Total suspended solids (TSS) represent a critical parameter for water quality assessment and an essential indicator for remote sensing water quality monitoring. The Gaofen (GF) series satellites are a crucial component of China's “Major Special Project of High Resolution Earth Observation System”, widely applied in fields like environmental protection and land resources monitoring. In our efforts to further explore the applicability of the satellite network composed of GF-1 and GF-1B for TSS change monitoring, we developed a TSS concentration model for the coastal waters south of Yantai, China, and discussed the impact of different aerosol models on inversion results. Our findings indicate that the optimal band combination for TSS inversion modeling in the coastal waters south of Yantai is "ln(B3)-ln(B2)". The model best suited for TSS concentration inversion in the study area is y = 9.9348x2 + 29.713x + 23.879, with a coefficient of determination (R^2) of 0.73. The choice of aerosol model when employing the FLAASH model for atmospheric correction influences the predictive accuracy of the inversion model for TSS concentration. GF-1 and GF-1B satellite data are promising for inverting TSS concentrations in water bodies, and high temporal resolution satellite constellation images are beneficial for enhancing regional water body environmental monitoring.
The spatial resolution of multi-spectral remote sensing data can satisfy multi-scale structure interpretation. The authors took Qinglong area in Hebei as the study area, utilized the comprehens ive advantages of ETM+ , Spot6 and WorldView3 data of the study area to interpret the geological structures at two different levels from ETM+ data with 15 m resolution and Spot6 data with 6 m resolution to WorldView3 data with 0.5m resolution, and obtained a goo d result. Firstly, based on ETM+ data interpretation structure, the band operation results of SPOT6 data are used to indirectly reflect the structure informat ion, and the high resolution WorldView3 data is integrated to construct the interpretation analysis. Finally, the interpretation structure information is revised based on field validation. The results show that multi-source remote sensing data have the characteristics of high resolution, accuracy and high efficiency in geological structure interpretation.
By leveraging the remote sensing technology, we have delved into the remote sensing prospecting model for typical uranium mining area along the Sino-Russian Economic Corridor. According to the remote sensing interpretation results of the basic geology along the Sino-Russian Economic Corridor, we have analyzed and summarized the remote sensing geological features of the structure, stratum and rock mass in this area. Moreover, by providing the remote sensing interpretation of basic geology in the Russian Streltsovsky typical hydrothermal uranium mining area based on the data of the domestic GF-1 satellite, we have made conclusive analysis on the characteristics of its ore-controlling elements and preliminarily summarized the remote sensing geological prospecting model for typical volcanic hydrothermal uranium deposits in this area. By using the remote sensing prospecting model, we have delineated three favorable ore-forming sections, which provides an important basis for regional mineralization prediction and the delineation of favorable ore-forming areas, and helps seek such deposits in the same or similar areas.
Spectral stability characteristic parameter analysis is the basis of all the quantitative information extraction in hyperspectral image. The results show that the stability of the spectral parameters used in the spectral identification has a great influence on the efficiency of mineral identification. A mineral recognition method for hyperspectral remote sensing image based on spectral stability characteristic parameter is introduced. First, reference spectrum spectral peaks and valleys positions were extracted, then calculates the measured spectra corresponding spectral wavelength and reference spectrum of each with a characteristic peak and valley of the correlation coefficient, basis of comparison of two spectral similarity to determine the matching effect of the two spectra, in order to achieve the best mineral identification precision and accuracy. Gansu Beishan Shijinpo gold mining area as an example, the mineral identification map was obtained. After field verification, it was confirmed that the method has higher accuracyon the mineral recognition.
Hyperspectral remote sensing has one of the technical advantages atlas. The known deposits of Gansu Beishan South Beach deposits as the study area, based on the theory of wall rock alteration, using airborne hyperspectral remote sensing data (CASI/SASI), extracted mineralization alteration information and analysis. Based on airborne hyperspectral remote sensing mineral mapping results in the study area, Combining analysising of possible mineral formation fluid properties, spatial distribution characteristics and time evolution with analysising of mineral formation environment (lithology and tectonic environment), construction of the South Beach gold deposit location model, the deposit location model as a guide, comprehensive analysis of mineralization geological background and surface geochemical data, delineated mineralization favorable areas. The field investigation showed that signs of altered development of strong in the delineation of the mineralization favorable areas and metallogenic potential of better, is worth paying attention to the prospecting target area. Further explanation that the hyperspectral remote sensing can provide accurate and reliable information for the prospecting, and is worthy of further mining the ore prospecting potential.
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