Remote sensing techniques via Google Earth Engine for land degradation assessment in the Brazilian semiarid region, Brazil

Spatiotemporal Dynamics of Land Use and Land Cover through Physical–Hydraulic Indices: Insights in the São Francisco River Transboundary Region, Brazilian Semiarid Area

“…In a study by Silva et al [34], which evaluated the spatiotemporal changes in environmental degradation processes of vegetation cover and water resources through physical and water-related parameters (NDVI and MNDWI) on the surface, using remote sensing techniques, in northeastern Brazil, the authors observed the impacts of the degradative processes of anthropogenic actions and their intensification on water bodies and vegetation dynamics. Consistently with the aforementioned study, Silva et al [35], who explored the NDVI, LAI, and MNDWI to characterize natural and anthropogenic degradation processes in a microregion of northeastern Brazil, also emphasized in their study results the importance of applying physical and water indices to highlight soil use and land cover degradation processes. Furthermore, this study addresses the need to fill existing knowledge gaps regarding the environmental and agricultural impacts of the São Francisco River Transboundary Project and some of its associated reservoirs.…”

“…It is worth noting that very-high-resolution Earth observation data are currently not available in an open-source format for all users [27]. Despite this, important results are being obtained from high-resolution images in the Brazilian semiarid region [4,8,9,35,63,67]. For instance, a study by Sousa et al [67] on the spatial distribution of the annual precipitation in a Brazilian semiarid basin and its impact on land use and land cover dynamics (vegetation-water nexus) used images with resolutions of 30 m, thus providing information on rainfall patterns and their correlation with vegetation and water availability.…”

Spatiotemporal Analysis of Rainfall and Droughts in a Semiarid Basin of Brazil: Land Use and Land Cover Dynamics

“…According to a study by Marengo et al [28], which evaluated the climate patterns of drought in the NEB from 2010 to 2016, there was a sequence of dry years that affected the levels of reservoirs in the region and led to a water crisis. In addition, Silva et al [23] evaluated the spatiotemporal dynamics of water bodies in the micro-region of Vale do Ipojuca (included in the NEB) from 2014 to 2021 and found a marked decrease in the area of water bodies between 2014 (1226 ha, the year of greatest water availability) and 2017 (683 ha), mainly in 2016 (558 ha). According to the authors, this dynamic is associated with the occurrence of severe droughts in the NEB, which caused significant reductions in water bodies volumes that lasted until mid-2019.…”

“…In addition, remote sensing can also be used to monitor landscape and biophysical changes in semiarid regions through the evaluation of land use and land cover (LULC) map spatial association with vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI). These indexes allow the estimation of land use and cover, enabling the characterization of spatiotemporal dynamics and quantification of vegetation conditions and water features [5,[19][20][21][22][23][24]. Additionally, the NDVI has proved to be a valuable tool in the analysis of irrigation in agricultural areas, allowing farmers and researchers to assess soil salinity and monitor crop growth and water stress to optimize yield and conserve resources [25,26].…”

Monitoring the Spatio-Temporal Distribution of Soil Salinity Using Google Earth Engine for Detecting the Saline Areas Susceptible to Salt Storm Occurrence

“…This powerful platform has found effective applications across various Earth science disciplines [25]. It has been utilized in deforestation analysis [26,27], land use mapping [28,29], monitoring the impacts of climate change [30], and air pollution monitoring [31,32]. One of the key features of the GEE is its ability to perform automated parallel processing, making use of Google's fast computing platform.…”