In working towards achieving the SDGs, integrating statistical data from various government sectors with geospatial data is essential for accurate and comprehensive SDG monitoring, assessment, and planning. Geospatial data have high relevance for certain sectors notably, infrastructure, disaster management, agriculture, water and marine environments and urban development.
However, in many countries, statistical and geospatial communities and institutions operate in silos, having separate mandates, institutions, technical knowledge, and skills. Furthermore, different sectors responsible for SDG monitoring and implementation have their own understanding of standards, techniques, language, and mechanisms which can cause confusion and problems when applying and using these data. Many Asia-Pacific countries face gaps in terms of integrating sectoral and geospatial data. There is generally a lack of operational integrated geospatial data systems that inhibit the understanding of the current progress towards achieving the SDGs. Existing geospatial approaches to problems are not always tailored for local (country or other administrative levels) needs. In addition, geospatial data needs to be further transformed into knowledge capacity for policymakers as not all end users can effectively use geospatial information.
To address this need, the Economic and Social Commission for Asia and the Pacific (ESCAP) will organize four days of capacity-building training on building institutional capacity for the use of integrated spatiotemporal data in local SDGs monitoring and decision-making. The training will specifically focus on Songkla city with an emphasis on a) exploring smart city solutions to improve the urban quality of life and increase the resilience to disasters and b) exploring spatiotemporal information-based solutions to address community and ecosystem challenges in the Songkhla Lake Basin.
