2026-10-12T16:11:39Z https://www.scidb.cn/oai

10.57760/sciencedb.IGA.001em 2026-09-15T13:24:04Z

2026-09-15 Spaceborne Remote Sensing Indicator System for Soil Parameters doi:10.57760/sciencedb.iga.001em en This report is in PDF format. It provides a systematic analysis centered on the construction of spaceborne remote sensing inversion models for key black soil parameters and the demonstration of satellite payload specifications. All research conclusions and design bases are supported by field systematic sampling and indoor analytical testing data collected by the research team in the black soil region of Northeast China and Da'an City, Jilin Province. Based on laboratory physicochemical analysis data of conventional soil samples from the Northeast black soil region and Da'an City, as well as reflectance spectra measured by an ASD spectrometer, the study systematically completes the analysis of spectral response characteristics of key soil parameters, the sorting of monitorable indicators, and the simulation-based inversion validation of multi-gradient satellite parameters. By setting cross-combinations of 5 integration time levels and 8 resampling resolution levels, 40 sets of simulated satellite spectral data are generated to quantify the influence of integration time, resampling resolution, and signal-to-noise ratio on the inversion accuracy of five core indicators of black soil—TN, SOM, TSS, MC, and Clay—and to identify the optimal observation parameter combinations for each indicator. Based on the statistical analysis results of simulation and model validation, design recommendations for payload parameters such as sensor integration time, resampling resolution, and signal-to-noise ratio are ultimately formulated, providing solid data support and scientific basis for the payload specification demonstration, observation mode planning, and operational inversion capability construction of the black soil spaceborne monitoring satellite ("Liangshi-1") under this project. key soil parameters in black s; space-based remote sensing inv; demonstration of satellite pay 王昌昆 PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank