Tres décadas y medio de cambio de cobertura y uso de suelo en un área protegida del sur de Bolivia
Three and a half decades of cover and land cuse change in a protected area in southern Bolivia
DOI:
https://doi.org/10.56469/rae.v3i1.1557Keywords:
mapbiomasAbstract
The loss of land cover and use in the Serranía del Iñao National Park and Integrated Management Natural Area was assessed over a 19-year period through multitemporal analysis. Eight satellite images were used, six from the Landsat 5 satellite and TM sensor from 1998, 2004, 2010 and one Landsat 8 OLI sensor from 2016. The images were corrected and an unsupervised classification was applied, distinguishing the classes Dense Forest (BOD), Disturbed Forest (BPR), Sparse Forest (BPD), Agriculture (AGR), Sparse Scrub (MAR), Dense Scrub (MAD). Four communities (Azero Norte, Iripity, Las Casas, Pedernal) were surveyed to identify the main activities and analyze the guidelines that may cause changes in the coverage of the Serranía del Iñao Protected Area. They were reclassified into two subclasses, natural and anthropic; and a fragment analysis was run to obtain metrics at the landscape and class level. For the modeling of the scenarios, the MOLUSCE plugin of QGIS was used to project a positive and a negative scenario. The results show a transitional change of six spectral classes, in which Disturbed forest (BPR), Agriculture (AGR), Sparse scrub (MAR), Sparse forest (BPD) had a growth equal to or less than 5%, and Dense scrub (MAD) and Dense forest (BOD) were reduced in area between 4% and 5% respectively. The period 1989-2016 shows a negative deforestation rate (-0.55%). The main factors that modify the landscape are Agriculture, Slope, Population and Roads, with the last two having the greatest influence (ROADS and POBL). The analysis of the landscape of the Serranía del Iñao Protected Area shows a growth trend in the metrics used for this research until 2010, decreasing by 2016 and in the modeling of scenarios there is a negative projection in which no severe changes are shown and another positive scenario (with the main factors of change in the Serranía del Iñao AP) in which a 22% change in the surface of the total protected area is observed.
References
Baesa, R., González, R., y García, A. (2022). MapBiomas: Innovaciones en el mapeo y monitoreo de la cobertura terrestre en Sudamérica. Revista de Geografía y Medio Ambiente, 10(3), 255-270.
Barbati, A., Corona, P., y Marchetti, M. (2014). Global forest monitoring systems: Strengths, weaknesses, and the potential of using remote sensing. Forest Ecology and Management, 313, 57-70.
Bazzato, E., Ceccherini, G., y Montanari, F. (2022). Analysis of volcanic deposits using remote sensing data: A case study on Semeru Volcano. Journal of Volcanology and Geothermal Research, 416, 107309.
Belgiu, M., y Drăguţ, L. (2016). Landsat image classification using random forest for land use/land cover mapping. Remote Sensing, 8(3), 263-278.
Brienen, R. J., Girardin, C. A., y Phillips, O. L. (2015). Estimating forest carbon stock changes in the Amazon: Comparison of methods and the effects of forest degradation. Global Change Biology, 21(1), 370-379
Brown, C., Ryan, D., y Mahony, T. (2022). Integrating Earth observation data for sustainable development. Remote Sensing Applications: Society and Environment, 28, 103-118.
Câmara, G., Maciel, A., Gomes, V., y Carvalho, A. (2021). Advances in big earth observation data analysis with MapBiomas and Google Earth Engine. International Journal of Remote Sensing, 42(2), 345-361.
Canadell, J. G., y Raupach, M. R. (2008). Managing forests for climate change mitigation. Science, 320(5882), 1456-1459.
Caron, P., Leclerc, G., y Mansourian, S. (2021). Landscape-scale monitoring of tropical forests using Google Earth Engine. Forests, 12(3), 456-469.
Ceccherini, G., Gobron, N., y Pugh, T. (2023). Multisensor analysis of volcanic activity using Google Earth Engine. Earth Systems Science Data, 15(3), 1347-1358.
Chi, H., Liang, S., y Yu, W. (2016). A review on Google Earth Engine applications in land use studies. Remote Sensing Letters, 7(9), 856-862.
Fonúrbel, M. (2007). Aplicación de imágenes satelitales para el análisis de cambios en la cobertura terrestre (Tesis de Maestría). Universidad de Chile.
Gebresamuel, G., Hager, A., y Keesstra, S. (2010). Análisis de la precisión en la clasificación de coberturas utilizando MODIS. Remote Sensing of Environment, 114(7), 1421-1434.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., y Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18-27.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., y Tyukavina, A. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), 850-853.
He, C., Liu, X., y Wang, X. (2014). Aplicación de Random Forest en el análisis de cambios de uso de suelo a partir de imágenes satelitales. Journal of Applied Remote Sensing, 8(1), 1-14.
Imtiaz, S., Ali, S., y Rahman, M. (2024). Estimation of crop soil moisture using remote sensing techniques. Agriculture and Water Management, 156, 345-356.
Kamaraj, M., y Rangarajan, S. (2022). Predicting the future land use and land cover changes for Bhavani basin, Tamil Nadu, India, using QGIS MOLUSCE plugin. Environmental Science and Pollution Research, 29, 86337-86348. https://doi.org/10.1007/s11356-021-17904-6
Killeen, T. J., Soria, L., y Calderón, V. (2005). Análisis de la deforestación en el Amazonas boliviano: factores y tendencias. Ecology and Society, 10(2), 22-45.
Killeen, T. J., Villegas, Z., Soria, L., y Soares-Filho, B. (1993). Guía de Árboles de Bolivia. Herbario Nacional de Bolivia – Missouri Botanical Garden, Ed. Quipus Srl.
Kurnianto, M., Suwarno, A., y Setiawan, B. (2024). Pyroclastic flow mapping using multisensor integration in Google Earth Engine. Natural Hazards and Earth System Sciences Discussions, 12, 34-56.
Liberman, M. C. (1991). Situación ambiental de Bolivia. En CIEDLA (Ed.), La situación ambiental en América Latina, algunos estudios de caso (pp. 77-140). Impreso en Balada-Buschi S. A.
MapBiomas. (2023). About MapBiomas. Recuperado de https://mapbiomas.org
Marsik, M., Garcés, A., y Huaraca, H. (2011). El uso de sensores multiespectrales en el monitoreo de cambios en la vegetación de regiones tropicales. International Journal of Remote Sensing, 32(6), 1517-1536.
Mas, J.-F., y Velázquez, A. (2009). Monitoreo de cambios en el uso del suelo en áreas protegidas mediante análisis de imágenes satelitales. Geocarto International, 24(6), 459-470.
Mengistu, T., Yeshitila, M., y Desta, L. (2024). Mapping honeybee forage classes using ensemble learning. Remote Sensing of Environment, 302, 156-172.
Müller, H., Pohl, C., y Kusters, K. (2014). Impacto de la expansión agrícola en las zonas montañosas de alta biodiversidad en América Latina. Environmental Monitoring and Assessment, 186(7), 4167-4183.
Navarro, G., y Ferreira, W. (2004). Zonas de vegetación potencial de Bolivia: una base para el análisis de vacíos de conservación. Revista Boliviana de Ecología, 15, 1-40.
Navarro, G., y Maldonado, L. (2002). Zonas de vegetación de la Cordillera Oriental de los Andes en Bolivia. Editorial de la Universidad Mayor de San Andrés.
Peñaranda, J. A. (2010). Análisis cuantitativo del cambio de cobertura vegetal – forestal en una cronosecuencia de 22 años (1988 - 2008) en el PN-ANMI Serranía del Iñao, Bolivia (Tesis de Licenciatura). Facultad de Ciencias Agrarias, Chuquisaca, Bolivia.
Peralta-Rivero, L., Barbosa, A., y Ríos, M. (2013). La expansión agrícola y la deforestación en la región amazónica de Bolivia. Environmental Conservation, 40(3), 255-263.
Pinto, J. R., Hernández, A. G., y López, P. (2010). Dinámicas de cambio de uso de suelo en América Latina y sus implicaciones para la biodiversidad. Global Ecology and Biogeography, 19(5), 603-611.
Serrano, M. (2003). Estructura y composición de bosques montanos subtropicales y sus implicaciones para la conservación y el manejo de los recursos forestales en la Serranía del Iñao, Bolivia (Tesis de Maestría). CATIE, Turrialba, CR.
Souza, C. M., Shimbo, J. Z., Rosa, M. R., Parente, L. L., Alencar, A. A., Rudorff, B. F. T., y Matsumoto, M. (2020). Reconstructing three decades of land use and land cover changes in Brazilian biomes with MapBiomas.
Scientific Data, 7, 1-11.
Velastegui-Montoya, A., Lima, A. D., & Adami, M. (2020). Multitemporal analysis of deforestation in response to the construction of the Tucuruí Dam. ISPRS International Journal of Geo-Information, 9(10), 583. https://
doi.org/10.3390/ijgi9100583