Abstract: Landscape index is a constant quantitative index to study the evolution of landscape pattern, and exploring the change of landscape pattern is of great practical significance to maintain the sustainable development of nature reserves. By using the moving window method in ArcGIS and Fragstats software, this paper spatialized the selected landscape index, analyzed it from the two aspects of time and space, and studied the spatial-temporal evolution characteristics and change rules of Hengshui Lake wetland landscape index. The results showed that before the Yellow River diversion, the area of farmland and unused land changed sharply, resulting in a high degree of fragmentation. The low-value area of landscape index was distributed all around the lake area and transferred to the lake area. With the beginning of yellow diversion, especially after 1999, the aggregation degree of all types of patches was strengthened, the edge shape became regular, and the degree of fragmentation was reduced. In recent years, due to the increase of residential areas and unused land area, the degree of human interference has increased, resulting in the increase of landscape diversity and the gradual transfer of low-value landscape index areas to construction land in the peripheral protection belt. It is of great guiding significance for wetland landscape evolution and land resource utilization to analyze the changes of landscape types in Hengshui Lake and explore the characteristics of patch evolution under different driving factors.

Key words: Hengshui Lake wetland, landscape index, spatial and temporal variation, moving window method, driving factors

摘要： 景观指数是研究景观格局演变的常量化指标,探究景观格局变化对维持自然保护区的可持续发展具有重要现实意义。文中借助ArcGIS与Fragstats软件中的移动窗口法将选取的景观指数空间化,从时间以及空间2个层面进行分析,针对衡水湖湿地景观指数时空演变特征及变化规律展开研究。结果表明:引黄前农田与未利用地面积变化较为剧烈,造成破碎化程度较高,景观指数低值区分布基本遍布湖区四周,并向湖区转移;随着引黄开始尤其1999年后各类型斑块聚集程度加强,边缘形状规律化,破碎程度减轻;近年来由于居民点与未利用地面积的增加,人类干扰程度加大,造成景观多样性增加、景观指数低值区逐渐向外围保护带的建设用地转移。分析衡水湖景观类型的更迭变化规律,探究不同驱动因子影响下的斑块演化特征,对湿地景观时空演变与土地资源利用具有重要指导意义。

关键词: 衡水湖湿地, 景观指数, 时空变化, 移动窗口法, 驱动因子