

  15. Potential of ensemble tree methods for early-season prediction of winter wheat yield from short time series of remotely sensed normalized difference vegetation index and in situ meteorological data

    NASA Astrophysics Data System (ADS)

    Heremans, Stien; Dong, Qinghan; Zhang, Beier; Bydekerke, Lieven; Van Orshoven, Jos

    2015-01-01

    We aimed at analyzing the potential of two ensemble tree machine learning methods-boosted regression trees and random forests-for (early) prediction of winter wheat yield from short time series of remotely sensed vegetation indices at low spatial resolution and of in situ meteorological data in combination with annual fertilization levels. The study area was the Huaibei Plain in eastern China, and all models were calibrated and validated for five separate prefectures. To this end, a cross-validation process was developed that integrates model meta-parameterization and simple forward feature selection. We found that the resulting models deliver early estimates that are accurate enough to support decision making in the agricultural sector and to allow their operational use for yield forecasting. To attain maximum prediction accuracy, incorporating predictors from the end of the growing season is, however, recommended.

  16. Radar response of vegetation: An overview

    NASA Technical Reports Server (NTRS)

    Ulaby, Fawwaz T.; Dobson, M. Craig

    1993-01-01

    This document contains a number of viewgraphs on surface and vegetation backscattering. A classification of vegetation based on general scattering properties is presented. Radar scattering mechanisms are discussed, and backscattering and reflection coefficients for soil back scattering models are given. Radar response to vegetation is presented, with the objectives to discriminate and classify vegetation; to estimate biomass, leaf area index (LAI), and soil moisture; and to monitor changes, including deforestation and growth. Both theory and observation (laboratory, field, air SAR, and European Remote Sensing Satellite (ERS-1) observations) are used to present backscatter coefficients and other data for various vegetation types. ERS-1 results include class statistics, comparison with theory, and biomass response and seasonal variation (LAI) for deciduous and coniferous forests.

  17. Adjusting the Measurement of the Output of the Medical Sector for Quality: A Review of the Literature.

    PubMed

    Hall, Anne E

    2016-08-11

    The Bureau of Economic Analysis recently created new price indexes for health care in its health care satellite account and now faces the problem of how to adjust them for quality. I review the literature on this topic and divide the articles that created quality-adjusted price indexes for individual medical conditions into those that use primarily outcomes-based adjustments and those that use only process-based adjustments. Outcomes-based adjustments adjust the indexes based on observed aggregate health outcomes, usually mortality. Process-based adjustments adjust the indexes based on the treatments provided and medical knowledge of their effectiveness. Outcomes-based adjustments are easier to implement, while process-based adjustments are more demanding in terms of data and medical knowledge. In general, the research literature shows adjusting for quality in the measurement of output in the medical sector to be quantitatively important.

  18. Vegetation dynamics and climate variability-associated biophysical process in West Africa

    NASA Astrophysics Data System (ADS)

    Song, G.; Xue, Y.; Cox, P. M.

    2012-12-01

    West Africa is a bioclimatic zone of predominantly annual grasses with shrubs and trees with a steep gradient in climate, soils, vegetation, fauna, land use and human utilization. West Africa ecosystem region suffered from the most severe and longest drought in the world during the Twentieth Century since the later 1960s. This study systematically investigates how climate variability and anomalies in West Africa affect the regional terrestrial ecosystem, including plant functional types' (PFT) spatial distribution and temporal variations and vegetation characteristics, through biophysical and photosynthesis processes at different scales. We use the offline Simplified Simple Biosphere Version 4/ Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), which is a fully coupled biophysical-dynamic vegetation (DVM) model to adequately incorporate the complex non-linear coupling dynamics between ecosystem and climate variability. The biophysical parameters in SSiB4 are adjusted with TRIFFID-produced vegetation parameter values, which ensure adequate biophysical process coupling. A 59-year simulation from 1948 was conducted using the meteorological forcing, which consists of substantial seasonal, interannual, and interdecal variability and long term dry trend. The results show that the simulated PFT's and leaf area index (LAI) correspond well to climate variability and are consistent with satellite derived vegetation conditions. The simulated inter-decadal variability in vegetation conditions is consistent with the Sahel drought in the 1970s and the 1980s and partial recovery in the 1990s and the 2000s (fig1). To further understand the biophysical mechanism of interactions of water, carbon, radiation, and vegetation dynamics, analyses are conducted to find relationships between vegetation variability and environmental conditions. It is found that the vegetation characteristics simulated by SSiB4/TRIFFID responds primarily to five

  19. Spatiotemporal variability analysis of vegetation cover status for drought study purposes over North Africa using 8-km NDVI-GIMMS data

    NASA Astrophysics Data System (ADS)

    Chokmani, K.; El Alem, A.; Chebana, F.

    2013-12-01

    Africa is considered as the second driest continent in the world behind Australia, its arid lands cover approximately 60 percent. Droughts that hit the continent in recent decades and land degradations at the margins of deserts, particularly for countries neighboring the Sahara such as Algeria, Morocco, and Tunisia have renewed concerns about desertification progress. For a better understanding to the complete nature of drought and the degree in which human activities and climate changes contribute to its development, it is imperative to determine this phenomenon more accurately. Previous drought assessments had several weaknesses making them less reliable. Indeed, standard measurement methods, based on an unevenly distributed sampling point network, are unrepresentative neither for spatial distribution nor for temporal frequency of desertification. As an alternative to these conventional methods, remote sensing data could offer the needed spatial and temporal coverage. In fact, drought study is possible through monitoring vegetation and/or temperature conditions using vegetation and/or temperatures driven indices. Thus, several indices including the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Soil Adjusted Vegetation Index (SAVI), and Temperature Condition Index (TCI), have been employed using various satellite sensors such as Advanced Very High Resolution Radiometer (AVHRR), Landsat Thematic Mapper (TM), and MODerate Resolution Imaging Spectroradiometer (MODIS) to monitor and analyze drought in various regions of the world. In this study, the AVHRR NDVI-GIMMS data at 8-km spatial resolution were used to study the evolution of the vegetation cover status in North Africa's countries over 25 years. The NDVI-GIMMS data were highly correlated with the rainfall in situ samples collected on different cities over the North Africa's countries as the determination coefficient (R2) was about 0.96. The vegetation cover study

  20. Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

    NASA Astrophysics Data System (ADS)

    Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

    Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

  1. Forest vegetation dynamics and its response to climate changes

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Zoran, Liviu Florin V.; Dida, Adrian I.

    2016-10-01

    Forest areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Satellite remote sensing provides a useful tool to capture the temporal dynamics of forest vegetation change in response to climate shifts, at spatial resolutions fine enough to capture the spatial heterogeneity. Frequent satellite data products, for example, can provide the basis for studying time-series of biophysical parameters related to vegetation dynamics. Vegetation index time series provide a useful way to monitor forest vegetation phenological variations. In this study, we used MODIS Terra/Aqua time-series data, along with yearly and monthly net radiation, air temperature, and precipitation data to examine the feedback mechanisms between climate and forest vegetation. Have been quantitatively described Normalized Difference Vegetation Index(NDVI) /Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Evapotranspiration (ET) and Gross Primary Production (GPP) temporal changes for Cernica- Branesti forest area, a periurban zone of Bucharest city in Romania, from the perspective of vegetation phenology and its relation with climate changes and extreme climate events (summer heat waves). A time series from 2000 to 2016 of the MODIS Terra was analyzed to extract forest biophysical parameters anomalies. Forest vegetation phenology analyses were developed for diverse forest land-covers providing a useful way to analyze and understand the phenology associated to those landcovers. Correlations between NDVI/EVI , LAI, ET and GPP time series and climatic variables have been computed.

  2. 12 CFR 160.35 - Adjustments to home loans.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... property to be occupied by the borrower, adjustments to the interest rate, payment, balance, or term to...) Adjustments to the interest rate shall correspond directly to the movement of an index satisfying the... rate pursuant to a formula or schedule that specifies the amount of the increase, the time at which...

  3. 42 CFR 412.316 - Geographic adjustment factors.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... Inpatient Hospital Capital Costs Basic Methodology for Determining the Federal Rate for Capital-Related Costs § 412.316 Geographic adjustment factors. (a) Local cost variation. CMS adjusts for local cost variation based on the hospital wage index value that is applicable to the hospital under subpart D of...

  4. "Masculinity,""Femininity," and Adjustment in College Men.

    ERIC Educational Resources Information Center

    Payne, Frank D.; Futterman, Jack R.

    1983-01-01

    Studied the relationships between the Bem Sex Role Inventory (BSRI), the Personality Research Form ANDRO and the short BSRI in connection with adjustment in 122 college men. Results include findings that: (1) anxiety and depression marked a single adjustment factor; and (2) the Short BSRI index of expressiveness behaved differently from the other…

  5. 47 CFR 1.1117 - Adjustments to charges.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    .... (1) The fees will be adjusted by the Commission to reflect the percentage change in the Consumer Price Index for all Urban Consumers (CPI-U) from the date of enactment of the authorizing legislation... modifications will be limited to correction of arithmetical errors made during an adjustment cycle....

  6. Remotely Adjustable Hydraulic Pump

    NASA Technical Reports Server (NTRS)

    Kouns, H. H.; Gardner, L. D.

    1987-01-01

    Outlet pressure adjusted to match varying loads. Electrohydraulic servo has positioned sleeve in leftmost position, adjusting outlet pressure to maximum value. Sleeve in equilibrium position, with control land covering control port. For lowest pressure setting, sleeve shifted toward right by increased pressure on sleeve shoulder from servovalve. Pump used in aircraft and robots, where hydraulic actuators repeatedly turned on and off, changing pump load frequently and over wide range.

  7. Adjustable Pitot Probe

    NASA Technical Reports Server (NTRS)

    Ashby, George C., Jr.; Robbins, W. Eugene; Horsley, Lewis A.

    1991-01-01

    Probe readily positionable in core of uniform flow in hypersonic wind tunnel. Formed of pair of mating cylindrical housings: transducer housing and pitot-tube housing. Pitot tube supported by adjustable wedge fairing attached to top of pitot-tube housing with semicircular foot. Probe adjusted both radially and circumferentially. In addition, pressure-sensing transducer cooled internally by water or other cooling fluid passing through annulus of cooling system.

  8. Birthweight for length: ponderal index, body mass index or Benn index?

    PubMed

    Cole, T J; Henson, G L; Tremble, J M; Colley, N V

    1997-01-01

    This study compares how effectively the ponderal index and the body mass index adjust birthweight for length at different gestations, and derives an improved index suitable for all gestations. The study was a cross-sectional survey, in a London teaching hospital, using a total of 999 neonates of 33 weeks gestation or later. Main outcome measures were the ponderal index (birthweight/length3), body mass index (birthweight/length2), and Benn index (birthweight/length(n)), where the length power n varies with gestation and is estimated by log-log regression. Results showed that up to 39 weeks gestation, the ponderal index is uncorrelated with length and so is a good index of birthweight for length. Past 39 weeks gestation, the ponderal index is negatively correlated with length, while the body mass index is uncorrelated, so that the body mass index is better. Neither index is optimal at all gestations. Deriving the Benn index (birthweight/length(n)) for each week of gestation, choosing n to make the index uncorrelated with length, shows that n falls steadily and very significantly (p < 0.0001) with increasing gestation. This in turn means that predicted birthweight for length depends on gestation: for a neonate 48 cm long, predicted birthweight varies from 2485 g at 34 weeks to 3030 g at 43 weeks, a 20% range. However, for a 54 cm long infant, predicted birthweight is the same at all gestations. A Benn index where the value of n changes linearly with gestation is described. We conclude that the ponderal index is not appropriate for measuring intra-uterine malnutrition, as it fails to adjust for length at all gestations. No other index of birthweight/length(n) with constant n is any better, as different gestations require different indices. Birthweight predicted from an infant's length depends on the infant's gestation. If, as Barker proposes, thinness at birth assessed by birthweight for length is used to predict later health status, more account needs to be taken of

  9. Weighted triangulation adjustment

    USGS Publications Warehouse

    Anderson, Walter L.

    1969-01-01

    The variation of coordinates method is employed to perform a weighted least squares adjustment of horizontal survey networks. Geodetic coordinates are required for each fixed and adjustable station. A preliminary inverse geodetic position computation is made for each observed line. Weights associated with each observed equation for direction, azimuth, and distance are applied in the formation of the normal equations in-the least squares adjustment. The number of normal equations that may be solved is twice the number of new stations and less than 150. When the normal equations are solved, shifts are produced at adjustable stations. Previously computed correction factors are applied to the shifts and a most probable geodetic position is found for each adjustable station. Pinal azimuths and distances are computed. These may be written onto magnetic tape for subsequent computation of state plane or grid coordinates. Input consists of punch cards containing project identification, program options, and position and observation information. Results listed include preliminary and final positions, residuals, observation equations, solution of the normal equations showing magnitudes of shifts, and a plot of each adjusted and fixed station. During processing, data sets containing irrecoverable errors are rejected and the type of error is listed. The computer resumes processing of additional data sets.. Other conditions cause warning-errors to be issued, and processing continues with the current data set.

  10. Monitoring the spatial and temporal dynamics of the Brazilian Cerrado physiognomies with spectral vegetation indices: An assessment within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA)

    NASA Astrophysics Data System (ADS)

    Ferreira, Laerte Guimaraes, Junior

    The large extension and diversity of the Cerrado vegetative cover, the second largest biome in South America, has a strong impact on regional, and possibly global, energy, water, and carbon balances. Nevertheless, as a major farming frontier in Brazil, it is estimated that about 40% of the Cerrado land cover has already been converted into cultivated pastures, field crops, urban development, and degraded areas. Despite this aggressive pace of land conversion, there have been few investigations on the operational utilization of remote sensing data to effectively monitor and understand this biome. Within this context, and within the goals and framework of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), we evaluated the usefulness of spectral vegetation indices (VIs), to effectively monitor the Cerrado, detect land conversions, and discriminate and assess the conditions of the major structural types of Cerrado vegetation. Using a full hydrologic year (1995) of AVHRR, local-area-coverage (LAC), data over the Cerrado, converted to normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), we were able to spatially discriminate three major communities based on their phenologic patterns. These included savanna formations and pasture sites, forested areas, and agricultural crops. We also analyzed wet and dry season, aircraft-based radiometric data and a ground-based set of biophysical measurements, collected over the Brasilia National Park (BNP), the largest LBA core site in the Cerrado biome. Overall, we found the MODIS vegetation indices, which include a continuity NDVI and the new enhanced vegetation index (EVI), to provide better performance capabilities with improved dynamic ranges and contrasts in seasonal dynamics. Land cover discrimination was favored by the NDVI, while the EVI more strongly responded to the seasonal contrast of the vegetative cover. Thus, the synergistic use of the MODIS VI products will very likely

  11. INDEXING MECHANISM

    DOEpatents

    Kock, L.J.

    1959-09-22

    A device is presented for loading and unloading fuel elements containing material fissionable by neutrons of thermal energy. The device comprises a combination of mechanical features Including a base, a lever pivotally attached to the base, an Indexing plate on the base parallel to the plane of lever rotation and having a plurality of apertures, the apertures being disposed In rows, each aperture having a keyway, an Index pin movably disposed to the plane of lever rotation and having a plurality of apertures, the apertures being disposed in rows, each aperture having a keyway, an index pin movably disposed on the lever normal to the plane rotation, a key on the pin, a sleeve on the lever spaced from and parallel to the index pin, a pair of pulleys and a cable disposed between them, an open collar rotatably attached to the sleeve and linked to one of the pulleys, a pin extending from the collar, and a bearing movably mounted in the sleeve and having at least two longitudinal grooves in the outside surface.

  12. Using an optimality model to understand medium and long-term responses of vegetation water use to elevated atmospheric CO2 concentrations.

    PubMed

    Schymanski, Stanislaus J; Roderick, Michael L; Sivapalan, Murugesu

    2015-05-27

    Vegetation has different adjustable properties for adaptation to its environment. Examples include stomatal conductance at short time scale (minutes), leaf area index and fine root distributions at longer time scales (days-months) and species composition and dominant growth forms at very long time scales (years-decades-centuries). As a result, the overall response of evapotranspiration to changes in environmental forcing may also change at different time scales. The vegetation optimality model simulates optimal adaptation to environmental conditions, based on the assumption that different vegetation properties are optimized to maximize the long-term net carbon profit, allowing for separation of different scales of adaptation, without the need for parametrization with observed responses. This paper discusses model simulations of vegetation responses to today's elevated atmospheric CO2 concentrations (eCO2) at different temporal scales and puts them in context with experimental evidence from free-air CO2 enrichment (FACE) experiments. Without any model tuning or calibration, the model reproduced general trends deduced from FACE experiments, but, contrary to the widespread expectation that eCO2 would generally decrease water use due to its leaf-scale effect on stomatal conductance, our results suggest that eCO2 may lead to unchanged or even increased vegetation water use in water-limited climates, accompanied by an increase in perennial vegetation cover.

  13. Using an optimality model to understand medium and long-term responses of vegetation water use to elevated atmospheric CO2 concentrations

    PubMed Central

    Schymanski, Stanislaus J.; Roderick, Michael L.; Sivapalan, Murugesu

    2015-01-01

    Vegetation has different adjustable properties for adaptation to its environment. Examples include stomatal conductance at short time scale (minutes), leaf area index and fine root distributions at longer time scales (days–months) and species composition and dominant growth forms at very long time scales (years–decades–centuries). As a result, the overall response of evapotranspiration to changes in environmental forcing may also change at different time scales. The vegetation optimality model simulates optimal adaptation to environmental conditions, based on the assumption that different vegetation properties are optimized to maximize the long-term net carbon profit, allowing for separation of different scales of adaptation, without the need for parametrization with observed responses. This paper discusses model simulations of vegetation responses to today's elevated atmospheric CO2 concentrations (eCO2) at different temporal scales and puts them in context with experimental evidence from free-air CO2 enrichment (FACE) experiments. Without any model tuning or calibration, the model reproduced general trends deduced from FACE experiments, but, contrary to the widespread expectation that eCO2 would generally decrease water use due to its leaf-scale effect on stomatal conductance, our results suggest that eCO2 may lead to unchanged or even increased vegetation water use in water-limited climates, accompanied by an increase in perennial vegetation cover. PMID:26019228

  14. Fruit and vegetables and cancer risk.

    PubMed

    Key, T J

    2011-01-04

    The possibility that fruit and vegetables may help to reduce the risk of cancer has been studied for over 30 years, but no protective effects have been firmly established. For cancers of the upper gastrointestinal tract, epidemiological studies have generally observed that people with a relatively high intake of fruit and vegetables have a moderately reduced risk, but these observations must be interpreted cautiously because of potential confounding by smoking and alcohol. For lung cancer, recent large prospective analyses with detailed adjustment for smoking have not shown a convincing association between fruit and vegetable intake and reduced risk. For other common cancers, including colorectal, breast and prostate cancer, epidemiological studies suggest little or no association between total fruit and vegetable consumption and risk. It is still possible that there are benefits to be identified: there could be benefits in populations with low average intakes of fruit and vegetables, such that those eating moderate amounts have a lower cancer risk than those eating very low amounts, and there could also be effects of particular nutrients in certain fruits and vegetables, as fruit and vegetables have very varied composition. Nutritional principles indicate that healthy diets should include at least moderate amounts of fruit and vegetables, but the available data suggest that general increases in fruit and vegetable intake would not have much effect on cancer rates, at least in well-nourished populations. Current advice in relation to diet and cancer should include the recommendation to consume adequate amounts of fruit and vegetables, but should put most emphasis on the well-established adverse effects of obesity and high alcohol intakes.

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

    USGS Publications Warehouse

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

    2009-01-01

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

  16. Applying new methodologies for quantifying total vegetation cover in arid regions using MODIS data

    NASA Astrophysics Data System (ADS)

    Shreve, C.; Okin, G. S.

    2009-12-01

    Vegetation in arid regions can show physical adaptations to the harsh climate such as waxy cuticles, leaf hairs, and lower chlorophyll content than vegetation in more humid regions, which results in the vegetation in arid environments appearing less green. Satellite measurements of vegetative cover currently rely primarily on a measure of greenness and serve as important inputs for climate models, thus requiring as accurate a portrayal as possible. Remotely derived metrics such as the Normalized Difference Vegetation Index (NDVI), which exploit the “red edge” of vegetation that results primarily from increased chlorophyll concentration during plant growth, may not accurately reflect vegetative cover or be suitable to use in biomass estimations for arid regions. We discuss a method for deriving fractional (subpixel) cover of vegetation from MODIS imagery better suited for both hot and cold arid regions than NDVI because it minimizes soil effects, is more robust in the presence of snow than NDVI and provides a more inclusive measure of total vegetation cover. A case study of spatial and temporal trends of vegetative cover in the Tibetan Plateau is discussed and results show the vegetation dynamics differ markedly than those portrayed by NDVI alone. Applying a cosine fitting method to the timeseries of green and brown vegetation indices allows for additional vegetation metrics to be derived describing the contribution of each index to the total dynamics within a pixel. The amplitude provides information on the total amount of cyclic intraanual variability in a pixel for both green and brown vegetation indices. A simple ratio of the brown vegetation index to total vegetation cover provides the relative contribution of brown vegetation to the total cyclic intraanual variability. Examining the simple ratio and the brown vegetation index results in combination, yields information on the amount of cyclic variability within a pixel that is explained by changes in brown

  17. Recirculating valve lash adjuster

    SciTech Connect

    Stoody, R.R.

    1987-02-24

    This patent describes an internal combustion engine with a valve assembly of the type including overhead valves supported by a cylinder head for opening and closing movements in a substantially vertical direction and a rotatable overhead camshaft thereabove lubricated by engine oil pumped by an engine oil pump. A hydraulic lash adjuster with an internal reservoir therein is solely supplied with run-off lubricating oil from the camshaft which oil is pumped into the internal reservoir of the lash adjuster by self-pumping operation of the lash adjuster produced by lateral forces thereon by the rotative operation of the camshaft comprising: a housing of the lash adjuster including an axially extending bore therethrough with a lower wall means of the housing closing the lower end thereof; a first plunger member being closely slidably received in the bore of the housing and having wall means defining a fluid filled power chamber with the lower wall means of the housing; and a second plunger member of the lash adjuster having a portion being loosely slidably received and extending into the bore of the housing for reciprocation therein. Another portion extends upwardly from the housing to operatively receive alternating side-to-side force inputs from operation of the camshaft.

  18. Antioxidant and antiproliferative activities of common vegetables.

    PubMed

    Chu, Yi-Fang; Sun, Jie; Wu, Xianzhong; Liu, Rui Hai

    2002-11-06

    Epidemiological studies have shown that consumption of fruits and vegetables is associated with reduced risk of chronic diseases. Increased consumption of fruits and vegetables containing high levels of phytochemicals has been recommended to prevent chronic diseases related to oxidative stress in the human body. In this study, 10 common vegetables were selected on the basis of consumption per capita data in the United States. A more complete profile of phenolic distributions, including both free and bound phenolics in these vegetables, is reported here using new and modified methods. Broccoli possessed the highest total phenolic content, followed by spinach, yellow onion, red pepper, carrot, cabbage, potato, lettuce, celery, and cucumber. Red pepper had the highest total antioxidant activity, followed by broccoli, carrot, spinach, cabbage, yellow onion, celery, potato, lettuce, and cucumber. The phenolics antioxidant index (PAI) was proposed to evaluate the quality/quantity of phenolic contents in these vegetables and was calculated from the corrected total antioxidant activities by eliminating vitamin C contributions. Antiproliferative activities were also studied in vitro using HepG(2) human liver cancer cells. Spinach showed the highest inhibitory effect, followed by cabbage, red pepper, onion, and broccoli. On the basis of these results, the bioactivity index (BI) for dietary cancer prevention is proposed to provide a simple reference for consumers to choose vegetables in accordance with their beneficial activities. The BI could be a new alternative biomarker for future epidemiological studies in dietary cancer prevention and health promotion.

  19. 24 CFR 203.49 - Eligibility of adjustable rate mortgages.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... most recent figure available before the date of mortgage loan origination. The current index figure shall be the most recent index figure available 30 days before the date of each interest rate adjustment... houses in federally impacted areas), 203.45 (graduated payment mortgages), or 203.47 (growing...

  20. 24 CFR 203.49 - Eligibility of adjustable rate mortgages.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... most recent figure available before the date of mortgage loan origination. The current index figure shall be the most recent index figure available 30 days before the date of each interest rate adjustment... houses in federally impacted areas), 203.45 (graduated payment mortgages), or 203.47 (growing...

  1. 24 CFR 203.49 - Eligibility of adjustable rate mortgages.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... most recent figure available before the date of mortgage loan origination. The current index figure shall be the most recent index figure available 30 days before the date of each interest rate adjustment... houses in federally impacted areas), 203.45 (graduated payment mortgages), or 203.47 (growing...

  2. 24 CFR 203.49 - Eligibility of adjustable rate mortgages.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... most recent figure available before the date of mortgage loan origination. The current index figure shall be the most recent index figure available 30 days before the date of each interest rate adjustment... houses in federally impacted areas), 203.45 (graduated payment mortgages), or 203.47 (growing...

  3. 24 CFR 203.49 - Eligibility of adjustable rate mortgages.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... most recent figure available before the date of mortgage loan origination. The current index figure shall be the most recent index figure available 30 days before the date of each interest rate adjustment... houses in federally impacted areas), 203.45 (graduated payment mortgages), or 203.47 (growing...

  4. Relation of Vegetation and Temperature Condition Indices (1981-1999) and Drought conditions in Indian Region

    NASA Astrophysics Data System (ADS)

    Kanwar, R.; Narayan, U.; Kumar, M.

    The Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA series of satellites has been used for regional and global vegetation coverage since 1978 employing the Normalized Difference Vegetation Index (NDVI). Recently, this technique has been improved combining NDVI with one of the thermal channels and converting them into the vegetation condition Index (VCI) and Temperature condition Index (TCI). W e have analysed NDVI, Vegetation and Temperature Condition Indices for the year 1981-1999 to the map the state of vegetation for Indian regions. Further, we have correlated these indices with the crop yield and crop production for different parts of India. The NDVI is also correlated with the scattering index derived form ERS data. The preset study shows that scattering coefficient, the NDVI, vegetation and temperature condition indices can be employed together in monitoring drought conditions and the vegetation vigor of Indian regions.

  5. Fruits and vegetables (image)

    MedlinePlus

    A healthy diet includes adding vegetables and fruit every day. Vegetables like broccoli, green beans, leafy greens, zucchini, cauliflower, cabbage, carrots, and tomatoes are low in calories and high in fiber, ...

  6. Retrieval of wheat growth parameters with radar vegetation indices

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Seasonal patterns of vegetative indices over cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing offers potential to precision agriculture applications in terms of providing both temporal and spatial information. There have been applications of the vegetative indices based on reflectance in the visible and near-infrared of which the normalized difference vegetative index (NDVI) i...

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

    USGS Publications Warehouse

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

    2011-01-01

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

  9. Airborne observations of vegetation and implications for biogenic emission characterization.

    PubMed

    Hawes, Amy K; Solomon, Susan; Portmann, Robert W; Daniel, John S; Langford, Andrew O; Miller, H LeRoy; Eubank, Charles S; Goldan, Paul; Wiedinmyer, Christine; Atlas, Elliot; Hansel, Armin; Wisthaler, Armin

    2003-12-01

    Measuring hydrocarbons from aircraft represents one way to infer biogenic emissions at the surface. The focus of this paper is to show that complementary remote sensing information can be provided by optical measurements of a vegetation index, which is readily measured with high temporal coverage using reflectance data. We examine the similarities between the vegetation index and in situ measurements of the chemicals isoprene, methacrolein, and alpha-pinene to estimate whether the temporal behavior of the in situ measurements of these chemicals could be better understood by the addition of the vegetation index. Data were compared for flights conducted around Houston in August and September 2000. The three independent sets of chemical measurements examined correspond reasonably well with the vegetation index curves for the majority of flight days. While low values of the vegetation index always correspond to low values of the in situ chemical measurements, high values of the index correspond to both high and low values of the chemical measurements. In this sense it represents an upper limit when compared with in situ data (assuming the calibration constant is adequately chosen). This result suggests that while the vegetation index cannot represent a purely predictive quantity for the in situ measurements, it represents a complementary measurement that can be useful in understanding comparisons of various in situ observations, particularly when these observations occur with relatively low temporal frequency. In situ isoprene measurements and the vegetation index were also compared to an isoprene emission inventory to provide additional insight on broad issues relating to the use of vegetation indices in emission database development.

  10. Capping risk adjustment?

    PubMed

    Eugster, Patrick; Sennhauser, Michèle; Zweifel, Peter

    2010-07-01

    When premiums are community-rated, risk adjustment (RA) serves to mitigate competitive insurers' incentive to select favorable risks. However, unless fully prospective, it also undermines their incentives for efficiency. By capping its volume, one may try to counteract this tendency, exposing insurers to some financial risk. This in term runs counter the quest to refine the RA formula, which would increase RA volume. Specifically, the adjuster, "Hospitalization or living in a nursing home during the previous year" will be added in Switzerland starting 2012. This paper investigates how to minimize the opportunity cost of capping RA in terms of increased incentives for risk selection.

  11. Monitoring East African vegetation using AVHRR data

    NASA Technical Reports Server (NTRS)

    Justice, C. O.; Holben, B. N.; Gwynne, M. D.

    1986-01-01

    NOAA Advanced Very High Resolution Radiometer satellite data are applied to regional vegetation monitoring in East Africa. Normalized Difference Vegetation Index (NDVI) data for a one-year period from May 1983 are used to examine the phenology of a range of vegetation types. The integrated NDVI data for the same period are compared with an ecoclimatic zone map of the region and show marked similarities. Particular emphasis is placed on quantifying the phenology of the Acacia Commiphora bushlands. Considerable variation was found in the phenology of the bushlands as determined by the satellite NDVI, and is explained through the high spatial variability in the distribution of rainfall and the resulting green-up of the vegetation. The relationship between rainfall and NDVI is further examined for selected meteorological stations existing within the bushland. A preliminary estimate is made of the length of growing season using an NDVI thresholding technique.

  12. Width adjustment: relative dominance in unstable alluvial streams

    USGS Publications Warehouse

    Simon, Andrew

    1994-01-01

    The mechanisms that control the relative dominance of width adjustment in unstable streams are described. Specifically, the role of the following factors affecting the fluvial environment were investigated: vertical processes and fluvial action, bed-material particle, cohesive strength of bank material, and riparian vegetation.

  13. Intakes of vegetables and related nutrients such as vitamin B complex, potassium, and calcium, are negatively correlated with risk of stroke in Korea

    PubMed Central

    2010-01-01

    Consumption of vegetables and fruits is associated with a reduced risk of stroke, but it is unclear whether their protective effects are due to antioxidant vitamins or folate and metabolically related B vitamins. The purpose of the study was to test the hypothesis that intake of fruits and vegetables, which are major sources of antioxidant and vitamin B complex vitamins, reduces the risk of stroke. Cases consisted of patients diagnosed with first event of stroke (n = 69). Controls (n = 69) were age-, sex-, and body mass index-matched to cases. Multivariable-adjusted regression analysis showed that subjects who ate four to six servings of vegetable per day had a 32% reduction in the risk of stroke, and those with more than six servings per day had a reduction of 69% after adjusting for age, sex, BMI, and family history of stroke. Intakes of total fat, plant fat, calcium, potassium, vitamin B1, vitamin B2, vitamin B6, niacin, and folate were significantly and negatively associated with the risk of stroke. Although the trend was not significant, stroke risk was reduced in the second quartile (1.21-2.66 servings per week) of fish intake. However, intake of fruits (average daily intake of 1.0 serving) and antioxidant vitamins such as carotene, vitamin C, and vitamin E was not associated with the risk of stroke. In conclusion, our observational study suggests that intake of fat and vegetables, rich sources of vitamin B complex, calcium, and potassium may protect against stroke. PMID:20827346

  14. Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults

    PubMed Central

    Mathur, Maya; King, Abby C

    2016-01-01

    Background Mobile apps present a potentially cost-effective tool for delivering behavior change interventions at scale, but no known studies have tested the efficacy of apps as a tool to specifically increase vegetable consumption among overweight adults. Objective The purpose of this pilot study was to assess the initial efficacy and user acceptability of a theory-driven mobile app to increase vegetable consumption. Methods A total of 17 overweight adults aged 42.0 (SD 7.3) years with a body mass index (BMI) of 32.0 (SD 3.5) kg/m2 were randomized to the use of Vegethon (a fully automated theory-driven mobile app enabling self-monitoring of vegetable consumption, goal setting, feedback, and social comparison) or a wait-listed control condition. All participants were recruited from an ongoing 12-month weight loss trial (parent trial). Researchers who performed data analysis were blinded to condition assignment. The primary outcome measure was daily vegetable consumption, assessed using an adapted version of the validated Harvard Food Frequency Questionnaire administered at baseline and 12 weeks after randomization. An analysis of covariance was used to assess differences in 12-week vegetable consumption between intervention and control conditions, controlling for baseline. App usability and satisfaction were measured via a 21-item post-intervention questionnaire. Results Using intention-to-treat analyses, all enrolled participants (intervention: 8; control: 9) were analyzed. Of the 8 participants randomized to the intervention, 5 downloaded the app and logged their vegetable consumption a mean of 0.7 (SD 0.9) times per day, 2 downloaded the app but did not use it, and 1 never downloaded it. Consumption of vegetables was significantly greater among the intervention versus control condition at the end of the 12-week pilot study (adjusted mean difference: 7.4 servings; 95% CI 1.4-13.5; P=.02). Among secondary outcomes defined a priori, there was significantly greater

  15. Reduced risk of pre-eclampsia with organic vegetable consumption: results from the prospective Norwegian Mother and Child Cohort Study

    PubMed Central

    Torjusen, Hanne; Brantsæter, Anne Lise; Haugen, Margaretha; Alexander, Jan; Bakketeig, Leiv S; Lieblein, Geir; Stigum, Hein; Næs, Tormod; Swartz, Jackie; Holmboe-Ottesen, Gerd; Roos, Gun; Meltzer, Helle Margrete

    2014-01-01

    Objective Little is known about the potential health effects of eating organic food either in the general population or during pregnancy. The aim of this study was to examine associations between organic food consumption during pregnancy and the risk of pre-eclampsia among nulliparous Norwegian women. Design Prospective cohort study. Setting Norway, years 2002–2008. Participants 28 192 pregnant women (nulliparous, answered food frequency questionnaire and general health questionnaire in mid-pregnancy and no missing information on height, body weight or gestational weight gain). Main outcome measure Relative risk was estimated as ORs by performing binary logistic regression with pre-eclampsia as the outcome and organic food consumption as the exposure. Results The prevalence of pre-eclampsia in the study sample was 5.3% (n=1491). Women who reported to have eaten organic vegetables ‘often’ or ‘mostly’ (n=2493, 8.8%) had lower risk of pre-eclampsia than those who reported ‘never/rarely’ or ‘sometimes’ (crude OR=0.76, 95% CI 0.61 to 0.96; adjusted OR=0.79, 95% CI 0.62 to 0.99). The lower risk associated with high organic vegetable consumption was evident also when adjusting for overall dietary quality, assessed as scores on a healthy food pattern derived by principal component analysis. No associations with pre-eclampsia were found for high intake of organic fruit, cereals, eggs or milk, or a combined index reflecting organic consumption. Conclusions These results show that choosing organically grown vegetables during pregnancy was associated with reduced risk of pre-eclampsia. Possible explanations for an association between pre-eclampsia and use of organic vegetables could be that organic vegetables may change the exposure to pesticides, secondary plant metabolites and/or influence the composition of the gut microbiota. PMID:25208850

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

    USGS Publications Warehouse

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

    1999-01-01

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

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

    USGS Publications Warehouse

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

    1999-01-01

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

  18. Psychological Adjustment and Homosexuality.

    ERIC Educational Resources Information Center

    Gonsiorek, John C.

    In this paper, the diverse literature bearing on the topic of homosexuality and psychological adjustment is critically reviewed and synthesized. The first chapter discusses the most crucial methodological issue in this area, the problem of sampling. The kinds of samples used to date are critically examined, and some suggestions for improved…

  19. Self Adjusting Sunglasses

    NASA Technical Reports Server (NTRS)

    1986-01-01

    Corning Glass Works' Serengeti Driver sunglasses are unique in that their lenses self-adjust and filter light while suppressing glare. They eliminate more than 99% of the ultraviolet rays in sunlight. The frames are based on the NASA Anthropometric Source Book.

  20. Self adjusting inclinometer

    DOEpatents

    Hunter, Steven L.

    2002-01-01

    An inclinometer utilizing synchronous demodulation for high resolution and electronic offset adjustment provides a wide dynamic range without any moving components. A device encompassing a tiltmeter and accompanying electronic circuitry provides quasi-leveled tilt sensors that detect highly resolved tilt change without signal saturation.

  1. Vegetable oil fuel standards

    SciTech Connect

    Pryde, E.H.

    1982-01-01

    Suggested standards for vegetable oils and ester fuels, as well as ASTM specifications for No. 2 diesel oil are given. The following physical properties were discussed: cetane number, cloud point, distillation temperatures, flash point, pour point, turbidity, viscosity, free fatty acids, iodine value, phosphorus, and wax. It was apparent that vegetable oils and their esters cannot meet ASTM specifications D975 for No. 2 diesel oil for use in the diesel engine. Vegetable oil modification or engine design modification may make it possible eventually for vegetable oils to become suitable alternative fuels. Vegetable oils must be recognized as experimental fuels until modifications have been tested thoroughly and generally accepted. 1 table. (DP)

  2. Mapping small-scale vegetation changes in Mexico

    NASA Technical Reports Server (NTRS)

    Turcotte, Kevin M.; Lulla, Kemlesh; Venugopal, Gopalan

    1993-01-01

    This research attempts to map small-scale vegetation changes in Mexico. Forty-eight weeks of coarse resolution Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI), a digitized climax vegetation map, land cover samples from space shuttle photographs and actual vegetation samples were used as inputs. Principal components analyses and a clustering algorithm were applied to the NDVI data to generate a single layer that was stratified by the climax vegetation zones map. The purpose is to create a new layer that differentiates climax vegetation (hypothesized potential vegetation) from non-climax vegetation land covers. One of the keys to developing a present-day vegetation map was differentiating intrazone land covers based on the stratification; as great as 75% of the sampled land cover types differed from the climax vegetation. The present-day vegetation map achieved 80% classification accuracy when calculated from available ground reference data. About 55% of the temperate zones and 37% of the tropical zones were found to contain original climax vegetation. Most changes coincide with areas of major agricultural activity.

  3. Advanced Very High Resolution Radiometer (AVHRR) data evaluation for use in monitoring vegetation. Volume 1: Channels 1 and 2

    NASA Technical Reports Server (NTRS)

    Horvath, N. C.; Gray, T. I.; Mccrary, D. G. (Principal Investigator)

    1982-01-01

    Data from the National Oceanic and Atmospheric Administration satellite system (NOAA-6 satellite) were analyzed to study their nonmeteorological uses. A file of charts, graphs, and tables was created form the products generated. It was found that the most useful data lie between pixel numbers 400 and 2000 on a given scan line. The analysis of the generated products indicates that the Gray-McCrary Index can discern vegetation and associated daily and seasonal changes. The solar zenith-angle correction used in previous studies was found to be a useful adjustment to the index. The METSAT system seems best suited for providing large-area analyses of surface features on a daily basis.

  4. The effect of image radiometric correction on the accuracy of vegetation canopy density estimate using several Landsat-8 OLI’s vegetation indices: A case study of Wonosari area, Indonesia

    NASA Astrophysics Data System (ADS)

    Dewa, R. P.; Danoedoro, P.

    2017-01-01

    Recent studies on the use of spectral indices have involved radiometric correction as a prerequisite. However, study on the effect of radiometric correction level on the accuracy of biophysical parameters’ estimate is still rare in Indonesia. This study tried to investigate the influence of various radiometric correction levels and the number of vegetation strata on the accuracy of vegetation density estimates using NDVI, MSAVI2 and GEMI of Landsat 8 OLI. In this study, the dataset covering vegetated area in Wonosari, Gunung Kidul Regency, Indonesia was processed radiometrically using eight different methods, i.e. spectral radiance, at sensor reflectance, sun elevation correction, histogram adjustments using original DN, spectal radiance, at sensor reflectance, and sun position correction respectively, as well as dark object subtraction (DOS). Every image with specific correction level was then transformed using the aforementioned indices, in order correlate with the field-measured canopy density. The analysis were carried out by considering the number of canopy layers. This found that different radiometric correction methods resulted canopy density estimates with different accuracies. The number of canopy strata also played an important role. Every vegetation index transformation performed its best accuracy by using different radiometric correction method and different number of canopy layers.

  5. Multispectral vegetative canopy parameter retrieval

    NASA Astrophysics Data System (ADS)

    Borel, Christoph C.; Bunker, David J.

    2011-11-01

    Precision agriculture, forestry and environmental remote sensing are applications uniquely suited to the 8 bands that DigitalGlobe's WorldView-2 provides. At the fine spatial resolution of 0.5 m (panchromatic) and 2 m (multispectral) individual trees can be readily resolved. Recent research [1] has shown that it is possible for hyper-spectral data to invert plant reflectance spectra and estimate nitrogen content, leaf water content, leaf structure, canopy leaf area index and, for sparse canopies, also soil reflectance. The retrieval is based on inverting the SAIL (Scattering by Arbitrary Inclined Leaves) vegetation radiative transfer model for the canopy structure and the reflectance model PROSPECT4/5 for the leaf reflectance. Working on the paper [1] confirmed that a limited number of adjacent bands covering just the visible and near infrared can retrieve the parameters as well, opening up the possibility that this method can be used to analyze multi-spectral WV-2 data. Thus it seems possible to create WV-2 specific inversions using 8 bands and apply them to imagery of various vegetation covered surfaces of agricultural and environmental interest. The capability of retrieving leaf water content and nitrogen content has important applications in determining the health of vegetation, e.g. plant growth status, disease mapping, quantitative drought assessment, nitrogen deficiency, plant vigor, yield, etc.

  6. Adjustable Autonomy Testbed

    NASA Technical Reports Server (NTRS)

    Malin, Jane T.; Schrenkenghost, Debra K.

    2001-01-01

    The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

  7. Precision adjustable stage

    DOEpatents

    Cutburth, Ronald W.; Silva, Leonard L.

    1988-01-01

    An improved mounting stage of the type used for the detection of laser beams is disclosed. A stage center block is mounted on each of two opposite sides by a pair of spaced ball bearing tracks which provide stability as well as simplicity. The use of the spaced ball bearing pairs in conjunction with an adjustment screw which also provides support eliminates extraneous stabilization components and permits maximization of the area of the center block laser transmission hole.

  8. [Vegetation landscape health assessment in Changshan Archipelago, North Yellow Sea].

    PubMed

    Suo, An-ning; Sun, Yong-guang; Li, Bin-yong; Lin, Yong; Zhang, Yong-hua

    2015-04-01

    Island vegetation is an important component of island ecosystem. Multi-targets of island ecosystem health integrated with landscape ecology theory were employed to construct the index system for island vegetation health assessment in terms of landscape vigor, landscape stressing intensity and landscape stability. The Changshan Archipelago in the North Yellow Sea was chosen as a case to apply the island vegetation health assessment index system. The results showed that the overall vegetation health status in Changshan Archipelago was good and had a big island variation. The vegetation health index for Haiyang Island and Zhangzi Island was above 0.80, belonging to first eco-health level area, whereas that for Dachangshan Island, Xiaochangshan Island and Dawangjia Island ranged from 0.70 to 0.80, which could be categorized as the second eco-health level area. Guanglu Island and Shichen Island could be termed as the third eco-health level area with the vegetation health index below 0.70. The distance of island to mainland, area of island together with industrial structure were the main driving forces for the variation of vegetation landscape heath between different islands.

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  10. Biomechanics of fruits and vegetables.

    PubMed

    Peleg, K

    1985-01-01

    The scope of fruit and vegetable biomechanics is reviewed. Sources of mechanical injury to produce in harvesting, processing, storage, packaging and transportation are briefly described. A survey of produce handling and transportation environments was conducted, whereby an envelope model encompassing composite spectra of trucks, railroad, marine and cargo aircraft is presented. The protective quality, i.e. strength of shipping containers is quantified in static and dynamic loading such as encountered in storage, handling and transportation. Mechanical response of fruits and vegetables in quasistatic and dynamic loading are formulated by a nonlinear rheological model, whereby a time and deformation dependent relaxation modulus is defined. A realistic link is established between the model and real fruits and vegetables by test procedures for determination of the parameters in the governing nonlinear equations. Based on the nonlinear relaxation modulus, mechanical damage of fruits and vegetables is quantified for static compression, transients and vibration loading as well as for combined static and dynamic loading, by equations of contact circle diameter, bruise depth and contact pressure. Distribution of loads over a maximal number of contact points per fruit is linked to geometrical patterns of produce packs. The application of Shock Damage Boundary techniques for produce-package testing is described along with a case study comparing the protective qualities of two types of apple packs. Produce damage quantification by direct fruit inspection in terms of a 'Bruise Index' is described, including a practical example, comparing the protective qualities of three types of apple packs in shipping tests. Indirect methods of mechanical injury evaluation, based on weight loss and CO2 emission differences between bruised and wholesome fruits are also briefly discussed.

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

    USGS Publications Warehouse

    Ji, Lei; Peters, Albert J.

    2003-01-01

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

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

    PubMed

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

    2016-01-01

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

  13. Fire in a Changing Climate: Stochastic versus Threshold-constrained Ignitions in a Dynamic Global Vegetation Model

    NASA Astrophysics Data System (ADS)

    Sheehan, T.; Bachelet, D. M.; Ferschweiler, K.

    2015-12-01

    The MC2 dynamic global vegetation model fire module simulates fire occurrence, area burned, and fire impacts including mortality, biomass burned, and nitrogen volatilization. Fire occurrence is based on fuel load levels and vegetation-specific thresholds for three calculated fire weather indices: fine fuel moisture code (FFMC) for the moisture content of fine fuels; build-up index (BUI) for the total amount of fuel available for combustion; and energy release component (ERC) for the total energy available to fire. Ignitions are assumed (i.e. the probability of an ignition source is 1). The model is run with gridded inputs and the fraction of each grid cell burned is limited by a vegetation-specific fire return period (FRP) and the number of years since the last fire occurred in the grid cell. One consequence of assumed ignitions FRP constraint is that similar fire behavior can take place over large areas with identical vegetation type. In regions where thresholds are often exceeded, fires occur frequently (annually in some instances) with a very low fraction of a cell burned. In areas where fire is infrequent, a single hot, dry climate event can result in intense fire over a large region. Both cases can potentially result in large areas with uniform vegetation type and age. To better reflect realistic fire occurrence, we have developed a stochastic fire occurrence model that: a) uses a map of relative ignition probability and a multiplier to alter overall ignition occurrence; b) adjusts the original fixed fire thresholds with ignition success probabilities based on fire weather indices; and c) calculates spread by using a probability based on slope and wind direction. A Monte Carlo method is used with all three algorithms to determine occurrence. The new stochastic ignition approach yields more variety in fire intensity, a smaller annual total of cells burned, and patchier vegetation.

  14. Sensitivity Analysis of Remote Sensing Data: Comparing the Response of Vegetation Indices in Tropical Areas.

    NASA Astrophysics Data System (ADS)

    Bonifaz, R.

    2005-12-01

    During the past two decades, satellite remote sensing systems possessing high temporal resolution, but typically moderate or coarse spatial resolution, have increasingly been used to characterize and map vegetation dynamics. Assessing the seasonality of tropical vegetation has, however, been especially challenging. Tropical regimes of temperature and precipitation are generally less variable and pronounced than those in other biomes, and variations in plant growth are often more subtle. Using samples from selected tropical land cover types (tropical rain forest, tropical grasses, tropical deciduous forest, mixed forest and agricultural areas), sensitivity analysis will be carried out comparing different 'greenness' indices such as the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI) and the Wide Dynamic Range Vegetation Index (WDRVI) derived from the MODIS/TERRA sensor. This analysis will potentially allow the selection of the best index to describe the particular behavior of tropical vegetation for further characterization of seasonal changes of such areas.

  15. Assessing the effect of vegetation in the estimation of soil properties with field VNIR radiometry

    NASA Astrophysics Data System (ADS)

    Melendez-Pastor, I.; Córdoba-Sola, P.; Navarro-Pedreño, J.; Gómez, I.; Koch, M.

    2009-04-01

    regression models. In addition, vegetation water content and the NDVI (Normalized Difference Vegetation index) computed from field spectra also were used as explicative variables. Four combinations of explicative variables were used to predict soil variables: 1) high correlated bands, 2) high correlated bands and a soil parameter (LOI is used to predict soil moisture and vice versa), 3) high correlated bands and vegetation parameters, and 4) high correlated bands with soil and vegetation parameters. Models were developed for LOI and soil moisture with the first and second derivate. Medium to high correlation coefficients (R) were obtained in all regression models. R values ranged from 0.7 for the first approach (just high correlated bands) to 0.9 for the prediction of soil moisture with high correlated bands of the second derivate with vegetation parameters. Regression models with the second derivative achieved better model's adjustments and were almost equal for all combinations of explicative variables. A small improvement was observed for first derivate regression models using soil and vegetation explicative variables. Vegetation moisture was the most important parameter for the improvement of soil properties estimation. The combined used of soil and vegetation parameters for quantitative remote sensing of soil parameters allows accuracy improvements and a better knowledge of land cover mixtures. Regression models with the second derivate spectral peaks are less sensitive to changes in the vegetation coverage and thus retrieves better soil parameters estimations. References Konen, M., P. Jacobs, C. Lee Burras, B. Talaga, J. Mason. (2002) Equations for predicting soil organic carbon using loss-on-ignition for north central U.S. soils. Soil Science Society of America Journal, 66:1878-1881. Melendez-Pastor, I., J. Navarro-Pedreño, I. Gómez, M. Koch. (2008). Identifying optimal spectral bands to assess soil properties with VNIR radiometry in semi-arid soils. Geoderma, 147

  16. WANTED: Fully Automated Indexing.

    ERIC Educational Resources Information Center

    Purcell, Royal

    1991-01-01

    Discussion of indexing focuses on the possibilities of fully automated indexing. Topics discussed include controlled indexing languages such as subject heading lists and thesauri, free indexing languages, natural indexing languages, computer-aided indexing, expert systems, and the need for greater creativity to further advance automated indexing.…

  17. Adjustable Reeds For Weaving

    NASA Technical Reports Server (NTRS)

    Farley, Gary L.

    1994-01-01

    Local characteristics of fabrics varied to suit special applications. Adjustable reed machinery proposed for use in weaving fabrics in various net shapes, widths, yarn spacings, and yarn angles. Locations of edges of fabric and configuration of warp and filling yarns varied along fabric to obtain specified properties. In machinery, reed wires mounted in groups on sliders, mounted on lengthwise rails in reed frame. Mechanisms incorporated to move sliders lengthwise, parallel to warp yarns, by sliding them along rails; move sliders crosswise by translating reed frame rails perpendicular to warp yarns; and crosswise by spreading reed rails within group. Profile of reed wires in group on each slider changed.

  18. 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.

  19. Continuously adjustable Pulfrich spectacles

    NASA Astrophysics Data System (ADS)

    Jacobs, Ken; Karpf, Ron

    2011-03-01

    A number of Pulfrich 3-D movies and TV shows have been produced, but the standard implementation has inherent drawbacks. The movie and TV industries have correctly concluded that the standard Pulfrich 3-D implementation is not a useful 3-D technique. Continuously Adjustable Pulfrich Spectacles (CAPS) is a new implementation of the Pulfrich effect that allows any scene containing movement in a standard 2-D movie, which are most scenes, to be optionally viewed in 3-D using inexpensive viewing specs. Recent scientific results in the fields of human perception, optoelectronics, video compression and video format conversion are translated into a new implementation of Pulfrich 3- D. CAPS uses these results to continuously adjust to the movie so that the viewing spectacles always conform to the optical density that optimizes the Pulfrich stereoscopic illusion. CAPS instantly provides 3-D immersion to any moving scene in any 2-D movie. Without the glasses, the movie will appear as a normal 2-D image. CAPS work on any viewing device, and with any distribution medium. CAPS is appropriate for viewing Internet streamed movies in 3-D.

  20. Vegetation fire proneness in Europe

    NASA Astrophysics Data System (ADS)

    Pereira, Mário; Aranha, José; Amraoui, Malik

    2015-04-01

    Fire selectivity has been studied for vegetation classes in terms of fire frequency and fire size in a few European regions. This analysis is often performed along with other landscape variables such as topography, distance to roads and towns. These studies aims to assess the landscape sensitivity to forest fires in peri-urban areas and land cover changes, to define landscape management guidelines and policies based on the relationships between landscape and fires in the Mediterranean region. Therefore, the objectives of this study includes the: (i) analysis of the spatial and temporal variability statistics within Europe; and, (ii) the identification and characterization of the vegetated land cover classes affected by fires; and, (iii) to propose a fire proneness index. The datasets used in the present study comprises: Corine Land Cover (CLC) maps for 2000 and 2006 (CLC2000, CLC2006) and burned area (BA) perimeters, from 2000 to 2013 in Europe, provided by the European Forest Fire Information System (EFFIS). The CLC is a part of the European Commission programme to COoRdinate INformation on the Environment (Corine) and it provides consistent, reliable and comparable information on land cover across Europe. Both the CLC and EFFIS datasets were combined using geostatistics and Geographical Information System (GIS) techniques to access the spatial and temporal evolution of the types of shrubs and forest affected by fires. Obtained results confirms the usefulness and efficiency of the land cover classification scheme and fire proneness index which allows to quantify and to compare the propensity of vegetation classes and countries to fire. As expected, differences between northern and southern Europe are notorious in what concern to land cover distribution, fire incidence and fire proneness of vegetation cover classes. This work was supported by national funds by FCT - Portuguese Foundation for Science and Technology, under the project PEst-OE/AGR/UI4033/2014 and by

  1. Vegetation Identification With LIDAR

    DTIC Science & Technology

    2005-09-01

    Quercus agrifolia ).....27 3. Eucalyptus Tree (Eucalyptus Globus).........28 E. IDENTIFYING LOCATIONS WITHOUT VEGETATION.........30 F. IDENTIFYING...Relative First Return 25 ( Quercus dumosa), and the California Live Oak ( Quercus agrifolia ). These three species of trees are very abundant in this...ELEVATION OF TERRAIN...23 D. TYPES OF VEGETATION..............................26 1. California Scrub Oak ( Quercus dumosa).......26 2. California Live Oak

  2. Soil and vegetation surveillance

    SciTech Connect

    Antonio, E.J.

    1995-06-01

    Soil sampling and analysis evaluates long-term contamination trends and monitors environmental radionuclide inventories. This section of the 1994 Hanford Site Environmental Report summarizes the soil and vegetation surveillance programs which were conducted during 1994. Vegetation surveillance is conducted offsite to monitor atmospheric deposition of radioactive materials in areas not under cultivation and onsite at locations adjacent to potential sources of radioactivity.

  3. Sea Surface Temperature and Vegetation Index from MODIS

    NASA Technical Reports Server (NTRS)

    2002-01-01

    This is a composite MODIS image showing the 'green wave' of spring in North America and sea surface temperature in the ocean, collected over an 8-day period during the first week in April 2000. On land, the darker green pixels show where the most green foliage is being produced due to photosynthetic activity. Yellows on land show where there is little or no productivity and red is a boundary zone. In the ocean, orange and yellows show warmer waters and blues show colder values. (MODIS Data Type: MODIS-PFM)

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  5. Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

    PubMed Central

    Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

    2008-01-01

    This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG). We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand large-scale vegetation growth dynamics above the tree line in the European Alps. PMID:27879852

  6. Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements.

    PubMed

    Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

    2008-04-23

    This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG).We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand largescale vegetation growth dynamics above the tree line in the European Alps.

  7. The NLM Indexing Initiative's Medical Text Indexer.

    PubMed

    Aronson, Alan R; Mork, James G; Gay, Clifford W; Humphrey, Susanne M; Rogers, Willie J

    2004-01-01

    The Medical Text Indexer (MTI) is a program for producing MeSH indexing recommendations. It is the major product of NLM's Indexing Initiative and has been used in both semi-automated and fully automated indexing environments at the Library since mid 2002. We report here on an experiment conducted with MEDLINE indexers to evaluate MTI's performance and to generate ideas for its improvement as a tool for user-assisted indexing. We also discuss some filtering techniques developed to improve MTI's accuracy for use primarily in automatically producing the indexing for several abstracts collections.

  8. Modelling vegetated dune landscapes

    NASA Astrophysics Data System (ADS)

    Baas, A. C. W.; Nield, J. M.

    2007-03-01

    This letter presents a self-organising cellular automaton model capable of simulating the evolution of vegetated dunes with multiple types of plant response in the environment. It can successfully replicate hairpin, or long-walled, parabolic dunes with trailing ridges as well as nebkha dunes with distinctive deposition tails. Quantification of simulated landscapes with eco-geomorphic state variables and subsequent cluster analysis and PCA yields a phase diagram of different types of coastal dunes developing from blow-outs as a function of vegetation vitality. This diagram indicates the potential sensitivity of dormant dune fields to reactivation under declining vegetation vitality, e.g. due to climatic changes. Nebkha simulations with different grid resolutions demonstrate that the interaction between the (abiotic) geomorphic processes and the biological vegetation component (life) introduces a characteristic length scale on the resultant landforms that breaks the typical self-similar scaling of (un-vegetated) bare-sand dunes.

  9. Evapotranspiration estimation in heterogeneous urban vegetation

    NASA Astrophysics Data System (ADS)

    Nagler, P. L.; Nouri, H.; Beecham, S.; Anderson, S.; Sutton, P.; Chavoshi, S.

    2015-12-01

    Finding a valid approach to measure the water requirements of mixed urban vegetation is a challenge. Evapotranspiration (ET) is the main component of a plant's water requirement. A better understanding of the ET of urban vegetation is essential for sustainable urbanisation. Increased implementation of green infrastructure will be informed by this work. Despite promising technologies and sophisticated facilities, ET estimation of urban vegetation remains insufficiently characterized. We reviewed the common field, laboratory and modelling techniques for ET estimation, mostly agriculture and forestry applications. We opted for 3 approaches of ET estimation: 1) an observational-based method using adjustment factors applied to reference ET, 2) a field-based method of Soil Water Balance (SWB) and 3) a Remote Sensing (RS)-based method. These approaches were applied to an experimental site to evaluate the most suitable ET estimation approach for an urban parkland. To determine in-situ ET, 2 lysimeters and 4 Neutron Moisture Meter probes were installed. Based on SWB principles, all input water (irrigation, precipitation and upward groundwater movements) and output water (ET, drainage, soil moisture and runoff) were measured monthly for 14 months. The observation based approach and the ground-based approach (SWB) were compared. Our predictions were compared to the actual irrigation rates (data provided by the City Council). Results suggest the observational-based method is the most appropriate urban ET estimation. We examined the capability of RS to estimate ET for urban vegetation. Image processing of 5 WorldView2 satellite images enabled modelling of the relationship between urban vegetation and vegetation indices derived from high resolution images. Our results indicate that an ETobservational-based -NDVI modelling approach is a reliable method of ET estimation for mixed urban vegetation. It also has the advantage of not depending on extensive field data collection.

  10. 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.

  11. Use of spectral channels and vegetation indices from satellite VEGETATION time series for the Post-Fire vegetation recovery estimation

    NASA Astrophysics Data System (ADS)

    Coluzzi, Rosa; Lasaponara, Rosa; Montesano, Tiziana; Lanorte, Antonio; de Santis, Fortunato

    2010-05-01

    Satellite data can help monitoring the dynamics of vegetation in burned and unburned areas. Several methods can be used to perform such kind of analysis. This paper is focused on the use of different satellite-based parameters for fire recovery monitoring. In particular, time series of single spectral channels and vegetation indices from SPOT-VEGETATION have investigated. The test areas is the Mediterranean ecosystems of Southern Italy. For this study we considered: 1) the most widely used index to follow the process of recovery after fire: normalized difference vegetation index (NDVI) obtained from the visible (Red) and near infrared (NIR) by using the following formula NDVI = (NIR_Red)/(NIR + Red), 2) moisture index MSI obtained from the near infrared and Mir for characterization of leaf and canopy water content. 3) NDWI obtained from the near infrared and Mir as in the case of MSI, but with the normalization (as the NDVI) to reduce the atmospheric effects. All analysis for this work was performed on ten-daily normalized difference vegetation index (NDVI) image composites (S10) from the SPOT- VEGETATION (VGT) sensor. The final data set consisted of 279 ten-daily, 1 km resolution NDVI S1O composites for the period 1 April 1998 to 31 December 2005 with additional surface reflectance values in the blue (B; 0.43-0.47,um), red (R; 0.61-0.68,um), near-infrared (NIR; 0.78-0.89,um) and shortwave-infrared (SWIR; 1.58-1.75,um) spectral bands, and information on the viewing geometry and pixel status. Preprocessing of the data was performed by the Vlaamse Instelling voor Technologisch Onderzoek (VITO) in the framework of the Global Vegetation Monitoring (GLOVEG) preprocessing chain. It consisted of the Simplified Method for Atmospheric Correction (SMAC) and compositing at ten-day intervals based on the Maximum Value Compositing (MVC) criterion. All the satellite time series were analysed using the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation recovery

  12. a Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

    NASA Astrophysics Data System (ADS)

    Niazi, S.; Mokhtarzade, M.; Saeedzadeh, F.

    2015-12-01

    Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for

  13. Prenatal and Postnatal Fruit and Vegetable Intake Among US Women: Associations with WIC Participation.

    PubMed

    Stallings, Tiffany L; Gazmararian, Julie A; Goodman, Michael; Kleinbaum, David

    2016-08-01

    Objective Evaluate variation in fruit and vegetable intake by Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participation and poverty status among pregnant, and postpartum women participating in the Infant Feeding Practice Study II (IFPSII). Methods IFPSII (2005-2007) followed US women from third trimester through 1 year postpartum through mailed questionnaires measuring income, WIC participation, breastfeeding; and dietary history questionnaires (DHQ) assessing prenatal/postnatal fruit and vegetable consumption. Poverty measurements used U.S. Census Bureau Federal Poverty thresholds to calculate percent of poverty index ratio (PIR) corresponding to WIC's financial eligibility (≤185 % PIR). Comparison groups: WIC recipients; WIC eligible (≤185 % PIR), but non-recipients; and women not financially WIC eligible (>185 % PIR). IFPSII participants who completed at least one DHQ were included. Intake variation among WIC/poverty groups was assessed by Kruskal-Wallis tests and between groups by Mann-Whitney Wilcoxon tests and logistic regression. Mann-Whitney Wilcoxon tests examined postnatal intake by breastfeeding. Results Prenatal vegetable intake significantly varied by WIC/poverty groups (p = 0.04) with WIC recipients reporting significantly higher intake than women not financially WIC eligible (p = 0.02); association remained significant adjusting for confounders [odds ratio 0.66 (95 % confidence interval: 0.49-0.90)]. Prenatal fruit and postnatal consumption did not significantly differ by WIC/poverty groups. Postnatal intake was significantly higher among breastfeeding than non-breastfeeding women (fruit: p < 0.0001; vegetable: p = 0.006). Conclusions for Practice Most intakes did not significantly differ by WIC/poverty groups and thus prompts research on WIC recipient's dietary behaviors, reasons for non-participation in WIC, and the influence of the recent changes to the WIC food package.

  14. Vegetable variety is a key to improved diet quality in low-income women in California.

    PubMed

    Keim, Nancy L; Forester, Shavawn M; Lyly, Marika; Aaron, Grant J; Townsend, Marilyn S

    2014-03-01

    Primary prevention education interventions, including those sponsored by the US Department of Agriculture for low-income families, encourage and support increases in vegetable intake. Promoting vegetable variety as a focal point for behavior change may be a useful strategy to increase vegetable consumption. A simple vegetable variety evaluation tool might be useful to replace the time-intensive 24-hour dietary recall. The purpose of our study was to determine whether vegetable variety is associated with vegetable consumption and diet quality among US Department of Agriculture program participants. Variety of vegetable intake and measures of total vegetable intake, diet quality, and diet cost were evaluated. Low-income, female participants (N=112) aged 20 to 55 years with body mass index 17.7 to 68.5 who were the primary food purchasers/preparers for their households were recruited from four California counties representing rural, urban, and suburban areas. Energy density and Healthy Eating Index-2005 were used to assess diet quality. Vegetable variety was based on number of different vegetables consumed per week using a food frequency questionnaire, and three groups were identified as: low variety, ≤5 different vegetables per week; moderate variety, 6 to 9 vegetables per week; and high variety, ≥10 vegetables per week. Compared with the low-variety group, participants in the high-variety group ate a greater quantity of vegetables per day (P<0.001); their diets had a higher Healthy Eating Index score (P<0.001) and lower energy density (P<0.001); and costs of their daily diet and vegetable use were higher (P<0.001). Thus, greater vegetable variety was related to better overall diet quality, a larger quantity of vegetables consumed, and increased diet cost.

  15. Cruciferous Vegetables and Cancer Prevention

    MedlinePlus

    ... cruciferous vegetables? Cruciferous vegetables are part of the Brassica genus of plants. They include the following vegetables, ... others: Arugula Bok choy Broccoli Brussels sprouts Cabbage Cauliflower Collard greens Horseradish Kale Radishes Rutabaga Turnips Watercress ...

  16. Vegetable Production System (Veggie)

    NASA Technical Reports Server (NTRS)

    Levine, Howard G.; Smith, Trent M.

    2016-01-01

    The Vegetable Production System (Veggie) was developed by Orbital Technologies Corp. to be a simple, easily stowed, and high growth volume yet low resource facility capable of producing fresh vegetables on the International Space Station (ISS). In addition to growing vegetables in space, Veggie can support a variety of experiments designed to determine how plants respond to microgravity, provide real-time psychological benefits for the crew, and conduct outreach activities. Currently, Veggie provides the largest volume available for plant growth on the ISS.

  17. Dietary Intake of Fiber, Fruit, and Vegetables Decrease the Risk of Incident Kidney Stones in Women: A Women's Health Initiative (WHI) Report

    PubMed Central

    Sorensen, Mathew D.; Hsi, Ryan S.; Chi, Thomas; Shara, Nawar; Wactawski-Wende, Jean; Kahn, Arnold J.; Wang, Hong; Hou, Lifang; Stoller, Marshall L.

    2014-01-01

    Purpose We evaluated the relationship between dietary fiber, fruit, and vegetable intake, and the risk of kidney stone formation. Methods Overall, 83,922 postmenopausal women from the WHI Observational Study were included and followed prospectively. Cox proportional hazards regression analyses evaluated the associations between total dietary fiber, fruits, and vegetable intake, and the risk of incident kidney stone formation adjusting for nephrolithiasis risk factors (age, race/ethnicity, geographic region, diabetes mellitus, calcium supplementation, hormone therapy use, body mass index, calibrated caloric intake, and dietary water, sodium, animal protein, and calcium intake). Women with a prior history of kidney stones (3,471 women) were analyzed separately. Results Mean age was 64±7 years, 85% of women were Caucasian and 2,937 women (3.5%) experienced a kidney stone occurrence in 8 years median follow-up. In women with no history of kidney stones, higher total dietary fiber (6-26% decreased risk, p<0.001), higher fruit intake (12-25% decreased risk, p<0.001), and higher vegetable intake (9-22% decreased risk, p=0.002) were associated with a decreased risk of incident kidney stone formation in separate adjusted models. In women with a history of stones, there were no significant protective effects of fiber, fruits, or vegetable intake on the risk of kidney stone recurrence. Conclusions Greater dietary intake of fiber, fruits and vegetables were each associated with a reduced risk of incident kidney stones in postmenopausal women. The protective effects were independent of other known risk factors for kidney stones. In contrast, there was no reduction in risk in women with a history of stones. PMID:24859445

  18. Characterization of global vegetation using AVHRR data

    NASA Astrophysics Data System (ADS)

    Kiang, Richard K.

    1998-03-01

    Increase in the levels of carbon dioxide and other greenhouse gases over the next half-century may result in an increase in global mean temperature. The recent discoveries of possible advance of arctic tree line into the tundra and earlier greening of northern vegetation provide additional warnings that global warming may indeed be occurring. On the Earth surface, land cover and its changes affect the coupling between the biosphere and the atmosphere, and control many important Earth system processes. Satellite remote sensing provides long-term, repeated coverage over extended area and is the essential data source for monitoring climate changes. An Advanced Very-High Resolution Radiometer (AVHRR) Pathfinder dataset from 1987, in 1 degree latitude-longitude resolution, is used in this study. Two reflective channels, two thermal channels, and Normalized Difference Vegetation Index are the input parameters. In conjunction with a global vegetation ground truth, a multi-layer neural network is trained and used for global vegetation characterization. As the same type of vegetation may appear very differently over different parts of the Earth at any given time, global classification is more difficult than local classification. It is shown that a multitemporal approach, in which data from multiple dates are used, may improve the accuracy.

  19. Delay Adjusted Incidence

    Cancer.gov

    This Infographic shows the National Cancer Institute SEER Incidence Trends. The graphs show the Average Annual Percent Change (AAPC) 2002-2011. For Men, Thyroid: 5.3*,Liver & IBD: 3.6*, Melanoma: 2.3*, Kidney: 2.0*, Myeloma: 1.9*, Pancreas: 1.2*, Leukemia: 0.9*, Oral Cavity: 0.5, Non-Hodgkin Lymphoma: 0.3*, Esophagus: -0.1, Brain & ONS: -0.2*, Bladder: -0.6*, All Sites: -1.1*, Stomach: -1.7*, Larynx: -1.9*, Prostate: -2.1*, Lung & Bronchus: -2.4*, and Colon & Rectum: -3/0*. For Women, Thyroid: 5.8*, Liver & IBD: 2.9*, Myeloma: 1.8*, Kidney: 1.6*, Melanoma: 1.5, Corpus & Uterus: 1.3*, Pancreas: 1.1*, Leukemia: 0.6*, Brain & ONS: 0, Non-Hodgkin Lymphoma: -0.1, All Sites: -0.1, Breast: -0.3, Stomach: -0.7*, Oral Cavity: -0.7*, Bladder: -0.9*, Ovary: -0.9*, Lung & Bronchus: -1.0*, Cervix: -2.4*, and Colon & Rectum: -2.7*. * AAPC is significantly different from zero (p<.05). Rates were adjusted for reporting delay in the registry. www.cancer.gov Source: Special section of the Annual Report to the Nation on the Status of Cancer, 1975-2011.

  20. Nonlinear Hydrostatic Adjustment.

    NASA Astrophysics Data System (ADS)

    Bannon, Peter R.

    1996-12-01

    The final equilibrium state of Lamb's hydrostatic adjustment problem is found for finite amplitude heating. Lamb's problem consists of the response of a compressible atmosphere to an instantaneous, horizontally homogeneous heating. Results are presented for both isothermal and nonisothermal atmospheres.As in the linear problem, the fluid displacements are confined to the heated layer and to the region aloft with no displacement of the fluid below the heating. The region above the heating is displaced uniformly upward for heating and downward for cooling. The amplitudes of the displacements are larger for cooling than for warming.Examination of the energetics reveals that the fraction of the heat deposited into the acoustic modes increases linearly with the amplitude of the heating. This fraction is typically small (e.g., 0.06% for a uniform warming of 1 K) and is essentially independent of the lapse rate of the base-state atmosphere. In contrast a fixed fraction of the available energy generated by the heating goes into the acoustic modes. This fraction (e.g., 12% for a standard tropospheric lapse rate) agrees with the linear result and increases with increasing stability of the base-state atmosphere.The compressible results are compared to solutions using various forms of the soundproof equations. None of the soundproof equations predict the finite amplitude solutions accurately. However, in the small amplitude limit, only the equations for deep convection advanced by Dutton and Fichtl predict the thermodynamic state variables accurately for a nonisothermal base-state atmosphere.

  1. 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.

  2. Salad bars and fruit and vegetable consumption in elementary schools: a plate waste study.

    PubMed

    Adams, Marc A; Pelletier, Robin L; Zive, Michelle M; Sallis, James F

    2005-11-01

    The object of this study was to determine whether students attending schools with self-service salad bars consume a greater amount of fruits and vegetables compared with students using preportioned servings and to evaluate the relationship between number of items offered and fruit and vegetable consumption. Two hundred ninety-four students in first through fifth grade were randomly selected from two schools with salad bars and two with preportioned servings. Weights of fruit and vegetable items were measured pre- and postconsumption and interobserver agreement +/-1 g was > or =95%. Presence of a salad bar was not associated with greater fruit and vegetable consumption. Fruit and vegetable consumption was positively related to the number of fruit and vegetable items offered at salad bars (P < .05), adjusting for sex and grade. Fruit and vegetable variety was associated with elementary school-age children's fruit and vegetable consumption when using salad bars.

  3. Coma / Vegetative State

    MedlinePlus

    ... Vegetative State Legal Issues Sleeping Problems Anxiety & Stress Concussion / Mild TBI Living with Traumatic Brain Injury Speech & ... Conscious States After Severe Brain Injury Brain Trauma, Concussion, and Coma What Is the Glasgow Coma Scale? ...

  4. Vegetative pyoderma gangrenosum.

    PubMed

    Kim, Randie H; Lewin, Jesse; Hale, Christopher S; Meehan, Shane A; Stein, Jennifer; Ramachandran, Sarika

    2014-12-16

    Vegetative pyoderma gangrenosum is a rare, superficial variant of pyoderma gangrenosum that is more commonly found on the trunk as single or multiple, non-painful lesions. There is typically no associated underlying systemic disease. Compared to classic pyoderma gangrenosum, vegetative lesions are more likely to heal without the use of systemic glucocorticoids, although up to 39% of patients required a short course of prednisone in a review of 46 cases. Treatments for vegetative pyoderma gangrenosum include topical and intralesional glucocorticoids, minocycline or doxycycline, dapsone, colchicine, and, rarely, alternative steroid-sparing immunosuppressants. We present a case of multiple vegetative pyoderma gangrenosum lesions arising in prior surgical sites in a patient found to have IgA monoclonal gammopathy and abnormal urinary protein electrophoresis.

  5. Vegetable Oil-Biorefinery.

    PubMed

    Pudel, Frank; Wiesen, Sebastian

    2017-03-07

    Conventional vegetable oil mills are complex plants, processing oil, fruits, or seeds to vegetable fats and oils of high quality and predefined properties. Nearly all by-products are used. However, most of the high valuable plant substances occurring in oil fruits or seeds besides the oil are used only in low price applications (proteins as animal feeding material) or not at all (e.g., phenolics). This chapter describes the state-of-the-art of extraction and use of oilseed/oil fruit proteins and phyto-nutrients in order to move from a conventional vegetable oil processing plant to a proper vegetable oil-biorefinery producing a wide range of different high value bio-based products.

  6. Monitoring global vegetation

    NASA Technical Reports Server (NTRS)

    Macdonald, R. B.; Houston, A. G.; Heydorn, R. P.; Botkin, D. B.; Estes, J. E.; Strahler, A. H.

    1981-01-01

    An attempt is made to identify the need for, and the current capability of, a technology which could aid in monitoring the Earth's vegetation resource on a global scale. Vegetation is one of our most critical natural resources, and accurate timely information on its current status and temporal dynamics is essential to understand many basic and applied environmental interrelationships which exist on the small but complex planet Earth.

  7. Vegetation and soils

    USGS Publications Warehouse

    Burke, M.K.; King, S.L.; Eisenbies, M.H.; Gartner, D.

    2000-01-01

    Intro paragraph: Characterization of bottomland hardwood vegetation in relatively undisturbed forests can provide critical information for developing effective wetland creation and restoration techniques and for assessing the impacts of management and development. Classification is a useful technique in characterizing vegetation because it summarizes complex data sets, assists in hypothesis generation about factors influencing community variation, and helps refine models of community structure. Hierarchical classification of communities is particularly useful for showing relationships among samples (Gauche 1982).

  8. Vegetable oil fuels

    SciTech Connect

    Not Available

    1982-01-01

    Fifty contributions (presentations) involving more than one hundred people worldwide were given at the International Conference on Plant and Vegetable Oils as Fuels. The proceedings were in Fargo, North Dakota, from August 2-4, 1982. The conference helped to promote renewable fuels, bio-oils, from plant and vegetable oils. Separate abstracts were prepared for 44 items for inclusion in the Energy Data Base.

  9. Vegetation classification based on Advanced Very High Resolution Radiometer /AVHRR/ satellite imagery

    NASA Technical Reports Server (NTRS)

    Norwine, J.; Greegor, D. H.

    1983-01-01

    Data from the NOAA-6 spacecraft Advanced Very High Resolution Radiometer (AVHRR) were tested for effectiveness for vegetation classification. Vegetation, climatological, and meteorological data were gathered for three days over 12 locations, and the normalized differences between the AVHRR bands 1 and 2 were determined. A vegetative greenness index was compared with a hydrologic factor and vegetation characteristics as measured by ground truth. A multivariate vegetation gradient model was formulated, incorporating AVHRR and climatological data. The hydrologic factor was calculated in terms of the precipitation, evaporation, maximum and minimum temperatures, and the hydrologic capacity. The observations were taken over Texas, which has a wide range of climates. A high correlation was found in the vegetation-HF index. The AVHRR data are concluded to be an effective tool for analysis of vegetation/climate relationships.

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  11. [Remote sensing estimation of vegetation coverage in guangzhou based on the correction of atmospheric radiation].

    PubMed

    Gong, Jian-Zhou; Xia, Bei-Cheng

    2007-03-01

    Vegetation coverage is a basic parameter in describing landscape ecosystem, and an important index in assessing ecosystem health and security. Based on the four TM images in 1990, 1995, 2000 and 2005, and by using the correction model to deduct atmospheric radiation effect and the spatial operating model for TM image under unsupervised classification, the relationship model between vegetation coverage and normalized vegetation index was established, and the vegetation coverage in different phases in Guangzhou was calculated. The results showed that the vegetation coverage in Guangzhou decreased continuously from 1990 to 2000 but began to increase thereafter, which accorded with the economic development and environmental construction of the city. The model established in this paper could simulate well the dynamics of regional vegetation cover, and have the advantage in describing the dynamics of vegetation coverage more accurately, being available to the assessment of urban eco-environmental quality and its dynamic characters.

  12. [Fruits and vegetables].

    PubMed

    Aranceta, Javier

    2004-06-01

    Fruits and vegetables are particularly interesting for health for their content in minerals, antioxidant vitamins, phytochemicals and dietary fiber. All these substances are related to lower risk for the development of health probems, such as certain types of cancer, cardiovascular diseases, type 2 diabetes, obesity, constipation or diverticolsys. The sound basis of scientific evidence led European and American scientific organizations and societies to recommend an intake up to 150-200 g of vegetables every day; ie. 2 or more portions daily and 3 or more portions of fruit; five portions of fruit and vegetables all together. According to the consumer panel from the Spanish Ministry of Agriculture, Fisheries and Food, between the late 80s and the end of the 90s. consumption of fruit and vegetables decreased. However, in late years this trend has slow down and even reversed. Results from food consumption studies based on individual level assessment in Spain estimate an average consumption of fruit and vegetables of 154 g/per person/day in adults aged 25-60 yr. Prevalence of inadequate intake of fruit and vegetables is high among children and young people. In this age group above 70% of the population consume less than 3 portions of fruit every day on average. Reorientation of prevailing food patterns nowadays require investment in measures aimed at increasing the consumption of plant foods and estimulate healthy food habits in families.

  13. Treatment of vegetable oils

    SciTech Connect

    Bessler, T.R.

    1986-05-13

    A process is described for preparing an injectable vegetable oil selected from the group consisting of soybean oil and sunflower oil and mixtures thereof which comprise: (a) first treating the vegetable oil at a temperature of 80/sup 0/C to about 130/sup 0/C with an acid clay; (b) deodorizing the vegetable oil with steam at a temperature of 220/sup 0/C to about 280/sup 0/C and applying a vacuum to remove volatilized components; (c) treating the deodorized vegetable oil, at a temperature of from about 10/sup 0/C to about 60/sup 0/C, with an acid clay to reduce the content of a member selected from the group consisting of diglycerides, tocopherol components, and trilinolenin and mixtures thereof, wherein the acid clay is added in a weight ratio to the deoderized vegetable oil of from about 1:99 to about 1:1; and (d) thereafter conducting a particulate filtration to remove a substantial portion of the acid clay from the vegetable oil, wherein the filtration is accomplished with filters having a pore size of from about 0.1 to 0.45 microns, thereby obtaining the injectable oil.

  14. Response of vegetation to the 2003 European drought was mitigated by height

    NASA Astrophysics Data System (ADS)

    Bevan, S. L.; Los, S. O.; North, P. R. J.

    2014-06-01

    The effects on climate of land-cover change, predominantly from the conversion of forests to crops or grassland, are reasonably well understood for low and high latitudes but are largely unknown for temperate latitudes. The main reason for this gap in our knowledge is that there are compensating effects on the energy and water balance that are related to changes in land-surface albedo, soil evaporation and plant transpiration. We analyse how vegetation height affected the response of vegetation during the 2003 European drought using precipitation data, temperature data, normalized difference vegetation index data and a new vegetation height data set obtained from the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat). At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature (DTR) range, indicating less water stress and drought impacts on tall vegetation. Over Germany for example, 98% of significant correlations showed a smaller anomaly in vegetation index anomaly with greater height, and 95% of significant correlations showed a smaller DTR with greater vegetation height. Over France the equivalent percentages were 94 and 88%, respectively. Vegetation height is likely associated with greater rooting depth, canopy heat capacity or both. Our results suggest that land-surface models can be improved by better estimates of vegetation height and associated with this a more realistic response to drought.

  15. Indexing Consistency and Quality.

    ERIC Educational Resources Information Center

    Zunde, Pranas; Dexter, Margaret E.

    A measure of indexing consistency is developed based on the concept of 'fuzzy sets'. It assigns a higher consistency value if indexers agree on the more important terms than if they agree on less important terms. Measures of the quality of an indexer's work and exhaustivity of indexing are also proposed. Experimental data on indexing consistency…

  16. 44 CFR 206.47 - Cost-share adjustments.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... effective for disasters declared on or after May 21, 1999, $75 per capita of State population; (2) Effective... population; (3) Effective for disasters declared after January 1, 2001, $100 per capita of State population... of State population, adjusted annually for inflation using the Consumer Price Index for All...

  17. 44 CFR 206.47 - Cost-share adjustments.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... effective for disasters declared on or after May 21, 1999, $75 per capita of State population; (2) Effective... population; (3) Effective for disasters declared after January 1, 2001, $100 per capita of State population... of State population, adjusted annually for inflation using the Consumer Price Index for All...

  18. Nanometer-thick flat lens with adjustable focus

    SciTech Connect

    Son, T. V.; Haché, A.; Ba, C. O. F.; Vallée, R.

    2014-12-08

    We report laser beam focusing by a flat, homogeneous film with a thickness of less than 100 nm. The effect relies on refractive index changes occurring in vanadium dioxide as it undergoes a phase transition from insulator to metal. Phase front curvature is achieved by means of temperature gradients, and adjustable focal lengths from infinity to 30 cm are attained.

  19. 12 CFR 34.22 - Index.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY REAL ESTATE LENDING AND APPRAISALS Adjustable-Rate...) applies (i.e., the annual percentage rate of a loan may increase after consummation, the term exceeds one... an index or combination of indices to which changes in the interest rate will be linked. This...

  20. 12 CFR 34.22 - Index.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Index. 34.22 Section 34.22 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY REAL ESTATE LENDING AND APPRAISALS Adjustable-Rate... that the notice presents supervisory concerns or raises significant issues of law or policy. If the...

  1. Advances in remote sensing for vegetation dynamics and agricultural management

    NASA Astrophysics Data System (ADS)

    Tucker, C. J.; Puma, M. J.

    2015-12-01

    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.

  2. 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.

  3. Grassland birds orient nests relative to nearby vegetation

    USGS Publications Warehouse

    Hoekman, S.T.; Ball, I.J.; Fondell, T.E.

    2002-01-01

    We studied orientation of nest sites relative to nearby vegetation for dabbling ducks (Cinnamon Teal, Anas cyanoptera; Blue-winged Teal, A. discors; Gadwall, A. strepera; Mallard, A. platyrhynchos; and Northern Shoveler, A. clypeata) and Short-eared Owls (Asio flammeus) in ungrazed grassland habitat during 1995-1997 in westcentral Montana. We estimated an index of vegetation height and density in intercardinal directions (NE, SE, SW, NW) immediately around nests. All species oriented nests with the least vegetation to the southeast and the most vegetation to either the southwest or northwest. Furthermore, maximum vegetation around nests shifted from the southwest to the northwest with increasing nest initiation date, apparently as a response of individuals tracking seasonal change in the afternoon solar path. Thus, nests were relatively exposed to solar insolation during cool morning hours but were shaded from intense insolation in the afternoon throughout the breeding season. We suggest that nest microhabitat was selected in part to moderate the thermal environment.

  4. Soil, water, and vegetation conditions in south Texas

    NASA Technical Reports Server (NTRS)

    Wiegand, C. L.; Gausman, H. W.; Leamer, R. W.; Richardson, A. J.; Everitt, J. H.; Gerbermann, A. H. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. The best wavelengths in the 0.4 to 2.5 micron interval were determined for detecting lead toxicity and ozone damage, distinguishing succulent from woody species, and detecting silverleaf sunflower. A perpendicular vegetation index, a measure of the distance from the soil background line, in MSS 5 and MSS 7 data space, of pixels containing vegetation was developed and tested as an indicator of vegetation development and crop vigor. A table lookup procedure was devised that permits rapid identification of soil background and green biomass or phenological development in LANDSAT scenes without the need for training data.

  5. 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...

  6. 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...

  7. Effects of vegetation structure on biomass accumulation in a coupled water-carbon-energy balance model in West Africa

    NASA Astrophysics Data System (ADS)

    Yin, Zun; Dekker, Stefan; van den Hurk, Bart; Dijkstra, Henk

    2013-04-01

    A myriad of interactions exist between vegetation and local climate for arid and semi-arid regions. Vegetation function, structure and individual behavior have enormous impacts on carbon-water-energy balances, which consequently influence local climate variability that, in turn, feeds back to the vegetation. In this study, a conceptual vegetation structure scheme is formulated and tested in a new carbon-water-energy coupled model to explore the importance of vegetation structure on equilibrium biomass states. Two different strategies of vegetation adaptation to water stress are included. Surface energy, water and carbon fluxes are simulated for a range of vegetation structures across a precipitation gradient in West Africa and optimal vegetation structures that maximize biomass for each precipitation regime are determined. Und