Gutierrez-Velez, Victor: Temple University (Project Lead)
Project Funding:
2018 - 2021
NRA: 2016 NASA: Group on Earth Observations Work Programme
Funded by NASA
Abstract:
Earth Observations data and products represent great potential for understanding, managing, and conserving biodiversity. The ability of decision makers to translate this vast amount of data into information for practical decisions is constrained by differences in data structures, sources, and formats and the complexity of operations necessary for data assimilation, merging, analysis, and interpretation. Overcoming these constraints is critical in Colombia, where recent and unprecedented achievements to end more than 50 years of internal war constitute challenges and opportunities for sustainable development and biodiversity conservation. Colombia is one of the most biodiverse countries in the world. Current high rates of deforestation and ecosystem degradation constitute sensitive pressures for biodiversity conservation. Colombia is also one of only three countries worldwide pioneering the implementation of a national Biodiversity Observation Network (BON) under the GEOBON umbrella. The Colombian BON has identified as crucial, the need to provide processing tools and analytical skills to decision-makers for integrating biodiversity information into national and regional development planning.
We propose to develop a Decision Support System (DSS) for Biodiversity Conservation and Management in Colombia. The DSS will facilitate the integration, processing and
analysis of Earth observations in one platform, to inform biodiversity decision-making. The DSS will allow users to bring existing Earth Observations into compatible data structures and to develop metrics for different geographic domains and time periods. These metrics can then be integrated into modules to characterize: 1) biodiversity conservation status, 2) human and climatic drivers of biodiversity and ecosystem change, 3) future impacts of land use on biodiversity and 4) priority areas for biodiversity sampling and monitoring.
The DSS will be dynamic, interactive, open source and flexible to include new data and functionality as new products are generated or needs emerge. The toolset will be accessible at two “tiers” of complexity, suitable to different levels of user expertise. The first tier will contain user-friendly dashboards and customizable queries to enable users, with no previous experience in computer coding, the ability to parameterize, visualize, and interpret information for monitoring, reporting and verification purposes. The second tier will offer greater flexibility in customization, parameter settings and modeling outputs to users with basic to advanced skills on computer coding. A case study will be implemented in Colombia to test the functionality of the DSS. The project also includes workshops, training sessions and webinars to broaden the participation of stakeholders in the development of the DSS and to build capacity for its use for research, policy decision-making and environmental monitoring.
The DSS will inform the National Environmental Information System of Colombia and will be hosted and administered by the official institution leading the implementation of the BON in Colombia, the Alexander von Humboldt Institute for Biodiversity, with support from the other participant organizations. The functionality of the system will also be provided as a BON in a Box set and will be designed with a level of generalization to facilitate the development biodiversity support systems for other national or regional BONs.
The DSS is highly relevant to NASA’s Earth Science and Applied Sciences Program. Given the demonstrated human dependence on ecological systems, enabling the use of Earth Observations for timely and informed decisions on biodiversity planning and management will promote long-term societal benefits. The system will also add to GEOBON’s goals of contributing to effective policies for sustainable management of biodiversity and ecosystems by facilitating the delivery of Earth Observation information for research and decision-making.
Publications:
Anaya, J. A., Gutierrez-Velez, V. H., Pacheco-Pascagaza, A. M., Palomino-Angel, S., Han, N., Balzter, H. 2020. Drivers of Forest Loss in a Megadiverse Hotspot on the Pacific Coast of Colombia. Remote Sensing. 12(8), 1235. DOI: 10.3390/rs12081235
Gutierrez-Velez, V. H., Rodriguez-Escobar, J., Lara, W., Sarmiento-Giraldo, V. 2021. Probabilistic approximation to change and no change in multispectral remote sensing. International Journal of Remote Sensing. 42(19), 7428-7453. DOI: 10.1080/01431161.2021.1958391
Lapola, D. M., Pinho, P., Barlow, J., Aragao, L. E. O. C., Berenguer, E., Carmenta, R., Liddy, H. M., Seixas, H., Silva, C. V. J., Silva-Junior, C. H. L., Alencar, A. A. C., Anderson, L. O., Armenteras, D., Brovkin, V., Calders, K., Chambers, J., Chini, L., Costa, M. H., Faria, B. L., Fearnside, P. M., Ferreira, J., Gatti, L., Gutierrez-Velez, V. H., Han, Z., Hibbard, K., Koven, C., Lawrence, P., Pongratz, J., Portela, B. T. T., Rounsevell, M., Ruane, A. C., Schaldach, R., da Silva, S. S., von Randow, C., Walker, W. S. 2023. The drivers and impacts of Amazon forest degradation. Science. 379(6630). DOI: 10.1126/science.abp8622
Lapola, D. M., Pinho, P., Barlow, J., Aragao, L. E. O. C., Berenguer, E., Carmenta, R., Liddy, H. M., Seixas, H., Silva, C. V. J., Silva-Junior, C. H. L., Alencar, A. A. C., Anderson, L. O., Armenteras, D., Brovkin, V., Calders, K., Chambers, J., Chini, L., Costa, M. H., Faria, B. L., Fearnside, P. M., Ferreira, J., Gatti, L., Gutierrez-Velez, V. H., Han, Z., Hibbard, K., Koven, C., Lawrence, P., Pongratz, J., Portela, B. T. T., Rounsevell, M., Ruane, A. C., Schaldach, R., da Silva, S. S., von Randow, C., Walker, W. S. 2023. The drivers and impacts of Amazon forest degradation. Science. 379(6630). DOI: 10.1126/science.abp8622
Lara, W., Londono, M. C., Gonzalez, I., Gutierrez-Velez, V. H. 2022. ecochange: An R-package to derive ecosystem change indicators from freely available earth observation products. Methods in Ecology and Evolution. 13(11), 2379-2388. DOI: 10.1111/2041-210X.13986
Lara, W., Londono, M. C., Gonzalez, I., Gutierrez-Velez, V. H. 2022. ecochange: An R-package to derive ecosystem change indicators from freely available earth observation products. Methods in Ecology and Evolution. 13(11), 2379-2388. DOI: 10.1111/2041-210X.13986
More details may be found in the following project profile(s):
