Claim Missing Document
Check
Articles

Found 2 Documents
Search

How effective crowdsourced data during crisis emergency? A case of the 2018 Palu-Donggala earthquake Ramadhanis, Zainab; Akrimullah, Anjar
Jurnal Teknik Sipil dan Lingkungan Vol. 9 No. 2: Oktober 2024
Publisher : Departemen Teknik Sipil dan Lingkungan IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jsil.9.2.221-230

Abstract

In disaster situations, updated geographic data is crucial for disaster relief efforts. OpenStreetMap (OSM) has demonstrated significant value in disaster response scenarios due to its capacity for rapid data collection and dissemination, since the 2010 Haiti earthquake. This study investigates the quality of OSM data during the 2018 Palu-Donggala earthquake, focusing on how contributor expertise affects data reliability and how effectively OSM data supports decision-making in emergencies. The research highlights the critical role of OSM in providing timely geospatial information, with 205 contributors mapping roads and buildings in Palu City and Donggala Regency within just three days of the earthquake. Our findings show that while road data exhibited substantial topological errors—7,085 errors primarily due to overshoots—building data had considerably fewer errors, with only 76 recorded. This disparity suggests that OSM data for buildings was of higher quality during the crisis. The preference of eight out of nine mapper types for building data over road data further underscores the value of OSM in emergencies, as experienced mappers tended to focus on features that were less error-prone. The study also evaluates contributor behavior, revealing that while a significant portion of contributors were inactive, a majority of experienced contributors remained engaged. This finding indicates the potential for inactive expert mappers to return and contribute in future crises. Additionally, the study assesses the rapid collection of data by OSM and its impact on decision-making. The National Disaster Management Agency of Indonesia (BNPB) and the ASEAN Coordinating Centre for Humanitarian Assistance (AHA Centre) effectively utilized the data to provide updates on fatalities, injuries, and displacement, facilitating a swift and equitable distribution of aid.
Spatial Disparities in Jakarta’s Health and Education Infrastructures: An OpenStreetMap-Based Analysis Ramadhanis, Zainab; Akrimullah, Anjar; Heriza, Dewinta
Jurnal Teknik Sipil dan Lingkungan Vol. 10 No. 1: April 2025
Publisher : Departemen Teknik Sipil dan Lingkungan IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jsil.10.1.139-148

Abstract

Jakarta, as Indonesia’s most populous megacity, had a population of 11.14 million in 2024. Covering an area of 661 square kilometers, it is also the country’s most densely populated city, with over 16,500 individuals per square kilometer. High population density brings challenges, particularly in access to essential public services like education and healthcare, which are crucial for sustainable urban development. This study examines spatial disparities in the distribution of health and educational infrastructures in Jakarta concerning population density. Through overlay analysis, two models were developed: the Educational Facilities Gaps Map and the Health Facilities Gaps Map, categorizing areas as well-served, moderately served, or underserved. The findings highlight significant disparities across Jakarta’s administrative regions. Central Jakarta has the highest accessibility, with 57.43% of its area well-served for education and 65.06% for healthcare. Conversely, North Jakarta and Kepulauan Seribu experience the most severe service gaps, with 51.92% and 100% of their areas underserved in education, and 50.20% and 85.92% in healthcare, respectively. East, South, and West Jakarta exhibit moderate service coverage, though underserved zones remain. These results emphasize the importance of strategic urban planning to improve equitable access to public services. By incorporating geospatial analysis into policymaking, decision-makers can optimize facility distribution and infrastructure development, reducing service disparities, especially in underserved areas.