Currently, the problem of illegal mining is still acute. Such illegal use of natural resources harms the environment and leads to irrational use of mineral resources. Modern methods with the use of remote sensing technologies will effectively detect such law violations. In the current study, a method for automatically detection of non-metallic mineral extraction sites based on remote sensing data analysis has been developed. The study uses Sentinel-2 satellite images with spatial resolution 10 m and 20 m and considers four types of minerals: sand, clay, carbonate rocks and sand gravel mix. The spectral indices help to determine the specific quantitative characteristics of the mineral resources. The result is probability maps with mineral resourses characteristics in each pixel. In order to determine to which of known classes relates the point, you need to find the covariance matrices for all classes and take the class with the smallest Mahalanobis distance to the point. Based on the obtained probability maps, an analysis of the applicability of the selected spectral indices was performed, as well as a visual assessment of the quality of interpretation. For each spectral channel and index, two frequency histograms were created to determine how different the channels values and spectral indices on the entire scene and at the reference objects. Each object found by the program was checked for it presence on the studied territory. The developed system is a modern, secure, non-contact method for the rational land use monitoring and natural resources extracted by open-pit mining study.
To determine the degree of degradation of agricultural lands for a key values (humus content, mobile potassium, mobile phosphorus, PH), the use of multispectral UAV materials synchronized with ground-based spectrometric imagery is proposed. Spectroradiometer HandHeld 2, soil acidity (pH) meter, satellite GLONASS-GPS receiver of geodetic class were used for field survey. Multispectral orthophoto obtained at the time of ground surveys using multispectral cameras Tetracam Micro-MCA 4 and Tetracam ADC-micro installed on board of the Supercam-S350F UAV. In parallel with the spectrometric work, samples of soils of different soil varieties and washout degree were taken, in representative sites of elementary soil areas. Laboratory studies were carried out with the selected samples, in order to determine the main agrochemical parameters: humus (%), mobile phosphorus (mg), mobile potassium (mg), pH (H2O). The work was tested on two field sites located in the Chuvash Republic (Russia), on cultivated (arable land) forest-steppe zonal soils (leached chernozems, dark gray forest soils). As a result of mathematical data processing, statistically significant relationships were obtained between certain groups of agrochemical indicators and spectral data in different channels of UAV images for specific soil varieties. In the course of the study, relationships were found between the green, NDVI, NIR, red channels obtained using the Supercam-S350F unmanned aerial vehicle and laboratory data: humus, phosphorus, potassium and soil pH. In general, the results of the experiment prove the fundamental possibility of using multispectral UAV materials, together with ground spectrometric imagery for automated express determination of agrochemical indicators of agricultural lands.
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