| Based on the dual concepts of ecological livability and people-oriented, this paper selected six indexes including regional greenness, regional heat, regional blueness, regional brightness, regional transparency and regional undulation to construct regional habitat environment index (RHEI) based on remote sensing by principal component analysis. Taking Fujian Province as an example, RHEI was calculated quarterly to reveal the spatial and temporal differences of regional habitat environment. The results showed that the RHEI in Fujian Province gradually decreased with seasonal changes, showing a spatial distribution pattern of low in the southeast and high in the northwest, and rising inland along the coastline. By comparing the regression model coefficients of each index, it was found that regional blueness had the greatest influence on regional habitat, while regional transparency had the least influence. Based on the annual mean regression model, every 0.166 units increase in regional blueness or 0.278 units decrease in regional heat in the future could improve the quality of habitat environment by 0.1 units. |
