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县域夜光遥感指数与生态环境状况指数相关性研究——以贵州省为例
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  • 英文篇名:Correlation between night light remote sensing index and ecological environment status index:a case study of Guizhou
  • 作者:宋善海 ; 王堃 ; 陈艳 ; 梁萍萍
  • 英文作者:SONG Shanhai;WANG Kun;CHEN Yan;LIANG Pingping;School of Geography and Environmental Science,Guizhou Normal University;Key Laboratory of Mountain Resources and Environmental Remote Sensing,Guizou Normal University;
  • 关键词:NPP-VIIRS ; 夜光遥感指数 ; 生态环境状况评价 ; EI指数
  • 英文关键词:NPP-VIIRS;;night lightremote sensing index;;ecological environment status evaluation;;EI index
  • 中文刊名:GZKX
  • 英文刊名:Guizhou Science
  • 机构:贵州师范大学地理与环境科学学院;贵州师范大学山地资源与环境遥感重点实验室;
  • 出版日期:2019-02-15
  • 出版单位:贵州科学
  • 年:2019
  • 期:v.37;No.149
  • 基金:国家自然科学基金项目(61540072)资助;; 贵州省科学技术基金(黔科合J字〔2014〕2127号)资助
  • 语种:中文;
  • 页:GZKX201901009
  • 页数:9
  • CN:01
  • ISSN:52-1076/N
  • 分类号:41-48+79
摘要
基于2015年NPP-VIIRS的年合成夜光遥感影像,经过预处理后,获取到500 m空间分辨率的贵州省夜光分布图,构建夜光强度(I_j)与夜光面积(S_j)两个夜光指数后统计分析得到贵州省88个地区的夜光状况信息。同时从生物丰度、植被覆盖、水网密度、土地胁迫、污染负荷五个方面通过EI指数对县域生态环境状况进行综合评价。最后分析探讨EI与I_j、S_j在县级尺度上的相关性,并构建回归模型。结果表明,贵州夜光分布主要集中在黔中、黔西地区,东西差异明显。生态环境状况结果则相反,黔东南地区生态环境状况最优,黔中、黔西地区则相对较差;分析证明了EI与S_j存在较高的负相关关系,且线性回归模型精度较高,结果验证显示70%的县域EI估算误差均不超过5%。表明了夜光面积指数可用于县级生态环境状况的快速评估,丰富了夜光遥感的应用领域。
        The night light remote sensing image of Guizhou Province with 500 m resolution was obtained based on the NPP-VIIRS synthetic night light remote sensing image of 2015.The luminous area index(I_j) and the luminous intensity index(S_j) were used to analyze the night light status of the 88 districts of Guizhou.At the same time,from the aspects of biological abundance,vegetation cover,water network density,soil stress and pollution load,the ecological environment status index(EI) was used to comprehensively evaluate the ecological environment status of Guizhou Province.Finally,the correlation between EI and I_j/S_jat county level was analyzed.The results showed that,night light mainly distributed in the central and west part of Guizhou,with obvious difference between west and east of Guizhou;on the other hand,the ecological environment status in the southeast part of Guizhou was the best,and in the central and west part the status was worse.The results confirmed that there was strong negative correlation between EI and S_j,and the linear regression model had high precision(EI error was within 5% in over 70% of the counties).In conclusion,the luminous area index can be used for county-level ecological environment quality assessment.
引文
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