基于S-G滤波的江西省植被覆盖度时空变化遥感分析

利用2004~2013年MODIS-EVI植被指数数据集,应用S-G滤波数据重建技术,采用像元二分模型和趋势分析法对江西省植被覆盖变化进行了时空动态监测。结果表明:S-G滤波能够有效提高植被指数产品数据质量;2013年江西省平均植被覆盖度为69.3%,处于中高覆盖度水平,空间分布呈现出"东西南三面高,中部和北部较低"的特点。2004年植被覆盖度最小为65.4%,2012年增加至最大值69.6%,整体呈现改善增加趋势。过去的10年中,植被覆盖增加面积为5.87×104km2,主要集中在抚州,萍乡市和赣州市以北地区;植被覆盖减少面积为4.53×104km2,主要集中在九江,宜春,南昌等地区。

[18] Stow D, Daeschner S, Hope A et al. Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the 1900s[J]. International Journal of Remote Sensing, 2003, 24(5): 1111-1117.Temporal and Spatial Analysis of Remotely Sensed Vegetation Coverage Changes

Based on MODIS-EVI vegetation index datasets in 2004-2013, S-G filter was applied for data reconstruction, then dimidiate pixel method, tendency analysis and correlation analysis was adopted to monitor vegetation coverage changes in Jiangxi Province. Results show that S-G filter can be useful in data quality improving. In 2013, the average of vegetation coverage is 66.7%, which is at high level in China. Compared with the middle and northern parts of the province, the other regions show a higher vegetation coverage in its spatial distribution. Furthermore, 2004 and 2013 has its minimum and maximum vegetation coverage with 65.4% and 69.6%. The areas of total improved region and total deterioration region are respectively 58700 km2 and 45300km2, which presents improved trend in the last 10 years. In detail, the improved region is mainly distributed in Fuzhou, Pinxiang, and northern area of Ganzhou, while deterioration region distributed in Jiujiang, Yichun and Nanchang. Forestation serves as a significant humanity impetus which contributes to the increase of vegetation coverage, while precipitation is the principle climate factor.