摘要
土壤水分是作物生长发育的基本条件,同时也是旱情监测的重要指标。以彰武县为研究区域,基于影像的Artist算法和二维特征空间模型算法,进行了环境减灾卫星数据的地表温度(LST)反演,提取了归一化植被指数(NDVI)和修正的土壤调节植被指数(MSAVI),并构建二维特征空间,提取干、湿边方程,分析了地表实测土壤水分和植被指数的线性关系。结果表明,鉴于彰武地区土质的多样化,修正的土壤调节植被指数可提高土壤墒情的反演精度,相关系数为R2=0.852,标准差为2.064,协方差为3.139,相关性较好。
Soil moisture is the basic condition for crop growth, also an important index of drought monitoring. Taking Zhangwu County as the study area, based on the image of the Artist algorithm and two dimensional feature space model algorithm, this paper carried out environmental disaster mitigation satellite data of land surface temperature （LST） inversion, extracted the normalized difference vegetation index （NDVI） and modified soil regulate vegetation index （MSAVI）, built two dimensional feature space, ex- tracting dry and wet side equation , analyzed the linear relationship between the measured surface soil moisture and vegetation index. The results show that the given the soil diversity in Zhangwu region, modified soil vegetation index adjustment can improve the soil moisture inversion accuracy, the correlation coefficient is R2 =0. 852, the standard deviation is 2.064, and the eovariance is 3. 139.
出处
《节水灌溉》
北大核心
2014年第7期16-18,21,共4页
Water Saving Irrigation
基金
辽宁省科学事业公益研究基金项目(2011005002)
关键词
土壤水分
地表温度
植被指数
特征空间
soil moisture
surface temperature
vegetation index
feature space
