Using the Google Earth Engine to rapidly monitor impacts of geohazards on ecological quality in highly susceptible areas

Abstract

Frequent geohazards have knock-on effects on ecological quality. Timely and dynamically monitoring the damage of geohazards to ecological quality is important to the geological hazards prevention, ecological restoration, and policy formulation. Existing studies mainly focused on the impacts of climate change, urbanization, and extreme weather on the ecological quality, largely ignoring the role of frequent geohazards in the highly susceptible area. At present, the impact mechanism of the high susceptibility of geohazards on ecological quality remains unknown. To fill this knowledge gap, we use the Remote Sensing Ecological Index (RSEI, a widely accepted ecological quality index) calculated on the Google Earth Engine (GEE) platform, geohazard density data, and the Landsat series of surface reflectance datasets to explore the mechanism that drives spatial–temporal variations of ecological quality. Taking the Danba County as the study area, our results indicate that the total number of geohazards is 944 during 1995–2019, and the number of geohazards fluctuates and rises every year (10 in 1995 and 82 in 2019). A conceptual framework was proposed to quantify the impact of the high susceptibility of geohazards on ecological quality by separately exploring its impact on the 4 ecological components of RSEI (i.e., greenness, wetness, dryness, and heat). We found that the density of geohazards is significantly negatively correlated with greenness (R = 0.48, Pearson Correlation Coefficient (PCC) = −0.528, p < 0.01), and humidity (R = 0.45, PCC = −0.364, p < 0.01), whereas it is significantly positively correlated with dryness (R = 0.63, PCC = -0.335, p < 0.01) and heat (R = 0.47, PCC = −0.368, p < 0.01). Therefore, geohazards make a negative contribution to ecological quality by reducing greenness and humidity and increasing dryness and heat. This study provides insights on the mechanism of geohazards on ecological quality, benefiting stakeholders in designing better management plans for sustainable ecosystem cycling, application of GEE, and geological remote sensing.