Remote sensing is very useful in the study and characterization of terrestrial areas based on satellite images and specific indices. The present study aimed to characterize an area using remote sensing facilities. The study considered ATU Lupsa, Alba County, Romania, an area with mountainous area specificity. DEM (Digital Elevation Model) and SLOPE parameters were used to analyze and characterize the area considered in the study. Land areas with different soil types were identified in terms of texture, Clayey loam texture (CLt), Clay texture (Ct), Sandy clay texture (SCt), Sandy loam - clayey texture (SLCt), and Varied texture (Vt). The studied area was classified based on DEM and SLOPE parameters into ten classes. Multivariate analysis (PCA, CA) was used to explain the variance in the results set and the correlation of DEM and SLOPE classes with soil types. In the case of the DEM parameter, PC1 explained 57.044% of variance, and PC2 explained 25.803%. In the case of the SLOPE parameter, PC1 explained 41.406% of variance, and PC2 explained 37.572% of variance. Cluster analysis (CA) grouped the DEM (Coph.corr. = 0.982) and SLOPE (Coph.corr. =0.781) classes based on similarity. The highest level of similarity in the case of DEM was recorded between classes DC4 and DC5, with the SDI value = 60.28, and in the case of SLOPE it was recorded between classes SC4 and SC5, with the SDI value = 99.87. The recorded results provide important information for management decisions for the area considered.

cluster, DEM, PCA, remote sensing, SLOPE

geodesy engineering

Presentation: poster