Abstract: To understand the change in ecological environment quality and driving forces of Hebei Wuan national forest park, remote sensing data of the years 2005, 2013, and 2021 were utilized to investigate land use changes and ecological environment quality in the study area. Furthermore, the spatial distribution of POI density in the park in 2021 is discussed, and the geographic detector model is used to analyze the effects of elevation, slope, aspect, population density, POI density, greenness, wetness, dryness and heat based on the 2021 RSEI value is investigated, and the effects of relevant driving factor on- DOI:10.3969/j.issn.1000-1565.2023.02.012河北武安国家森林公园生态环境质量评价及驱动因子分析苏玉姣¹, 张鹏¹,张晓华²,赵艳丽²,李良涛¹(1. 河北工程大学 园林与生态工程学院,河北 邯郸 056000;2.武安林业局,河北 武安 056300)摘 要:为了解河北武安国家森林公园的生态环境质量变化及驱动因子,选择2005年、2013年和2021年3期遥感数据对研究区的土地利用变化及生态环境质量进行评价.此外,讨论了园内2021年POI密度的空间分布,并在2021年遥感生态指数(remote sensing ecological index, RSEI)的基础上,采用地理探测器模型分析园内高程、坡度、坡向、人口密度、POI密度、绿度、湿度、干度、热度对RSEI值的影响程度,并进一步探究相关驱动因子对RSEI模型中4项指标的影响程度.结果表明:1)2005—2013年,区域内生态环境质量出现“两级化”趋势,2013—2021年,西南区域的环境质量大幅提升,但生态质量较好的区域(主要位于自然保护区内)占比大幅下降;2)旅游开发较好的景区POI密度最高,旅游环线及重点乡镇的POI密度次之;3)绿度、湿度、干度、热度及高程对公园内RSEI值影响较强,而坡向、坡度及人口密度影响较弱,POI密度对RSEI值无显著影响;4)绿度、湿度对高程、坡度、坡向及人口密度较为敏感,干度和热度则不敏感.本研究成果可为国家森林公园生态环境管护优化提供依据.关键词:国家森林公园;生态环境质量;驱动因子;地理探测器模型中图分类号:S7 文献标志码:A 文章编号:1000-1565(2023)02-0197-10Ecological environment quality evaluation and driving factor analysis of Wuan national forest park in Hebei provinceSU Yujiao¹, ZHANG Peng¹, ZHANG Xiaohua², ZHAO Yanli², LI Liangtao¹(1.College of Landscape and Ecological Engineering,Hebei University of Engineering,Handan 056000,China;2.Wuan Forestry Bureau, Wuan 056300,China)Abstract: To understand the change in ecological environment quality and driving forces of Hebei Wuan national forest park, remote sensing data of the years 2005, 2013, and 2021 were utilized to investigate land use changes and ecological environment quality in the study area. Furthermore, the spatial distribution of POI density in the park in 2021 is discussed, and the geographic detector model is used to analyze the effects of elevation, slope, aspect, population density, POI density, greenness, wetness, dryness and heat based on the 2021 RSEI value is investigated, and the effects of relevant driving factor on- 收稿日期:2022-05-14 基金项目:河北省林业和草原科学技术研究项目(2001019);武安青崖寨国家级自然保护区建设项目(20180702);邯郸市科学技术研究与发展计划项目(1727201065) 第一作者: 苏玉姣(1994—), 女, 新疆阿克苏人,河北工程大学在读硕士研究生, 主要从事土地利用变化及生态环境评价研究.E-mail: 2506043414@qq.com 通信作者:李良涛(1978—), 男, 河北邯郸人, 河北工程大学副教授, 博士, 主要从事景观生态学研究.E-mail: liliangtao@hebeu.edu.cn第2期苏玉姣等:河北武安国家森林公园生态环境质量评价及驱动因子分析河北大学学报(自然科学版) 第43卷four indicators in the RSEI model were further explored. The results showed that: 1)From 2005 to 2013, the regions ecological environment quality displayed a “two-level” pattern; from 2013 to 2021, the southwest regions environmental quality grew dramatically, while the number of regions with greater ecological quality declined significantly, mostly in nature reserves;2)The POI density of scenic spots with better tourism development is the highest, followed by the POI density of tourist ring roads and key towns;3)Greenness, wetness, dryness, heat and elevation had strong effects on RSEI values of the park, whereas aspect, slope and population density have lower impact, POI density has no significant effect on RSEI value;4)While wetness and greenness are more sensitive to elevation, slope, aspect, and population density, dryness and heat are not. The findings of this study can be used to improve ecological environment management and protect national forest parks.

Key words: national forest park, ecological environment quality, driving factor, geographical detector model