Understanding soil erosion in the northeastern area of China with black soil is vital for protecting the natural environment and preserving food security. Although spatial and temporal studies of soil erosion have been conducted, further research is needed on the correlation between soil erosion and land use type changes. In this study, the soil erosion modulus is computed using RUSLE. The model that is most suitable to the research area was produced by contrasting three different approaches to estimating the rainfall erosion factor. The RUSLE based on the multi-year continuous high-density hourly average precipitation had the best performance of the bunch, with a MAPE of 15.49%, RMSPE of 7.99%, and R2 of 0.99. Based on this model, simulated soil erosion trends in the study region from 1980 to 2020 were examined, along with the link between soil erosion and land use change. The results showed that 40.47% of the overall erosion area is made up of cultivated land, and 97.83% of it is low erosion. The most severe soil erosion occurred on unused land, with moderate and above soil erosion occupying 48.93%. Since 2000, there has been an increase in the erosion of soil in the study region, which is primarily spatially represented in the rise in the soil erosion of forests in the central and northern mountainous areas. The study’s findings serve as a guide for land planning and the development of sustainable agriculture.
Remote sensing (RS) of alteration zones and anomalies can provide information that is useful for geological prospecting and exploration. RS is an effective method for porphyry copper mineral exploration and prospecting prediction. More specifically, the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) data, which include 14 spectral channels from visible light to thermal infrared, are useful in such cases. This study uses visible-shortwave infrared and thermal infrared ASTER data together with surface material spectra from the Duolong porphyry copper ore district to construct an RS-based alteration zonation model of the deposit. In this study, an RS alteration zoning model is established based on ground-spectral alteration zoning results. The methods include PCA (Principal Component Analysis), Ratio, and Slope methods. The information obtained by each method is different. RS-based alteration zonation is developed based on the intersection of maps, resultant from the different methods for extracting information related to different minerals. The alteration zonation information extracted from ASTER RS data is consistent with geological observations. Using information from the RS-based model, we mapped the alteration minerals and zones of the Duolong ore district, thereby identifying prospecting target areas of the deposit.
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