Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data

[1]  Luca Fanucci,et al.  CloudScout: A Deep Neural Network for On-Board Cloud Detection on Hyperspectral Images , 2020, Remote. Sens..

[2]  Son V. Nghiem,et al.  Evaluating the Preconditions of Two Remote Sensing SWE Retrieval Algorithms over the US , 2020, Remote. Sens..

[3]  P. Rodríguez-Veiga,et al.  MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP , 2019, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

[4]  Sadhan Malik,et al.  Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques , 2018, Geology, Ecology, and Landscapes.

[5]  R. Kunwar,et al.  Change in forest and vegetation cover influencing distribution and uses of plants in the Kailash Sacred Landscape, Nepal , 2018, Environment, Development and Sustainability.

[6]  Subodh Chandra Pal,et al.  Modeling and mapping of groundwater potentiality zones using AHP and GIS technique: a case study of Raniganj Block, Paschim Bardhaman, West Bengal , 2018, Modeling Earth Systems and Environment.

[7]  Subodh Chandra Pal,et al.  Application of forest canopy density model for forest cover mapping using LISS-IV satellite data: a case study of Sali watershed, West Bengal , 2018, Modeling Earth Systems and Environment.

[8]  Ndifreke I. Udosen,et al.  A finite integration forward solver and a domain search reconstruction solver for electrical resistivity tomography (ERT) , 2018, Modeling Earth Systems and Environment.

[9]  S. Liang,et al.  Methodologies for Integrating Multiple High-Level Remotely Sensed Land Products , 2018 .

[10]  F. U. Ochege,et al.  Geospatial assessment of vegetation status in Sagbama oilfield environment in the Niger Delta region, Nigeria , 2017 .

[11]  Bahram Salehi,et al.  Temperature-Vegetation-soil Moisture Dryness Index (TVMDI) , 2017 .

[12]  Yanchen Bo,et al.  A shadow identification method using vegetation indices derived from hyperspectral data , 2017 .

[13]  F. U. Ochege,et al.  Remote sensing of vegetation cover changes in the humid tropical rainforests of Southeastern Nigeria (1984–2014) , 2017 .

[14]  Fetriyuna,et al.  Impact of Land-Use Changes on Kuranji River Basin Functions , 2017 .

[15]  L. Qin,et al.  Seasonal dynamics of vegetation of the central Loess Plateau (China) based on tree rings and their relationship to climatic warming , 2017, Environment, Development and Sustainability.

[16]  S. Mandal,et al.  Monitoring forest dynamics and landslide susceptibility in Mechi–Balason interfluves of Darjiling Himalaya, West Bengal using forest canopy density model (FCDM) and Landslide Susceptibility Index model (LSIM) , 2016, Modeling Earth Systems and Environment.

[17]  Cecilia Masemola,et al.  Comparison of Landsat 8 OLI and Landsat 7 ETM+ for estimating grassland LAI using model inversion and spectral indices: case study of Mpumalanga, South Africa , 2016 .

[18]  Jindi Wang,et al.  Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Xuemei Yang,et al.  Extracting and analyzing forest and woodland cover change in Eritrea based on landsat data using supervised classification , 2016 .

[20]  Bo Jiang,et al.  Retrieval of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from VIIRS Time-Series Data , 2016, Remote. Sens..

[21]  C. Hülsebusch,et al.  High impact grazing as a management tool to optimize biomass growth in northern Argentinean grassland , 2016 .

[22]  Mathieu Garel,et al.  The Enhanced Vegetation Index (EVI) as a proxy for diet quality and composition in a mountain ungulate , 2016 .

[23]  Ute Beyer,et al.  Remote Sensing And Image Interpretation , 2016 .

[24]  Haroon Sajjad,et al.  Assessing spatio-temporal health of forest cover using forest canopy density model and forest fragmentation approach in Sundarban reserve forest, India , 2015, Modeling Earth Systems and Environment.

[25]  D. Dutta,et al.  Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI) , 2015 .

[26]  D. Dutta,et al.  Monitoring the extent of desertification processes in western Rajasthan (India) using geo-information science , 2015, Arabian Journal of Geosciences.

[27]  Futao Wang,et al.  A new index for mapping built-up and bare land areas from Landsat-8 OLI data , 2014 .

[28]  D. Dutta,et al.  Identifying the Process of Environmental Changes of Churu district, Rajasthan (India) Using Remote Sensing Indices , 2014 .

[29]  B. Fang,et al.  Soil moisture at watershed scale: Remote sensing techniques , 2014 .

[30]  Claudia Notarnicola,et al.  Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT2 images and hydrological modeling , 2014 .

[31]  Olivier Roupsard,et al.  Leaf area index as an indicator of ecosystem services and management practices: An application for coffee agroforestry , 2014 .

[32]  S. Li,et al.  A new bare-soil index for rapid mapping developing areas using LANDSAT 8 data , 2014 .

[33]  Alan H. Strahler,et al.  Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: a case study in Sierra National Forest, CA , 2014 .

[34]  M. Elhag.  Sensitivity analysis assessment of remotely based vegetation indices to improve water resources management , 2014, Environment, Development and Sustainability.

[35]  Susmita Das,et al.  Time Series Analysis of Forest and Tree Cover of West Bengal from 1988 to 2010, using RS/GIS, for Monitoring Afforestation Programmes , 2014 .

[36]  S. Li.  A NEW BARE-SOIL INDEX FOR RAPID MAPPING DEVELOPING AREAS USING LANDSAT 8 DATA , 2014 .

[37]  Gulab Singh,et al.  Application of remote sensing techniques toward the role of traditional water bodies with respect to vegetation conditions , 2014, Environment, Development and Sustainability.

[38]  A. Westergaard‐Nielsen,et al.  Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area , 2013 .

[39]  Pavel Propastin,et al.  Retrieval of remotely sensed LAI using Landsat ETM+ data and ground measurements of solar radiation and vegetation structure: Implication of leaf inclination angle , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[40]  Zheng Niu,et al.  Estimating the spatial pattern of soil respiration in Tibetan alpine grasslands using Landsat TM images and MODIS data , 2013 .

[41]  Paulin Coulibaly,et al.  Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications , 2013 .

[42]  B. Pradhan,et al.  Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran , 2012, Natural Hazards.

[43]  Wen Liu,et al.  Object-Based Shadow Extraction and Correction of High-Resolution Optical Satellite Images , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[44]  Tsuyoshi Kajisa,et al.  Estimating forest canopy density of tropical mixed deciduous vegetation using Landsat data: a comparison of three classification approaches , 2012 .

[45]  Alireza Sharifi,et al.  Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas , 2011 .

[46]  C. Peres,et al.  The empty forest revisited , 2011, Annals of the New York Academy of Sciences.

[47]  Christopher O. Justice,et al.  Land remote sensing and global environmental change : NASA's earth observing system and the science of ASTER and MODIS , 2011 .

[48]  Arnab Kundu,et al.  Monitoring desertification risk through climate change and human interference using Remote sensing and GIS techniques , 2011 .

[49]  M. AboelGhar,et al.  Retrieving leaf area index from SPOT4 satellite data , 2010 .

[50]  Clement Atzberger,et al.  Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat , 2010 .

[51]  Mehrez Zribi,et al.  Analysis of Local Variation of Soil Surface Parameters With TerraSAR-X Radar Data Over Bare Agricultural Fields , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[52]  A. Ono,et al.  DEVELOPMENT OF NEW VEGETATION INDEXES, SHADOW INDEX (SI) AND WATER STRESS TREND (WST) , 2010 .

[53]  Yanhong Tang,et al.  Changes in topsoil carbon stock in the Tibetan grasslands between the 1980s and 2004 , 2009 .

[54]  F. Jay Breidt,et al.  Predicting Enhanced Vegetation Index (EVI) curves for ecosystem modeling applications , 2009 .

[55]  R. Lefroy,et al.  Spatial identification by satellite imagery of the crop–fallow rotation cycle in northern Laos , 2009 .

[56]  Valentinas Podvezko,et al.  Application of AHP technique , 2009 .

[57]  G. D’Urso,et al.  Experimental assessment of the Sentinel-2 band setting for RTM-based LAI retrieval of sugar beet and maize , 2009 .

[58]  S. Ganguly,et al.  Author ' s personal copy Generating vegetation leaf area index Earth system data record from multiple sensors . Part 2 : Implementation , analysis and validation , 2008 .

[59]  Andrew T. Hudak,et al.  Discrete return lidar-based prediction of leaf area index in two conifer forests , 2008 .

[60]  A. Huete,et al.  Development of a two-band enhanced vegetation index without a blue band , 2008 .

[61]  N. Coops,et al.  Estimation of insect infestation dynamics using a temporal sequence of Landsat data , 2008 .

[62]  Clement Atzberger,et al.  Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[63]  A. Skidmore,et al.  Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland , 2008 .

[64]  Keisuke Hanaki,et al.  Application of analytical hierarchy process to analyze stakeholders preferences for municipal solid waste management plans, Boston, USA. , 2008 .

[65]  José M. Paruelo,et al.  Grazing effect on NDVI across an aridity gradient in Argentina , 2008 .

[66]  Gérard Dedieu,et al.  Estimation of leaf area and clumping indexes of crops with hemispherical photographs , 2008 .

[67]  J. Moreno,et al.  Seasonal variations of leaf area index of agricultural fields retrieved from Landsat data , 2008 .

[68]  M. Vohland,et al.  Estimating structural and biochemical parameters for grassland from spectroradiometer data by radiative transfer modelling (PROSPECT+SAIL) , 2008 .

[69]  P. Gowda,et al.  COMPARING ARTIFICIAL NEURLA NETWORK WITH LEAST SQUARE REGRESSION TECHNIQUES FOR LAI RETRIEVAL FROM REMTOE SENSING DATA , 2008 .

[70]  Z. azizia,et al.  FOREST CANOPY DENSITY ESTIMATING , USING SATELLITE IMAGES , 2008 .

[71]  Bunkei Matsushita,et al.  Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-Density Cypress Forest , 2007, Sensors.

[72]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

[73]  P. Robbins,et al.  Enforcement Authority and Vegetation Change at Kumbhalgarh Wildlife Sanctuary, Rajasthan, India , 2007, Environmental management.

[74]  Pamela L. Nagler,et al.  Relationship between evapotranspiration and precipitation pulses in a semiarid rangeland estimated by moisture flux towers and MODIS vegetation indices , 2007 .

[75]  D. Diner,et al.  Analysis of the MISR LAI/FPAR product for spatial and temporal coverage, accuracy and consistency , 2007 .

[76]  James P. Verdin,et al.  A five‐year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States , 2007 .

[77]  John F. Mustard,et al.  A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data , 2007 .

[78]  I. Vasiliniuc.  Book review of „Remote Sensing and Image Interpretation”, 5th edition (Lillesand M. Thomas, Kiefer W. Ralph, Chipman W. Jonathan) , 2007 .

[79]  Jason P. Evans,et al.  Classifying rangeland vegetation type and coverage using a Fourier component based similarity measure , 2006 .

[80]  Xiaoling Chen,et al.  Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes , 2006 .

[81]  Shefali Agrawal,et al.  Vegetation cover mapping in India using multi-temporal IRS Wide Field Sensor (WiFS) data , 2006 .

[82]  Jan Pisek,et al.  Algorithm for global leaf area index retrieval using satellite imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[83]  Jan Verbesselt,et al.  Evaluating satellite and climate data-derived indices as fire risk indicators in savanna ecosystems , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[84]  Siamak Khorram,et al.  Regional Scale Land Cover Characterization Using MODIS-NDVI 250 m Multi-Temporal Imagery: A Phenology-Based Approach , 2006 .

[85]  Yuhong He,et al.  Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices , 2006 .

[86]  E. Hunt,et al.  Comparison of Stocking Rates From Remote Sensing and Geospatial Data , 2006 .

[87]  Benjamin F. Zaitchik,et al.  Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity , 2005 .

[88]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[89]  N. Pettorelli,et al.  Using the satellite-derived NDVI to assess ecological responses to environmental change. , 2005, Trends in ecology & evolution.

[90]  Xiaoling Chen,et al.  Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+ , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[91]  Bruce K. Wylie,et al.  Integration of CO 2 flux and remotely-sensed data for primary production and ecosystem respiration analyses in the Northern Great Plains: potential for quantitative spatial extrapolation , 2005 .

[92]  S. Reutebuch,et al.  Estimating forest canopy fuel parameters using LIDAR data , 2005 .

[93]  Pamela L. Nagler,et al.  Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data , 2005 .

[94]  W. Shi,et al.  Quantitative Analysis of Shadow Effects in High-resolution Images of Urban Areas , 2005 .

[95]  Alex Fortescue,et al.  Remote sensing and change detection in rangelands , 2004 .

[96]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[97]  Emilio Chuvieco,et al.  Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests , 2004 .

[98]  Kevin P. Price,et al.  Relations between NDVI and tree productivity in the central Great Plains , 2004 .

[99]  W. Cohen,et al.  Hyperspectral versus multispectral data for estimating leaf area index in four different biomes , 2004 .

[100]  Luca Ridolfi,et al.  The Effect of Vegetation Density on Canopy Sub-Layer Turbulence , 2004 .

[101]  Rasmus Fensholt,et al.  Earth observation of vegetation status in the Sahelian and Sudanian West Africa: comparison of Terra MODIS and NOAA AVHRR satellite data , 2004 .

[102]  Roland Geerken,et al.  Assessment of rangeland degradation and development of a strategy for rehabilitation , 2004 .

[103]  Jiyuan Liu,et al.  Land cover characterization of Temperate East Asia using multi-temporal VEGETATION sensor data , 2004 .

[104]  A J Morrissey,et al.  Waste management models and their application to sustainable waste management. , 2004, Waste management.

[105]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[106]  Ronald J. Hall,et al.  Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program , 2003 .

[107]  G. Asner,et al.  Grazing gradient detection with airborne imaging spectroscopy on a semi-arid rangeland , 2003 .

[108]  J. Wellens.  Rangeland vegetation dynamics and moisture availability in Tunisia: an investigation using satellite and meteorological data , 2003 .

[109]  Franklin César Flores,et al.  Automatic shadow segmentation in aerial color images , 2003, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003).

[110]  M. Qureshi,et al.  Application of the analytic hierarchy process to riparian revegetation policy options , 2003, Small-scale Forest Economics, Management and Policy.

[111]  L. Ji,et al.  Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices , 2003 .

[112]  J. C. Price.  Comparing MODIS and ETM+ data for regional and global land classification , 2003 .

[113]  J. Kerr,et al.  From space to species: ecological applications for remote sensing , 2003 .

[114]  S. Liang,et al.  Retrieving leaf area index using a genetic algorithm with a canopy radiative transfer model , 2003 .

[115]  Emilio A. Laca,et al.  Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem , 2003 .

[116]  W. Cohen,et al.  An improved strategy for regression of biophysical variables and Landsat ETM+ data. , 2003 .

[117]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[118]  T. Stewart,et al.  Evaluation of water supply augmentation and water demand management options for the City of Cape Town , 2003 .

[119]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[120]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[121]  Jiyuan Liu,et al.  Characterization of forest types in Northeastern China, using multi-temporal SPOT-4 VEGETATION sensor data , 2002 .

[122]  S. Sader,et al.  Detection of forest harvest type using multiple dates of Landsat TM imagery , 2002 .

[123]  I. Sandholt,et al.  A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status , 2002 .

[124]  R. McMaster,et al.  A History of Twentieth-Century American Academic Cartography , 2002 .

[125]  Limin Yang,et al.  Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance , 2002 .

[126]  Yoshifumi Yasuoka,et al.  Simulated recovery of information in shadow areas on IKONOS image by combing ALS data , 2002 .

[127]  A. Huete,et al.  An error and sensitivity analysis of atmospheric resistant vegetation indices derived from dark target-based atmospheric correction , 2001 .

[128]  C. Tucker,et al.  Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999 , 2001 .

[129]  Tong Zhang,et al.  An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods , 2001, AI Mag..

[130]  I. Sandholt,et al.  Derivation of a dryness index from NOAA-AVHRR data for use in large-scale hydrological modelling , 2001 .

[131]  Wolter Arnberg,et al.  Assessment of vegetation indexes useful for browse (forage) prediction in semi-arid rangelands , 2001 .

[132]  Kevin P. Price,et al.  Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains , 2001 .

[133]  Compton J. Tucker,et al.  NDVI anomaly patterns over Africa during the 1997/98 ENSO warm event , 2001 .

[134]  Shefali Agarwal,et al.  Forest cover assessment in western Himalayas, Himachal Pradesh using IRS 1C/1D WiFS data , 2001 .

[135]  J. C. Winslow,et al.  Numerical Terradynamic Simulation Group 3-2001 Mapping Weekly Rangeland Vegetation Productivity Using MODIS Algorithms , 2018 .

[136]  J. Paruelo,et al.  Estimation of primary production of subhumid rangelands from remote sensing data , 2000 .

[137]  A. Huete,et al.  Optical-Biophysical Relationships of Vegetation Spectra without Background Contamination , 2000 .

[138]  Dennis J. Dunning,et al.  Multiattribute utility analysis for addressing Section 316(b) of the Clean Water Act , 2000 .

[139]  Marshall Flug,et al.  Multicriteria decision analysis applied to Glen Canyon Dam , 2000 .

[140]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[141]  F. Kogan,et al.  Monitoring weather impact and crop yield from NOAA AVHRR data in Argentina , 2000 .

[142]  Chandra Shekhar Jha,et al.  Deforestation and land use changes in Western Ghats, India , 2000 .

[143]  Timo Tokola,et al.  Gain to be achieved from stand delineation in LANDSAT TM image-based estimates of stand volume , 1999 .

[144]  Karin S. Fassnacht,et al.  Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites , 1999 .

[145]  A. Huete,et al.  MODIS Vegetation Index Compositing Approach: A Prototype with AVHRR Data , 1999 .

[146]  W. D. Plessis,et al.  Linear regression relationships between NDVI, vegetation and rainfall in Etosha National Park, Namibia , 1999 .

[147]  Jessica A. Faust,et al.  Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) , 1998 .

[148]  P. Bicheron,et al.  LAI and fAPAR mapping at global scale by model inversion against spaceborne POLDER data , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[149]  D. Fuller,et al.  Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987-1993 , 1998 .

[150]  R. M. Hoffer,et al.  Biomass estimation on grazed and ungrazed rangelands using spectral indices , 1998 .

[151]  T. Carlson,et al.  On the relation between NDVI, fractional vegetation cover, and leaf area index , 1997 .

[152]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .

[153]  J. Randerson,et al.  Interannual variation in global‐scale net primary production: Testing model estimates , 1997 .

[154]  A. Huete,et al.  The use of vegetation indices in forested regions: issues of linearity and saturation , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.

[155]  Saul I. Gass,et al.  Encyclopedia of Operations Research and Management Science , 1997 .

[156]  J. Paruelo,et al.  ANPP ESTIMATES FROM NDVI FOR THE CENTRAL GRASSLAND REGION OF THE UNITED STATES , 1997 .

[157]  F. Kogan,et al.  Global Drought Watch from Space , 1997 .

[158]  Ramakrishna R. Nemani,et al.  LAND COVER CHARACTERIZATION USING MULTITEMPORAL RED, NEAR‐IR, AND THERMAL‐IR DATA FROM NOAA/AVHRR , 1997 .

[159]  A. Rikimaru,et al.  Development of Forest Canopy Density Mapping and Monitoring Model using Indices of Vegetation, Bare soil and Shadow , 1997 .

[160]  S. Goetz.  Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site , 1997 .

[161]  Thomas R. Loveland,et al.  The IGBP-DIS global 1 km land cover data set , 1997 .

[162]  T. Clarke.  An Empirical Approach for Detecting Crop Water Stress Using Multispectral Airborne Sensors , 1997 .

[163]  Qinghan Xiao,et al.  Land cover classification with AVHRR multichannel composites in northern environments , 1996 .

[164]  Karl Fred Huemmrich,et al.  Effects of shadows on vegetation indices , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.

[165]  Eric F. Lambin,et al.  The surface temperature-vegetation index space for land cover and land-cover change analysis , 1996 .

[166]  A. Huete,et al.  A review of vegetation indices , 1995 .

[167]  T. Hobbs,et al.  The use of NOAA-AVHRR NDVI data to assess herbage production in the arid rangelands of Central Australia , 1995 .

[168]  C. Field,et al.  Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types , 1995 .

[169]  F. Kogan.  Application of vegetation index and brightness temperature for drought detection , 1995 .

[170]  Fabio Maselli,et al.  Estimation of forest parameters through fuzzy classification of TM data , 1995, IEEE Trans. Geosci. Remote. Sens..

[171]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[172]  V. Judson Harward,et al.  Mapping forest vegetation using landsat TM imagery and a canopy reflectance model , 1994 .

[173]  J. Townshend,et al.  NDVI-derived land cover classifications at a global scale , 1994 .

[174]  S. Nicholson,et al.  The influence of soil type on the relationships between NDVI, rainfall, and soil moisture in semiarid Botswana. I. NDVI response to rainfall , 1994 .

[175]  A. Vidal,et al.  Evaluation of a temporal fire risk index in mediterranean forests from NOAA thermal IR , 1994 .

[176]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[177]  R. Myneni,et al.  On the relationship between FAPAR and NDVI , 1994 .

[178]  A. Huete,et al.  A Modified Soil Adjusted Vegetation Index , 1994 .

[179]  M. S. Moran,et al.  Evaluation of hydrologic parameters in a semiarid rangeland using remotely sensed spectral data , 1994 .

[180]  T. Carlson,et al.  A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover , 1994 .

[181]  A. Bégué.  Leaf area index, intercepted photosynthetically active radiation, and spectral vegetation indices: A sensitivity analysis for regular-clumped canopies , 1993 .

[182]  R. H. Haas,et al.  Evaluating Landsat Thematic Mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands , 1993 .

[183]  J. Peñuelas,et al.  The reflectance at the 950–970 nm region as an indicator of plant water status , 1993 .

[184]  S. Running,et al.  Developing Satellite-derived Estimates of Surface Moisture Status , 1993 .

[185]  M. Fiorella,et al.  Determining successional stage of temperate coniferous forests with Landsat satellite data , 1993 .

[186]  Linda Cyr.  Apport des indices de végétation pour l'évaluation de la couverture du sol en vue d'une modélisation spatiale de l'érosion , 1993 .

[187]  P. Sellers.  Remote sensing of the land surface for studies of global change , 1993 .

[188]  William J. Ripple,et al.  Analysis of conifer forest regeneration using Landsat Thematic Mapper data , 1993 .

[189]  P. G. Diwakar,et al.  Tropical forest typo mapping and monitoring using remote sensing , 1991 .

[190]  Bhaskar J. Choudhury,et al.  Analysis of normalized difference and surface temperature observations over southeastern Australia , 1991 .

[191]  J. R. Jensen,et al.  The measurement of mangrove characteristics in southwest Florida using spot multispectral data , 1991 .

[192]  F. Baret,et al.  Potentials and limits of vegetation indices for LAI and APAR assessment , 1991 .

[193]  C. Justice,et al.  Global land cover classification by remote sensing: present capabilities and future possibilities , 1991 .

[194]  B. H. Briz-Kishore,et al.  A methodology for locating potential aquifers in a typical semi-arid region in India using resistivity and hydrogeologic parameters , 1991 .

[195]  A. J. Richardson,et al.  Vegetation indices in crop assessments , 1991 .

[196]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[197]  R. Wasson,et al.  Vegetational and seasonal climatic changes since the last full glacial in the Thar Desert , 1990 .

[198]  Thomas L. Saaty,et al.  How to Make a Decision: The Analytic Hierarchy Process , 1990 .

[199]  F. Baret,et al.  A ratio vegetation index adjusted for soil brightness , 1990 .

[200]  B. Rock,et al.  Detection of changes in leaf water content using Near- and Middle-Infrared reflectances , 1989 .

[201]  S. Running,et al.  Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data , 1989 .

[202]  B. Rock,et al.  Assessing forest damage in high-elevation coniferous forests in vermont and new Hampshire using thematic mapper data , 1988 .

[203]  C. Tucker,et al.  Satellite remote sensing of primary production , 1986 .

[204]  F. J. Ahern,et al.  Forestry information content of Thematic Mapper data , 1986 .

[205]  R. J. Kauth,et al.  The Tasseled Cap de-mystified. [transformations of MSS and TM data] , 1986 .

[206]  R. J. Kauth,et al.  The Tasseled Cap de-mystified , 1986 .

[207]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[208]  T. Saaty.  Analytic Hierarchy Process , 2005 .

[209]  R. Jackson,et al.  Spectral response of a plant canopy with different soil backgrounds , 1985 .

[210]  Richard H. Waring,et al.  Forest Ecosystems: Analysis at Multiple Scales , 1985 .

[211]  P. D. Jong.  A statistical approach to Saaty's scaling method for priorities , 1984 .

[212]  V. Klemas,et al.  Growth response and spectral characteristics of a short Spartina alterniflora salt marsh irrigated with freshwater and sewage effluent , 1983 .

[213]  S. Idso,et al.  Canopy temperature as a crop water stress indicator , 1981 .

[214]  C. Tucker.  Remote sensing of leaf water content in the near infrared , 1980 .

[215]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[216]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[217]  R. Kauth,et al.  The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat , 1976 .

[218]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[219]  C. Jordan.  Derivation of leaf-area index from quality of light on the forest floor , 1969 .

[220]  G. Jenks.  The Data Model Concept in Statistical Mapping , 1967 .

[221]  Topographical Maps , 1931, Science.