Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset
Accurate knowledge of soil moisture (SM) is crucial in hydrological, micrometeorological, and agricultural applications; however, the SM estimation is particularly challenging in agricultural regions due to high spatial variability and dynamic vegetation conditions. The need for information about SM...
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| creator | Monsivais-Huertero, Alejandro Constantino-Recillas, Daniel Enrique Hernandez-Sanchez, Juan Carlos Huerta-Batiz, Hector Ernesto Judge, Jasmeet Lopez-Estrada, Pedro Alejandro Jimenez-Escalona, Jose Carlos Arizmendi-Vasconcelos, Eduardo Garcia-Bernal, Marco Antonio Zambrano-Gallardo, Cira Francisca Lopez-Caloca, Alejandra Aurelia Zempoaltecatl-Ramirez, Enrique Rosa-Montero, Ivan Edmundo De la Villalobos-Martinez, Roberto Ivan Aparicio-Garcia, Ramon Sidonio Sanchez-Villanueva, Carlos Rodolfo Arizmendi-Vasconcelos, Leonardo Cotero-Manzo, Roberto Puebla-Lomas, Jaime Hugo Sauce-Rangel, Victor Manuel |
| description | Accurate knowledge of soil moisture (SM) is crucial in hydrological, micrometeorological, and agricultural applications; however, the SM estimation is particularly challenging in agricultural regions due to high spatial variability and dynamic vegetation conditions. The need for information about SM conditions is even more evident in developing countries with limited monitoring infrastructure. Satellite SM products are a useful tool as a proxy for SM conditions on the ground, but they need to be evaluated for specific regions. In this study, we assess the quality of the soil moisture active passive (SMAP) SM retrievals at 36, 9, and 3 km in an agricultural region in Central Mexico using in situ measurements during the Terrestrial Hydrology Experiments in Mexico 2018 and 2019. In addition, we provide insights into soil and vegetation parameters in the retrieval algorithms compared to those observed in the region. It was found that the SM spatial variability at the SMAP pixel grids was well represented by upscaled in situ SM measurements (SM_{\text{up}}) from five monitoring stations using the soil-weighted averaging and the Voronoï diagrams. Overall, the SMAP SM retrievals are highly correlated with SM_{\text{up}} at all scales, but they estimated wetter conditions and the average root-mean-square difference (RMSD) > 0.045 m^{3}/m^{3}. The lowest RMSD was obtained for the SM product at 36 km, while the highest RMSD was found for the SM product at 3 km. In addition, the single-channel algorithm using H-polarization provided the lowest RMSD for the products at 36 and 9 km. The main sources of uncertainty in the region may arise from the higher clay fraction used in the SMAP retrieval algorithm, by 13% compared to that observed, and a nonrepresentative characterization of land cover heterogeneity for vegetation water content estimation. The incorporation of in situ values into an SM retrieval algorithm resulted in differences < 0.04 m^{3}/m |
| doi_str_mv | 10.1109/JSTARS.2022.3165078 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2663646106</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9751405</ieee_id><doaj_id>oai_doaj_org_article_c2c2d4a5866e4c41ae9aa6a5c75e73e9</doaj_id><sourcerecordid>2663646106</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-3a6556e66c0a2d3d2506b068f12eb0a058d3a76d0f528e0985e32fe62453b7813</originalsourceid><addsrcrecordid>eNo9kU9r3DAQxUVooduknyAXQc_e6I8l27m5222TkG1DvIXcxKw83mpxrFSSITn3i9dbh8DAwJt5bxh-hJxztuScVRc3zba-b5aCCbGUXCtWlCdkIbjiGVdSvSMLXskq4znLP5CPMR4Y06Ko5IL8rWPEGB9xSNR39Efd1LTZ1He08a6nG-9iGgPSu-Db0aZIOx9ovQ_Ojv00gJ7e4975IVI30NUUcpQ2-Oysv6T1MBX0L9FF-gUittQPNP1Gur1aP2zWD_QrpElOZ-R9B33ET6_9lPz6tt6urrLbn9-vV_VtZnNWpkyCVkqj1paBaGUrFNM7psuOC9wxYKpsJRS6ZZ0SJbKqVChFh1rkSu6KkstTcj3nth4O5im4RwgvxoMz_wUf9gZCcrZHY4UVbQ6q1Bpzm3PACkCDsoXCQmI1ZX2es56C_zNiTObgxzB9G43QWupcc6anLTlv2eBjDNi9XeXMHMmZmZw5kjOv5CbX-exyiPjmqAo18VPyH0wIk3k</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2663646106</pqid></control><display><type>article</type><title>Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Monsivais-Huertero, Alejandro ; Constantino-Recillas, Daniel Enrique ; Hernandez-Sanchez, Juan Carlos ; Huerta-Batiz, Hector Ernesto ; Judge, Jasmeet ; Lopez-Estrada, Pedro Alejandro ; Jimenez-Escalona, Jose Carlos ; Arizmendi-Vasconcelos, Eduardo ; Garcia-Bernal, Marco Antonio ; Zambrano-Gallardo, Cira Francisca ; Lopez-Caloca, Alejandra Aurelia ; Zempoaltecatl-Ramirez, Enrique ; Rosa-Montero, Ivan Edmundo De la ; Villalobos-Martinez, Roberto Ivan ; Aparicio-Garcia, Ramon Sidonio ; Sanchez-Villanueva, Carlos Rodolfo ; Arizmendi-Vasconcelos, Leonardo ; Cotero-Manzo, Roberto ; Puebla-Lomas, Jaime Hugo ; Sauce-Rangel, Victor Manuel</creator><creatorcontrib>Monsivais-Huertero, Alejandro ; Constantino-Recillas, Daniel Enrique ; Hernandez-Sanchez, Juan Carlos ; Huerta-Batiz, Hector Ernesto ; Judge, Jasmeet ; Lopez-Estrada, Pedro Alejandro ; Jimenez-Escalona, Jose Carlos ; Arizmendi-Vasconcelos, Eduardo ; Garcia-Bernal, Marco Antonio ; Zambrano-Gallardo, Cira Francisca ; Lopez-Caloca, Alejandra Aurelia ; Zempoaltecatl-Ramirez, Enrique ; Rosa-Montero, Ivan Edmundo De la ; Villalobos-Martinez, Roberto Ivan ; Aparicio-Garcia, Ramon Sidonio ; Sanchez-Villanueva, Carlos Rodolfo ; Arizmendi-Vasconcelos, Leonardo ; Cotero-Manzo, Roberto ; Puebla-Lomas, Jaime Hugo ; Sauce-Rangel, Victor Manuel</creatorcontrib><description><![CDATA[Accurate knowledge of soil moisture (SM) is crucial in hydrological, micrometeorological, and agricultural applications; however, the SM estimation is particularly challenging in agricultural regions due to high spatial variability and dynamic vegetation conditions. The need for information about SM conditions is even more evident in developing countries with limited monitoring infrastructure. Satellite SM products are a useful tool as a proxy for SM conditions on the ground, but they need to be evaluated for specific regions. In this study, we assess the quality of the soil moisture active passive (SMAP) SM retrievals at 36, 9, and 3 km in an agricultural region in Central Mexico using in situ measurements during the Terrestrial Hydrology Experiments in Mexico 2018 and 2019. In addition, we provide insights into soil and vegetation parameters in the retrieval algorithms compared to those observed in the region. It was found that the SM spatial variability at the SMAP pixel grids was well represented by upscaled in situ SM measurements (SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula>) from five monitoring stations using the soil-weighted averaging and the Voronoï diagrams. Overall, the SMAP SM retrievals are highly correlated with SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula> at all scales, but they estimated wetter conditions and the average root-mean-square difference (RMSD) <inline-formula><tex-math notation="LaTeX">></tex-math></inline-formula> 0.045 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>. The lowest RMSD was obtained for the SM product at 36 km, while the highest RMSD was found for the SM product at 3 km. In addition, the single-channel algorithm using H-polarization provided the lowest RMSD for the products at 36 and 9 km. The main sources of uncertainty in the region may arise from the higher clay fraction used in the SMAP retrieval algorithm, by 13% compared to that observed, and a nonrepresentative characterization of land cover heterogeneity for vegetation water content estimation. The incorporation of in situ values into an SM retrieval algorithm resulted in differences <inline-formula><tex-math notation="LaTeX">< </tex-math></inline-formula>0.04 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula> between SM estimates and in situ SM for the complete growing season. Particularly, the use of in situ information helped in improving SM estimation when optimizing V- and dual-polarization brightness temperature observations.]]></description><identifier>ISSN: 1939-1404</identifier><identifier>EISSN: 2151-1535</identifier><identifier>DOI: 10.1109/JSTARS.2022.3165078</identifier><identifier>CODEN: IJSTHZ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Agricultural region ; Algorithms ; Brightness temperature ; Developing countries ; Growing season ; Heterogeneity ; Hydrology ; In situ measurement ; L-band passive microwave ; Land cover ; LDCs ; Mexico ; Moisture content ; Moisture effects ; Monitoring ; Monitoring systems ; multiscale soil moisture (SM) ; Polarization ; Quality assessment ; Retrieval ; Soil ; Soil measurements ; Soil moisture ; soil moisture active passive (SMAP) ; Spatial variations ; Surface radiation temperature ; terrestrial hydrology experiments in Mexico 2018 (THEXMEX-18) ; terrestrial hydrology experiments in Mexico 2019 (THEXMEX-19) ; Uncertainty ; Urban areas ; Vegetation ; Vegetation mapping ; Water content</subject><ispartof>IEEE journal of selected topics in applied earth observations and remote sensing, 2022, Vol.15, p.3421-3443</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-3a6556e66c0a2d3d2506b068f12eb0a058d3a76d0f528e0985e32fe62453b7813</citedby><cites>FETCH-LOGICAL-c408t-3a6556e66c0a2d3d2506b068f12eb0a058d3a76d0f528e0985e32fe62453b7813</cites><orcidid>0000-0001-9311-8654 ; 0000-0001-9849-7411 ; 0000-0002-8426-1050</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,2096,4010,27900,27901,27902</link.rule.ids></links><search><creatorcontrib>Monsivais-Huertero, Alejandro</creatorcontrib><creatorcontrib>Constantino-Recillas, Daniel Enrique</creatorcontrib><creatorcontrib>Hernandez-Sanchez, Juan Carlos</creatorcontrib><creatorcontrib>Huerta-Batiz, Hector Ernesto</creatorcontrib><creatorcontrib>Judge, Jasmeet</creatorcontrib><creatorcontrib>Lopez-Estrada, Pedro Alejandro</creatorcontrib><creatorcontrib>Jimenez-Escalona, Jose Carlos</creatorcontrib><creatorcontrib>Arizmendi-Vasconcelos, Eduardo</creatorcontrib><creatorcontrib>Garcia-Bernal, Marco Antonio</creatorcontrib><creatorcontrib>Zambrano-Gallardo, Cira Francisca</creatorcontrib><creatorcontrib>Lopez-Caloca, Alejandra Aurelia</creatorcontrib><creatorcontrib>Zempoaltecatl-Ramirez, Enrique</creatorcontrib><creatorcontrib>Rosa-Montero, Ivan Edmundo De la</creatorcontrib><creatorcontrib>Villalobos-Martinez, Roberto Ivan</creatorcontrib><creatorcontrib>Aparicio-Garcia, Ramon Sidonio</creatorcontrib><creatorcontrib>Sanchez-Villanueva, Carlos Rodolfo</creatorcontrib><creatorcontrib>Arizmendi-Vasconcelos, Leonardo</creatorcontrib><creatorcontrib>Cotero-Manzo, Roberto</creatorcontrib><creatorcontrib>Puebla-Lomas, Jaime Hugo</creatorcontrib><creatorcontrib>Sauce-Rangel, Victor Manuel</creatorcontrib><title>Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset</title><title>IEEE journal of selected topics in applied earth observations and remote sensing</title><addtitle>JSTARS</addtitle><description><![CDATA[Accurate knowledge of soil moisture (SM) is crucial in hydrological, micrometeorological, and agricultural applications; however, the SM estimation is particularly challenging in agricultural regions due to high spatial variability and dynamic vegetation conditions. The need for information about SM conditions is even more evident in developing countries with limited monitoring infrastructure. Satellite SM products are a useful tool as a proxy for SM conditions on the ground, but they need to be evaluated for specific regions. In this study, we assess the quality of the soil moisture active passive (SMAP) SM retrievals at 36, 9, and 3 km in an agricultural region in Central Mexico using in situ measurements during the Terrestrial Hydrology Experiments in Mexico 2018 and 2019. In addition, we provide insights into soil and vegetation parameters in the retrieval algorithms compared to those observed in the region. It was found that the SM spatial variability at the SMAP pixel grids was well represented by upscaled in situ SM measurements (SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula>) from five monitoring stations using the soil-weighted averaging and the Voronoï diagrams. Overall, the SMAP SM retrievals are highly correlated with SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula> at all scales, but they estimated wetter conditions and the average root-mean-square difference (RMSD) <inline-formula><tex-math notation="LaTeX">></tex-math></inline-formula> 0.045 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>. The lowest RMSD was obtained for the SM product at 36 km, while the highest RMSD was found for the SM product at 3 km. In addition, the single-channel algorithm using H-polarization provided the lowest RMSD for the products at 36 and 9 km. The main sources of uncertainty in the region may arise from the higher clay fraction used in the SMAP retrieval algorithm, by 13% compared to that observed, and a nonrepresentative characterization of land cover heterogeneity for vegetation water content estimation. The incorporation of in situ values into an SM retrieval algorithm resulted in differences <inline-formula><tex-math notation="LaTeX">< </tex-math></inline-formula>0.04 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula> between SM estimates and in situ SM for the complete growing season. Particularly, the use of in situ information helped in improving SM estimation when optimizing V- and dual-polarization brightness temperature observations.]]></description><subject>Agricultural region</subject><subject>Algorithms</subject><subject>Brightness temperature</subject><subject>Developing countries</subject><subject>Growing season</subject><subject>Heterogeneity</subject><subject>Hydrology</subject><subject>In situ measurement</subject><subject>L-band passive microwave</subject><subject>Land cover</subject><subject>LDCs</subject><subject>Mexico</subject><subject>Moisture content</subject><subject>Moisture effects</subject><subject>Monitoring</subject><subject>Monitoring systems</subject><subject>multiscale soil moisture (SM)</subject><subject>Polarization</subject><subject>Quality assessment</subject><subject>Retrieval</subject><subject>Soil</subject><subject>Soil measurements</subject><subject>Soil moisture</subject><subject>soil moisture active passive (SMAP)</subject><subject>Spatial variations</subject><subject>Surface radiation temperature</subject><subject>terrestrial hydrology experiments in Mexico 2018 (THEXMEX-18)</subject><subject>terrestrial hydrology experiments in Mexico 2019 (THEXMEX-19)</subject><subject>Uncertainty</subject><subject>Urban areas</subject><subject>Vegetation</subject><subject>Vegetation mapping</subject><subject>Water content</subject><issn>1939-1404</issn><issn>2151-1535</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNo9kU9r3DAQxUVooduknyAXQc_e6I8l27m5222TkG1DvIXcxKw83mpxrFSSITn3i9dbh8DAwJt5bxh-hJxztuScVRc3zba-b5aCCbGUXCtWlCdkIbjiGVdSvSMLXskq4znLP5CPMR4Y06Ko5IL8rWPEGB9xSNR39Efd1LTZ1He08a6nG-9iGgPSu-Db0aZIOx9ovQ_Ojv00gJ7e4975IVI30NUUcpQ2-Oysv6T1MBX0L9FF-gUittQPNP1Gur1aP2zWD_QrpElOZ-R9B33ET6_9lPz6tt6urrLbn9-vV_VtZnNWpkyCVkqj1paBaGUrFNM7psuOC9wxYKpsJRS6ZZ0SJbKqVChFh1rkSu6KkstTcj3nth4O5im4RwgvxoMz_wUf9gZCcrZHY4UVbQ6q1Bpzm3PACkCDsoXCQmI1ZX2es56C_zNiTObgxzB9G43QWupcc6anLTlv2eBjDNi9XeXMHMmZmZw5kjOv5CbX-exyiPjmqAo18VPyH0wIk3k</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Monsivais-Huertero, Alejandro</creator><creator>Constantino-Recillas, Daniel Enrique</creator><creator>Hernandez-Sanchez, Juan Carlos</creator><creator>Huerta-Batiz, Hector Ernesto</creator><creator>Judge, Jasmeet</creator><creator>Lopez-Estrada, Pedro Alejandro</creator><creator>Jimenez-Escalona, Jose Carlos</creator><creator>Arizmendi-Vasconcelos, Eduardo</creator><creator>Garcia-Bernal, Marco Antonio</creator><creator>Zambrano-Gallardo, Cira Francisca</creator><creator>Lopez-Caloca, Alejandra Aurelia</creator><creator>Zempoaltecatl-Ramirez, Enrique</creator><creator>Rosa-Montero, Ivan Edmundo De la</creator><creator>Villalobos-Martinez, Roberto Ivan</creator><creator>Aparicio-Garcia, Ramon Sidonio</creator><creator>Sanchez-Villanueva, Carlos Rodolfo</creator><creator>Arizmendi-Vasconcelos, Leonardo</creator><creator>Cotero-Manzo, Roberto</creator><creator>Puebla-Lomas, Jaime Hugo</creator><creator>Sauce-Rangel, Victor Manuel</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9311-8654</orcidid><orcidid>https://orcid.org/0000-0001-9849-7411</orcidid><orcidid>https://orcid.org/0000-0002-8426-1050</orcidid></search><sort><creationdate>2022</creationdate><title>Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset</title><author>Monsivais-Huertero, Alejandro ; Constantino-Recillas, Daniel Enrique ; Hernandez-Sanchez, Juan Carlos ; Huerta-Batiz, Hector Ernesto ; Judge, Jasmeet ; Lopez-Estrada, Pedro Alejandro ; Jimenez-Escalona, Jose Carlos ; Arizmendi-Vasconcelos, Eduardo ; Garcia-Bernal, Marco Antonio ; Zambrano-Gallardo, Cira Francisca ; Lopez-Caloca, Alejandra Aurelia ; Zempoaltecatl-Ramirez, Enrique ; Rosa-Montero, Ivan Edmundo De la ; Villalobos-Martinez, Roberto Ivan ; Aparicio-Garcia, Ramon Sidonio ; Sanchez-Villanueva, Carlos Rodolfo ; Arizmendi-Vasconcelos, Leonardo ; Cotero-Manzo, Roberto ; Puebla-Lomas, Jaime Hugo ; Sauce-Rangel, Victor Manuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-3a6556e66c0a2d3d2506b068f12eb0a058d3a76d0f528e0985e32fe62453b7813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agricultural region</topic><topic>Algorithms</topic><topic>Brightness temperature</topic><topic>Developing countries</topic><topic>Growing season</topic><topic>Heterogeneity</topic><topic>Hydrology</topic><topic>In situ measurement</topic><topic>L-band passive microwave</topic><topic>Land cover</topic><topic>LDCs</topic><topic>Mexico</topic><topic>Moisture content</topic><topic>Moisture effects</topic><topic>Monitoring</topic><topic>Monitoring systems</topic><topic>multiscale soil moisture (SM)</topic><topic>Polarization</topic><topic>Quality assessment</topic><topic>Retrieval</topic><topic>Soil</topic><topic>Soil measurements</topic><topic>Soil moisture</topic><topic>soil moisture active passive (SMAP)</topic><topic>Spatial variations</topic><topic>Surface radiation temperature</topic><topic>terrestrial hydrology experiments in Mexico 2018 (THEXMEX-18)</topic><topic>terrestrial hydrology experiments in Mexico 2019 (THEXMEX-19)</topic><topic>Uncertainty</topic><topic>Urban areas</topic><topic>Vegetation</topic><topic>Vegetation mapping</topic><topic>Water content</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Monsivais-Huertero, Alejandro</creatorcontrib><creatorcontrib>Constantino-Recillas, Daniel Enrique</creatorcontrib><creatorcontrib>Hernandez-Sanchez, Juan 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Technologies Database with Aerospace</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE journal of selected topics in applied earth observations and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Monsivais-Huertero, Alejandro</au><au>Constantino-Recillas, Daniel Enrique</au><au>Hernandez-Sanchez, Juan Carlos</au><au>Huerta-Batiz, Hector Ernesto</au><au>Judge, Jasmeet</au><au>Lopez-Estrada, Pedro Alejandro</au><au>Jimenez-Escalona, Jose Carlos</au><au>Arizmendi-Vasconcelos, Eduardo</au><au>Garcia-Bernal, Marco Antonio</au><au>Zambrano-Gallardo, Cira Francisca</au><au>Lopez-Caloca, Alejandra Aurelia</au><au>Zempoaltecatl-Ramirez, Enrique</au><au>Rosa-Montero, Ivan Edmundo De la</au><au>Villalobos-Martinez, Roberto Ivan</au><au>Aparicio-Garcia, Ramon Sidonio</au><au>Sanchez-Villanueva, Carlos Rodolfo</au><au>Arizmendi-Vasconcelos, Leonardo</au><au>Cotero-Manzo, Roberto</au><au>Puebla-Lomas, Jaime Hugo</au><au>Sauce-Rangel, Victor Manuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset</atitle><jtitle>IEEE journal of selected topics in applied earth observations and remote sensing</jtitle><stitle>JSTARS</stitle><date>2022</date><risdate>2022</risdate><volume>15</volume><spage>3421</spage><epage>3443</epage><pages>3421-3443</pages><issn>1939-1404</issn><eissn>2151-1535</eissn><coden>IJSTHZ</coden><abstract><![CDATA[Accurate knowledge of soil moisture (SM) is crucial in hydrological, micrometeorological, and agricultural applications; however, the SM estimation is particularly challenging in agricultural regions due to high spatial variability and dynamic vegetation conditions. The need for information about SM conditions is even more evident in developing countries with limited monitoring infrastructure. Satellite SM products are a useful tool as a proxy for SM conditions on the ground, but they need to be evaluated for specific regions. In this study, we assess the quality of the soil moisture active passive (SMAP) SM retrievals at 36, 9, and 3 km in an agricultural region in Central Mexico using in situ measurements during the Terrestrial Hydrology Experiments in Mexico 2018 and 2019. In addition, we provide insights into soil and vegetation parameters in the retrieval algorithms compared to those observed in the region. It was found that the SM spatial variability at the SMAP pixel grids was well represented by upscaled in situ SM measurements (SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula>) from five monitoring stations using the soil-weighted averaging and the Voronoï diagrams. Overall, the SMAP SM retrievals are highly correlated with SM<inline-formula><tex-math notation="LaTeX">_{\text{up}}</tex-math></inline-formula> at all scales, but they estimated wetter conditions and the average root-mean-square difference (RMSD) <inline-formula><tex-math notation="LaTeX">></tex-math></inline-formula> 0.045 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>. The lowest RMSD was obtained for the SM product at 36 km, while the highest RMSD was found for the SM product at 3 km. In addition, the single-channel algorithm using H-polarization provided the lowest RMSD for the products at 36 and 9 km. The main sources of uncertainty in the region may arise from the higher clay fraction used in the SMAP retrieval algorithm, by 13% compared to that observed, and a nonrepresentative characterization of land cover heterogeneity for vegetation water content estimation. The incorporation of in situ values into an SM retrieval algorithm resulted in differences <inline-formula><tex-math notation="LaTeX">< </tex-math></inline-formula>0.04 m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula>/m<inline-formula><tex-math notation="LaTeX">^{3}</tex-math></inline-formula> between SM estimates and in situ SM for the complete growing season. Particularly, the use of in situ information helped in improving SM estimation when optimizing V- and dual-polarization brightness temperature observations.]]></abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/JSTARS.2022.3165078</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0001-9311-8654</orcidid><orcidid>https://orcid.org/0000-0001-9849-7411</orcidid><orcidid>https://orcid.org/0000-0002-8426-1050</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1939-1404 |
| ispartof | IEEE journal of selected topics in applied earth observations and remote sensing, 2022, Vol.15, p.3421-3443 |
| issn | 1939-1404 2151-1535 |
| language | eng |
| recordid | cdi_proquest_journals_2663646106 |
| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Agricultural region Algorithms Brightness temperature Developing countries Growing season Heterogeneity Hydrology In situ measurement L-band passive microwave Land cover LDCs Mexico Moisture content Moisture effects Monitoring Monitoring systems multiscale soil moisture (SM) Polarization Quality assessment Retrieval Soil Soil measurements Soil moisture soil moisture active passive (SMAP) Spatial variations Surface radiation temperature terrestrial hydrology experiments in Mexico 2018 (THEXMEX-18) terrestrial hydrology experiments in Mexico 2019 (THEXMEX-19) Uncertainty Urban areas Vegetation Vegetation mapping Water content |
| title | Assessment of NASA SMAP Soil Moisture Products for Agricultural Regions in Central Mexico: An Analysis Based on the THEXMEX Dataset |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T18%3A58%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessment%20of%20NASA%20SMAP%20Soil%20Moisture%20Products%20for%20Agricultural%20Regions%20in%20Central%20Mexico:%20An%20Analysis%20Based%20on%20the%20THEXMEX%20Dataset&rft.jtitle=IEEE%20journal%20of%20selected%20topics%20in%20applied%20earth%20observations%20and%20remote%20sensing&rft.au=Monsivais-Huertero,%20Alejandro&rft.date=2022&rft.volume=15&rft.spage=3421&rft.epage=3443&rft.pages=3421-3443&rft.issn=1939-1404&rft.eissn=2151-1535&rft.coden=IJSTHZ&rft_id=info:doi/10.1109/JSTARS.2022.3165078&rft_dat=%3Cproquest_cross%3E2663646106%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2663646106&rft_id=info:pmid/&rft_ieee_id=9751405&rft_doaj_id=oai_doaj_org_article_c2c2d4a5866e4c41ae9aa6a5c75e73e9&rfr_iscdi=true |