12B.1 Empowering Decision-Making in Small Islands: Cloud-Based Land Use/Land Cover Analysis for Resilience in Changing Climates

Wednesday, 31 January 2024: 4:30 PM
336 (The Baltimore Convention Center)
Haley Anderson, Caribbean Meteorological Organization, Port of Spain, Trinidad and Tobago; and P. Paz, D. Ramsewak, D. Mahadeo, PhD Candidate, N. Gooding, V. Mohan, R. Sookdeo, D. Mitchell, K. Kerr IV, and A. G. Laing

During January to April 2023, the Caribbean Meteorological Organization (CMO) Headquarters Unit partnered with the International Center for Tropical Agriculture (CIAT) under the SERVIR Amazonia Program to conduct a training program aimed at enhancing geospatial technology skills and promoting innovative approaches for generating climate and geospatial data in Trinidad and Tobago. The program included twelve hybrid workshops, benefiting over twenty participants from ten public sector and academic institutions. The initiative focused on strengthening capacity to forecast extreme hydrological events and monitor land use changes in mangrove ecosystems.

Towards the program's conclusion, trainees engaged in discussions facilitated by CMO to identify challenges in applying geospatial information and tools. This led to the recognition of the need for a service providing current land use/land cover information to support decision-making across participating institutions. This information was crucial for watershed planning, flood prediction, ecosystem protection, coastal management, and environmental conservation.

Trainees conceptualized an inter-agency workflow utilizing Google Earth Engine (GEE) cloud infrastructure to produce high-quality, regularly updated land use/land cover data. This data served as a common input for collective spatial and strategic planning, environmental service delivery, disaster risk assessments, and flood forecasting, fostering collaboration between public sector organizations and academia.

This presentation showcases the successful partnership between public sector entities and academia in implementing a cloud-enabled workflow for producing up-to-date land use/land cover information using open-source data and infrastructure. The conceptual process, institutional framework, and pilot results highlight the potential impact achievable through collaborative efforts.

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