Analysis of differentiation effect of surface thermal environment in intensive mining areas based on NDVI-DFI model

Currently, the dimidiate pixel model is used in most studies to discuss vegetation fractional coverage (VFC) and explore its relationship with urban heat islands. Few studies have used the three-component pixel model to invert vegetation fractional coverage (VFC) and discuss the relationship between VFC and the differentiation effect of the surface thermal environment in mining-intensive areas. In this study, VFC was inverted based on the normalized difference vegetation index (NDVI)-dry fuel index (DFI) three-component pixel model using Landsat satellite remote sensing images from 2000 to 2018. Mixed pixels were decomposed into photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and bare soil (BS). The radiative transfer equation (RTE) was used to invert the surface temperature. The basic principle of this method is to remove the atmospheric influence and use the atmospheric radiation transfer equation; surface heat radiation intensity observed by the satellite is converted to the corresponding surface temperature. The parameters involved are mainly atmospheric profile parameters and surface specific emissivity. Heat-island index (HI) was used to grade the mean LST of the 2000-2018 study area. The relationship between the spatial-temporal changes in VFC and the differentiation effect of the surface thermal environment in the study area was analyzed using hierarchical statistics, a red-blue difference image method, correlation analysis, and regression analysis. On this basis, the influence mechanism of spatial-temporal variation in the VFC on the differentiation effect of surface thermal environment was studied. The results showed that the NDVI-DFI feature space of the study area conformed to the basic assumption of the three-component pixel model. The correlation matrix showed that there was a strong correlation between the changes in land surface temperature (LST) and VFC (the fractional cover of PV, fractional cover of NPV, and fractional cover of BS) from 2000 to 2018. The study areas of the fractional cover of PV, fractional cover of NPV, and fractional cover of BS have large overlap with the high, medium and low temperature regions in the LST eighteen-year mean distribution map based on the thermal field variation index, which indicates that the spatial distribution of vegetation coverage affects the surface temperature space to some extent. The correlations between fPV, fNPV, fBS and LST were ?0.81, 0.72, and 0.90 respectively, which indicated that changes in VFC had a significant impact on LST. The degree of influence of fPV, fNPV, and fBS changes on LST for the 19 years is ranked as fBS>fPV>fNPV. The regression analysis was between the vegetation fractional coverage and the surface temperature of the township administrative unit scale in the areas with intensive mining development. The results showed that fPV, fNPV, and fBS were very significant negative correlation (P<0.01), no significant positive correlation (P<0.01), and very significant positive correlation (P<0.01) with LST, respectively. To be specific, the land surface temperature (LST) decreased 0.52 ℃ with every 10% increase of fPV. It increased 0.61 ℃ and 0.98 ℃ respectively as the 10% increase of fNPV and fBS. The results provided a quantitative reference for the improvement of the surface thermal environment in mining-intensive areas.