Arid
DOI10.1007/s12524-016-0626-x
An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data
Tao, Liangliang1,2; Li, Jing1,2; Chen, Xi1,2; Cai, Qingkong3; Zhang, Yunfei1,2
通讯作者Li, Jing
来源期刊JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
ISSN0255-660X
EISSN0974-3006
出版年2017
卷号45期号:4页码:621-629
英文摘要

This study investigated an appropriate method for soil moisture retrieval from radar images and coincident ground measurements acquired over bare soil and sparsely vegetated regions. The adopted approach based on a single scattering integral equation method (IEM) was developed to establish the relationship between backscatter coefficient and surface soil parameters including volumetric soil moisture content and surface roughness. The performance of IEM in 0-7.6 cm is better than that in 0-20 cm. Moreover, IEM can simulate correctly the backscatter coefficients only for the root mean square (RMS) height s < 1.5 cm at C-band and s < 2.5 cm at L-band by using an exponential correlation function and for s > 1.5 cm at C-band and s > 2.5 cm at L-band by using Gaussian function. However, due to the difficulties involved in the parameterization of soil surface roughness, the estimated accuracy is not satisfactory for the inversion of IEM. This paper used a combined roughness parameter and Fresnel reflection coefficient to develop an empirical model. Simulations were performed to support experimental results and to highlight soil moisture content and surface roughness effects in different polarizations. Results showed that a good agreement was found between the IEM simulations and the SAR measurements over a wide range of soil moisture and surface roughness characteristics. The model had a significant operational advantage in soil moisture retrieval. The correlation coefficients were 77.03 % at L-band and 81.45 % at C-band with the RMSEs of 0.515 and 0.4996 dB, respectively. Additionally, this work offered insight into the required application accuracy of soil moisture retrieval at a large area of arid regions.


英文关键词Soil moisture SAR IEM Autocorrelation function Backscatter coefficient Surface roughness
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000406359500006
WOS关键词RADAR BACKSCATTER MODELS ; SURFACE-ROUGHNESS ; EMPIRICAL-MODEL ; PARAMETERIZATION ; SCATTERING ; PROFILES ; IEM
WOS类目Environmental Sciences ; Remote Sensing
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing
来源机构北京师范大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/200849
作者单位1.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China;
2.Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Beijing 100875, Peoples R China;
3.Henan Inst Engn, Inst Civil Engn, Zhengzhou 451191, Henan, Peoples R China
推荐引用方式
GB/T 7714
Tao, Liangliang,Li, Jing,Chen, Xi,et al. An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data[J]. 北京师范大学,2017,45(4):621-629.
APA Tao, Liangliang,Li, Jing,Chen, Xi,Cai, Qingkong,&Zhang, Yunfei.(2017).An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data.JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,45(4),621-629.
MLA Tao, Liangliang,et al."An Effective Model to Retrieve Soil Moisture from L- and C-Band SAR Data".JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 45.4(2017):621-629.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Tao, Liangliang]的文章
[Li, Jing]的文章
[Chen, Xi]的文章
百度学术
百度学术中相似的文章
[Tao, Liangliang]的文章
[Li, Jing]的文章
[Chen, Xi]的文章
必应学术
必应学术中相似的文章
[Tao, Liangliang]的文章
[Li, Jing]的文章
[Chen, Xi]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。