モルディブのゴミ焼却終了を空の目が確認(Eyes in the Skies Confirm the End of Trash Burning in the Maldives)

2023-07-14

2023-07-12 テキサス A&M大学

◆モルディブ共和国の政府が公共のゴミ焼却と一回限りの使い捨てプラスチックの禁止措置を実施していることが、デューク大学の最新研究によって確認されました。研究では、AI技術を使用してモルディブの衛星画像を分析し、煙の柱が効果的に排除されたことが示されました。
◆このアプローチは、野火や発電所などが生成する煙の柱を検出する潜在能力を持っています。今回の研究結果は、環境科学と技術の専門誌に掲載されました。これにより、AIツールを使用して世界中のさまざまな環境問題を監視する力が強化される可能性があると言えます。

＜関連情報＞

高解像度衛星画像と機械学習によるゴミ焼却の煙の特定：モルディブでのケーススタディ Identifying Waste Burning Plumes Using High-Resolution Satellite Imagery and Machine Learning: A Case Study in the Maldives

Sarah R. Scott, Philemon E. Hailemariam, Prakash V. Bhave, Michael H. Bergin, and David E. Carlson
Environmental Science & Technology Letters Published:July 7, 2023
DOI:https://doi.org/10.1021/acs.estlett.3c00225

Abstract

A rapid increase in municipal solid waste generation has far outpaced resources to manage waste in many developing countries, resulting in the burning of trash in designated landfills or public places, the release of harmful air pollutants, and exposure of nearby populations. While some governments have recently banned open burning at municipal facilities, monitoring the success of mitigation strategies has been challenging due to the lack of adequate air pollution monitoring methodologies. To address this, we have developed a machine learning approach that utilizes high-resolution (3 m/pixel) satellite imagery and applied the methodology to detect plumes of smoke from waste burning on Thilafushi in the Maldives. We employed an image classification and semantic segmentation model based on a pretrained convolutional neural network to identify and locate plumes within images. Our approach achieved an average intersection over union (overlap) of 0.70 between visually identified plumes and the machine learning output as well as a pixel-level classification accuracy of 96.3% on our holdout testing data. Our results demonstrate the potential of machine learning models in detecting plumes from sources where measurements are not available, including wildfires, coal-fired power plants, and industrial plumes, as well as in tracking the progress of mitigation strategies.