|
| Google Earth Engine平台支持下的南流江流域生态环境质量动态监测 |
| Dynamic monitoring of ecological and environmental quality of the Nanliu River basin, supported by Google Earth Engine |
| 投稿时间：2020-09-22 |
| DOI：10.13254/j.jare.2020.0536 |
| 中文关键词: 南流江流域，Google Earth Engine，区域生态环境评价，遥感生态指数，生态风险等级 |
| 英文关键词: Nanliu River basin, Google Earth Engine, regional ecological environmental assessment, remote sensing ecological index, ecological risk grade |
| 基金项目:国家自然科学基金项目（41661043）；广西自然科学基金项目（2015GXNSFAA139234）；广西科技重点研发计划（AB16380318）；广西研究生教育创新计划项目（YCSW2020192） |
|
| 摘要点击次数: 1156 |
| 全文下载次数: 1208 |
| 中文摘要: |
| 为探究南流江流域2000—2019年生态环境质量的时空变化，利用Google Earth Engine（GEE）平台对2000—2019年南流江流域Landsat影像进行优化重构，并耦合植被绿度、湿度、地表温度、土壤干度等生态环境指标，构建遥感生态指数（RSEI）模型对南流江流域生态环境质量进行监测和评价。结果表明：2000—2019年南流江流域生态环境质量呈现逐年好转的态势，RSEI均值从2000年的0.543 4增长至2019年的0.636 4；南流江流域生态环境质量面积变化主要以中等生态风险等级向良生态等级转移为主，其中流域上游的中生态等级面积占比减少29.90个百分点，下游的良生态等级面积占比增加28.11个百分点。研究表明，使用GEE平台重构年度无云影像，可以对常年多云覆盖区的生态环境质量进行长时序的监测和评价。 |
| 英文摘要: |
| To explore the temporal and spatial changes of the ecological and environmental quality in the Nanliu River basin from 2000 to 2019, the Google Earth Engine(GEE) platform was used to optimize the reconstruction of Landsat images of the Nanliu River basin from 2000 to 2019. Coupling the vegetation greenness, humidity, temperature of the earth's surface, soil dryness, and other ecological environment indicators facilitated the construction of a remote sensing ecological index(RSEI) to monitor and evaluate the ecological and environmental quality of the Nanliu River basin. The ecological and environmental quality of the Nanliu River basin showed an improvement year on year from 2000 to 2019. The average RSEI increased from 0.543 4 in 2000 to 0.636 4 in 2019. The transfer of area in the ecological and environmental quality of the Nanliu River basin change was mainly a shift from medium ecological risk grade to good ecological grade. In the upper reaches of the basin, the area of medium ecological grade decreased by 29.90 percent points, and the area of good ecological grade downstream increased by 28.11 percent points. Studies have shown that the use of the GEE platform to reconstruct annual, cloud-free images can facilitate long-term monitoring and evaluation of the ecological environment quality in areas of perennial cloud cover. |
| HTML
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
