摘要
为了有效解决大尺度区域土壤水分时、空间变化监测的问题,在总结了被动微波遥感反演土壤湿度规律的基础上,基于先进的AMSR星载被动微波遥感数据,提出了利用双谱模型计算土壤表面发射率的计算机算法。首先需要由双站散射系数计算反射率和发射率,然后应用人工神经网络反演土壤湿度,实现了在随机粗糙面状况下基于被动微波遥感的土壤表面水分反演,并在实验区进行了成功的应用。
In order to effectively solve the problem of emonitoring temporal-spatial changes of soil moisture in the large-scale region, a method was proposed, which used BSM model to calculate soil surface emissivity based on the conclusion of soil moisture inversion by passive microwave remote sensing and AMSR-E microwave remote sensing data. The reflectivity and emissivity were calculated with bistatic scattering coefficient. The soil moisture was inversed by using artificial neural network models. Then the inversion of soil surface moisture was performed based on passive microwave remote sensing under the condition of random rough surface, which had been applied successful in experimental area.
出处
《测绘科学》
CSCD
北大核心
2009年第3期34-36,共3页
Science of Surveying and Mapping
关键词
计算机算法
微波遥感
土壤湿度
BSM模型
人工神经网络
computer algorithm
microwave remote sensing
soil moisture
BSM model
artificial neural network
