基于多源遥感数据协同反演森林地表土壤水分研究

土壤水分在土壤监测中是一项重要的指标,对于农业生产、生态环境以及水资源管理有着重要的影响.随着遥感建模与反演理论的不断成熟,其逐渐成为分析土壤指标的重要技术与手段.因此,利用光学影像与雷达影像数据,以大兴安岭地区漠河市为研究区域,分别建立以Landsat 8为数据源的土壤水分反演模型和由Landsat 8影像数据与GF...

Multi-source Remote Sensing Data Cooperates to Retrieve Forest Surface Soil Moisture

Soil moisture is an important index in soil monitoring， which has an important impact on agricultural production， ecological environment and water resources management. With the remote sensing modeling and remote sensing inversion theory have gradually become important techniques and means to estimate soil indicators. Therefore， using the optical image data and radar image data， with Mohe City of Daxing'anling area as research area， to establish model of soil moisture inversion based on Landsat8 data and the model based on Landsat8 image data and high-resolution 3 remote sensing image data， the inversion results compared with the measured data analysis， and make evaluation on the model. The results showed that： （1） The surface temperature in the study area was inverted， and the TS-NDMI feature space was constructed by using surface temperature （Ts） and normalized difference humidity index NDMI. Combined with the measured data， it could be found that the inversion results of ts-NDMI feature space soil water inversion model were negatively correlated with the measured soil water content；（2） The soil moisture retrieval model based on GF-3 satellite data and Landsat 8 remote sensing data can get better retrieval results， and in areas with high vegetation coverage， the results obtained from this model are more accurate than those from a single optical data source， which provides a new way for the study of soil moisture in high vegetation coverage areas.