摘要
该文以巴楚县邦克尔国家湿地公园为研究对象,基于Landsat遥感影像数据,利用Fragstats软件对景观格局进行分析,并使用SPSS软件对景观格局指数与驱动因素进行分析。结果表明:(1)对景观类型变化分析后可知,邦克尔国家湿地公园的各个土地利用类型在1990—2020年的面积变化明显,水域面积减少了2229.51 hm^(2);草地面积在1990—2020年逐渐增加,其面积由616.81 hm^(2)增长到1748.10 hm^(2);未利用土地在1990—2020年间面积增加了624.21 hm^(2);林地面积在1990—2020年期间先减少后增加。(2)对邦克尔国家湿地公园的景观指数分析可知,湿地公园类型分布较为均匀,景观多样性较好,但破碎程度均加剧。(3)对邦克尔国家湿地公园的景观格局指数与驱动因素进行分析,结果说明自然因素对于邦克尔国家湿地公园的水域、林地变化具有显著作用,对于耕地、草地的变化有一定影响。而人为因素对于邦克尔国家湿地公园的建设用地及未利用地影响较大。
This paper takes Bangkel National Wetland Park in Bachu County as the research object,based on Landsat remote sensing image data,uses Fragstats software to analyze the landscape pattern,and uses SPSS software to analyze the landscape pattern index and driving factors.The results showed that:(1)After analyzing the change of landscape types,the area of each land use type in Bunkel National Wetland Park changed obviously from 1990 to 2020,and the water area decreased by 2229.51 hm^(2);The grassland area increased from 616.81 hm^(2)to 1748.10 hm^(2)from 1990 to 2020.The area of unused land increased by 624.21 hm^(2)from 1990 to 2020.The area of forest land decreased first and then increased during 1990-2020.(2)The landscape index analysis of Bunkel National Wetland Park shows that the types of wetland park are evenly distributed and the landscape diversity is good,but the degree of fragmentation is intensified.(3)The landscape pattern index and driving factors of Bunkel National Wetland Park were analyzed.The results show that natural factors have significant effects on the changes of water area and forest land in Bangkel National Wetland Park,and have certain effects on the changes of cultivated land and grassland.Human factors have a greater impact on the construction land and unused land of Bangkel National Wetland Park.
作者
张玉琪
颜安
ZHANG Yuqi;YAN An(College of Resource and Environment Science,Xinjiang Agricultural University,Urumqi,Xinjiang Uygur Autonomous Region,830025 China)
出处
《科技资讯》
2023年第2期70-74,134,共6页
Science & Technology Information
关键词
湿地公园
景观格局
变化
驱动因素
Wetland park
Landscape pattern
Change
Driving factors
