Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/rs15071870 http://hdl.handle.net/11449/247189 |
Resumo: | In two small and isolated wetlands located at the interface of the Atlantic Forest and Brazilian savanna (Cerrado) in São Paulo State, Brazil, we employed a pixel-based supervised classification approach using a combination of panchromatic and multispectral bands obtained from Landsat 2, 5, 7, and CBERS-04A satellites (ranging from 80 to 2 m/pixel). In addition, we acquired DJI Phantom 4 Pro UAV-RGB images in twelve different periods with a resolution of +5 cm/pixel. Furthermore, we utilized 2D and 3D Electrical Resistivity Tomography (ERT) to obtain data on the surroundings and center of the wetlands. Finally, we conducted a climatological data analysis. The results from the multisource data allowed us to classify the ecosystems as geographically isolated wetlands (GIWs), for which we documented a seasonal month-to-month (12 months) spatial variation of inundated area, vegetation pattern, soil water interaction, and a point of surface and deep-subsurface water interaction. These results are essential for high-accuracy characterization of small wetlands’ hydrodynamics and hydroperiods at the local scale. Our study contributes to optimizing GIWs understanding, monitoring, and reapplication of the methodology in other wetlands or small ecosystems. |
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Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazildroneelectrical resistivity tomographysatellitesavannaunmanned aerial vehicleIn two small and isolated wetlands located at the interface of the Atlantic Forest and Brazilian savanna (Cerrado) in São Paulo State, Brazil, we employed a pixel-based supervised classification approach using a combination of panchromatic and multispectral bands obtained from Landsat 2, 5, 7, and CBERS-04A satellites (ranging from 80 to 2 m/pixel). In addition, we acquired DJI Phantom 4 Pro UAV-RGB images in twelve different periods with a resolution of +5 cm/pixel. Furthermore, we utilized 2D and 3D Electrical Resistivity Tomography (ERT) to obtain data on the surroundings and center of the wetlands. Finally, we conducted a climatological data analysis. The results from the multisource data allowed us to classify the ecosystems as geographically isolated wetlands (GIWs), for which we documented a seasonal month-to-month (12 months) spatial variation of inundated area, vegetation pattern, soil water interaction, and a point of surface and deep-subsurface water interaction. These results are essential for high-accuracy characterization of small wetlands’ hydrodynamics and hydroperiods at the local scale. Our study contributes to optimizing GIWs understanding, monitoring, and reapplication of the methodology in other wetlands or small ecosystems.Department of Geology Institute of Geosciences and Exact Sciences São Paulo State University (UNESP), Av. 24A, 1515, Bela VistaLAPIG—Image Processing and GIS Laboratory Institute of Socio-Environmental Studies Federal University of Goiás, Samambaia Campus, Av. Esperança s/nDepartment of Geology Institute of Geosciences and Exact Sciences São Paulo State University (UNESP), Av. 24A, 1515, Bela VistaUniversidade Estadual Paulista (UNESP)Universidade Federal de Goiás (UFG)Furlan, Lucas Moreira [UNESP]Ferreira, Manuel EduardoMoreira, César Augusto [UNESP]de Alencar, Paulo Guilherme [UNESP]Casagrande, Matheus Felipe Stanfoca [UNESP]Rosolen, Vânia [UNESP]2023-07-29T13:08:49Z2023-07-29T13:08:49Z2023-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/rs15071870Remote Sensing, v. 15, n. 7, 2023.2072-4292http://hdl.handle.net/11449/24718910.3390/rs150718702-s2.0-85152773010Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensinginfo:eu-repo/semantics/openAccess2023-07-29T13:08:49Zoai:repositorio.unesp.br:11449/247189Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-07-29T13:08:49Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
title |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
spellingShingle |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil Furlan, Lucas Moreira [UNESP] drone electrical resistivity tomography satellite savanna unmanned aerial vehicle |
title_short |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
title_full |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
title_fullStr |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
title_full_unstemmed |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
title_sort |
Satellite, UAV, and Geophysical Data to Identify Surface and Subsurface Hydrodynamics of Geographically Isolated Wetlands: Understanding an Undervalued Ecosystem at the Atlantic Forest-Cerrado Interface of Brazil |
author |
Furlan, Lucas Moreira [UNESP] |
author_facet |
Furlan, Lucas Moreira [UNESP] Ferreira, Manuel Eduardo Moreira, César Augusto [UNESP] de Alencar, Paulo Guilherme [UNESP] Casagrande, Matheus Felipe Stanfoca [UNESP] Rosolen, Vânia [UNESP] |
author_role |
author |
author2 |
Ferreira, Manuel Eduardo Moreira, César Augusto [UNESP] de Alencar, Paulo Guilherme [UNESP] Casagrande, Matheus Felipe Stanfoca [UNESP] Rosolen, Vânia [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade Federal de Goiás (UFG) |
dc.contributor.author.fl_str_mv |
Furlan, Lucas Moreira [UNESP] Ferreira, Manuel Eduardo Moreira, César Augusto [UNESP] de Alencar, Paulo Guilherme [UNESP] Casagrande, Matheus Felipe Stanfoca [UNESP] Rosolen, Vânia [UNESP] |
dc.subject.por.fl_str_mv |
drone electrical resistivity tomography satellite savanna unmanned aerial vehicle |
topic |
drone electrical resistivity tomography satellite savanna unmanned aerial vehicle |
description |
In two small and isolated wetlands located at the interface of the Atlantic Forest and Brazilian savanna (Cerrado) in São Paulo State, Brazil, we employed a pixel-based supervised classification approach using a combination of panchromatic and multispectral bands obtained from Landsat 2, 5, 7, and CBERS-04A satellites (ranging from 80 to 2 m/pixel). In addition, we acquired DJI Phantom 4 Pro UAV-RGB images in twelve different periods with a resolution of +5 cm/pixel. Furthermore, we utilized 2D and 3D Electrical Resistivity Tomography (ERT) to obtain data on the surroundings and center of the wetlands. Finally, we conducted a climatological data analysis. The results from the multisource data allowed us to classify the ecosystems as geographically isolated wetlands (GIWs), for which we documented a seasonal month-to-month (12 months) spatial variation of inundated area, vegetation pattern, soil water interaction, and a point of surface and deep-subsurface water interaction. These results are essential for high-accuracy characterization of small wetlands’ hydrodynamics and hydroperiods at the local scale. Our study contributes to optimizing GIWs understanding, monitoring, and reapplication of the methodology in other wetlands or small ecosystems. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T13:08:49Z 2023-07-29T13:08:49Z 2023-04-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/rs15071870 Remote Sensing, v. 15, n. 7, 2023. 2072-4292 http://hdl.handle.net/11449/247189 10.3390/rs15071870 2-s2.0-85152773010 |
url |
http://dx.doi.org/10.3390/rs15071870 http://hdl.handle.net/11449/247189 |
identifier_str_mv |
Remote Sensing, v. 15, n. 7, 2023. 2072-4292 10.3390/rs15071870 2-s2.0-85152773010 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Remote Sensing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1797789345736818688 |