Abstract
The Qinling Mountains represent the dividing line of the natural landscape of north-south in China. The prediction on vegetation coverage is important for protecting the ecological environment of the Qinling Mountains. In this paper, the data accuracy and reliability of three vegetation index data (GIMMS NDVI, SPOT NDVI, and MODIS NDVI) were compared at first. SPOT, NDVI, and MODIS NDVI were used for calculating the vegetation coverage in the Qinling Mountains. Based on the CA–Markov model, the vegetation coverage grades in 2008, 2010, and 2013 were used to simulate the vegetation coverage grade in 2025. The results show that the grades of vegetation coverage of the Qinling Mountains calculated by SPOT, NDVI, and MODIS NDVI are highly similar. According to the prediction results, the grade of vegetation coverage in the Qinling Mountains has a rising trend under the guidance of the policy, particularly in urban areas. Most of the vegetation coverage transit from low vegetation coverage to middle and low vegetation coverage. The grades of the vegetation coverage, which were predicted by the CA–Markov model using SPOT, NDVI, and MODI NDVI, are consistent in spatial distribution and temporal variation.
Highlights
As an important part of the global ecosystem, the vegetation plays an irreplaceable role in the ecological protection, ecological stability, and social environment [1,2]
Comparing with SPOT normalized difference vegetation index (NDVI), the red light band of GIMMS NDVI is narrower, which reduces the sensitivity of chlorophyll to red light radiation
As the detected vegetation index is greatly affected by the water of green vegetation, the interference of water vapor makes the average value of GIMMS NDVI
Summary
As an important part of the global ecosystem, the vegetation plays an irreplaceable role in the ecological protection, ecological stability, and social environment [1,2]. Vegetation coverage is the ratio of the vertical projection area of the vegetation to the unit area It is a quantitative indicator of the growth of vegetation, which reflects the conditions of vegetation [5,6]. As a very important ecological climate parameter, vegetation coverage is a comprehensive quantitative indicator for the surface condition of phytocoenosium, which is the basic data for studying regional or global issues in hydrology, meteorology, and ecology. It is widely used in the theories and models of geological disasters, geological structures, natural environment evolution, and soil and water conservation [7,8]. The normalized difference vegetation index (NDVI) is considered as the commonly used VI due to its high sensitivity and good temporal and spatial adaptability [11]
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