Tian Zhi-Hui, Yin Chuan-Xin, Wang Xiao-Lei
School of Earth Sciences and Technology, Zhengzhou University, Zhengzhou 450000, China.
Joint Laboratory of Eco-meteorology, Zhengzhou University-Chinese Academy of Meteorological Sciences, Zhengzhou University, Zhengzhou 450000, China.
Huan Jing Ke Xue. 2023 Feb 8;44(2):816-827. doi: 10.13227/j.hjkx.202201097.
The ecological environment of Poyang Lake basin is an important part of the construction of ecological civilizations in the south of China. Based on the Landsat satellite remote sensing images, using the principal component analysis (PCA) method to construct the remote sensing ecological index (RSEI) as an evaluation index of ecological environment quality, introducing the Geodetector model to quantitatively detect the explanatory power of different influencing factors on the spatial divergence of the ecological environment, and exploring the changes in ecological environment quality in the Poyang Lake basin from 1990 to 2020 and the impact of different driving factors. The results of the study showed that there were obvious regional differences in the ecological environment quality in the basin. The areas with bad and poor ecological quality were mainly distributed in the central and northern plains; the areas with high and good quality grades were mainly distributed in the hilly and mountainous region of the southwestern part of the basin; the overall ecological environment of the Poyang Lake basin has been improving over the past 30 years; and the improved areas were mainly distributed in low-altitude areas. Geodetector results showed that population density was the factor with the highest explanatory power for the spatial divergence of ecological environment quality in the Poyang Lake basin. Among different natural factors, topographic factors (slope, aspect) had a higher driving force than meteorological factors (temperature, precipitation). The night light index factor showed an increasing yearly trend, indicating that the ecological environment quality of the Poyang Lake basin was gradually increased due to the influence of urbanization development. The construction of the RSEI model based on Google Earth Engine could not only effectively ensure the accuracy of ecological environment quality evaluation in different years but could also quickly realize image preprocessing and index calculations, which greatly improved the efficiency of ecological environment evaluation. These research results can provide a theoretical basis and scientific data support for the ecological environment protection work in the Poyang Lake basin.
鄱阳湖流域的生态环境是中国南方生态文明建设的重要组成部分。基于Landsat卫星遥感影像，运用主成分分析法构建遥感生态指数（RSEI）作为生态环境质量评价指标，引入地理探测器模型定量探测不同影响因素对生态环境空间分异的解释力，探究1990—2020年鄱阳湖流域生态环境质量变化及不同驱动因素的影响。研究结果表明：流域生态环境质量存在明显的区域差异，生态质量较差和差的区域主要分布在中部和北部平原；质量等级高和好的区域主要分布在流域西南部的丘陵山区；近30年来鄱阳湖流域整体生态环境不断改善，改善区域主要分布在低海拔地区。地理探测器结果显示，人口密度是鄱阳湖流域生态环境质量空间分异解释力最高的因素。在不同自然因素中，地形因素（坡度、坡向）的驱动力高于气象因素（气温、降水）。夜光指数因子呈逐年上升趋势，表明受城镇化发展影响，鄱阳湖流域生态环境质量逐渐提升。基于谷歌地球引擎构建RSEI模型，不仅能有效保证不同年份生态环境质量评价的准确性，还能快速实现影像预处理和指数计算，大大提高了生态环境评价效率。这些研究成果可为鄱阳湖流域生态环境保护工作提供理论依据和科学数据支撑。
