Ground deformation measurements in mining areas play a key role in revealing the surface subsidence law, retrieving the subsidence parameters, warning of geological disasters and restoring the surface ecology. With the development of science and technology, there have emerged a great number of monitoring techniques and buildings of diverse protection levels. The diversity of monitoring techniques and the multiplicity of monitoring objects have brought challenges for surface deformation monitoring in the coal industry. Based on the existing deformation monitoring techniques, this paper established a framework of "space-sky-ground" collaborative monitoring system in mining area. We also constructed an AHP-TOPSIS (Analytic Hierarchy Process method- Technique for Order Preference by Similarity to an Ideal Solution) preference model of "space-sky-ground" collaborative monitoring of surface deformation in mining area, and carried out engineering application. Our study shows that the framework of the "space-sky-ground" collaborative monitoring system for surface subsidence in mining areas established in this paper, combined with the AHP-TOPSIS monitoring preference model, which can fully combine the advantages of each monitoring technique, overcome the limitations of a single monitoring technique, comprehensively obtain the surface subsidence data and work out the surface deformation subsidence pattern. This information provides a data and technical support for surface environment management.

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In the context of those countries around the world that are actively promoting sustainable development of the environment, China has formulated a new “double carbon” strategic goal to assume corresponding responsibilities. Vegetation carbon sequestration plays a key role in enhancing the carbon sink capacity toward reaching the carbon peak and carbon neutrality. In order to quantitatively study vegetation carbon sequestration, in this article, we used the net primary productivity (NPP) as an indicator to measure it. In this research, the Datai Coal Mine in western Beijing was used as the study area, and the spatiotemporal distribution characteristics and the influencing factors of carbon sequestration through vegetation were analyzed. Based on the meteorological data, remote sensing images, and the land use data of the mining area, the improved Carnegie–Ames–Stanford Approach (CASA) was used to calculate the net primary productivity (NPP) of vegetation in the Datai mining area from 2013 to 2021, to analyze its temporal and spatial distribution in relation to meteorological factors. The results showed that in the past 9 years, the NPP in the Datai mining area generally increased from 546 gC/m2 to 601 gC/m2. The NPP in the Mentougou District generally decreased and had a significant relationship with precipitation, temperature, and solar radiation. The Mentougou District’s NPP change had a significant positive correlation with the precipitation change (R2 = 0.8). The Mentougou District’s NPP change had no significant relationship with temperature (R2 = 0.98) and solar radiation fluctuations (R2 = 0.75). In conclusion, the vegetation NPP in the Datai Mine regularly changed throughout the year, and its annual vegetation NPP was about twice that of the Mentougou District, which probably due to the low-intensity mining of the Datai Mine. Thus, there is no significant impact on the vegetation carbon in this area.