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Use of Geographically Weighted Regression Model for Exploring Spatial Patterns and Local Factors Behind NDVI-Precipitation Correlation

contributor authorLingjun Kang
contributor authorLiping Di
contributor authorMeixia Deng
contributor authorYuanzheng Shao
contributor authorGenong Yu
contributor authorShrestha, Ranjay
date accessioned2020-03-13T00:26:35Z
date available2020-03-13T00:26:35Z
date issued2014
identifier issn1939-1404
identifier other6930718.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1146927?show=full
formatgeneral
languageEnglish
publisherIEEE
titleUse of Geographically Weighted Regression Model for Exploring Spatial Patterns and Local Factors Behind NDVI-Precipitation Correlation
typeJournal Paper
contenttypeMetadata Only
identifier padid8329834
subject keywordsatmospheric precipitation
subject keywordsclimatology
subject keywordsland use
subject keywordspermeability
subject keywordssoil
subject keywordsvegetation
subject keywordsNDVI change increasing unit rate
subject keywordsNDVI-precipitation correlation local factor
subject keywordsNDVI-precipitation correlation spatial pattern
subject keywordsUS central great plain area
subject keywordsagricultural management
subject keywordsclimatic factor
subject keywordsfallow-idle land
subject keywordsgeographically weighted regression model
subject keywordsglobal regression model
subject keywordsgrassland
subject keywordsland use type
subject keywordslower residual proportion
subject keywordsnormalized difference index-precipitation correlation
subject keywordsprecipitation crop response
identifier doi10.1109/JSTARS.2014.2361128
journal titleSelected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
journal volume7
journal issue11
filesize1331778
citations2


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