Land use and land cover change patterns from orbital remote sensing products: spatial dynamics and trend analysis in northeastern Brazil

dc.creatorSilva, Jhon Lennon Bezerra da
dc.creatorSilva, Marcos Vinícius da
dc.creatorLopes, Pabrício Marcos Oliveira
dc.creatorSantos, Rodrigo Couto
dc.creatorCarvalho, Ailton Alves de
dc.creatorMoura, Geber Barbosa de Albuquerque
dc.creatorSilva, Thieres George Freire da
dc.creatorBezerra, Alan Cézar
dc.creatorJardim, Alexandre Maniçoba da Rosa Ferraz
dc.creatorFerreira, Maria Beatriz
dc.creatorMesquita, Marcio
dc.date.accessioned2025-11-07T19:47:08Z
dc.date.available2025-11-07T19:47:08Z
dc.date.issued2025
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.identifier.citationSILVA, Jhon Lennon Bezerra da et al. Land use and land cover change patterns from orbital remote sensing products: spatial dynamics and trend analysis in northeastern Brazil. Land, Basel, v. 14, n. 10, p. 1954, 2025. DOI: 10.3390/land14101954. Disponível em: https://www.mdpi.com/2073-445X/14/10/1954. Acesso em: 16 out. 2025.
dc.identifier.doi10.3390/land14101954
dc.identifier.issne- 2073-445X
dc.identifier.urihttps://repositorio.bc.ufg.br//handle/ri/29011
dc.language.isoeng
dc.publisher.countryAlemanha
dc.publisher.departmentEscola de Agronomia - EA (RMG)
dc.rightsAcesso Aberto
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMODIS sensor product
dc.subjectMapBiomas Brazil
dc.subjectMann–Kendall and Sen’s slope
dc.subjectLULC
dc.subjectLand degradation
dc.subjectRegional climate variability
dc.subjectGoogle Earth Engine
dc.titleLand use and land cover change patterns from orbital remote sensing products: spatial dynamics and trend analysis in northeastern Brazil
dc.typeArtigo

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