The perils of misusing remote sensing data. The case of forest cover
Research on deforestation has grown exponentially due to the availability of satellitebased measures of forest cover. One of the most popular is Global Forest Change (GFC). Using GFC, we estimate that the Colombian civil conflict increases ¿forest cover¿. Using an alternative source that validates t...
- Autores:
-
Fergusson Talero, Leopoldo
Saavedra, Santiago
Vargas, Juan F.
- Tipo de recurso:
- Work document
- Fecha de publicación:
- 2020
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/41127
- Acceso en línea:
- http://hdl.handle.net/1992/41127
- Palabra clave:
- Forest cover
Conflict
Measurement
D74, Q23, Q34
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
Summary: | Research on deforestation has grown exponentially due to the availability of satellitebased measures of forest cover. One of the most popular is Global Forest Change (GFC). Using GFC, we estimate that the Colombian civil conflict increases ¿forest cover¿. Using an alternative source that validates the same remote sensing images in the ground, we find the opposite effect. This occurs because, in spite of its name, GFC measures tree cover, including vegetation other than native forest. Most users of GFC seem unaware of this. In our case, most of the conflicting results are explained by GFC¿s misclassification of oil palm crops as ¿forest¿. Our findings call for caution when using automated classification of imagery for specific research questions. |
---|