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Remote Sens. 2016, 8(12), 990; doi:10.3390/rs8120990

MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

1
Centre d’Etudes Spatiales de la BIOsphère (CESBIO), Université de Toulouse, CNES/CNRS/IRD/UPS, 31401 Toulouse CEDEX 9, France
2
Department of Civil Engineering, Indian Institute of Science, Bangalore 560 012, India
3
Aapah Innovations Private Limited, Hyderabad 500 032, India
4
Indian Space Research Organisation Headquarters (ISRO HQ.), Bangalore 560 231, India
*
Author to whom correspondence should be addressed.
Academic Editors: Prashant K. Srivastava, Nicolas Baghdadi and Prasad S. Thenkabail
Received: 2 October 2016 / Revised: 8 November 2016 / Accepted: 25 November 2016 / Published: 1 December 2016

Simple Summary

- A novel algorithm delivering high resolution soil moisture maps is developed by merging active (SAR) and passive microwave. - MAPSM is based on the concept ofWater Change Capacity. - A case study using MAPSM is presented by using the RADARSAT-2 and SMOS retrieved soil moisture data products over Berambadi watershed, Karnataka, India. - The algorithm parameters show scalability from the spatial resolution of 20 m to 2000 m.

Abstract

Availability of soil moisture observations at a high spatial and temporal resolution is a prerequisite for various hydrological, agricultural and meteorological applications. In the current study, a novel algorithm for merging soil moisture from active microwave (SAR) and passive microwave is presented. The MAPSM algorithm—Merge Active and Passive microwave Soil Moisture—uses a spatio-temporal approach based on the concept of the Water Change Capacity (WCC) which represents the amplitude and direction of change in the soil moisture at the fine spatial resolution. The algorithm is applied and validated during a period of 3 years spanning from 2010 to 2013 over the Berambadi watershed which is located in a semi-arid tropical region in the Karnataka state of south India. Passive microwave products are provided from ESA Level 2 soil moisture products derived from Soil Moisture and Ocean Salinity (SMOS) satellite (3 days temporal resolution and 40 km nominal spatial resolution). Active microwave are based on soil moisture retrievals from 30 images of RADARSAT-2 data (24 days temporal resolution and 20 m spatial resolution). The results show that MAPSM is able to provide a good estimate of soil moisture at a spatial resolution of 500 m with an RMSE of 0.025 m3/m3 and 0.069 m3/m3 when comparing it to soil moisture from RADARSAT-2 and in-situ measurements, respectively. The use of Sentinel-1 and RISAT products in MAPSM algorithm is envisioned over other areas where high number of revisits is available. This will need an update of the algorithm to take into account the angle sampling and resolution of Sentinel-1 and RISAT data. View Full-Text
Keywords: soil moisture; active; passive; microwave; downscaling; SMOS; RadarSat-2; India soil moisture; active; passive; microwave; downscaling; SMOS; RadarSat-2; India
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Tomer, S.K.; Al Bitar, A.; Sekhar, M.; Zribi, M.; Bandyopadhyay, S.; Kerr, Y. MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing. Remote Sens. 2016, 8, 990.

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