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Abstract
Background
The Cerrado is the most biodiverse savanna and maintains other biomes. Aware of its significance, this paper evaluated the Brazilian Cerrado’s climatic, environmental, and socioeconomic aspects using remote sensing data and spatial statistics (correlation analysis and principal components analysis—PCA). Following the measures of sample adequacy (MSA) and Kaiser–Meyer–Olkin (KMO) tests, seventeen variables were evaluated.
Results
The MSA revealed that the dataset had a good quality (0.76), and nine variables were selected: elevation, evapotranspiration, active fires, Human Development Index (HDI), land use and land cover (LULC; shrubland and cropland/rainfed), rainfall (spring and autumn), and livestock. The correlation matrix indicated a positive (negative) association between HDI and autumn rainfall (HDI and active fires) with a value of 0.77 (− 0.55). The PCA results determined which three principal components (PC) were adequate for extracting spatial patterns, accounting for 68.02% of the total variance with respective values of 38.59%, 16.89%, and 12.5%. Due to economic development and agribusiness, Cerrado’s northern (central, western, and southern) areas had negative (positive) score HDI values, as shown in PC1. Climatic (rainfall—spring and fall) and environmental (cropland/rainfed and shrubland) aspects dominated the PC2, with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability. On the other hand, environmental aspects (LULC-shrubland and elevation) influenced the PC3; areas with high altitudes (> 500 m) received a higher score.
Conclusion
Agricultural expansion substantially affected LULC, leading to deforestation-caused suppression of native vegetation.
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Details

1 Federal University of Rio Grande (FURG), Postgraduate Program in Environmentrics (PPGAmb), Institute of Mathematics, Statistics, and Physics (IMEF), Rio Grande, Brazil (GRID:grid.411598.0) (ISNI:0000 0000 8540 6536)
2 Federal University of Alagoas (UFAL), Institute of Atmospheric Sciences (ICAT), Maceió, Brazil (GRID:grid.411179.b) (ISNI:0000 0001 2154 120X); Federal Fluminense University (UFF), Postgraduate Program in Biosystems Engineering (PGEB), Niterói, Brazil (GRID:grid.411173.1) (ISNI:0000 0001 2184 6919)
3 Unidade Acadêmica de Ciências Atmosféricas (UACA), Federal University of Campina Grande (UFCG), Postgraduate Program in Meteorology, Campina Grande, Brazil (GRID:grid.411182.f) (ISNI:0000 0001 0169 5930)
4 Tartous University, Geography Department, Faculty of Arts and Humanities, Tartous, Syria (GRID:grid.411182.f); Damascus University, Geography Department, Faculty of Arts and Humanities, Damascus, Syria (GRID:grid.8192.2) (ISNI:0000 0001 2353 3326); Tishreen University, Geography Department, Faculty of Arts and Humanities, Lattakia, Syria (GRID:grid.412741.5) (ISNI:0000 0001 0696 1046)
5 Qassim University, Department of Geography, College of Arabic Language and Social Studies, Buraydah, Saudi Arabia (GRID:grid.412602.3) (ISNI:0000 0000 9421 8094)
6 State University of Mato Grosso (UNEMAT), Departamento de Geografia, Sinop, Brazil (GRID:grid.412602.3)