基于Landsat卫星遥感的2000年~2020年天山区植被覆盖时空变化研究

Temporal and Spatial Changes of Vegetation Cover in Tianshan Mountains from 2000 vegetatio to 2020 Based on Landsat Remote Sensing

植被是对应一个区域生态系统十分重要的组成部分,是评价和反映区域的气候与环境情况情况的重要指标。利用2000年~2020年三期不同时相Landsat系数据提取NDVI,基于像元二分模型估算天山区植被覆盖度。结果表明:(1)过去21年,天山区整体分析,植被覆盖面积和覆盖度均呈减小趋势,其中总植被覆盖面积降幅较明显,2020年相比2000年,总植被覆盖面积减小57.91km^(2),降幅为42.33%,其余极高、中与低覆盖面积有所减小,高覆盖面积基本稳定,裸地或极低覆盖面积增加;(2)近21年,三个时期增加区合计面积都大于减小区总和面积,主要以轻微改善区域与轻微退化区面积为主,整体上分析,天山区植被覆盖度变化不仅有阶段性差异,还存在区域性差异;(3)近21年,林地、草地、水域与未利用土地面积降幅分别为100%、14.3%、5.2%和1000%,耕地和建设用地面积增幅分别为320.6%和46.9%。

Vegetation is a very important component of the coresponding regional ecosystem,and an important indicator to evaluate and reflect the regional climate and environmental conditions.In this paper,NDVI is extracted from Landsat series data of three different phases from 2000 to 2020,and the vegetation coverage in Tianshan is estimated based on pixel dichotomy model.The results show that:(1)In the past 21 years,according to the overall analysis of Tianshan District,the vegetation coverage area and coverage have shown a decreasing trend,of which the total vegetation coverage area has decreased significantly.Compared with 2000,the total vegetation coverage area in 2020 has decreased by 57.91 km^(2),with a decrease of 42.33%.The other extremely high,medium and low coverage areas have decreased,the high coverage area is basically stable,and the bare land or extremely low coverage area has increased;(2)In the past 21 years,the total area of the increased areas in the three periods is greater than the total area of the reduced areas,mainly the areas of the slightly improved areas and the slightly degraded areas.On the whole,the changes in vegetation coverage in Tianshan District have not only staged differences,but also regional differences;(3)In the past 21 years,the area of forest land,grassland,water area and unused land decreased by 100%,14.3%,5.2%and 1000%respectively,and the area of cultivated land and construction land increased by 320.6%and 46.9%respectively.