• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于遥感生态指数的塔里木河流域生态环境质量评价及其驱动因素分析。

Evaluation and driving factors of ecological environment quality in the Tarim River basin based on remote sensing ecological index.

机构信息

College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, China.

Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi, China.

出版信息

PeerJ. 2024 Oct 28;12:e18368. doi: 10.7717/peerj.18368. eCollection 2024.

DOI:10.7717/peerj.18368
PMID:39484209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11526787/
Abstract

Changes in the ecological environment quality (EEQ) in the main inland Tarim River Basin in China substantially impact the regional development. Indeed, comprehensive ecological environment measures have been implemented in the Tarim River Basin since 2000. In this context, the main objective of the present study was to investigate the spatiotemporal evolution of the EEQ and monitor the effectiveness of ecological restoration measures in the Tarim River Basin over the 2000-2020 period using remote sensing data. First, a Remote Sensing Ecological Index (RSEI) was constructed based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Second, the spatial distributions and factors of the RSEI were analyzed by using Moran's Index and Geodetector. The results indicated that the overall RSEI values for the Tarim River Basin increased from 0.22 in 2000 to 0.25 in 2020. Moreover, the values for areas with poor EEQ decreased from 50.7% to 44.73%, while those with moderate EEQ increased from 11.45% to 16.91%. Therefore, the results demonstrated a slight overall improvement in the EEQ of the study area over the 2000-2020 period. On the other hand, the EEQ in the Tarim River Basin exhibited a significant spatial autocorrelation in the 2000-2020 period, with a relatively stable overall spatial distribution. Areas with high-high aggregation were distributed in the high-elevation mountainous areas in the western, northern, and southern parts of the study area. In contrast, areas with low-low aggregation were observed in the central and eastern low-elevation desert areas. The EEQ in the Tarim River Basin was driven by the interactions of several factors, including the normalized difference vegetation index, land surface moisture, land surface temperature, normalized differential build-up and bare soil index, and elevation. In particular, heat was the main driving factor that severely impacted the EEQ in the study area. Indeed, increase in the heat values could directly enhance meltwater runoff from glaciers in the basin, thereby resulting in short-term improvement in the basin EEQ. Furthermore, rapid urbanization from 2015 to 2020 resulted in a decrease in the average RSEI value of the Tarim River Basin by 0.1 over this period, consequently, the EEQ level decreased slightly. Briefly, the EEQ in the Tarim River Basin showed an overall increasing trend from 2000 to 2020, further demonstrating the effectiveness of a series of implemented ecological restoration measures in the Tarim River Basin over this period.

摘要

中国内陆塔里木河流域生态环境质量(EEQ)的变化对区域发展有重大影响。实际上,自 2000 年以来,塔里木河流域已经实施了综合生态环境措施。在此背景下,本研究的主要目的是利用遥感数据,调查 2000-2020 年期间塔里木河流域 EEQ 的时空演变,并监测生态恢复措施的有效性。首先,基于中分辨率成像光谱仪(MODIS)遥感数据构建了遥感生态指数(RSEI)。其次,利用 Moran 指数和地理探测器分析了 RSEI 的空间分布和影响因素。结果表明,塔里木河流域的整体 RSEI 值从 2000 年的 0.22 增加到 2020 年的 0.25。此外,EEQ 较差地区的面积从 50.7%减少到 44.73%,而 EEQ 中等地区的面积从 11.45%增加到 16.91%。因此,研究结果表明,2000-2020 年期间,研究区的 EEQ 整体略有改善。另一方面,塔里木河流域的 EEQ 在 2000-2020 年期间具有显著的空间自相关,整体空间分布较为稳定。高-高聚集区分布在研究区西部、北部和南部的高海拔山区。相反,低-低聚集区分布在研究区中部和东部的低海拔沙漠地区。驱动塔里木河流域 EEQ 的因素有多种,包括归一化植被指数、地表湿度、地表温度、归一化差分建筑指数和裸土指数以及海拔。特别是,热量是严重影响研究区 EEQ 的主要驱动因素。实际上,热量值的增加会直接增强流域内冰川的融水径流,从而导致流域 EEQ 的短期改善。此外,2015 年至 2020 年期间的快速城市化导致塔里木河流域的平均 RSEI 值在此期间下降了 0.1,因此 EEQ 水平略有下降。总之,2000-2020 年塔里木河流域 EEQ 呈总体上升趋势,进一步证明了该时期塔里木河流域实施的一系列生态恢复措施的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/67e54b804932/peerj-12-18368-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/382dc8336fdf/peerj-12-18368-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/58fee1d75285/peerj-12-18368-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/3df929c5d3c3/peerj-12-18368-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/207232c24f55/peerj-12-18368-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/7ab7c3252a5c/peerj-12-18368-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/02d54908abb8/peerj-12-18368-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/47a2e30344b5/peerj-12-18368-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/67e54b804932/peerj-12-18368-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/382dc8336fdf/peerj-12-18368-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/58fee1d75285/peerj-12-18368-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/3df929c5d3c3/peerj-12-18368-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/207232c24f55/peerj-12-18368-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/7ab7c3252a5c/peerj-12-18368-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/02d54908abb8/peerj-12-18368-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/47a2e30344b5/peerj-12-18368-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f76/11526787/67e54b804932/peerj-12-18368-g008.jpg

相似文献

1
Evaluation and driving factors of ecological environment quality in the Tarim River basin based on remote sensing ecological index.基于遥感生态指数的塔里木河流域生态环境质量评价及其驱动因素分析。
PeerJ. 2024 Oct 28;12:e18368. doi: 10.7717/peerj.18368. eCollection 2024.
2
Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China.从地理空间分异角度探究遥感生态指数变化的驱动因素:以中国渭河流域为例。
Int J Environ Res Public Health. 2022 Sep 1;19(17):10930. doi: 10.3390/ijerph191710930.
3
[Ecological environment quality of the Shanxi section of the Yellow River Basin under different development scenarios].[不同发展情景下黄河流域山西段生态环境质量]
Ying Yong Sheng Tai Xue Bao. 2024 May;35(5):1337-1346. doi: 10.13287/j.1001-9332.202405.027.
4
Evaluation of the Ecological Environment Quality of the Kuye River Source Basin Using the Remote Sensing Ecological Index.运用遥感生态指数评价窟野河源头流域生态环境质量。
Int J Environ Res Public Health. 2022 Sep 30;19(19):12500. doi: 10.3390/ijerph191912500.
5
Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China.城市生态环境质量评价与国土空间规划响应——以中国中部长沙为例。
Int J Environ Res Public Health. 2023 Feb 20;20(4):3753. doi: 10.3390/ijerph20043753.
6
Exploring evolution characteristics of eco-environment quality in the Yangtze River Basin based on remote sensing ecological index.基于遥感生态指数的长江流域生态环境质量演变特征探究
Heliyon. 2023 Dec 3;9(12):e23243. doi: 10.1016/j.heliyon.2023.e23243. eCollection 2023 Dec.
7
Spatiotemporal Evolution and Spatial Analysis of Ecological Environmental Quality in the Longyangxia to Lijiaxia Basin in China Based on GEE.基于谷歌地球引擎的中国龙羊峡至李家峡流域生态环境质量时空演变及空间分析
Sensors (Basel). 2024 Aug 10;24(16):5167. doi: 10.3390/s24165167.
8
Assessment of spatial and temporal ecological environment quality under land use change of urban agglomeration in the North Slope of Tianshan, China.评估中国天山北坡城市群土地利用变化下的时空生态环境质量。
Environ Sci Pollut Res Int. 2022 Feb;29(8):12282-12299. doi: 10.1007/s11356-021-16579-3. Epub 2021 Sep 25.
9
Coupling eco-environmental quality and ecosystem services to delineate priority ecological reserves-A case study in the Yellow River Basin.耦合生态环境质量与生态系统服务以划定优先生态保护区——以黄河流域为例
J Environ Manage. 2024 Aug;365:121645. doi: 10.1016/j.jenvman.2024.121645. Epub 2024 Jul 2.
10
[Ecological Environment Assessment and Driving Mechanism Analysis of Nagqu and Amdo Sections of Qinghai-Xizang Highway Based on Improved Remote Sensing Ecological Index].基于改进遥感生态指数的青藏公路那曲与安多段生态环境评价及驱动机制分析
Huan Jing Ke Xue. 2024 Mar 8;45(3):1586-1597. doi: 10.13227/j.hjkx.202303252.

本文引用的文献

1
Spatiotemporal change in ecological quality and its influencing factors in the Dongjiangyuan region, China.中国东江源地区生态质量的时空变化及其影响因素。
Environ Sci Pollut Res Int. 2023 Jun;30(26):69533-69549. doi: 10.1007/s11356-023-27229-1. Epub 2023 May 4.
2
Analysis of ecological quality changes and influencing factors in Xiangjiang River Basin.湘江流域生态质量变化及影响因素分析。
Sci Rep. 2023 Mar 16;13(1):4375. doi: 10.1038/s41598-023-31453-7.
3
Evaluation of ecological quality in southeast Chongqing based on modified remote sensing ecological index.
基于改进遥感生态指数的重庆东南部生态质量评价。
Sci Rep. 2022 Sep 20;12(1):15694. doi: 10.1038/s41598-022-19851-9.
4
Instability of remote sensing based ecological index (RSEI) and its improvement for time series analysis.基于遥感的生态指数(RSEI)的不稳定性及其在时间序列分析中的改进。
Sci Total Environ. 2022 Mar 25;814:152595. doi: 10.1016/j.scitotenv.2021.152595. Epub 2022 Jan 4.
5
Spatiotemporal dynamics of wetlands and their driving factors based on PLS-SEM: A case study in Wuhan.基于偏最小二乘结构方程模型的湿地时空动态及其驱动因素:以武汉为例
Sci Total Environ. 2022 Feb 1;806(Pt 3):151310. doi: 10.1016/j.scitotenv.2021.151310. Epub 2021 Oct 29.
6
Spatiotemporal ecological vulnerability analysis with statistical correlation based on satellite remote sensing in Samara, Russia.基于卫星遥感的俄罗斯萨马拉时空生态脆弱性分析与统计相关。
J Environ Manage. 2021 May 1;285:112138. doi: 10.1016/j.jenvman.2021.112138. Epub 2021 Feb 14.
7
Quantitatively evaluating the effect of urbanization on heat waves in China.定量评估城市化对中国热浪的影响。
Sci Total Environ. 2020 Aug 20;731:138857. doi: 10.1016/j.scitotenv.2020.138857. Epub 2020 May 5.
8
Evaluation of the ecological protective effect of the "large basin" comprehensive management system in the Tarim River basin, China.中国塔里木河流域“大流域”综合管理体系的生态保护效果评价。
Sci Total Environ. 2019 Feb 10;650(Pt 2):1696-1706. doi: 10.1016/j.scitotenv.2018.09.327. Epub 2018 Sep 26.