The perils of misusing remote sensing data: The case of forest cover

Research on deforestation has grown exponentially due to the availability of satellite-based 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...

Descripción completa

Detalles Bibliográficos
Autores Principales: Fergusson, Leopoldo, Saavedra, Santiago, Vargas, Juan F.
Otros Autores: Grupo de Investigaciones. Facultad de Economía. Universidad del Rosario
Formato: Documento de trabajo (Working Paper)
Lenguaje:Español (Spanish)
Publicado: 2020
Materias:
D74
Q23
Q34
Acceso en línea:https://repository.urosario.edu.co/handle/10336/21919
id ir-10336-21919
recordtype dspace
institution EdocUR - Universidad del Rosario
collection DSpace
language Español (Spanish)
topic Economía de la tierra
Educación, investigación, temas relacionados
Forest Cover
Conflict
Measurement
D74
Q23
Q34
spellingShingle Economía de la tierra
Educación, investigación, temas relacionados
Forest Cover
Conflict
Measurement
D74
Q23
Q34
Fergusson, Leopoldo
Saavedra, Santiago
Vargas, Juan F.
The perils of misusing remote sensing data: The case of forest cover
description Research on deforestation has grown exponentially due to the availability of satellite-based 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.
author2 Grupo de Investigaciones. Facultad de Economía. Universidad del Rosario
author_facet Grupo de Investigaciones. Facultad de Economía. Universidad del Rosario
Fergusson, Leopoldo
Saavedra, Santiago
Vargas, Juan F.
format Documento de trabajo (Working Paper)
author Fergusson, Leopoldo
Saavedra, Santiago
Vargas, Juan F.
author_sort Fergusson, Leopoldo
title The perils of misusing remote sensing data: The case of forest cover
title_short The perils of misusing remote sensing data: The case of forest cover
title_full The perils of misusing remote sensing data: The case of forest cover
title_fullStr The perils of misusing remote sensing data: The case of forest cover
title_full_unstemmed The perils of misusing remote sensing data: The case of forest cover
title_sort perils of misusing remote sensing data: the case of forest cover
publishDate 2020
url https://repository.urosario.edu.co/handle/10336/21919
_version_ 1696284763967455232
spelling ir-10336-219192021-04-05T01:42:56Z The perils of misusing remote sensing data: The case of forest cover Fergusson, Leopoldo Saavedra, Santiago Vargas, Juan F. Grupo de Investigaciones. Facultad de Economía. Universidad del Rosario Economía de la tierra Educación, investigación, temas relacionados Forest Cover Conflict Measurement D74 Q23 Q34 Research on deforestation has grown exponentially due to the availability of satellite-based 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. 2020-05-06 2020-05-08T19:09:56Z info:eu-repo/semantics/workingPaper info:eu-repo/semantics/draft Fergusson, Leopoldo; Saavedra, Santiago; Vargas, Juan F. (2020) The perils of misusing remote sensing data: The case of forest cover. Bogota : Universidad del Rosario, Department of Economics, Bogota. Documentos de trabajo economía. 21 pp. https://repository.urosario.edu.co/handle/10336/21919 spa info:eu-repo/semantics/openAccess application/pdf reponame:Repositorio Institucional EdocUR instname:Universidad del Rosario Alix-Garcia, J. M., Sims, K. R., & Yanez-Pagans, P. (2015). Only one tree from each ˜ seed? environmental effectiveness and poverty alleviation in mexico’s payments for ecosystem services program. American Economic Journal: Economic Policy, 7(4), 1–40. Berazneva, J., & Byker, T. S. (2017). Does forest loss increase human disease? evidence from nigeria. American Economic Review, 107(5), 516–21. Blackman, A., Goff, L., & Planter, M. R. (2018). Does eco-certification stem tropical deforestation? forest stewardship council certification in mexico. Journal of Environmental Economics and Management, 89, 306–333. Chervier, C., & Costedoat, S. (2017). Heterogeneous impact of a collective payment for environmental services scheme on reducing deforestation in cambodia. World Development, 98, 148–159. Cook, N. J., Wright, G. D., & Andersson, K. P. (2017). Local politics of forest governance: why ngo support can reduce local government responsiveness. World Development, 92, 203–214. Damania, R., Russ, J., Wheeler, D., & Barra, A. F. (2018). The road to growth: Measuring the tradeoffs between economic growth and ecological destruction. World Development, 101, 351–376. de Souza Cunha, F. A. F., Borner, J., Wunder, S., Cosenza, C. A. N., & Lucena, A. F. ¨ (2016). The implementation costs of forest conservation policies in brazil. Ecological economics, 130, 209–220. Galindo, G., Espejo, O., Rubiano, J., Vergara, L., & Cabrera, E. (2014). Protocolo de procesamiento digital de imagenes para la cuantificacion de la deforestacion en colombia. V2. 0. IDEAM, Bogota. Gallemore, C., & Jespersen, K. (2016). Transnational markets for sustainable development governance: The case of redd+. World Development, 86, 79–94. Gibson, J. (2018). Forest loss and economic inequality in the solomon islands: using small-area estimation to link environmental change to welfare outcomes. Ecological economics, 148, 66–76. Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., . . . Townshend, J. R. G. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), 850–853. Retrieved from http://science .sciencemag.org/content/342/6160/850 Jung, S., & Polasky, S. (2018). Partnerships to prevent deforestation in the amazon. Journal of Environmental Economics and Management, 92, 498–516. Kou, W., Xiao, X., Dong, J., Gan, S., Zhai, D., Zhang, G., . . . Li, L. (2015). Mapping deciduous rubber plantation areas and stand ages with palsar and landsat images. Remote Sensing, 7(1), 1048–1073. Restrepo, J., Spagat, M., & Vargas, J. (2004). The dynamics of the columbian civil conflict: A new dataset. Homo Oeconomicus, 21, 396–429. Richards, P. (2017). It’s not just where you farm; it’s whether your neighbor does too. how agglomeration economies are shaping new agricultural landscapes. Journal of Economic Geography, 18(1), 87–110. Song, X.-P. (2018). Global estimates of ecosystem service value and change: Taking into account uncertainties in satellite-based land cover data. Ecological Economics, 143, 227–235. Taki, H., Yamaura, Y., Okabe, K., & Maeto, K. (2011). Plantation vs. natural forest: Matrix quality determines pollinator abundance in crop fields. Scientific Reports, 1, 132. Tropek, R., Sedlacek, O., Beck, J., Keil, P., Musilov ´ a, Z., S ´ ´ımova, I., & Storch, D. (2014). ´ Comment on “high-resolution global maps of 21st-century forest cover change”. Science, 344(6187), 981.
score 12,111491