COMPETITION dETAIL

Problem 1

Flood Risk and Impact Assessment in Refugee Camps Settings, Bangladesh

Problem Statement: "The Rohingya refugee camps in Cox's Bazar are prone to flooding due to monsoon rains. Using open-source remote sensing data, identify flood-prone areas within the camps and assess the potential impact on shelters and infrastructure. Your task is to create a detailed flood risk map, highlighting areas at high risk, and provide recommendations for flood mitigation strategies to aid emergency response efforts."

Research Question: Can global flood risk data be used to understand camp flood risk?

Through this assessment you will answer these questions

How many camps are exposed?
Which camps are most exposed?
Where shall you conduct more detailed assessments?
Integrating building footprints, to understand which buildings/shelters are exposed?
Incorporate vulnerability to understand how different flood depths might impact the camp?

Objectives:

Identify and apply open geospatial datasets (global model outputs and EO data & products) to undertake flood risk assessments for Rohingya refugee camps in Bangladesh.
Recognize specific humanitarian challenges when assessing flood risk in refugee camps.

Data Sources:

Camp Boundaries and Information: You can download Rohingya refugee camp locations, populations and demographics data from UNHCR Operational Data Portal for Bangladesh. You can also visit the Humanitarian Data Exchange.
Global Flood Data: You can download the global flood hazard map produced by Fathom Global (v2) dataset.
Building Footprint Data: To understand where buildings are located within the camps, you will use Google Open Buildings footprints and Open Street Map

N.B: You are encouraged to explore and use any other open-source global datasets and software.

Software:

A geographical information software, you can use and download it from here QGIS.
You can also use Google Earth Engine, Google Colab and ArcGIS Pro software.

Expected Deliverables: A flood risk map (project file) and short report highlighting the shelters and areas are most vulnerable to flooding within the camps.

PROBLEM 2

Landslide Susceptibility Assessment in the Chittagong Hill Tracts, Bangladesh

Problem Statement: The Chittagong Hill Tracts (CHT) region in Bangladesh is highly vulnerable to landslides, especially during the monsoon season. Steep terrain, extensive deforestation, and frequent heavy rainfall significantly increase the landslide risk. The region’s rugged topography and limited accessibility make traditional, field-based surveys challenging, costly, and time-intensive. The goal of this project is to develop a landslide susceptibility map using open-source remote sensing data and Google Earth Engine (GEE) without relying on field data. This project will empower stakeholders to take proactive steps to mitigate landslide risks in this high-impact area.

Research Question: How effectively can remote sensing and open-access satellite data be utilized to predict and visualize landslide-prone areas in the Chittagong Hill Tracts, supporting anticipatory actions and risk mitigation?

This project will address the following key questions:

1. Which areas within the Chittagong Hill Tracts are most susceptible to landslides?

2. How do vegetation cover, slope, and rainfall patterns contribute to landslide risk in this region?

3. What is the role of satellite-based surface deformation monitoring in landslide early warning?

Objectives:

1. Utilize Google Earth Engine (GEE) and open-source satellite data to create a landslide susceptibility map for the CHT region.

2. Analyze changes in slope, vegetation cover, rainfall patterns, and ground stability to identify high-risk areas.

3. Develop a visualization tool that provides real-time monitoring and updates, supporting early warning efforts.

Data Sources:

Digital Elevation Model (DEM): SRTM DEM from NASA, for slope and aspect calculations.
Vegetation Data: Sentinel-2 satellite data from the European Space Agency (ESA), using NDVI for vegetation health and land cover assessment.
Rainfall Data: CHIRPS (Climate Hazards Group InfraRed Precipitation with Station Data) for monitoring rainfall distribution.
Surface Deformation Data: Sentinel-1 SAR data, used in interferometric (InSAR) analysis to detect ground deformation that may indicate landslide risk.

Expected Deliverables:

1. A dynamic landslide susceptibility map for the Chittagong Hill Tracts, visualizing high-risk zones with regularly updated data layers.

2. An interactive GEE application that allows users to toggle between different risk layers (slope, vegetation, rainfall) and monitor conditions in real-time.

3. A short project report with findings, insights, and recommendations for proactive landslide risk management and anticipatory action.

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