Under the Belt and Road Initiatives, China’s overseas cooperation in constructing mining projects has developed rapidly. The development and utilization of mining resources are essential requirements for socio-economic development. At the same time, the ecological impacts of the exploitation and utilization of mining resources have increasingly aroused the widespread concern of the international community. This paper uses Landsat images, high-resolution images, and nighttime light (NTL) data to remotely monitor Sino Iron in Australia and Taldybulak Levoberezhny in Kyrgyzstan in different development periods to provide a reference for the rational development of mineral resources and environmental management. The results show that the Chinese enterprises have achieved good results in the ecological protection of the mining area during the construction period. The development of the mine has caused minor damage to the surrounding environment and has not destroyed the local natural ecological pattern. The different NTL indices show an overall rising trend, indicating that the construction of mines has dramatically promoted the socio-economic development of countries along the Belt and Road in both time and space. Therefore, relevant departments should practice green development in overseas projects, establish a scientific mine governance system, and promote a win-win economic growth and environmental governance situation.

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Using reflectance spectroscopy to monitor vegetation pigments is a crucial method to know the nutritional status, environmental stress, and phenological phase of vegetation. Defining cities as targeted areas and common greening plants as research objects, the pigment concentrations and dust deposition amounts of the urban plants were classified to explore the spectral difference, respectively. Furthermore, according to different dust deposition levels, this study compared and discussed the prediction models of chlorophyll concentration by correlation analysis and linear regression analysis. The results showed: (1) Dust deposition had interference effects on pigment concentration, leaf reflectance, and their correlations. Dust was an essential factor that must be considered. (2) The influence of dust deposition on chlorophyll—a concentration estimation was related to the selected vegetation indexes. Different modeling indicators had different sensitivity to dust. The SR705 and CIrededge vegetation indexes based on the red edge band were more suitable for establishing chlorophyll-a prediction models. (3) The leaf chlorophyll concentration prediction can be achieved by using reflectance spectroscopy data. The effect of the chlorophyll estimation model under the levels of “Medium dust” and “Heavy dust” was worse than that of “Less dust”, which meant the accumulation of dust had interference to the estimation of chlorophyll concentration. The quantitative analysis of vegetation spectrum by reflectance spectroscopy shows excellent advantages in the research and application of vegetation remote sensing, which provides an important theoretical basis and technical support for the practical application of plant chlorophyll content prediction.

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