Dem, Slope and Aspect Parameters in the Characterization of a Terrestrial Area through Remote Sensing

Abstract

The study used remote sensing techniques to analyze and characterize a land area based on DEM, SLOPE and ASPECT parameters. An area of ​​5337,368 ha was considered, within the Surduc ATU, Timis County, Romania. Satellite scenes (Sentinel 2) were taken in the summer season, 2025. The territory was classified, considering nine classes within each parameter (DC1 to DC9 for DEM; SC1 to SC9 for SLOPE; AC1 to AC9 for ASPECT). Within the DEM parameter, two classes (DC1 and DC2) presented a larger area compared to the class average, with statistically significant differences (p<0.01), and three classes presented smaller areas compared to the average (p<0.05). Within the SLOPE parameter, one class (SC1) presented a value above the mean (p<0.001), and two classes (SC8, and SC9) presented values ​​below the mean (p<0.01). Within the ASPECT parameter, one class (AC1) presented a value above the mean (p<0.001), and three classes (AC4, AC5, and AC9) presented values ​​below the mean (p<0.05). According to PCA, three classes were positioned correlated with DEM, SLOPE, ASPECT parameters, and the other classes were positioned independently. DEM and SLOPE parameters showed positive action, of very strong intensity in PC1, and the ASPECT parameter showed positive action of moderate intensity in PC1 and PC2. According to Cluster Analysis, class C1 presented an independent position, and the other classes were grouped into two clusters based on similarity in the cluster dendrogram.