Abstract: Scientific and effective monitoring of the eco-environment in mining areas is the prerequisite for the protection and governance，which is of great significance to promote the ecological civilization construction.Remote sensing technology has become an important tool for monitoring the eco-environment in mining areas.Especially in recent years，the rapid development of remote sensing technology in data，algorithms，and computing power has greatly promoted the development of quantitative remote sensing of eco-environment in mining areas，which leads to a series of excellent research results.This paper summarizes and analyzes the progress of quantitative remote sensing for monitoring the ecoenvironment in mining areas from the aspects of identifying the surface types，retrieval of the parameters about vegetation，soil，water，atmosphere，and ecosystem in mining areas.The results show that the application of new remotely sensed data has improved the temporal and spatial resolution;the methods for identifying surface types and retrieving parameters in mining areas have been optimized，and the accuracy of identification and inversion has been improved;deep learning and remote sensing cloud computing platforms are preliminarily used in mining areas.However，there are also some shortcomings:① The application of deep learning in the identification of surface types in mining areas has not yet been fully developed，and there is a lack of remote sensing surface classification system standards and large-scale high resolution sample databases in mining areas.The level of automation and intelligence for surface types identification in mining areas needs to be improved;② The breadth of the retrieval of parameters using quantitative remote sensing needs to be expanded，and the methods of retrieving parameters need to be deepened;③ The research on the moderate-high resolution，long time series，high-frequency synchronous observation and collaborative analysis of multi-parameters in the mining area is relatively lacking.On this basis，prospects for future directions are listed as follows:① A remote sensing surface classification system and a large-scale high-resolution sample database for mining areas should be built，and the state of art deep learning algorithms should be tracked to achieve high precision identification of typical surface types in mining areas;② Quantitative remote sensing methods for physical mechanism modeling should be conducted in the scene of mining areas，and the parameters retrieved by remote sensing should be expanded，to improve the accuracy and stability of the retrieving methods;③ Integrating the multi-sources big data in mining areas，the systematic synchronous retrieval and monitoring of parameters should be conducted with moderate high resolution，long time series，and high frequency.

Key words: ecological restoration in mining area, monitoring by remote sensing, quantitative remote sensing, ecology and environment, research progress, developing direction, review