Advanced Training on Earth Observation (EO) Applications for Disaster Risk Management in Lao PDR
UNOSAT is implementing The project “Strengthening Capacities in the Use of Geospatial Information for Improved Resilience in Asia-Pacific and Africa.” (2021-2024) intends to develop sustainable capacities and implement ad-hoc and tailored geospatial solutions. These can help to improve existing policy and decision-making processes to solve priority issues in the fields of Disaster Risk Reduction. Partnership with the government is crucial to the success of the project. UNOSAT aims to develop innovative capacity development solutions and geospatial services by integrating data, technology, knowledge, and people - custom-tailored to the country's needs. This 3-year long project builds on previous experiences and aims to further enhance capacities by leveraging technological advances and innovation and providing integrated geospatial solutions for improved decision making in the fields of Disaster Risk Reduction, Climate Resilience, Environmental Preservation in the eight target countries: Bangladesh, Bhutan, Fiji, Lao PDR, Nigeria, Solomon Islands, Uganda, and Vanuatu.
LaoPDR is exposed to various natural hazards like flood, tropical depressions, landslides specially from hydrometeorological hazards which are likely to worsen with changing climate. For example, droughts are expected to significantly worse in the southern parts of the country. Precipitation is expected to increase by 10% to 30% with a temperature rise of 1 to 2 degrees (Government of Lao PDR, 2010) with that flooding and rainfall triggered landslides are likely to occur more frequently. The social and economic impact of disasters undermines the development progress and possibility of the country to achieve its target of graduating beyond the Least Developed Countries (LCDs) by 2024. The lack of reliable and updated baseline data for hazards, exposure, and vulnerability undermines the capacity at the national and subnational levels to plan and implement effective disaster risk management and climate resilience actions in both the short and long-term. Especially in the immediate aftermath of disasters there is lack of reliable information to support response activities.
To reduce the risks, its essential to understand the risk using geospatial technologies, as factors like hazard, exposure, vulnerability are location-bound. Earth Observation (EO) has become one of the most crucial tools for DRM, both for risk reduction and response. EO gives us the ability to collect continuous observation of the earth’s surface, and which shapes our understanding of hazard dynamics, development patterns, monitoring of risk driving factors like climate change, environmental degradation. After disasters, satellite images can help us to estimate impacts and losses for immediate response. In the first training the project team covered emergency response support analysis using satellite imagery.
As a follow-up and to cater to the needs of government official of Lao PDR, UNOSAT is offering a technical course in the use of Earth Observation (EO) for disaster risk management (DRM).
At the end of the course participants should be able to:
- Describe the fundamental concepts of remote sensing and recognise its importance for disaster risk management.
- Identify and gather remote sensing derived dataset from web-based platforms.
- Utilise remote sensing indices for conducting disaster exposure analysis.
- Perform digital image classification of satellite image for landcover mapping and change detection.
- Apply EO derived information to enhance decision making related to disaster risk management.
Produce maps for supporting decision making process.
This course is designed to provide advanced training in remote sensing and geospatial analysis, with a focus on the use of technologies and tools for disaster risk management. Participants will gain hands-on experience with various software platforms and techniques, enabling them to extract valuable insights from remote sensing data that can be used for DRM. The course covers a wide range of topics, including advanced image processing, digital image classification, and change detection using open-source software QGIS. Moreover, participants will delve into real-world applications of remote sensing to support decision making process related to DRM.
This is a 5-day full-time face-to-face technical training divided into 5 modules. This face-to-face course will consist of lectures and GIS lab exercises using GIS datasets and real case scenarios, whereas 70% of the training content will focus on lab exercises while 30% will be lectures and discussions.
The course is designed to accommodate selected participants by Department of Social Welfare and other relevant stakeholders preferably selected from the participants of the Introductory Course on Strengthening Capacities in the Use of Geospatial Information Technology (GIT) for Disaster Risk Management.
The course will be delivered in Laotian & Thai. Training materials will be made available both in English and Laotian.
GIS lab exercises will be based on Open Source QGIS software.