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dc.contributor.authorSANTOS, C. V. B. dos
dc.contributor.authorGALVÍNCIO, J. D.
dc.contributor.authorMIRANDA, R. de Q.
dc.contributor.authorCARVALHO, H. F. de S.
dc.contributor.authorSOUZA, A. G. S. S.
dc.contributor.authorSOUSA, I. F. de
dc.contributor.authorMOURA, M. S. B. de
dc.date.accessioned2026-03-12T14:49:01Z-
dc.date.available2026-03-12T14:49:01Z-
dc.date.created2026-03-12
dc.date.issued2026
dc.identifier.citationJournal of South American Earth Sciences, v. 169, 105857, 2026.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1185338-
dc.descriptionSoil moisture is a key variable in the hydrological cycle, influencing water, soil, and energy exchanges between the land surface and the atmosphere. This study aimed to develop simplified equations and validate satellite-based soil moisture estimates in seasonally dry tropical forest areas. The study area included part of Petrolina-PE, Brazil, where a preserved Caatinga vegetation site provided surface observations. Daily-resolution satellite data were obtained from SMAP (9 km), SMOS (25 km; ascending and descending), and ESA CCI SM (25 km; combined). Validation was performed by comparing satellite pixel values with surface measurements. Initially, linear models were created and assessed using the correlation coefficient (r). Our results showed the SMAP achieved r = 0.80; SMOS ranged from r = 0.68 (ascending) to r = 0.69 (descending); and ESA CCI SM reached r = 0.61. Further validation employed r, RMSE, RSMD, MAE, and PBIAS. SMAP performed best, yielding r = 0.85, RMSE and RSMD = 0.01 m3 m−3, MAE = 0.01 m3 m−3, and PBIAS = −2.50. SMOS results were also satisfactory, with r = 0.76 (ascending) and r = 0.75 (descending), RMSE/RSMD = 0.01–0.02 m3 m−3, MAE = 0.01 m3 m−3, and PBIAS = −1.80 to −3.00. ESA CCI SM showed lower correlation (r = 0.41), though error metrics remained within acceptable ranges. Overall, SMAP and SMOS data accurately estimated daily and hourly soil moisture in dry tropical forests. Despite moderate correlation, ESA CCI SM remains useful for long-term analysis due to its historical coverage (1978–2022, version v08.1).
dc.language.isoeng
dc.rightsopenAccess
dc.subjectValidação de modelos
dc.subjectFloresta seca
dc.titleValidation of SMAP, SMOS, and ESA CCI SM soil moisture products in a seasonally dry tropical forest.
dc.typeArtigo de periódico
dc.subject.thesagroSolo
dc.subject.thesagroFloresta Tropical
dc.subject.thesagroUmidade do Solo
dc.subject.thesagroSensoriamento Remoto
dc.subject.thesagroCaatinga
dc.subject.nalthesaurusSoil
dc.subject.nalthesaurusRemote sensing
dc.subject.nalthesaurusModel validation
dc.subject.nalthesaurusDry forests
riaa.ainfo.id1185338
riaa.ainfo.lastupdate2026-03-12
dc.identifier.doihttps://doi.org/10.1016/j.jsames.2025.105857
dc.contributor.institutionCLOVES VILAS BOAS DOS SANTOS, FEDERAL UNIVERSITY OF PERNAMBUCO; JOSICLÊDA DOMICIANO GALVÍNCIO, FEDERAL UNIVERSITY OF PERNAMBUCO; RODRIGO DE QUEIROGA MIRANDA, FEDERAL UNIVERSITY OF PERNAMBUCO; HERICA FERNANDA DE SOUSA CARVALHO, RENATO ARCHER INFORMATION TECHNOLOGY CENTER; ALZIRA GABRIELLE SOARES SARAIVA SOUZA, FEDERAL INSTITUTE OF BAHIA; INAJÁ FRANCISCO DE SOUSA E, MAGNA SOELMA BESERRA DE MOURA, FEDERAL UNIVERSITY OF SERGIPE; MAGNA SOELMA BESERRA DE MOURA, CNPAT / CPATSA.
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