Paper Info
Title
Remote sensing retrieval of soil moisture using ENVISAT-ASAR images: A case study in suburban region of Peking, China
Abstract
Soil moisture is a highly variable component of soil, and plays an important role in materials and energy exchanges between earth and atmosphere. It is also the basic parameter of crop growing and crop yield forecast. With the features of observing large area synchronously, timely, and economically, remote sensing technique makes dynamic soil moisture monitoring possible. Soil moisture remote sensing monitoring has 30 years history and many researches have been done home and abroad in this field, including visible and infrared remote sensing based NDVI methods, hyper spectral remote sensing based algorithm, and microwave remote sensing orientated methodology and so on. Among these methods, microwave has great advantage in retrieval soil moisture because of the characteristics of all-weather, penetrability and not affected by the cloud. Through study people found that microwave is one of the most effective methods in retrieval soil moisture in various technologies. This paper summarizes the major microwave sensors and the principle of microwave remote sensing, and introduces the microwave model and soil moisture algorithm. Based on ENVISAT Radar data, with suburban farmland (wheat and corn as the main crop) of Peking as the study area, we established the microwave scattering characteristics database of local exposed surface. We used the selected model to simulate the response characteristics of backscattering coefficient influenced by a variety of parameters, such as soil moisture, surface roughness, incidence angle, polarization, etc. Then we got the updated inversion empirical model of the exposed surface, and evaluated the accuracy of model with the actually surveyed data in the field. This article makes certain contributions to the active microwave soil moisture retrieval methods study, and provide a viable model for water resources decision-making support to the Peking municipal government.
Year
DOI
Venue
2010
10.1109/GEOINFORMATICS.2010.5567495
Geoinformatics
Keywords
Field
DocType
hyper spectral remote sensing,remote sensing,visible remote sensing,crop growing,surface roughness,backscattering coefficient,decision making,dynamic soil moisture monitoring,china,incidence angle,microwave scattering characteristics database,decision-making support,polarization,envisat-asar images,crop yield forecast,microwave remote sensing,wheat,crops,clouds,soil moisture,cloud,geophysical image processing,soil moisture algorithm,envisat,envisat radar data,water resources,active microwave soil moisture retrieval methods,suburban farmland,microwave model,ndvi methods,vegetation mapping,soil,peking municipal government,local exposed surface,remote sensing technique,inversion empirical model,microwave sensors,infrared remote sensing,rough surfaces,empirical model,survey data,crop yield,backscatter,infrared
Radar,Microwave,Inversion (meteorology),Computer science,Remote sensing,Backscatter,Normalized Difference Vegetation Index,Water content,Water resources,Surface roughness
Conference
ISBN
Citations 
PageRank 
978-1-4244-7301-4
0
0.34
References 
Authors
8
4
Name
Order
Citations
PageRank
Xuhua Cai100.34
Huili Gong28829.37
Xiaojuan Li3122.38
Lin Zhu424.13