遥感
濒危物种
环境科学
森林砍伐(计算机科学)
持续性
高光谱成像
环境资源管理
新兴技术
计算机科学
地理
生态学
生物
人工智能
栖息地
程序设计语言
作者
Danilo Roberti Alves de Almeida,Laura B. Vedovato,Matheus S. Fuza,Paulo Guilherme Molin,Henrique Cassol,Angélica Faria de Resende,Pedro Medrado Krainovic,Catherine Torres de Almeida,Cibele Hummel do Amaral,Leo Haneda,Rafael Walter Albuquerque,Eric Bastos Görgens,João Paulo Romanelli,Matheus Pinheiro Ferreira,Carl Salk,Nikolai S. Espinoza,Carlos Alberto Silva,Eben N. Broadbent,Pedro H. S. Brancalion
标识
DOI:10.1111/1365-2664.14830
摘要
Abstract Tropical forests are increasingly threatened by deforestation and degradation, impacting carbon storage, climate regulations and biodiversity. Restoring these ecosystems is crucial for environmental sustainability, yet monitoring these efforts poses significant challenges. Secondary forests are in a constant state of flux, with growth depending on multiple factors. Remote sensing technologies offer cost‐effective, scalable and transferable solutions, advancing forest restoration monitoring towards more accurate, efficient and real‐time data analysis and interpretation. This review provides a comprehensive evaluation of the current state and advancements in remote sensing technologies applied to monitoring tropical forest restoration. Synthesis and applications : This review brings together the state of the art of remote sensing technologies, such as very‐high‐resolution RGB imagery, multi‐ and hyperspectral imaging, lidar, radar and thermal‐infrared technologies and their applicability in monitoring forest restoration. In conclusion, this review emphasizes the potential of remote sensing technologies, coupled with advanced computational techniques, to enhance global efforts towards effective and sustainable forest restoration monitoring.
科研通智能强力驱动
Strongly Powered by AbleSci AI