Data and Code underlying the article Forest Disturbance and Recovery in Peruvian Amazonia
doi: 10.4121/44f7b164-d85e-49a5-b0db-64f3f71772fb
The data and code in this repository can be used to reproduce the analysis Requena Suarez et al. (2023), "Forest Disturbance and Recovery in Peruvian Amazonia". Spatial datasets used in this study are accessible from the sources cited in Table 1 of the main study. Estimation of disturbance and time since disturbance was done using the AVOCADO algorithm (Decuyper et al, 2022, https://doi.org/10.1016/j.rse.2021.112829), and Landsat imagery downloaded from Google Earth Engine. The underlying code for AVOCADO can be found in the following GitHub repository: https://github.com/MDecuy/AVOCADO, as well as a tutorial: https://www.pucv.cl/uuaa/labgrs/proyectos/avocado.
- 2023-03-20 first online
- 2023-03-22 published, posted
Plant Production Systems Group, Wageningen University & Research
Centre for Crop Systems Analysis, Wageningen University & Research
Forest Ecology and Forest Management Group, Wageningen University & Research
Centre for International Forestry Research and World Agroforestry (CIFOR-ICRAF)
Servicio Nacional Forestal y de Fauna Silvestre (SERFOR)
Helmholtz Center Potsdam GFZ German Research Centre for Geosciences
DATA
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README.txt - 10,209 bytesMD5:
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Codes.zip - 139,407 bytesMD5:
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Data.zip -
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