The land reclamation and its monitoring in coal mining area is of great significance to land use and ecological environment governance in China. The Microbial Reclamation Technology can promote the plant’s absorption and utilization for mineral nutrient and water, and strengthen the soil fertility, having a significant effect on ecological restoration of mining area. The traditional method for monitoring the land reclamation on plant growth is usually collecting plant and soil samples in the field for indoor analysis. But this method not only destroys rhizosphere soil, causing damages to plants, but also consumes large quantity of manpower, material resources, and time. The hyperspectral remote sensing technology has the advantages of fast data acquisition, large information, high precision and nondestructive for plants, having great potential for land reclamation monitoring. At present, the research on the monitoring of land reclamation through remote sensing still stays at the laboratory level of observing the leaf spectra of potted soybean, corn and other crops. In fact, the observation of satellite remote sensing data is the canopy spectra, not the leaf spectra, but now there is no research result on the monitoring of land reclamation in the mining area based on vegetation canopy spectra. The vegetation canopy spectrum is not only affected by the leaf spectrum, but also influenced by other factors such as plant growth condition and underlying surface, and the spectral change is more complicated. Analysis on susceptibility of vegetation canopy spectra in coal mining area to land reclamation is the basis of the quantitative inversion for the physical and chemical parameters of vegetation, and the main bottlenecks of the hyperspectral technology to be applied in large area reclamation monitoring.This research performs field experiment on vegetation canopy spectral observation in the land reclamation basement of coal mining area, obtains the wild plant canopy spectral data of reclamation group and the control group, and comprehensively analyses the spectral susceptibility of vegetation canopy spectra to land reclamation, from the aspects of spectral waveform and spectral feature parameters. In terms of the spectral waveform of canopy, standard deviation and spectral sensitivity are used as effective indicators for the difference of spectral waveform within each group and between two groups. As for the canopy spectral feature parameters, we selected the red edge, yellow edge, blue edge, red valley and green mountain as typical spectral features, calculated their parameters (such as wavelength position, slope and area), and performed descriptive statistical analysis and one-way ANOVA to investigate the canopy spectral feature parameters’ sensitivity to the effect of land reclamation. Results showed that the canopy spectral waveform trend of the reclamation group is similar with that of the control group, but the plants in the reclamation group have smaller spectral difference, and their vegetation typical features, such as green peak and red valley, are more prominent. This indicated that land reclamation can reduce the canopy spectral difference between plants and strengthen the typical vegetation spectral features, while green peak and red valley are the most sensible spectral features to land reclamation effect. In terms of the specific canopy spectral feature parameters, the wavelengths of green peak, red valley and red edge tend to shift to longer wavelength significantly under the function of land reclamation, but the slope of red edge and blue edge, which are sensitive to land reclamation changes in previous studies on leaf spectra, are not significant any more in this research. This showed that the analysis results based on vegetation canopy spectra in the field are not in consistent with previous laboratory analysis results of leaf spectra, which may be caused by vegetation types, growth cycle, the interference of soil background, etc. When monitoring the vegetation environment in mining area based on satellite or aerial remote sensing, the data obtained are canopy spectra, not leaf spectra. Therefore, the conclusions of this research have strong reference value for future practical applications.