Methodology for generating a global forest management layer

Lesiv, M. ORCID:, Shchepashchenko, D. ORCID:, Buchhorn, M., See, L. ORCID:, Dürauer, M., Georgieva, I. ORCID:, Jung, M., Hofhansl, F. ORCID:, et al. (2020). Methodology for generating a global forest management layer. Zenodo 10.5281/zenodo.3933966. (Submitted)

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The first ever global map of forest management was generated based on remote sensing data. To collect training data, we launched a series of Geo-Wiki ( campaigns involving forest experts from different world regions, to explore which information related to forest management could be collected by visual interpretation of very high-resolution images from Google Maps and Microsoft Bing, Sentinel time series and normalized difference vegetation index (NDVI) profiles derived from Google Earth Engine. A machine learning technique was then used with the visually interpreted sample (280K locations) as a training dataset to classify PROBA-V satellite imagery. Finally, we obtained a global wall-to-wall map of forest management at a 100m resolution for the year 2015. The map includes classes such as intact forests; forests with signs of management, including logging; planted forests; woody plantations with a rotation period up to 15 years; oil palm plantations; and agroforestry. The map can be used to deliver further information about forest ecosystems, protected and observed forest status changes, biodiversity assessments, and other ecosystem-related aspects.

Item Type: Other
Depositing User: Luke Kirwan
Date Deposited: 07 Aug 2023 11:16
Last Modified: 27 Mar 2024 05:00

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