{"title":"利用 LTSS 和修正的 RSEI 分析 1990-2020 年城市森林公园的生态环境质量--南京紫金山国家森林公园案例研究","authors":"Fang Ren, Jiaoyang Xu, Yi Wu, Tao Li, Mingyang Li","doi":"10.3390/f14122458","DOIUrl":null,"url":null,"abstract":"Evaluating the long-term urban forest ecological environmental quality (EEQ) and analyzing the drivers of its spatiotemporal changes can provide a scientific basis for making long-term urban forest planning decisions. Taking into account the characteristics of urban forest parks with low area proportions of construction land and bare land, high vegetation coverage, and serious forest disturbances, we constructed a modified urban forest park EEQ evaluation index based on a remote sensing ecological index named MRSEI, which is composed of the Landsat enhanced vegetation index (EVI), wetness, land surface temperature (LST), and forest disturbance index (FDI). We selected the Nanjing Zijin Mountain National Forest Park as the study area, used landsat time series stack (LTSS) remote sensing images from 1990 to 2020 as the main data source, and adopted the suggested modified MRSEI, the Theil-Sen median method, and the Hurst index to evaluate the EEQ to analyze its spatiotemporal variations and its driving factors in the study area. The main research results were as follows: (1) the EEQ of Zijin Mountain showed an up-and-down, overall slowly increasing trend from 1990 to 2020, while the spatial auto-correlation coefficient showed an overall decreasing trend; (2) the area percentage of the EEQ-persistent region accounted for 78.69%, and the anti-sustainable region accounted for 21.31%; (3) the spatial centers of the EEQ in the study area were mainly concentrated on the middle and upper part of the southern slope of Zijin Mountain, moving southward from 1990 to 2020; (4) the analysis of drivers showed that climate factors, forest landscape structure, forest disturbances, and forest growth conditions were the main driving factors affecting the EEQ in the study area. These results provide a research framework for the analysis of EEQ changes over a long-term period in the urban forest parks of China.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"339 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Eco-Environmental Quality of an Urban Forest Park Using LTSS and Modified RSEI from 1990 to 2020—A Case Study of Zijin Mountain National Forest Park, Nanjing, China\",\"authors\":\"Fang Ren, Jiaoyang Xu, Yi Wu, Tao Li, Mingyang Li\",\"doi\":\"10.3390/f14122458\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluating the long-term urban forest ecological environmental quality (EEQ) and analyzing the drivers of its spatiotemporal changes can provide a scientific basis for making long-term urban forest planning decisions. Taking into account the characteristics of urban forest parks with low area proportions of construction land and bare land, high vegetation coverage, and serious forest disturbances, we constructed a modified urban forest park EEQ evaluation index based on a remote sensing ecological index named MRSEI, which is composed of the Landsat enhanced vegetation index (EVI), wetness, land surface temperature (LST), and forest disturbance index (FDI). We selected the Nanjing Zijin Mountain National Forest Park as the study area, used landsat time series stack (LTSS) remote sensing images from 1990 to 2020 as the main data source, and adopted the suggested modified MRSEI, the Theil-Sen median method, and the Hurst index to evaluate the EEQ to analyze its spatiotemporal variations and its driving factors in the study area. The main research results were as follows: (1) the EEQ of Zijin Mountain showed an up-and-down, overall slowly increasing trend from 1990 to 2020, while the spatial auto-correlation coefficient showed an overall decreasing trend; (2) the area percentage of the EEQ-persistent region accounted for 78.69%, and the anti-sustainable region accounted for 21.31%; (3) the spatial centers of the EEQ in the study area were mainly concentrated on the middle and upper part of the southern slope of Zijin Mountain, moving southward from 1990 to 2020; (4) the analysis of drivers showed that climate factors, forest landscape structure, forest disturbances, and forest growth conditions were the main driving factors affecting the EEQ in the study area. These results provide a research framework for the analysis of EEQ changes over a long-term period in the urban forest parks of China.\",\"PeriodicalId\":12339,\"journal\":{\"name\":\"Forests\",\"volume\":\"339 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forests\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.3390/f14122458\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forests","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.3390/f14122458","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
Analysis of Eco-Environmental Quality of an Urban Forest Park Using LTSS and Modified RSEI from 1990 to 2020—A Case Study of Zijin Mountain National Forest Park, Nanjing, China
Evaluating the long-term urban forest ecological environmental quality (EEQ) and analyzing the drivers of its spatiotemporal changes can provide a scientific basis for making long-term urban forest planning decisions. Taking into account the characteristics of urban forest parks with low area proportions of construction land and bare land, high vegetation coverage, and serious forest disturbances, we constructed a modified urban forest park EEQ evaluation index based on a remote sensing ecological index named MRSEI, which is composed of the Landsat enhanced vegetation index (EVI), wetness, land surface temperature (LST), and forest disturbance index (FDI). We selected the Nanjing Zijin Mountain National Forest Park as the study area, used landsat time series stack (LTSS) remote sensing images from 1990 to 2020 as the main data source, and adopted the suggested modified MRSEI, the Theil-Sen median method, and the Hurst index to evaluate the EEQ to analyze its spatiotemporal variations and its driving factors in the study area. The main research results were as follows: (1) the EEQ of Zijin Mountain showed an up-and-down, overall slowly increasing trend from 1990 to 2020, while the spatial auto-correlation coefficient showed an overall decreasing trend; (2) the area percentage of the EEQ-persistent region accounted for 78.69%, and the anti-sustainable region accounted for 21.31%; (3) the spatial centers of the EEQ in the study area were mainly concentrated on the middle and upper part of the southern slope of Zijin Mountain, moving southward from 1990 to 2020; (4) the analysis of drivers showed that climate factors, forest landscape structure, forest disturbances, and forest growth conditions were the main driving factors affecting the EEQ in the study area. These results provide a research framework for the analysis of EEQ changes over a long-term period in the urban forest parks of China.
期刊介绍:
Forests (ISSN 1999-4907) is an international and cross-disciplinary scholarly journal of forestry and forest ecology. It publishes research papers, short communications and review papers. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.