NDLI: Mapping Soil Moisture Using RADARSAT-2 Data and Local Autocorrelation Statistics

Content Provider	IEEE Xplore Digital Library
Author	Merzouki, A. McNairn, H. Pacheco, A.
Copyright Year	2008
Abstract	The purpose of this study is to evaluate the capability of surface radar backscatter models to estimate soil moisture over agricultural fields from fully polarimetric RADARSAT-2 C-band synthetic aperture radar (SAR) responses. For validation purposes, ground measurements over 44 sampling sites in eastern Ontario, Canada were carried out in the spring of 2008 simultaneously with satellite data acquisitions. Soil moisture retrieval was accomplished using two semi-empirical scattering models (Dubois and Oh) and the SAR image backscatter. Discrepancies between measured radar backscatter coefficients and those predicted by the models were previously reported, requiring correction factors to reduce biases associated with these semi-empirical approaches. Soil moisture was estimated by explicitly solving the two backscatter equations of the Dubois model, and using a look-up table (LUT) approach applied to the Oh model. Results showed that the Oh model in a cross-polarization (HH-HV) and Dubois in a co-polarization (HH-VV) inversion scheme provide the best estimates. These model configurations were implemented to produce multi-date soil moisture maps for the eastern Ontario site. To expand the range of validity of these soil moisture estimates, the maps produced by the Dubois and Oh models were uniquely combined. These estimates of absolute soil moisture were then used to derive spatial patterns of near-surface moisture content using the Getis statistic. The Getis statistic maps provide meaningful spatial information, demonstrating the potential of combining the Getis statistic and RADARSAT-2 data in predicting soil moisture conditions.
Starting Page	128
Ending Page	137
Page Count	10
File Size	1787985
File Format	PDF
ISSN	19391404
Volume Number	4
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Soil moisture Backscatter Soil measurements Pixel Radar Correlation spatial autocorrelation Backscatter models Getis RADARSAT-2 soil moisture mapping
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Computers in Earth Sciences

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Monitoring Soil Moisture to Support Risk Reduction for the Agriculture Sector Using RADARSAT-2

RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring

Surface parameters estimation using Radarsat-2 polarimetric data over wheat covered area

Speckle Noise and Soil Heterogeneities as Error Sources in a Bayesian Soil Moisture Retrieval Scheme for SAR Data

Joining a Discrete Radiative Transfer Model and a Kernel Retrieval Algorithm for Soil Moisture Estimation From SAR Data

On Mapping Surface Moisture Content of Japanese Andisol Using GPR

Potential for High Resolution Systematic Global Surface Soil Moisture Retrieval via Change Detection Using Sentinel-1

Coherent Model of L-Band Radar Scattering by Soybean Plants: Model Development, Evaluation, and Retrieval

L-Band Radar Soil Moisture Retrieval Without Ancillary Information

Mapping Soil Moisture Using RADARSAT-2 Data and Local Autocorrelation Statistics

Similar Documents

Monitoring Soil Moisture to Support Risk Reduction for the Agriculture Sector Using RADARSAT-2

RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring

Surface parameters estimation using Radarsat-2 polarimetric data over wheat covered area

Speckle Noise and Soil Heterogeneities as Error Sources in a Bayesian Soil Moisture Retrieval Scheme for SAR Data

Joining a Discrete Radiative Transfer Model and a Kernel Retrieval Algorithm for Soil Moisture Estimation From SAR Data

On Mapping Surface Moisture Content of Japanese Andisol Using GPR

Potential for High Resolution Systematic Global Surface Soil Moisture Retrieval via Change Detection Using Sentinel-1

Coherent Model of L-Band Radar Scattering by Soybean Plants: Model Development, Evaluation, and Retrieval

L-Band Radar Soil Moisture Retrieval Without Ancillary Information

Mapping Soil Moisture Using RADARSAT-2 Data and Local Autocorrelation Statistics