山东省植被覆盖度长时序动态监测与分析

Long-term Dynamic Monitoring and Analysis of Vegetation Coverage in Shandong Province

针对经典的遥感影像处理方式已难以满足大范围、多模态、高效率的监测需求的问题,本文基于Google Earth Engine(GEE)遥感大数据云平台,收集山东省2000-2020年Landsat系列、哨兵2号、MODIS共27614景遥感影像,采用像元二分模型、趋势分析法等手段,探讨山东省21年间植被覆盖度的时空变化特点及其变化趋势。实验结果表明,计算所得植被覆盖度数据精度评定指标相关系数在2013年为0.62,在2017年为0.64,同时得出以下结论:1)2000-2020年间,山东省年均植被覆盖度为65.6%;2)山东省植被覆盖度呈现全局增长趋势;3)山东省境内77.1%地区的植被覆盖度呈现高、中高稳定性,85.4%的区域持续性明显。本文研究结果有望应用于山东省生态环境质量与碳固定等指标的监测与分析。

The classic remote sensing image processing method cannot meet the needs of large-scale,multi-modal,and high-efficiency vegetation monitoring.Based on the Google Earth Engine(GEE)remote sensing big data cloud platform,we calculated and analyzed the vegetation coverage data of Shandong Province over the past 21 years.We collected Landsat-4,-5,-7,-8,Sentinel-2 and MODIS data in Shandong Province from 2000 to 2020,a total of 27614 remote sensing images,and carried out batch processing such as cloud removal and mosaic on the GEE platform.Based on the Dimidiate pixel model,trend analysis and other methods,we evaluated the characteristics and trends in the temporal and spatial changes of vegetation coverage in Shandong Province.Experimental results show that the correlation coefficient between our vegetation coverage and existing data was 0.62 in 2013 and 0.6 in 2017.We drew the following conclusions:1.From 2000 to 2020,the average annual vegetation coverage in Shandong Province was 65.6%;2.The vegetation coverage in Shandong Province shows a global growth trend;3.The vegetation coverage in 77.1%of Shandong Province is high and medium-high,and 85.4%has obvious sustainability.The results of this study are expected to be applied to the monitoring and analysis of indicators such as the quality of the ecological environment and carbon fixation in Shandong Province.