Derivation of Soil Moisture using Modified Dubois Model with field assisted surface roughness on RISAT-1 data

The study discusses the soil moisture estimation using dual polarimetric RISAT-1. The semi-empirical approach of Modified Dubois Model (MDM) derived by (SrinivasaRao 2013) is worked out using (σ ̊HH) and (σ ̊HV) for soil moisture estimation using dual polarimetric backscattering image. IRS LISS IV d...

Full description

Autores:
Palanisamy, Thanabalan
R, Vidhya
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/63555
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/63555
http://bdigital.unal.edu.co/64001/
Palabra clave:
55 Ciencias de la tierra / Earth sciences and geology
Soil moisture
surface roughness
Modified Dubois Model
Topp’s model
RISAT 1- SAR.
Húmedad del suelo
desigualdad de la superficie
Modelo Modificado de Dubois
Modelo de Topp
Radar de Apertura Sintética
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:The study discusses the soil moisture estimation using dual polarimetric RISAT-1. The semi-empirical approach of Modified Dubois Model (MDM) derived by (SrinivasaRao 2013) is worked out using (σ ̊HH) and (σ ̊HV) for soil moisture estimation using dual polarimetric backscattering image. IRS LISS IV data have been used to analyze the site suitability of different land use/cover types. The retrieval of backscattering coefficient values (σ ̊) from SAR is the common principle factor for soil moisture estimation. The surface roughness was measured in the selected sample location, for which the same backscattering values derived from the SAR is linearly correlated showing r2 = 0.93. The estimated surface roughness is used for retrieval of dielectric constant using MDM. The dielectric constant derived from MDM in combination with the Topps model proposed by (Topp 1980), is used to derive satellite-based soil moisture estimation. Linear regression analysis was performed, and the soil moisture derived from SAR are well correlated with the volumetric soil moisture showing the value of r2 = 0.63.