基于改进遥感生态指数的岩溶山区生态质量评价——以澄碧河流域为例

孙桂凯; 王国帅; 魏义熊; 赵荣娜; 莫崇勋; 杨云川

doi:10.13961/j.cnki.stbctb.2021.02.031

您当前的位置：

首页 >

文章列表页 >

基于改进遥感生态指数的岩溶山区生态质量评价——以澄碧河流域为例

试验研究

- 基于改进遥感生态指数的岩溶山区生态质量评价——以澄碧河流域为例
- Improvement of Remote Sensing Ecological Index in Karst Mountainous Areas—Taking Chengbi River Basin as an Example
- 水土保持通报 2021年41卷第2期页码：230-239
- 作者机构：
  
  1. 广西大学土木建筑工程学院,广西,南宁,530004
  2. 工程防灾与结构安全教育部重点实验室,广西,南宁,530004
  3. 广西防灾减灾与工程安全重点实验室,广西,南宁,530004
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“基于长短期优化调度嵌套的西南岩溶区流域水库智能调度决策研究”（51969004）;广西自然科学基金项目（2017GXNSFAA198361）;广西研究生教育创新计划项目（YCBZ2019022）
- DOI：10.13961/j.cnki.stbctb.2021.02.031
  中图分类号： X87;X171.1
- 纸质出版：2021
- 稿件说明：
移动端阅览
孙桂凯, 王国帅, 魏义熊, 等. 基于改进遥感生态指数的岩溶山区生态质量评价——以澄碧河流域为例[J]. 水土保持通报, 2021,41(2):230-239.

Sun Guikai, Wang Guoshuai, Wei Yixiong, et al. Improvement of Remote Sensing Ecological Index in Karst Mountainous Areas—Taking Chengbi River Basin as an Example[J]. Bulletin of Soiland Water Conservation, 2021, 41(2): 230-239.
孙桂凯, 王国帅, 魏义熊, 等. 基于改进遥感生态指数的岩溶山区生态质量评价——以澄碧河流域为例[J]. 水土保持通报, 2021,41(2):230-239. DOI： 10.13961/j.cnki.stbctb.2021.02.031.

Sun Guikai, Wang Guoshuai, Wei Yixiong, et al. Improvement of Remote Sensing Ecological Index in Karst Mountainous Areas—Taking Chengbi River Basin as an Example[J]. Bulletin of Soiland Water Conservation, 2021, 41(2): 230-239. DOI： 10.13961/j.cnki.stbctb.2021.02.031.

摘要

[目的] 研究澄碧河流域1988—2019年生态环境的时空演变特征及其变化原因，旨在快速、科学地评价岩溶区生态环境质量变化，为岩溶区生态环境的保护、治理以及发展规划提供科学依据。[方法] 基于Landsat遥感影像，引入归一化山地植被指数（NDMVI），改进综合生态评价指数（CEEI）模型，对西南典型岩溶区澄碧河流域1988—2019年生态环境质量进行动态监测，利用空间自相关方法定量分析流域生态环境质量的空间分布特征。[结果] ①CEEI具有一定的科学性，并能较好反映研究区生态环境质量情况及时空分异特征；②1988—2019年研究区生态环境质量处于中上水平，整体呈上升趋势，低值区主要分布在流域北部岩溶峰林区与库区周边；③研究区生态环境质量具有一定的空间正相关关系，但聚集性逐渐减弱。[结论] 改进的CEEI模型能够较好地反映澄碧河流域生态环境质量。澄碧河流域CEEI均值总体呈上升趋势，生态环境质量得到改善。

Abstract

[Objective] The spatio-temporal evolution characteristics of the ecological environment in Chengbi River basin from 1988 to 2019

and the causes of its change were studied

in order to provide scientific basis for the protection

management and development planning of the ecological environment in karst area

and scientifically evaluate the change of ecological environment quality in karst area.[Methods] Based on Landsat images

the normalized difference mountain vegetation index (NDMVI) was introduced

and the comprehensive ecological evaluation index (CEEI) model was improved. The ecological environment quality of a typical karst basin in Southwest China

the Chengbi River basin was dynamically monitored from 1988 to 2019. The spatial distribution characteristics of the ecological environment quality in the basin were quantitatively analyzed using spatial autocorrelation methods

and the causes of ecological environment quality changes in the study area were analyzed.[Results] ① CEEI could scientifically reflect the ecological environment quality of the study area. ② The quality of the ecological environment in the research area from 1988 to 2019 was at the middle and upper middle level

and the overall trend was increasing. The low value areas were mainly distributed in the karst peak forest area and surrounding the reservoir area in the northern part of the basin. ③ The ecological environment quality of the study area had a certain spatial positive correlation

but the aggregation gradually weakened. ④ Vigorously carrying out the construction of ecological civilization and the management of stone desertification had greatly promoted the improvement of ecological environment quality in karst areas.[Conclusion] The improved CEEI model can better reflect the ecological environment quality of Chengbi River basin

the average CEEI of Chengbi River basin is on the rise

and the ecological environment quality has been improved.

关键词

Keywords

references

李先琨,何成新,蒋忠诚.岩溶脆弱生态区生态恢复、重建的原理与方法[J].中国岩溶,2003(1):12-17.

苏维词,李久林.乌江流域生态环境预警评价初探[J].贵州科学,1997(3):207-214.

田佳良.区域生态环境质量评价研究综述[J].环境保护与循环经济,2013,33(11):63-66.

Sun Jinyu, Wang Xuhui, Chen Anping, et al. NDVI indicated characteristics of vegetation cover change in China's metropolises over the last three decades[J]. Environ Monit Assess, 2011,179(1/4):1-14.

Badreldin N, Goossens R. A satellite-based disturbance index algorithm for monitoring mitigation strategies effects on desertification change in an arid environment[J]. Mitigation and Adaptation Strategies for Global Change, 2015,20(2):263-276.

徐涵秋.区域生态环境变化的遥感评价指数[J].中国环境科学,2013,33(5):889-897.

张乃明,陈冬花,邢菲,等.基于遥感生态指数的新疆干旱区博乐市生态变化分析[J].水土保持通报,2019,39(1):154-159.

张灿,徐涵秋,张好,等.南方红壤典型水土流失区植被覆盖度变化及其生态效应评估:以福建省长汀县为例[J].自然资源学报,2015,30(6):917-928.

Jing Yunqing, Zhang Fei, He Yufeng, et al. Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China[J]. Ecological Indicators, 2020,110:105874.

Yang Chao, Zhang Chenchen, Li Qingquan, et al. Rapid urbanization and policy variation greatly drive ecological quality evolution in Guangdong-Hong Kong-Macau Greater Bay Area of China:A remote sensing perspective[J]. Ecological Indicators, 2020,115:106373.

王小宇.基于遥感生态指数的石漠化地区生态环境质量评价[D].贵州贵阳:贵州师范大学,2019.

余晓芳.基于遥感生态指数的喀斯特地区生态环境质量变化研究[D].贵州贵阳:贵州师范大学,2018.

蒋忠诚,等.岩溶峰丛洼地生态重建[M].北京:地质出版社,2007.

闻建光,柳钦火,肖青,等.复杂山区光学遥感反射率计算模型[J].中国科学(D辑):地球科学,2008,33(11):1419-1427.

杨奇勇,蒋忠诚,罗为群,等.岩溶区峰丛洼地山体阴影区域植被指数随机模拟[J].农业机械学报,2013,44(5):232-236.

莫崇勋,覃俊凯,段丽敏,等.基于Burn-in和D8法的岩溶区流域边界提取研究[J].广西大学学报(自然科学版),2020,45(1):248-253.

郭永强,王乃江,褚晓升,等.基于Google Earth Engine分析黄土高原植被覆盖变化及原因[J].中国环境科学,2019,39(11):4804-4811.

徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005(5):589-595.

吴志杰,徐涵秋.卫星影像数据构建山地植被指数与应用分析[J].地球信息科学学报,2011,13(5):656-664.

吴志杰,何国金,黄绍霖,等.南方丘陵区植被覆盖度遥感估算的地形效应评估[J].遥感学报,2017,21(1):159-167.

李苗苗,吴炳方,颜长珍,等.密云水库上游植被覆盖度的遥感估算[J].资源科学,2004(4):153-159.

梁晓.云南鹤庆县石漠化地区典型植物生理生态适应性研究[D].广西南宁:广西师范大学,2014.

胡秀娟,徐涵秋,郭燕滨,等.水土流失区生态修复后植被健康的遥感判别[J].应用生态学报,2017,28(1):250-256.

John R, Chen J, Lu N, et al. Predicting plant diversity based on remote sensing products in the semi-arid region of Inner Mongolia[J]. Remote Sensing of Environment, 2008,112(5):2018-2032.

Bausch W C. Remote sensing of plant nitrogen status in Corn[J]. Transactions of the Asae, 1996,39(5):1869-1875.

Huang Chengquan, Wylie B, Yang Limin, et al. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance[J]. International Journal of Remote Sensing, 2002,23(8):1741-1748.

Hu Xisheng, Xu Hanqiu. A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality:A case from Fuzhou City, China[J]. Ecological Indicators, 2018,89:11-21.

Nichol J. Remote sensing of urban heat islands by day and night[J]. Photogrammetric Engineering and Remote Sensing, 2005,71(5):613-621.

覃志豪, 李文娟, 徐斌, 等. 陆地卫星TM6波段范围内地表比辐射率的估计[J]. 国土资源遥感, 2004, 3(61):28-32.

宋慧敏,薛亮.基于遥感生态指数模型的渭南市生态环境质量动态监测与分析[J].应用生态学报,2016,27(12):3913-3919.

徐涵秋.水土流失区生态变化的遥感评估[J].农业工程学报,2013,29(7):91-97.

王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134.

张金茜,巩杰,柳冬青.地理探测器方法下甘肃白龙江流域景观破碎化与驱动因子分析[J].地理科学,2018,38(8):1370-1378.

浏览量

1201

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

高寒地区荒漠化动态监测技术构想

长江三峡工程库区水土保持遥感动态监测及 GIS系统开发

基于遥感和GIS的全国土壤侵蚀动态监测方法研究

沂蒙山区农业碳排放时空特征与脱钩弹性

基于CiteSpace的中国荒漠植物多样性研究现状与热点分析