使用SAR遥感和基于云计算的处理,进行高分辨率的垃圾填埋场表征
Shashank Agrawal1, Shivukumar Rakkasagi1, Manish Kumar Goyal2
1Department of Civil Engineering, Indian Institute of Technology Indore, Indore, India.
Scientific reports
|December 20, 2025
概括
这项研究介绍了一种使用Sentinel-1 SAR图像和Python绘制印度垃圾填埋场地图的遥感方法. 该方法准确量化废物量,支持发展中国家更好地管理固体废物.
科学领域:
- 环境科学 环境科学
- 地理空间分析是什么
- 遥感 遥感 遥感 遥感
背景情况:
- 像印度这样的发展中国家由于监测和垃圾填埋数据不佳,难以处理固体废物.
- 现有的方法缺乏可靠的垃圾填埋统计报告机制,阻碍了有效的规划.
研究的目的:
- 开发和验证一个遥感方法来量化印度的垃圾填埋场特征.
- 建立一个可扩展和具有成本效益的全国性垃圾填埋场监测框架.
主要方法:
- 将 Python 编程与 Sentinel 应用平台 (SNAP) 集成,从 Sentinel-1 SAR 图像中生成数字海拔模型 (DEM).
- 利用谷歌地球引擎 (GEE) 对印度80个垃圾填埋场的废物高度和体积估计进行大规模分析.
- 在两个代表性垃圾填埋场使用无人机调查和差分全球定位系统 (DGPS) 进行现场验证.
主要成果:
- 该研究介绍了使用统一的遥感框架对垃圾填埋场体积的首次全国性评估.
- 现场验证证明了高精度,在特定地点,体积偏差低至0.8%.
- 提出的基于SAR的DEM方法被证明是可靠的,用于估计垃圾填埋场的高度,面积和体积.
结论:
- 使用基于SAR的DEM的远程传感为系统的,近乎实时的垃圾填埋场监测提供了具有成本效益的,可扩展的解决方案.
- 该框架支持关键的能力规划,环境评估和废物管理政策制定.
- 该方法为发展中国家提供了一条途径,在城市化和日益增加的废物产生中采用数据驱动的废物管理策略.
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