A Survey of Computer Vision Techniques for Forest Characterization and Carbon Monitoring Tasks

Illarionova, S.; Shadrin, D.; Tregubova, P.; Ignatiev, V.; Efimov, A.; Oseledets, I.; Burnaev, E.

Авторы: Illarionova Svetlana, Shadrin Dmitrii, Tregubova Polina, Ignatiev Vladimir, Efimov Albert, Oseledets Ivan, Burnaev Evgeny
Журнал: Remote Sensing
Том: 14
Номер: 22
Год издания: 2022
Издательство: MDPI
Местоположение издательства: Basel, Switzerland
DOI: 10.3390/rs14225861
Аннотация: Estimation of terrestrial carbon balance is one of the key tasks in the understanding and prognosis of climate change impacts and the development of tools and policies according to carbon mitigation and adaptation strategies. Forest ecosystems are one of the major pools of carbon stocks affected by controversial processes influencing carbon stability. Therefore, monitoring forest ecosystems is a key to proper inventory management of resources and planning their sustainable use. In this survey, we discuss which computer vision techniques are applicable to the most important aspects of forest management actions, considering the wide availability of remote sensing (RS) data of different resolutions based both on satellite and unmanned aerial vehicle (UAV) observations. Our analysis applies to the most occurring tasks such as estimation of forest areas, tree species classification, and estimation of forest resources. Through the survey, we also provide a necessary technical background with a description of suitable data sources, algorithms’ descriptions, and corresponding metrics for their evaluation. The implementation of the provided techniques into routine workflows is a significant step toward the development of systems of continuous actualization of forest data, including real-time monitoring. It is crucial for diverse purposes on both local and global scales. Among the most important are the implementation of improved forest management strategies and actions, carbon offset projects, and enhancement of the prediction accuracy of system changes under different land-use and climate scenarios.
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A Survey of Computer Vision Techniques for Forest Characterization and Carbon Monitoring Tasksстатья

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