A global analysis of forest management types: towards sustainable forest restoration and improved carbon assessment.
Forests play an important role in regulating the global climate, acting as important carbon stores and natural filters for air and water. Effective management of these forest ecosystems is therefore essential not only for the conservation of biodiversity but also in the fight against climate change. However, the lack of global forest management maps hinders the implementation of sustainable forest restoration methods and the accurate assessment of biomass and carbon stocks. Our study aims to fill this gap by using random forests and modifying detection algorithms to generate annual maps of forest management types from 2001 to 2020.
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Innovative techniques for forest management mapping
Traditional approaches to forest mapping often struggle with the challenges posed by the spectral uniformity of different types of forest management. To overcome this, we have applied advanced machine learning techniques, specifically random forest algorithms, in conjunction with change detection methods using multi-source datasets. This method identified six types of forest management: regenerating natural forests (managed and unmanaged), planted forests (rotation > 15 years and ≤ 15 years), oil palm plantations and agroforestry.
Spatial and temporal variation in forest management types
The analysis revealed significant variations in the spatial distribution and temporal trends of forest management types across continents. In particular, there was a significant increase in planted forest areas and agroforestry, partially offsetting the decline in naturally regenerated forests. This expansion reflects a trend towards reforestation and afforestation practices, although the decline of natural forests raises concerns in terms of loss of biodiversity and ecosystem services.
Carbon stocks and biomass changes
Estimates of annual carbon stocks under different types of forest management have shown that, despite the loss of naturally regenerated forests, the expansion of planted forests, oil palm plantations, and agroforestry offsets the loss of a significant portion of forest area and carbon stocks. This highlights the importance of forest management practices in mitigating climate change, although the quality and type of forest cover are also critical factors to consider.
Implications for forest management and climate change mitigation
The results of our study provide valuable information for policy makers, forest managers, and the scientific community, facilitating the implementation of nature-based forest management practices and forest restoration planning. Furthermore, they contribute to a better understanding of the impact of different types of forest management on carbon stocks and biodiversity, providing the basis for more informed and targeted climate change mitigation strategies.
Limitations and future perspectives
Although our approach represents a significant advance in forest management mapping, finer spatial resolutions and more precise carbon stock assessments are needed to improve the accuracy of forest maps and carbon estimates. Future research should focus on integrating high resolution data and examining the long-term effects of different management practices on forest ecosystems and global climate.
This article explores the use of machine learning techniques to generate annual maps of forest management types globally from 2001 to 2020, revealing significant changes in forest cover and management. This study highlights the partial compensation for the loss of naturally regenerated forests through the expansion of plantations. Forests and agroforestry, as well as the importance of forest management in mitigating climate change.
Source: Journal of Remote Sensing
