TVDI在冬小麦春季干旱监测中的应用

Remote Sensing Technology and Application(2011)

Cited 28|Views23
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Abstract
应用冬小麦春季生长期的NOAA/AVHRR资料,反演归一化植被指数(NDVI)、土壤调整植被指数(SAVI)和下垫面温度(Ts),分析了植被指数和下垫面温度空间特征,采用温度植被旱情指数(TVDI),研究了河北省2005年3~5月的冬小麦旱情状况。结果表明:基于SAVI的温度植被旱情指数与土壤表层相对湿度的相关性好于基于NDVI的温度植被旱情指数。通过与气象站土壤水分观测资料进行相关性分析,表明温度植被旱情指数与10 cm土壤相对湿度关系最好,20 cm次之,50 cm较差。因此,基于SAVI的温度植被旱情指数更适于监测冬小麦春季的旱情。
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Key words
Winter wheat,Normalized difference vegetation index(NDVI),Soil-adjusted vegetation index(SAVI),Remote sensing,Temperature vegetation dryness index
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