地表过程研究

基于遥感的库尔勒地区生态环境质量评价及成因分析

  • 李世娇 ,
  • 张珂珂 ,
  • 谢宝妮 ,
  • 王世文 ,
  • 李治广
展开
  • 1.河北地质大学城市地质与工程学院,河北 石家庄 050031
    2.河北地质大学-河北省农业干旱遥感监测国际联合研究中心,河北 石家庄 050031
    3.河北地质大学-河北省地下人工环境智慧开发与管控技术创新中心,河北 石家庄 050031
李世娇(2000-),女,硕士研究生,主要从事地质灾害及防治等方面的研究. E-mail: lsj_149@126.com
李治广(1978-),男,博士,副教授,主要从事区域生态环境等方面的研究. E-mail: lizhg1978@126.com

收稿日期: 2024-04-21

  修回日期: 2024-05-13

  网络出版日期: 2025-01-02

基金资助

国家自然科学基金项目(42001380)

Ecological environment quality evaluation and driving factors of Korla region based on remote sensing

  • LI Shijiao ,
  • ZHANG Keke ,
  • XIE Baoni ,
  • WANG Shiwen ,
  • LI Zhiguang
Expand
  • 1. School of Urban and Engineering, Hebei GEO University, Shijiazhuang 050031, Hebei, China
    2. Hebei GEO University-Hebei International Joint Research Center for Remote Sensing of Agriculture Drought Monitoring, Shijiazhuang 050031, Hebei, China;
    3. Hebei GEO University-Hebei Technology Innovation Center for Intelligent Development and Control of Underground Built Environment, Shijiazhuang 050031, Hebei, China

Received date: 2024-04-21

  Revised date: 2024-05-13

  Online published: 2025-01-02

摘要

库尔勒地区生态环境敏感脆弱,准确认知该地区的生态环境质量是当地政府科学制定生态环境保护和修复政策的基础。基于遥感生态指数思想,结合研究区生态系统特征,耦合植被覆盖、土壤湿度、地表温度、地表干度、沙漠化程度、盐渍化程度、蒸散发7个生态要素,采用主成分分析法构建了改进型遥感生态指数(Modified remote sensing based ecology index,MRSEI),对1994—2021年库尔勒地区生态环境质量进行评价和成因分析。结果表明:(1)MRSEI可以反映库尔勒地区的生态环境质量。(2)1994—2021年库尔勒地区MRSEI变化范围为0.253~0.346,总体为上升趋势,生态环境质量整体改善;生态环境质量等级以“差”和“较差”为主,二者面积占比为70.96%,整体生态环境质量呈现为“西部相对较差、东部相对较好”。(3)近27 a来,库尔勒地区60.41%面积上生态环境质量基本不变,主要分布在丘陵西部和台地;16.47%的面积上生态环境质量退化,主要分布在平原北部、部分中起伏山地和小起伏山地;23.12%的面积上生态环境质量改善,主要分布在平原和丘陵的东部。(4)气候、社会经济与库尔勒地区生态环境质量关系密切,其中蒸发量对生态环境质量的影响高于其他气候要素,年末总人口是影响该地区生态环境质量的第一社会经济要素。

本文引用格式

李世娇 , 张珂珂 , 谢宝妮 , 王世文 , 李治广 . 基于遥感的库尔勒地区生态环境质量评价及成因分析[J]. 干旱区地理, 2024 , 47(12) : 2064 -2074 . DOI: 10.12118/j.issn.1000-6060.2024.250

Abstract

The ecological environment of the Korla region, Xinjiang, China is highly sensitive and fragile, requiring meticulous attention and sustained efforts for its preservation. Understanding the variations in ecological environment quality in this area is crucial, forming the foundation for effective ecological protection and restoration policies by local authorities. This study employs the innovative concept of the remote sensing ecological index, adapted specifically temperature, land surface dryness, desertification degree, salinization degree, and evapotranspiration—a refined index termed the modified remote sensing ecological index (MRSEI) is developed through principal component analysis. This refined index is applied to conduct a comprehensive evaluation and analysis of the factors influencing the ecological environment quality in the Korla region from 1994 to 2021. The results demonstrate that the MRSEI effectively reflects the ecological environment quality of the Korla region. From 1994 to 2021, the MRSEI ranged from 0.253 to 0.346, showing an overall upward trend and indicating an improvement in ecological environment quality. However, the overall ecological environment quality is primarily categorized as “poor” and “relatively poor”, covering 70.96% of the area. The overall spatial distribution reveals a pattern of “relatively poor” in the western part and “relatively good” in the eastern part. Over the 27-year period, approximately 60.41% of the area exhibited minimal change in ecological environment quality, mainly in the western hilly areas and tablelands. Around 16.47% of the area experienced ecological degradation, particularly in the northern plains and some moderately and slightly undulating mountain areas, while 23.12% of the region showed improvement, primarily in the eastern plains and hilly regions. Climate and socioeconomic factors are closely linked to the ecological environment quality in the Korla region. Among climatic factors, evaporation exerts the most significant impact, while among socioeconomic factors, the year-end total population is the primary driver influencing ecological environment quality.

参考文献

[1] 杨宇, 李小云, 董雯, 等. 中国人地关系综合评价的理论模型与实证[J]. 地理学报, 2019, 74(6): 1063-1078.
  [Yang Yu, Li Xiaoyun, Dong Wen, et al. Comprehensive evaluation on China’s man-land relationship: Theoretical model and empirical study[J]. Acta Geographica Sinica, 2019, 74(6): 1063-1078.]
[2] 李桂花, 杜颖. “绿水青山就是金山银山”生态文明理念探析[J]. 新疆师范大学学报(哲学社会科学版), 2019, 40(4): 43-51.
  [Li Guihua, Du Ying. On the conviction that “lucid waters and lush mountains are invaluable assets”[J]. Journal of Xinjiang Normal University (Philosophy and Social Sciences Edition), 2019, 40(4): 43-51.]
[3] 刘纪远, 邵全琴, 樊江文, 等. 中国西部地区生态保护建设路径的探讨[J]. 中国人口·资源与环境, 2013, 23(10): 38-43.
  [Liu Jiyuan, Shao Quanqin, Fan Jiangwen, et al. Exploration on the path of ecological protection and construction in western China[J]. China Population, Resources and Environment, 2013, 23(10): 38-43.]
[4] 张朝辉, 于师琪. 基于土地利用情景模拟的和田地区生态系统服务价值时空特征与交互驱动研究[J]. 农业资源与环境学报, 2024, 41(4): 780-793.
  [Zhang Zhaohui, Yu Shiqi. Spatio-temporal characteristics and interaction drivers of ecosystem service value in Hotan region based on land-use scenario simulation[J]. Journal of Agriculture Resources and Environment, 2024, 41(4): 780-793.]
[5] 周寅桥, 李雄. 基于水体型生态指数的无锡市城区生态质量时空变化分析[J]. 生态学报, 2024, 44(4): 1476-1490.
  [Zhou Yinqiao, Li Xiong. Spatio-temporal changes of ecological quality in Wuxi urban area based on water-beneficial ecological index[J]. Acta Ecologica Sinica, 2024, 44(4): 1476-1490.]
[6] Jing Y Q, Zhang F, He Y F, 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(1): 105874, doi: 10.1016/j.ecolind.2019.105874.
[7] 徐涵秋. 城市遥感生态指数的创建及其应用[J]. 生态学报, 2013, 33(24): 7853-7862.
  [Xu Hanqiu. A remote sensing urban ecological index and its application[J]. Acta Ecologica Sinica, 2013, 33(24): 7853-7862.]
[8] Dong C Y, Qiao R R, Yang Z C, et al. Eco-environmental quality assessment of the artificial oasis of Ningxia section of the Yellow River with the MRSEI approach[J]. Frontiers in Environmental Science, 2023, 10: 1071631, doi: 10.3389/fenvs.2022.1071631.
[9] 李倩琳, 沙占江. 气候变暖背景下柴达木盆地生态环境质量遥感监测[J]. 生态科学, 2022, 41(6): 92-99.
  [Li Qianlin, Sha Zhanjiang. Remote sensing monitoring of ecological environment quality in Qaidam Basin under the background of climate warming[J]. Ecological Science, 2022, 41(6): 92-99.]
[10] 谭新. 库尔勒城市空间形态演变机制分析与扩展模拟[D]. 成都: 西南交通大学, 2020.
  [Tan Xin. Mechanism analysis and expansion simulation of urban spatial from evolution in Korla[D]. Chengdu: Southwest Jiaotong University, 2020.]
[11] 穆佳薇, 乔保荣, 余国新. 新疆塔里木河流域县域农业低碳生产率时空格局及影响效应研究[J]. 干旱区地理, 2023, 46(6): 968-981.
  [Mu Jiawei, Qiao Baorong, Yu Guoxin. Spatial and temporal patterns of agricultural low-carbon productivity and its influence effects in the counties of Tarim River Basin, Xinjiang[J]. Arid Land Geography, 2023, 46(6): 968-981.]
[12] 蔡朝朝, 安沙舟, 蒲智, 等. 基于TM NDVI的库尔勒市域植被覆盖动态变化[J]. 草业科学, 2015, 32(7): 1069-1078.
  [Cai Zhaozhao, An Shazhou, Pu Zhi, et al. A study on vegetation coverage change in Korla City based on the TM NDVI[J]. Pratacultural Science, 2015, 32(7): 1069-1078.]
[13] 魏兴, 周金龙, 曾妍妍, 等. 新疆库尔勒市水资源压力评价[J]. 水电能源科学, 2021, 39(4): 44-47.
  [Wei Xing, Zhou Jinlong, Zeng Yanyan, et al. Evaluation of water resources pressure in Korla City of Xinjiang[J]. Water Resources and Power, 2021, 39(4): 44-47.]
[14] 宋歌, 王金朔, 何立恒, 等. 基于CLUE-S模型的西部干旱区土地利用变化情景模拟[J]. 南京林业大学学报(自然科学版), 2013, 37(3): 135-139.
  [Song Ge, Wang Jinshuo, He Liheng, et al. Simulation of land use change in western arid region under different scenarios based on the CLUE-S model[J]. Journal of Nanjing Forest University (Natural Science Edition), 2013, 37(3): 135-139.]
[15] 陆忠奇, 赵竹君, 何清. 库尔勒市大气颗粒物浓度特征及来源[J]. 中国沙漠, 2022, 42(6): 74-84.
  [Lu Zhongqi, Zhao Zhujun, He Qing. Concentrations characteristics and sources of particulate matter in Korla, Xinjiang, China[J]. Journal of Desert Research, 2022, 42(6): 74-84.]
[16] Wu W C. The generalized difference vegetation index (GDVI) for dry land characterization[J]. Remote Sensing, 2014, 6(2): 1211-1233.
[17] 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, 294.
  [Xu Hanqiu. Assessment of ecological change in soil loss area using remote sensing technology[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(7): 91-97, 294.]
[18] Baig M H A, Zhang L F, Shuai T, et al. Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance[J]. Remote Sensing Letters, 2014, 5(5): 423-431.
[19] Nichol J. Remote sensing of urban heat island by day and night[J]. Photogrammetric Engineering and Remote Sensing, 2005, 71(5): 613-621.
[20] Chander G, Markham B L, Helder D L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors[J]. Remote Sensing of Environment, 2009, 113(5): 893-903.
[21] Yang X D, Bai Y P, Che L, et al. Incorporating ecological constraints into urban growth boundaries: A case study of ecologically fragile areas in the Upper Yellow River[J]. Ecological Indicators, 2021, 124: 107436, doi: 10.1016/j.ecolind.2021.107436.
[22] Zhang M M, Kafy A A, Ren B, et al. Application of the optimal parameter geographic detector model in the identification of influencing factors of ecological quality in Guangzhou, China[J]. Land, 2022, 11(8): 1303, doi: 10.3390/land11081303.
[23] 曾永年, 向南平, 冯兆东, 等. Albedo-NDVI特征空间及沙漠化遥感监测指数研究[J]. 地理科学, 2006, 26(1): 75-81.
  [Zeng Yongnian, Xiang Nanping, Feng Zhaodong, et al. Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring[J]. Scientia Geographica Sinica, 2006, 26(1): 75-81.]
[24] 邹明亮, 韩雅敏, 曾建军, 等. 基于Albedo-NDVI特征空间的玛曲县荒漠化时空动态监测[J]. 冰川冻土, 2019, 41(1): 45-53.
  [Zou Mingliang, Han Yamin, Zeng Jianjun, et al. Temporal and spatial dynamic mornitoring of desertification in Maqu County based on Albedo-NDVI features space[J]. Journal of Glaciology and Geocryology, 2019, 41(1): 45-53.]
[25] 魏伟, 俞啸, 张梦真, 等. 1995—2018年石羊河流域下游荒漠化动态变化[J]. 应用生态学报, 2021, 32(6): 2098-2106.
  [Wei Wei, Yu Xiao, Zhang Mengzhen, et al. Dynamics of desertification in the lower reaches of Shiyang River Basin, northwest China during 1995—2018[J]. Chinese Journal of Applied Ecology, 2021, 32(6): 2098-2106.]
[26] 代云豪, 管瑶, 张钦凯, 等. 阿拉尔垦区土壤盐渍化遥感监测及时空特征分析[J]. 干旱区地理, 2022, 45(4): 1176-1185.
  [Dai Yunhao, Guan Yao, Zhang Qinkai, et al. Remote sensing monitoring and temporal and spatial characteristics of soil salinization in Aral Reclamation Area[J]. Arid Land Geography, 2022, 45(4): 1176-1185.]
[27] 王苗, 刘普幸, 乔雪梅, 等. 基于RSEDI的宁夏生态环境质量时空演变及其驱动力贡献率分析[J]. 生态学杂志, 2021, 40(10): 3278-3289.
  [Wang Miao, Liu Puxing, Qiao Xuemei, et al. Analysis of the spatiotemporal evolution of ecological environmental quality in Ningxia and its driving force contribution based on RSEDI[J]. Chinese Journal of Ecology, 2021, 40(10): 3278-3289.]
[28] 石三娥, 魏伟, 杨东, 等. 基于RSEDI的石羊河流域绿洲区生态环境质量时空演变[J]. 生态学杂志, 2018, 37(4): 1152-1163.
  [Shi San’e, Wei Wei, Yang Dong, et al. Spatial and temporal evolution of eco-environmental quality in the oasis of Shiyang River Basin based on RSEDI[J]. Chinese Journal of Ecology, 2018, 37(4): 1152-1163.]
[29] 李红阳, 陈天宇, 王圣杰, 等. 1979—2021年新疆昆仑山北坡潜在蒸散时空变化研究[J]. 干旱区地理, 2024, 47(9): 1443-1450.
  [Li Hongyang, Chen Tianyu, Wang Shengjie, et al. Spatial and temporal variations of potential evapotranspiration on the northern slope of the Kunlun Mountains in Xinjiang from 1979 to 2021[J]. Arid Land Geography, 2024, 47(9): 1443-1450.]
[30] Peng S Z, Ding Y X, Liu W Z, et al. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017[J]. Earth System Science Data, 2019, 11(4): 1931-1946.
[31] 冯尚荣, 陈庆涛. 主成分分析在遥感处理中的应用[J]. 世界有色金属, 2019(11): 255-256.
  [Feng Shangrong, Chen Qingtao. Application of principal component analysis in remote sensing processing[J]. World Nonferrous Metals, 2019(11): 255-256.]
[32] 潘婷, 王懿祥, 刘宪钊, 等. 雄安新区土地利用变化及其对生态质量的影响[J]. 浙江农林大学学报, 2023, 40(5): 1102-1110.
  [Pan Ting, Wang Yixiang, Liu Xianzhao, et al. Land use change and its impact on ecological quality in Xiong’an New Area[J]. Journal of Zhejiang A & F University, 2023, 40(5): 1102-1110.]
文章导航

/