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Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas
In this paper, an evaluation strategy for two-candidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas...
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Published in: | IEEE journal of selected topics in applied earth observations and remote sensing 2015-08, Vol.8 (8), p.4094-4105 |
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creator | Grings, Francisco Bruscantini, Cintia A. Smucler, Ezequiel Carballo, Federico Dillon, Maria Eugenia Collini, Estela Angela Salvia, Mercedes Karszenbaum, Haydee |
description | In this paper, an evaluation strategy for two-candidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions. |
doi_str_mv | 10.1109/JSTARS.2015.2449237 |
format | article |
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In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.</description><identifier>ISSN: 1939-1404</identifier><identifier>EISSN: 2151-1535</identifier><identifier>DOI: 10.1109/JSTARS.2015.2449237</identifier><identifier>CODEN: IJSTHZ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Anomalies ; Correlation ; Cropland ; Estimation ; Freshwater ; Indexes ; Microwave measurement ; Monitors ; Pampas ; passive microwaves ; Pollution measurement ; Precipitation ; Salinity ; Satellites ; Soil moisture ; Strategy ; Temporal logic ; validation strategies</subject><ispartof>IEEE journal of selected topics in applied earth observations and remote sensing, 2015-08, Vol.8 (8), p.4094-4105</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Aug 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c478t-42bf9301d1209b7aeb00fa8afb607e183a4c2a8740a82bdf60a6d3a3ca8d9b0a3</citedby><cites>FETCH-LOGICAL-c478t-42bf9301d1209b7aeb00fa8afb607e183a4c2a8740a82bdf60a6d3a3ca8d9b0a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Grings, Francisco</creatorcontrib><creatorcontrib>Bruscantini, Cintia A.</creatorcontrib><creatorcontrib>Smucler, Ezequiel</creatorcontrib><creatorcontrib>Carballo, Federico</creatorcontrib><creatorcontrib>Dillon, Maria Eugenia</creatorcontrib><creatorcontrib>Collini, Estela Angela</creatorcontrib><creatorcontrib>Salvia, Mercedes</creatorcontrib><creatorcontrib>Karszenbaum, Haydee</creatorcontrib><title>Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas</title><title>IEEE journal of selected topics in applied earth observations and remote sensing</title><addtitle>JSTARS</addtitle><description>In this paper, an evaluation strategy for two-candidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.</description><subject>Anomalies</subject><subject>Correlation</subject><subject>Cropland</subject><subject>Estimation</subject><subject>Freshwater</subject><subject>Indexes</subject><subject>Microwave measurement</subject><subject>Monitors</subject><subject>Pampas</subject><subject>passive microwaves</subject><subject>Pollution measurement</subject><subject>Precipitation</subject><subject>Salinity</subject><subject>Satellites</subject><subject>Soil moisture</subject><subject>Strategy</subject><subject>Temporal logic</subject><subject>validation strategies</subject><issn>1939-1404</issn><issn>2151-1535</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkU1LxDAQhoMouH78Ai8FL166ZpK0SY7r4ieKYtVrmbapZOk2a5IK_nu7VDx48jTM8LzDDA8hJ0DnAFSf3xUvi-dizihkcyaEZlzukBmDDFLIeLZLZqC5TkFQsU8OQlhRmjOp-Yy8vWFnG4zW9UkRPUbzbk1IWueTYmy6zkaTXmAwTVI42yUPzoY4eJM8edcMdQzJ46fxycK_mz7afpzjeoPhiOy12AVz_FMPyevV5cvyJr1_vL5dLu7TWkgVU8GqVnMKDTCqK4mmorRFhW2VU2lAcRQ1QyUFRcWqps0p5g1HXqNqdEWRH5Kzae_Gu4_BhFiubajHs7E3bgglSJWDEjwT_0DzTGcAOYzo6R905Qbfj4-MFDAuOLDtQj5RtXcheNOWG2_X6L9KoOVWSzlpKbdayh8tY-pkSlljzG9CgmRMU_4NvwKJCw</recordid><startdate>20150801</startdate><enddate>20150801</enddate><creator>Grings, Francisco</creator><creator>Bruscantini, Cintia A.</creator><creator>Smucler, Ezequiel</creator><creator>Carballo, Federico</creator><creator>Dillon, Maria Eugenia</creator><creator>Collini, Estela Angela</creator><creator>Salvia, Mercedes</creator><creator>Karszenbaum, Haydee</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/JSTARS.2015.2449237</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Anomalies Correlation Cropland Estimation Freshwater Indexes Microwave measurement Monitors Pampas passive microwaves Pollution measurement Precipitation Salinity Satellites Soil moisture Strategy Temporal logic validation strategies |
title | Validation Strategies for Satellite-Based Soil Moisture Products Over Argentine Pampas |
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