摘要
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10cm土壤相对湿度关系最好，20cm次之，50cm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。
Droughts hazard occurs frequently in nature and has a great impact on agriculture. Timely monitoring and assessment of drought conditions is critical to mitigate its effects. Using NOAA/AVHRR satellite data,we derived the normalized difference vegetation index （NDVI）, soil-adjusted vegetation index （SAVI）,land surface temperature （LST） and analyzed the spatial characteristics of vegetation indices and land surface temperature. The temperature vegetation dryness index （TVDI） was used to monitor the winter wheat drought conditions from March to May of 2005 in the middle-south part of Hebei Province. The results showed that the correlation of soil moisture with TVDI based on SAVI was better than that based on NDVI. The analysis of TVDI and soil moisture data from weather stations＇ measurement demonstrated that a good correlation existed between TVDI and relative humidity of soil at 10cm and 20cm. Therefore,TVDI is a better indicator for operational drought monitoring.
出处
《遥感技术与应用》
CSCD
2008年第2期161-165,I0001,共6页
Remote Sensing Technology and Application
基金
“十五”国家科技攻关项目(2004BA509B14)
中国科学院知识创新项目(KZCX2-SW-317)
关键词
遥感
冬小麦
温度植被旱情指数
土壤调整植被指数
归一化植被指数
Remote sensing
Winter wheat
Temperature vegetation dryness index
Soil-adjusted vegetation index（SAVI）
Normalized difference vegetation index（NDVI）
