Assessment of Habitat Quality in Arid Regions Incorporating Remote Sensing Data and Field Experiments

Abstract

China’s arid regions are particularly vulnerable to the adverse effects of climate change and human activities, which pose threats to habitat quality. Consequently, evaluations of these effects are vital for devising ecological strategies and initiating regional remediation efforts. However, environmental variations in arid areas can cause habitat quality fluctuations, which complicates precise assessments. This study introduces a refined methodology that integrates remote sensing data and field survey biomass data to modify the habitat quality estimates obtained from the InVEST model in the Altai region over three decades. A comparative analysis of the unmodified, normalized difference vegetation index (NDVI)-modified and biomass-modified habitat quality estimates was conducted. The results revealed an improvement in the correlation between habitat quality and field observations, with a significant increase in the R2 value from 0.129 to 0.603. The unmodified model exhibits subtle variations in habitat quality in mountainous areas, with a slight decline in the plains. However, the modified model shows an increasing trend in mountainous areas. This finding contrasts with the reductions in mountains typically reported by other studies. The refined approach accurately expresses the variations in habitat quality across different habitat types, with declines in forested areas and improvements in shrubland and grassland regions. This model is suitable for arid regions and accommodates urban and agricultural ecosystems affected by human activities, offering empirical data for biodiversity and habitat management.