Application of GIS for Disaster Risk Management (Elective)
BGE
| Teaching Hours/week | Examination Scheme | Total Marks | ||||||||
| Internal | Final | |||||||||
| Theory | Practical | Theory | Practical | |||||||
| Cr | L | T | P | Duration | Marks | Duration | Marks | |||
| 3 | 3 | 1 | 40 | 3hrs | 60 | - | - | 100 | ||
Year: IV Semester: VIII
A. Course Objectives:
- Understand the Basic Concept of Disaster Risk Management
- Understand Role of GIS and RS in Disaster Risk Management
- Learn to acquire, process, and analyse spatial data for disaster risk management
- Explore the applications of GIS and RS in identifying hazards, assessing vulnerability, and planning disaster response and recovery
- Develop practical skills in utilizing GIS and RS software for disaster risk mapping, modelling, and decision-making
B. Course Content
1. Understanding DRM (6 hours)
1.1 Definition of terms: Disaster, Hazard, Risk, Vulnerability, Resilience, preparedness, mitigation, response, recovery, rehabilitation, early warning system, adaptation, DRR, DRM
1.2 Types of disaster: Natural disaster (Flooding, Landslide, GLOF, Earthquake, wildfire, drought, Pandemics, Epidemics etc) and Human induced disasters (Wars, Terrorism, Nuclear Accidents, Industrial pollutions, deforestation etc)
1.3 Disaster Management phases: Pre-Disaster Phase (Preparedness, Prevention, and Mitigation) and Post Disaster Phase (Emergency Response, Recovery, Reconstruction/ Rehabilitation)
2. Sources of Data and Information for DRM (8 hours)
2.1 Spatial Data: Topographic map, Satellite image, Aerial Photograph, Digital Elevation Model, GIS data layer such as land use/land cover, hydrology, building and construction, transportation, utility network, administrative boundary, geographic names, Cadastral data
2.2 Hazard specific data: Information on the characteristics, frequency, and intensity of various hazards, such as earthquakes, floods, landslide, and wildfires, historical records of past disasters, including their location, magnitude, duration, and impacts
2.3 Socio economic data: Census data information on population demographics, including age, gender, income levels, and disabilities, institutional data
2.4 Other various data and information: Information on emergency response protocols, evacuation routes, open spaces, shelter locations, and medical facilities available to affected populations, data on humanitarian aid, relief supplies, logistics, and coordination mechanisms used by government agencies, NGOs, and international organizations
3. Identifying Hazard (7 hours)
3.1 Identifying and mapping natural hazards using Remote Sensing data
3.2 Mapping land cover, land use, and terrain characteristics
3.3 Case studies: Mapping hazards such as floods, wildfires, and landslides
4. Vulnerability Assessment (7 hours)
4.1 Understanding vulnerability and exposure to disasters
4.2 GIS-based vulnerability assessment methodologies
4.3 Integrating socio-economic and infrastructure data for vulnerability analysis
5. Risk Modelling (7 hours)
5.1 Risk analysis concepts, Hazard, vulnerability, and exposure
5.2 GIS-based risk modelling techniques
5.3 Probabilistic and deterministic risk assessment approaches
5.4 Multi criteria analysis for disaster risk analysis
6. Visualization of DRM data (7 hours)
6.1 Static Map
6.2 Web map
6.3 3D visualization
6.4 Animation and time series data visualization
6.5 Simulation and modelling
7. Spatial Data Infrastructure for DRM (4 hours)
7.1 Concept of SDI
7.2 Meta data and clearing house
7.3 Data Policy and Data Standards, OGC, ISO
7.4 Integration of Multi source data and Interoperability
7.5 Bipad Portal
8. Brief introduction of Trends in DRM (4 hours)
8.1 Participatory approach: Stakeholder identification, Community engagement, use of opensource tool, participatory mapping, google earth
8.2 Technological Approach: Early Warning system, Real time monitoring, use of UAV, Integration of Artificial Intelligence and Machine Learning for DRM
Examination Scheme
| Chapter | Very short question | Short question | Long question | Total Marks | |||
|---|---|---|---|---|---|---|---|
| No of questions | Marks | No of questions | Marks | No of questions | Marks | ||
| 1 | 1 | 2 | 1 | 4 | - | - | 6 |
| 2 | - | - | 1 (2 or 3) | 10 | 10 | ||
| 3 | - | - | 2 | 4 | - | - | 8 |
| 4 | 1 | 2 | 1 | 4 | - | - | 6 |
| 5 | - | - | 1 (5 or 6) | 10 | 10 | ||
| 6 | - | - | 2 | 4 | - | - | 8 |
| 7 | 1 | 2 | 1 | 4 | - | - | 6 |
| 8 | 1 | 2 | 1 | 4 | - | - | 6 |
| Total | 4 | 8 | 4 | 32 | 2 | 20 | 60 |
Model questions:
Very short questions: [4*2=8]
- Define metadata
- What is the purpose of Spatial Data Infrastructure (SDI)?
- Write any two applications of Machine learning in Disaster risk management
- Define artificial intelligence
Short questions: [8*4=32]
- What is the difference between hazard, vulnerability, and risk in the context of Disaster Risk Management (DRM)
- How do early warning systems contribute to disaster preparedness and response?
- What is the concept of resilience? Briefly mention its significance in enhancing community livelihood
- What do you understand by spatial analysis? How does it play a role in assessing physical and socio-economic vulnerabilities within a given area?
- How do you identify various hazards by using an aerial or Remote Sensing image?
- What kind of static and dynamic technique can be used to visualize a flooding event effectively? Explain
- How can GIS be effective to forecast a disaster event? Explain with a suitable example
- Write short notes on any two:
- Vector and Raster Data
- Application of UAV in DRM
- Network Analysis
Long questions: [2*10=20]
- How does the integration of various types of spatial data, such as topographic, demographic, and environmental datasets, enhance the effectiveness of disaster risk modeling and assessment processes within DRM frameworks?
- Explain the principles and methodologies of GIS multicriteria analysis (MCA). How does it assist in hazard mapping, vulnerability assessment, and prioritization of risk reduction measures?