Terra-i+ Using machine learning to manage impacts of coffee production in Ocotepeque, Honduras
The report aims to address the needs of those involved in the environmental management of coffee production across Ocotepeque. We quantify the impact a series of drivers had on deforestation trends in the department, thus isolating coffee driven deforestation. Based on these key results, we identify...
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| Format: | Informe técnico |
| Language: | Inglés Español |
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CGIAR Research Program on Climate Change, Agriculture and Food Security
2020
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| Online Access: | https://hdl.handle.net/10568/111378 |
| Summary: | The report aims to address the needs of those involved in the environmental management of coffee production across Ocotepeque. We quantify the impact a series of drivers had on deforestation trends in the department, thus isolating coffee driven deforestation. Based on these key results, we identify forests that are under current and future risk of being replaced by coffee. Finally, we identify areas of concern for the coffee sector as well as opportunities arising from climate change. |
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