講演詳細

経営部門[Forest Management]

日付	2024年3月10日
開始時刻	ポスター発表
会場名	541
講演番号	PD-42
発表題目	Monitoring tropical forest degradation and deforestation in two municipalities within the Brazilian Amazon rainforest Monitoring tropical forest degradation and deforestation in two municipalities within the Brazilian Amazon rainforest
所属	The University of Tokyo
要旨本文	The extensive and often unsustainable human activities within the Amazon result in the rapid loss of valuable forested areas, and the vast areas of rainforest are a challenge for monitoring and management efforts. Therefore, this case study utilizes remote sensing to monitor deforestation and forest degradation in two main cities in the Brazilian Amazon and their respective conservation units and protected zones, within six years. We employed object-based image classification analysis using ensemble learning methods, including Random Forest and Gradient Boosting algorithms, along with different segmentation techniques on Sentinel-2 image annual composites. Eight land cover classes were identified, enabling calculation of transition areas to detect changes within study areas and their protected zones. This allows the comparison of deforestation rates in different areas and inspection of their policies towards conservation and management of the forested areas.
著者氏名	○Nogueira Lopes, Danielle ・ Tsuyuki, Satoshi
著者所属	The University of Tokyo
キーワード	Forest classification, Land use/Land cover change, Remote sensing
Key word	Forest classification, Land use/Land cover change, Remote sensing