XII. Disaster Management Early Warning and Decision Support Capacity Enhancement Project in Indonesia

Interaction type Public -> Government -> Public
Trigger Event
Organisation(s) HOT, USAID, OFDA, PDC, MIT, BNPB
Actors Local communities and Indonesia Government
Data sets in use Infrastructure data
Feedback Datasets that can be used for disaster management
Goal The project’s overall effort is to enhance capacity within national and provincial disaster management agencies to access automated international, regional, national, and local hazard information and supporting infrastructure data, as well as sharing information between agencies, and disseminating alert warnings to communities and populations at risk.
Side effects
Contact Point Online Resources

Disaster management and urban city planning in general is a demanding and challenging task when it comes to data required. It is often the case that the available datasets are outdated, incomplete, fragmented and dispersed among several public authorities, poorly organized and managed. Of high importance is the mapping of available infrastructure such as health and emergency services, transportation networks, large sport facilities and record all the necessary details and keep the data up-to-date. Similar was the case initially faced by a  Disaster Management, Early Warning and Decision Support Capacity Enhancement Project that focused on the two major cities of Indonesia, Surabaya and Jakarta. Surabaya consists of 31 sub-districts, 154 villages and 1,302 community groups being the second most populated city in Indonesia. Jakarta, Indonesia’s capital, has 44 sub-districts and 267 villages.

Due to local particularities, issues and difficulties in mapping might stem from dense settlements, surveying permits, low resolution imagery, inaccurate GPS points, weather conditions, ambiguity in road classifications and overlapping boundaries. These challenges have been raised by the Humanitarian OpenStreetMap Team (HOT) data entry and quality assurance specialists who worked for the project. HOT is collaborating on a USAID, Office of U.S. Foreign Disaster Assistance (OFDA) funded program together with the University of Hawaii: Pacific Disaster Centre (PDC) and the Massachusetts Institute of Technology (MIT): PetaBencana to support the Government of Indonesia, the Indonesian national disaster management agency (Badan Nasional Penanggulangan Bencana – BNPB). The project’s overall effort is to enhance capacity within national and provincial disaster management agencies to access automated international, regional, national, and local hazard information and supporting infrastructure data, as well as sharing information between agencies, and disseminating alert warnings to communities and populations at risk. The duration of the project will be from July 1 2016 until July 1 2017.

The program is based on and focuses on the development of InAWARE, a disaster management tool, to improve overall risk assessment, early-warning, and disaster-management decision making in Indonesia. InAWARE, the development of which started in 2013, is a hazard monitoring, disaster early warning, and decision support tool that aids disaster managers in Indonesia at both national and provincial levels. Furthermore, a collaborative effort between PDC and BNPB, led to DisasterAWARE, a specially customised version for disaster management purposes. In 2016, a second phase of the program was approved, focusing on the enhancement of crowdsourced data derived by the PetaBencana tool and the collection of key disaster management planning and response data by HOT in Jakarta and Surabaya for incorporation into InAWARE.

The project will need to develop a geospatial data base for disaster risk which will include administrative boundaries, building footprints, road networks, and disaster vulnerability characteristics. Data collection processes include remote mapping using Tasking Manager for buildings footprints, in-situ raw data gathering and feature attribute enrichment with the use of the OpenMapKit and GeoDataCollect (GDC) applications, close collaboration and consultation with local authorities, importing of existing datasets and training and collaboration with local universities. Common approaches for data collection for speeding up the process are mapathons and mapping parties. Both of these have been used by the project’s partners in order to gather as much information as possible. Once the information is mapped by the Data Entry specialists, it will be reviewed and validated by a team of dedicated Data Quality specialists.

The data collection effort was meticulously spread geographically over the project’s area at such level that potentially can become a best practice model to be replicated for future city-wide mapping projects, not only in Indonesia but in other countries with similar local context and predicaments.

During the lifespan of the project, particular attention was paid to user engagement, training and capacity building of the local communities and volunteers. For example, mapathons were open not only to university students but also to all volunteers and citizens. A collaboration with a local radio station helped to drum up support and urge citizens to participate in collaborative mapping and socialisation kick-off workshops with BNPB and BPBD took place in Jakarta and Surabaya. The HOT team was actively involved in training local BPBD staff and aspiring youth and university students. A structured university curriculum had been developed from HOT Indonesia’s previous project for students to follow up.

The OSM data collected will be used by Indonesia’s Disaster Management Agency, BNPB, as well as its subnational agencies BPBD DKI Jakarta and East Java to enhance its real-time early warning and decision making support with the use of InAWARE. In addition, OpenStreetMap and its exposure data provides the base map for Peta Bencana for a crowdsourced flood information using social media and instant messaging apps. As part of the project, the team will also be handing out printed of the areas mapped as a token of appreciation for their collaborative efforts of volunteers.

Main lessons:

  • The existence of efficient tools can considerably enhance the collaborative efforts.
  • The use of OSM and up-to-date satellite imagery can provide the basic backdrop maps for the collection of specific data
  • The collaboration and active involvement of experienced partners considerably helps towards the success of the project
  • Volunteer engagement, training and capacity building are fundamental for the success and the continuation of a project.