Affiliation:
1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
2. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Abstract
Considering Inner Mongolia as the study area, the ecological theory of climate change, and human activities affecting a wide range of biodiversity patterns, MODIS multi-timeseries remote sensing image data were used and the interannual variation index was obtained by the method of fitting the curve to obtain the annual phenological and seasonal indicators. At the same time, the Landsat 8 standard deviation image was calculated to obtain the spatial variation index and generate spatial–temporal remote sensing indices to quantify the threat of climate change to biodiversity. In addition, the impact of human activities on biodiversity was quantified by generating a map of the human footprint in Inner Mongolia. The spatial–temporal remote sensing index and the human footprint index were integrated to identify areas protected from climate change and human activities, respectively. Eventually, the hotspot areas of biodiversity conservation in Inner Mongolia were obtained and priority protected area planning was based on the hotspot identification results. In this study, remote sensing technology was used to identify biodiversity conservation hotspots, which can overcome the limitations of insufficient species data from the past, improve the reliability of large-scale biodiversity conservation analyses, and be used for targeted management actions that have practical significance for biodiversity conservation planning.
Funder
Key Science and Technology Project of Inner Mongolia
Subject
Nature and Landscape Conservation,Agricultural and Biological Sciences (miscellaneous),Ecological Modeling,Ecology