基于地理探测器的菜子湖群湿地景观格局变化及驱动因子分析

Analysis of wetland landscape pattern variation and its driving factors of Caizi Lake group based on geodetector

选取1999年、2004年、2011年和2017年4期卫星遥感影像,采用网格分析法研究景观指数和人为干扰的时空分异规律,借助地理探测器和相关性分析相结合的方法,从人为活动和社会经济角度分析安徽菜子湖群湿地景观格局变化原因。结果表明:1999—2017年菜子湖群自然湿地面积减少,人工湿地面积增加;滩涂和沼泽草滩占比分别减少12.23%和13.84%,农田及养殖塘面积分别增加12.12 km^(2)和20.71 km^(2),非湿地面积略有增加;湿地破碎化,景观斑块连通性下降,斑块形状趋于简单化,景观异质性增加;湿地人为干扰强度增加,较高、高干扰等级占比增大;农田、养殖、围网及围坝等人为活动对斑块数量分布的影响在时间及空间上存在明显差异,人为活动因子的交互作用较单个因子作用影响显著增强;景观指数与三大产业产值、国内生产总值、人口、渔业生产、耕地面积等社会经济因子有显著相关性。

With the 1999,2004,2011,and 2017 Landsat remote sensing images used as the main data sources,this study reveals the spatiotemporal evolution of wetland landscape characteristics of the Caizi Lake group from 1999 to 2017 and their relationships with human activities and socioeconomic factors by means of the grid analysis method,geodetector,and correlation analysis.Results are as follows:the artificial wetland area gradually increased while the natural wetland area gradually degraded;mudflats and herbaceous marshes showed a decreasing tendency,with proportions reducing by 12.23%and 13.84%,respectively,the areas of paddy fields and aquaculture ponds increased by 12.12 km^(2) and 20.71 km^(2),respectively,and the non-wetland area increased slightly;with the increase of the land use intensity,the landscape was more fragmented,the connectivity between patches became weak,the shape of wetland patches tended to be simplified,and the landscape heterogeneity increased.From 1999 to 2017,the wetland of the Caizi Lake group was significantly affected by human activities,and areas with high and relatively high intensities of human interferences dramatically expanded with time.Different human activities caused significant differences of impacts on the number of patches in time and space,and the interaction effect of human activities was even higher on the number of patches.The variation of wetland landscape indexes of the Caizi Lake group has close relationships with socioeconomic factors,including the output values of three industries,GDP,population,fishery production,and arable area.