Suppr超能文献

基于谷歌地球引擎的中国皖北地区生态环境质量影响因素的动态监测与分析。

Dynamic monitoring and analysis of factors influencing ecological environment quality in northern Anhui, China, based on the Google Earth Engine.

机构信息

School of Architecture and Planning, Anhui Jianzhu University, Hefei, 230022, China.

出版信息

Sci Rep. 2022 Nov 24;12(1):20307. doi: 10.1038/s41598-022-24413-0.

Abstract

Monitoring the ecological environment quality is an important task that is often connected to achieving sustainable development. Timely and accurate monitoring can provide a scientific basis for regional land use planning and environmental protection. Based on the Google Earth Engine platform coupled with the greenness, humidity, heat, and dryness identified in remote sensing imagery, this paper constructed a remote sensing ecological index (RSEI) covering northern Anhui and quantitatively analyzed the characteristics of the spatiotemporal changes in the ecological environment quality from 2001 to 2020. Geodetector software was used to explore the mechanism driving the characteristics of spatial differentiation in the ecological environment quality. The main conclusions were as follows. First, the ecological environment quality in northern Anhui declined rapidly from 2001 to 2005, but the rate of decline slowed from 2005 to 2020 and a trend of improvement gradually emerged. The ecological environment quality of Huainan from 2001 to 2020 was better and more stable compared with other regional cities. Bengbu and Suzhou showed a trend of initially declining and then improving. Huaibei, Fuyang, and Bozhou demonstrated a trend of a fluctuating decline over time. Second, vegetation coverage was the main influencing factor of the RSEI, while rainfall was a secondary factor in northern Anhui from 2001 to 2020. Finally, interactions were observed between the factors, and the explanatory power of these factors increased significantly after the interaction. The most apparent interaction was between vegetation coverage and rainfall (q = 0.404). In addition, we found that vegetation abundance had a positive impact on ecological environment quality, while population density and urbanization had negative impacts, and the ecological environment quality of wetlands was the highest. Our research will provide a theoretical basis for environmental protection and support the high-quality development of northern Anhui.

摘要

监测生态环境质量是实现可持续发展的重要任务。及时、准确的监测可以为区域土地利用规划和环境保护提供科学依据。本研究基于 Google Earth Engine 平台,结合遥感影像中的绿度、湿度、热度和干燥度,构建了覆盖安徽北部的遥感生态指数(RSEI),并定量分析了 2001 年至 2020 年生态环境质量的时空变化特征。利用地理探测器软件探讨了生态环境质量空间分异特征的驱动机制。主要结论如下:首先,2001-2005 年安徽北部生态环境质量快速下降,但 2005-2020 年下降速度放缓,逐渐呈现出改善趋势。2001-2020 年淮南的生态环境质量要好于其他区域城市,且更加稳定。蚌埠和宿州呈现出先下降后上升的趋势。淮北、阜阳和亳州则呈现出波动下降的趋势。其次,植被覆盖度是 RSEI 的主要影响因素,降水是 2001-2020 年安徽北部的次要影响因素。最后,各因素之间存在交互作用,且交互作用后各因素的解释力显著增加。植被覆盖度与降水之间的交互作用最为明显(q=0.404)。此外,我们发现植被丰度对生态环境质量有正向影响,而人口密度和城市化水平则有负向影响,湿地的生态环境质量最高。本研究可为环境保护提供理论依据,支持安徽北部的高质量发展。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验