Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan

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• 作者：de Beurs ; Kirsten M. ; Henebry ; Geoffrey M.
• 关键词：Landscape dynamics ; Spatio-temporal analysis ; LCLUC ; Growing degree-day models ; Pathfinder AVHRR Land (PAL) NDVI
• 刊名：Remote Sensing of Environment
• 出版年：2004
• 出版时间：February 29, 2004
• 年：2004
• 卷：89
• 期：4
• 页码：497-509
• 全文大小：342 K

文摘

Kazakhstan is the second largest country to emerge from the collapse of the Soviet Union. Consequent to the abrupt institutional changes surrounding the disintegration of the Soviet Union in the early 1990s, Kazakhstan has reportedly undergone extensive land cover/land use change. Were the institutional changes sufficiently great to affect land surface phenology at spatial resolutions and extents relevant to mesoscale meteorological models? To explore this question, we used the NDVI time series (1985–1988 and 1995–1999) from the Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset, which consists of 10 days maximum NDVI composites at a spatial resolution of 8 km. Daily minimum and maximum temperatures were extracted from the NCEP Reanalysis Project and 10 days composites of accumulated growing degree-days (AGDD) were produced. We selected for intensive study seven agricultural areas ranging from regions with rain-fed spring wheat cultivation in the north to regions of irrigated cotton and rice in the south. We applied three distinct but complementary statistical analyses: (1) nonparametric testing of sample distributions; (2) simple time series analysis to evaluate trends and seasonality; and (3) simple regression models describing NDVI as a quadratic function of AGDD.