Multi-source data-based method for retrieval of soil moisture in grassland

被引：2

作者：

Huang, Pingping ^{[1
,2
]}

Su, Ritu ^{[1
,2
]}

Xu, Wei ^{[1
,2
]}

Tan, Weixian ^{[1
,2
]}

Yang, Wen ^{[3
]}

机构：

[1] Inner Mongolia Univ Technol, Coll Informat Engn, Hohhot 010051, Peoples R China

[2] Inner Mongolia Key Lab Radar Technol & Applicat, Hohhot 010051, Peoples R China

[3] Wuhan Univ, Sch Elect Informat, Wuhan 430072, Hubei, Peoples R China

来源：

JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 19期

基金：

中国国家自然科学基金;

关键词：

radar imaging; backscatter; remote sensing by radar; synthetic aperture radar; moisture; vegetation; soil moisture; multisource data-based method; synthetic aperture radar data; optical data; SAR data; grassland area; retrieval results;

D O I：

10.1049/joe.2019.0259

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Taking into account the respective advantages of synthetic aperture radar (SAR) data and optical data in obtaining object information, this article presents a method for retrieval of soil moisture in grassland based on multi-source data (SAR data, optical data and measured data). First of all, optical data is used to classify the grassland area, and then the SAR data is used to obtain the backscattering coefficient of the grassland area. Finally, the soil moisture under the vegetation cover is obtained through the water-cloud model and the microwave backscatter model. The soil moisture in grassland is retrieved and the retrieval results are compared and validated using measured data. The results showed that the suggested method has better classification precision for complex terrain with densely overlapping scattering mechanisms. This method also uses the measured data to correct the soil moisture, which greatly improves the precision of the results.

引用

页码：5717 / 5721

页数：5