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利用 Sentinel-2 卫星图像识别印度尼西亚一条高度污染河流中的非法倾倒塑料垃圾。

Identification of illegally dumped plastic waste in a highly polluted river in Indonesia using Sentinel-2 satellite imagery.

机构信息

Remote Sensing and Geographic Information Sciences Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia.

Air and Waste Management Research Group, Faculty of Civil and Environmental Engineering, Institut Teknologi Bandung, Bandung, 40132, Indonesia.

出版信息

Sci Rep. 2023 Mar 28;13(1):5039. doi: 10.1038/s41598-023-32087-5.

DOI:10.1038/s41598-023-32087-5
PMID:36977803
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10049981/
Abstract

Plastic waste monitoring technology based on Earth observation satellites is one approach that is currently under development in various studies. The complexity of land cover and the high human activity around rivers necessitate the development of studies that can improve the accuracy of monitoring plastic waste in river areas. This study aims to identify illegal dumping in a river area using the adjusted plastic index (API) and Sentinel-2 satellite imagery data. Rancamanyar River has been selected as the research area; it is one of the tributaries of Citarum Indonesia and is an open lotic-simple form, oxbow lake type river. Our study is the first attempt to construct an API and random forest machine learning using Sentinel-2 to identify the illegal dumping of plastic waste. The algorithm development integrated the plastic index algorithm with the normalized difference vegetation index (NDVI) and normalized buildup indices. For the validation process, the results of plastic waste image classification based on Pleiades satellite imagery and Unmanned Aerial Vehicle (UAV) photogrammetry was used. The validation results show that the API succeeded in improving the accuracy of identifying plastic waste, which gave a better correlation in the r-value and p-value by + 0.287014 and + 3.76 × 10 with Pleiades, and + 0.143131 and + 3.17 × 10 with UAV.

摘要

基于地球观测卫星的塑料废物监测技术是目前各种研究中正在开发的一种方法。土地覆盖的复杂性和河流周围的高人类活动需要开发能够提高河流地区塑料废物监测准确性的研究。本研究旨在使用调整后的塑料指数 (API) 和 Sentinel-2 卫星图像数据识别河流地区的非法倾倒。Rancamanyar 河流被选为研究区域；它是印度尼西亚 Citarum 的支流之一，是一种开阔的流水-简单形式，牛轭湖型河流。我们的研究首次尝试使用 Sentinel-2 构建 API 和随机森林机器学习来识别塑料废物的非法倾倒。该算法开发将塑料指数算法与归一化差异植被指数 (NDVI) 和归一化建筑指数集成在一起。对于验证过程，我们使用了基于 Pleiades 卫星图像和无人机 (UAV) 摄影测量的塑料废物图像分类的结果。验证结果表明，API 成功地提高了识别塑料废物的准确性，这使得与 Pleiades 的 r 值和 p 值相关性更好，分别为+0.287014 和+3.76×10，与 UAV 的 r 值和 p 值相关性更好，分别为+0.143131 和+3.17×10。

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