文章基本信息

标题：Evaluating trends in spatial relationship between noaa/avhrr-ndvi and rainfall as computed by geographically weighted regression: a case study from a dry region in the middle Kazachstan
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作者：Pavel A. Propastin ; Martin Kappas ; Nadiya R. Muratova 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2006
卷号：XXXVI Part 7
出版社：Copernicus Publications
摘要：The spatial relationship between vegetation patterns and rainfall as well as its trend over the period 1985-2000 in the shrubland, grassland, and cropland of the Middle Kazakhstan was investigated with Normalized Difference Vegetation Index (NDVI) images (1985-2000) derived from the Advanced Very High Resolution Radiometer (AVHRR), and rainfall data from weather stations. The growing season relationship was examined using a local regression technique known as geographically weighted regression (GWR). Regression models for each pixel and every analysis year (1985-2000) were calculated using this approach. Both the strength of relationship and the regression parameters showed high spatial and temporal non-stationarity. Spatial and temporal drifts of regression parameters and drifts of correlation coefficient were estimated and mapped. There are notable associations between patterns in land cover types and patterns in intercept and slope parameters in the study region. Residuals from the regressions for each pixel and every year were computed. Trend in residual values for each pixel over 16-year period was used to determine a temporal change of conditions of the vegetation cover through the time: pixels with a negative slope are considered to represent ground areas with decreasing amount of vegetation. Four types of trend behaviour were determined and analysed
关键词：NDVI; vegetation condition time-trend; geographically weighted regression (GWR) modelling