摘要
为研究山东省植被覆盖时空变化趋势以及空间关联程度,基于2008—2020年的MODIS-NDVI数据,应用最大值合成法、一元线性回归分析、重心分析、空间自相关分析等方法,对山东省植被覆盖进行分析。结果表明:除北部黄河三角洲、莱州湾地区及南四湖植被覆盖较为匮乏外,山东省植被覆盖总体呈现良好的状态;线性回归分析与植被覆盖重心迁移路径分析表明山东省植被覆盖总体呈现稳定或增长趋势,2008—2020年植被覆盖重心坐标迁移方向为几个过程(东北方向、西南方向、西北方向、西南方向);空间自相关分析结果显示,全局Moran’s I为0.898,空间上有较强的相关性,植被覆盖呈空间聚集状态。局部空间相关性分析表明,山东省植被覆盖主要呈现出两种聚集趋势,除黄河三角洲和莱州湾以及南四湖地区,沿海地区NDVI表现为低-低自相关以外,山东省大部分地区呈高-高自相关。
To investigate the spatio-temporal change trend of vegetation cover and the spatial correlation degree in Shandong Province,based on MODIS-NDVI data from 2008 to 2020,we used MVC,linear regression analysis,barycenter analysis and spatial autocorrelation analysis meth-ods to study the change trend of vegetation cover in Shandong Province.The results show that in addition to the lack of vegetation cover in the northern Yellow River Delta,Laizhou Bay area and Nansi Lake,the vegetation cover in Shandong Province are generally in good condition.The linear regression analysis and the path analysis of gravity transfer center of vegetation cover indicate that the vegetation cover in Shandong Prov-ince shows a stable or increasing trend,from 2008 to 2020,the coordinate transfer directions of vegetation cover gravity include northeast direc-tion,southwest direction,northwest direction and southwest direction.The results of spatial autocorrelation analysis show that the global spatial auto-correlation index of NDVI is 0.898,indicated a positive global spatial auto-correlation,the vegetation cover is in a spatial aggregation state.Local spatial autocorrelation analysis shows that there are two main aggregation trends about vegetation cover,except the Yellow River Delta,Laizhou Bay and Nansi Lake,coastal areas show a low-low autocorrelation,and most areas show a high-high autocorrelation.
作者
段晨阳
王晓艳
DUAN Chenyang;WANG Xiaoyan(College of Geomatics,Xi’an University of Science and Technology,Xi’an 710054,China)
出处
《地理空间信息》
2022年第10期49-53,81,共6页
Geospatial Information
关键词
NDVI
时空变化
一元线性回归
重心分析
空间自相关
NDVI
spatio-temporal change
univariate linear regression
gravity analysis
spatial autocorrelation
