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Land Use and Land Cover Change Patterns from Orbital Remote Sensing Products: Spatial Dynamics and Trend Analysis in Northeastern Brazil

dc.contributor.authorda Silva, Jhon Lennon Bezerra
dc.contributor.authorda Silva, Marcos Vinícius
dc.contributor.authorLopes, Pabrício Marcos Oliveira
dc.contributor.authorSantos, Rodrigo Couto
dc.contributor.authorde Carvalho, Ailton Alves
dc.contributor.authorde Albuquerque Moura, Geber Barbosa
dc.contributor.authorda Silva, Thieres George Freire
dc.contributor.authorBezerra, Alan Cézar
dc.contributor.authorda Rosa Ferraz Jardim, Alexandre Maniçoba [UNESP]
dc.contributor.authorFerreira, Maria Beatriz
dc.contributor.authorSilva, Patrícia Costa
dc.contributor.authorSilva, Josef Augusto Oberdan Souza
dc.contributor.authorMesquita, Marcio
dc.contributor.authorBatista, Pedro Henrique Dias
dc.contributor.authorJordan, Rodrigo Aparecido
dc.contributor.authorde Oliveira, Henrique Fonseca Elias
dc.date.accessioned2026-05-15T19:07:01Z
dc.date.issued2025-09-26
dc.description.abstractEnvironmental degradation and soil desertification are among the most severe environmental issues of recent decades worldwide. Over time, these processes have led to increasingly extreme and highly dynamic climatic conditions. In Brazil, the Northeast Region is characterized by semi-arid and arid areas that exhibit high climatic variability and are extremely vulnerable to environmental changes and pressures from human activities. The application of geotechnologies and geographic information system (GIS) modeling is essential to mitigate the impacts and pressures on the various ecosystems of Northeastern Brazil (NEB), where the Caatinga biome is predominant and critically threatened by these factors. In this context, the objective was to map and assess the spatiotemporal patterns of land use and land cover (LULC), detecting significant trends of loss and gain, based on surface reflectance data and precipitation data over two decades (2000–2019). Remote sensing datasets were utilized, including Landsat satellite data (LULC data), MODIS sensor data (surface reflectance product) and TRMM data (precipitation data). The Google Earth Engine (GEE) software was used to process orbital images and determine surface albedo and acquisition of the LULC dataset. Satellite data were subjected to multivariate analysis, descriptive statistics, dispersion and variability assessments. The results indicated a significant loss trend over the time series (2000–2019) for forest areas (ZMK = −5.872; Tau = −0.958; p < 0.01) with an annual loss of −3705.853 km2 and a total loss of −74,117.06 km2. Conversely, farming areas (agriculture and pasture) exhibited a significant gain trend (ZMK = 5.807; Tau = 0.947; p < 0.01), with an annual gain of +3978.898 km2 and a total gain of +79,577.96 km2, indicating a substantial expansion of these areas over time. However, it is important to emphasize that deforestation of the region’s native vegetation contributes to reduced water production and availability. The trend analysis identified an increase in environmental degradation due to the rapid expansion of land use. LULC and albedo data confirmed the intensification of deforestation in the Northern, Northwestern, Southern and Southeastern regions of NEB. The Northwestern region was the most directly impacted by this increase due to anthropogenic pressures. Over two decades (2000–2019), forested areas in the NEB lost approximately 80.000 km2. Principal component analysis (PCA) identified a significant cumulative variance of 87.15%. It is concluded, then, that the spatiotemporal relationship between biophysical conditions and regional climate helps us to understand and evaluate the impacts and environmental dynamics, especially of the vegetation cover of the NEB.
dc.description.affiliationCerrado Irrigation Graduate Program, Goiano Federal Institute—Campus Ceres, GO-154, km 218-Zona Rural, Ceres 76300-000, GO, Brazil;, josef.silva@estudante.ifgoiano.edu.br, (J.A.O.S.S.);, marcio.mesquita@ufg.br, (M.M.);, henrique.fonseca@ifgoiano.edu.br, (H.F.E.d.O.)
dc.description.affiliationDepartment of Engineering Agricultural, Centro of Sciences Chapadinha, Federal University of Maranhão, BR-222, Chapadinha 65500-000, MA, Brazil;, mv.silva@ufma.br
dc.description.affiliationDepartment of Engineering Agricultural, Federal Rural University of Pernambuco (UFRPE), Rua Dom Manoel de Medeiros, Dois Irmãos, Recife 52171-900, PE, Brazil;, pabricio.lopes@ufrpe.br, (P.M.O.L.);, geber.moura@ufrpe.br, (G.B.d.A.M.);, thieres.silva@ufrpe.br, (T.G.F.d.S.);, alexandremrfj@gmail.com, (A.M.d.R.F.J.)
dc.description.affiliationFaculty of Agricultural Sciences, Federal University of Grande Dourados (UFGD), Rodovia Dourados-Itahum, km 12, Campus Universitário (Unidade II), Dourados 79804-970, MS, Brazil;, rodrigocouto@ufgd.edu.br, (R.C.S.);, rodrigojordan@ufgd.edu.br, (R.A.J.)
dc.description.affiliationAcademic Unit of Serra Talhada (UAST), Federal Rural University of Pernambuco (UFRPE), Gregório Ferraz Nogueira Ave., Serra Talhada 56909-535, PE, Brazil;, ailtonalvesst@gmail.com, (A.A.d.C.);, alan.bezerra@ufrpe.br, (A.C.B.)
dc.description.affiliationDepartment of Biodiversity, Institute of Biosciences, São Paulo State University (UNESP), Rio Claro 13506-900, SP, Brazil
dc.description.affiliationPostgraduate Program in Forest Sciences, Federal Rural University of Pernambuco (UFRPE), Rua Dom Manoel de Medeiros, Dois Irmãos, Recife 52171-900, PE, Brazil;, beatriz.ferreira2@ufrpe.br
dc.description.affiliationDepartment of Agricultural Engineering, State University of Goiás, Santa Helena de Goiás 75920-000, GO, Brazil;, patricia.costa@ueg.br
dc.description.affiliationPostgraduate Program in Computing (PPGC), Federal University of Pelotas (UFPEL), Rua Gomes Carneiro, 01-Balsa, Campus Anglo—UFPEL, Pelotas 96010-610, RS, Brazil
dc.description.affiliationFaculty of Agronomy, Federal University of Goiás (UFG), Nova Veneza, km 0, Campus Samambaia—UFG, Goiânia 74690-900, GO, Brazil
dc.description.affiliationCeará State Technical Assistance and Rural Extension Company, Tenente José Vicente Avenue, 1017, Center, Itapipoca 62504-095, CE, Brazil;, henrique.batista@ematerce.ce.gov.br
dc.description.affiliationUnespDepartment of Biodiversity, Institute of Biosciences, São Paulo State University (UNESP), Rio Claro 13506-900, SP, Brazil
dc.identifierhttps://app.dimensions.ai/details/publication/pub.1193352648
dc.identifier.dimensionspub.1193352648
dc.identifier.doi10.3390/land14101954
dc.identifier.issn2073-445X
dc.identifier.orcid0000-0002-2611-4036
dc.identifier.orcid0000-0002-1318-2320
dc.identifier.orcid0000-0003-4585-9305
dc.identifier.orcid0000-0001-8783-649X
dc.identifier.orcid0000-0002-8355-4935
dc.identifier.orcid0000-0002-9986-9464
dc.identifier.orcid0000-0003-4730-2287
dc.identifier.orcid0000-0002-8894-1512
dc.identifier.orcid0000-0001-9399-4478
dc.identifier.orcid0000-0002-8710-5678
dc.identifier.orcid0000-0002-2479-4461
dc.identifier.urihttps://hdl.handle.net/11449/324170
dc.publisherMDPI
dc.relation.ispartofLand; n. 10; v. 14; p. 1954
dc.rights.accessRightsAcesso abertopt
dc.rights.sourceRightsoa_all
dc.rights.sourceRightsgold
dc.sourceDimensions
dc.titleLand Use and Land Cover Change Patterns from Orbital Remote Sensing Products: Spatial Dynamics and Trend Analysis in Northeastern Brazil
dc.typeArtigopt
dspace.entity.typePublication
relation.isOrgUnitOfPublicationeecebc66-0524-4365-8462-6103e1c979de
relation.isOrgUnitOfPublication.latestForDiscoveryeecebc66-0524-4365-8462-6103e1c979de
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Rio Claropt

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