Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

Caatinga biome, located in the Brazilian semi-arid region, is most populous region world, causing intensification land degradation and loss of biodiversity over time. The main objective this paper to determine analyze changes cover use, time, on biophysical parameters biome Brazil using remote sensing. Landsat-8 images were used, along with Surface Energy Balance Algorithm for Land (SEBAL) Google Earth Engine platform, from 2013 2019, through spatiotemporal modeling vegetation indices, i.e., leaf area index (LAI) (VC). Moreover, surface temperature (LST) actual evapotranspiration (ETa) Petrolina, Brazil, was used. principal component analysis used select descriptive variables multiple regression predict ETa. results indicated significant effects use energy balances In 2013, 70.2% study composed Caatinga, while lowest percentages identified 2015 (67.8%) 2017 (68.7%). Rainfall records ranged 270 480 mm, values higher than 410 mm 46.5% area, concentrated northern part municipality. On other hand, annual rainfall (from 200 340 mm) occurred. Low rate observed by LAI VC values, a range 0 25% 52.3% which exposes dry season vegetation. highest LST mainly found urban areas and/or exposed soil. 40.5% region’s had between 48.0 52.0 °C, raising ETa rates (~4.7 day−1). Our model has shown good outcomes terms accuracy concordance (coefficient determination = 0.98, root mean square error 0.498, Lin’s correlation coefficient 0.907). increase agricultural resulted progressive reduction biome. Therefore, mitigation sustainable planning vital decrease impacts anthropic actions.