Bibliographische Detailangaben
| Titel: |
Using Spatial Literacy for Disaster Management in Coastal Communities of Small Island Developing States (SIDS): A Case Study from Lavongai, Papua New Guinea. |
| Autoren: |
Nirwansyah, Anang Widhi, Mandili, Abdel, Inez-Pedro, Bianca, Aini, John, Sriyanto, Sriyanto, Sadeli, Elly Hasan |
| Quelle: |
Sustainability (2071-1050); Nov2024, Vol. 16 Issue 21, p9152, 19p |
| Abstract: |
This study investigates the use of participatory geographic information systems (PGIS) for hazard assessment in small island developing states (SIDS), with a focus on spatial literacy and community-based disaster management. By partnering with the Lavongai community on Papua New Guinea, this research aimed to empower community members through skill development in geodata processing. The program leveraged local knowledge and the global positioning system to create participatory maps, enhancing both community capacity and researcher data quality. Workshops and focus group discussions (FGDs) were conducted to assess the community's understanding of spatial concepts related to disaster risks. The core objective was a preliminary assessment of the community's social and economic vulnerability to coastal disasters, using household data and GIS analysis. The results showed varied vulnerability levels within the community, highlighting the need for targeted disaster mitigation training and nature-based solutions. High-resolution satellite imagery and a simple bathtub model simulated sea level rise, identifying land-uses at risk. The program concluded with a community presentation of thematic maps, fostering collaboration and transparency. Future projects will address environmental challenges identified by local leaders and prioritize skill development, social data collection, and water resource mapping. [ABSTRACT FROM AUTHOR] |
|
Copyright of Sustainability (2071-1050) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Datenbank: |
Complementary Index |