High-Level Project Summary
The use of remote-sensed data for disaster management has been steadily growing throughout these years as the Earth observations provide reliable and accurate information about the surface and weather changes on Earth. Skilled professionals utilized and integrated the satellite data with other existing data or technologies such as ground-based monitoring data and machine learning, to support decision-making processes during disasters. Actions taken in flood-prone areas like Bangladesh in response to satellite data for flood disaster management can bring about societal and environmental advantages such as lives saved, property and infrastructure protection, and minimal total economic losses.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
Introduction
Bangladesh has a long history of experiencing disastrous floods which impacted the country adversely. One of the main causes of floods in Bangladesh is its geography. In the account of annual floods in Bangladesh, the densely populated country with around 163 million people, needs a great amount of money to repair the damage caused by the floods.
Throughout these years, Bangladesh has taken several actions for flood disaster management, which includes but is not limited to, shelters, embankments, recovery and relief, food aid, prevention, detection, mapping, and protection measures. Most actions are decided with the support of satellite data, while some are just based on local base data or past experiences.
Satellites provide remotely sensed information over large spatial areas, which is extremely helpful for certain inundated areas that are inaccessible. Herein, we focus on how satellite data supports flood disaster management in Bangladesh and what are the tangible outcomes by applying the Impact Assessment Framework.
Highlights
In Bangladesh, the flood forecasting and warning system relies on river level data provided by the JASON-2 satellite. When the FFWC experimented on this new JASON-2 solution during the 2014 monsoon season in Bangladesh, it was able to forecast flooding eight days in advance for nine locations in the country. Whereas in the case where JASON-2 satellite data is absent, warnings were only issued three to five days before the flood. This system was able to provide longer lead times due to the radar altimeter on the JASON-2 satellite.
It is vital to understand which areas are inundated to minimize flood damage and can be critical for disaster risk management. If disaster relief and rescue agencies receive timely flood inundation information, they can respond faster to relief and rescue efforts. Besides, this data is also intrinsic for post-disaster management, including the planning of post-disaster recovery and damage evaluation, evaluation of flooded areas and damage assessment which could help Project Managers and authorities involved to plan and coordinate their efforts more effectively.
Table 1. VALUABLES Impact Assessment Framework: Satellite Data versus Without Satellite Data
Implementations of machine learning (ML), multi-criteria decision making (MCDM) and location-allocation modelling (LAM) in geographic information systems (GIS) are used to improve the efficiency of flood evacuation planning in Bangladesh. The proposed method uses satellite imagery and various technologies to produce crucial flood susceptibility mapping and risk assessment to develop an emergency evacuation plan for pre-flood and post-flood situations.
Table 2. VALUABLES Impact Assessment Framework: Integration of Other Technologies with Satellite Data versus Satellite Data by Itself
Impacts and Needs
There are still many challenges ahead and improvements to be made. Collaborations between agencies, product developers, and decision-makers should grow stronger to unlock the full potential of satellite data in flood disaster management. Sustainable and interoperable use of Earth observation products or tools should also be ensured as well as proactive assimilation of methodologies into the mandated agencies. End-user driven validation and feedback are also needed so that developers or engineers can continually build satellite-based systems that are of high credibility to the decision-makers. It is imperative that this technology can be applied around the world, especially in vulnerable, flood-prone regions. satellite data is ultimately imperative when it comes to disaster management and can make a major difference between life and death for millions.
Link for 4-minutes Presentation Video (exclusively for SpaceApps Sarawak) : https://youtu.be/wEp7X2S_R4s
Space Agency Data
As shown in the Table above, the listed satellites provide data such as weather forecast, streamflow, and many more can help in various flood stages. This has greatly inspired us to look into how decision-makers can respond to remote-sensed data to bring about tangible outcomes in terms of flood disaster management in flood-prone areas like Bangladesh.
In our project, we used the Jason-2/Ocean Surface Topography Mission (OSTM), the third in a U.S.-European series of satellite missions designed to measure sea surface height, which successfully ended its science mission on 1st of October 2021. Besides, data from Landsat 8, an American Earth observation satellite, and NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data were integrated with ground-based data and machine learning algorithms to provide information for decision-making processes for flood disaster management.
Hackathon Journey
Building our team
We are 5 students from Xiamen University Malaysia who are all in our 3rd year of studies within the same faculty. Our team initially started out with 3 people (Yi Wei, Kai Li and Yuen Ean) from the same major (Electrical & Electronic Engineering) that were interested in joining this event. They later decided to include some more teammates from another major (Software Engineering) to diversify our team’s experiences and skills.
Choosing our challenge
Our first meet up was through Discord (three weeks before the event starts) where we got to know each other better and felt that we could get along quite well for this challenge. We roughly went through all of the challenges together and took two days to think about what we want. During the two days, we each went to read up about topics related to what we are interested in and prepare for the next meeting to decide on our topic. We held a meeting to propose our ideas and then we evaluated each topic by the match of our skills with the expected solution and think about the feasibility to complete the challenge in due time. At last, we agreed to work on the challenge “Measuring the value of earth observation”.
Preparing for the challenge
After settling down with our topic (two weeks before the event starts), we look into different benefits that satellite imaging has brought to different parts of the world. We initially invested a few days to look upon the tangible benefits that satellite imaging has contributed to reducing air pollution. After a few rounds of discussion, we decided to study the benefits of Earth observations for flood disaster management in Bangladesh. We used the last week of time left before the event starts to research more about this topic by reading the news, journal articles and videos that were recommended on the SpaceApps website.
D-Day (Hackathon starts)
As the Hackathon starts, we have already done enough research and are very clear on how we should proceed as the event goes. We planned the timeline of what we should do for the two days which includes (preparing the research paper, planning the flow of presentation, designing the slides, recording our presentation and submitting all the files). We delegated jobs for everyone and kept each other updated at all times during the event with our progress. We had a really fun time and obtained different experiences throughout this event especially these two days.
References
ARSET - Satellite Remote Sensing of Flood Monitoring and Management | NASA Applied Sciences. (2018, November 18). Nasa.gov. https://appliedsciences.nasa.gov/join-mission/training/satellite-remote-sensing-flood-monitoring-and-management
Bangladesh Meteorological Department. (2019). Bmd.gov.bd. http://live4.bmd.gov.bd/#Chattogram
Banglapedia National Encyclcopedia of Bangladesh. (2021) “River”. https://en.banglapedia.org/index.php/River
Department of Disaster Management Ministry of Disaster Management and Relief. (2014). Flood Response Preparedness Plan of Bangladesh. https://www.sheltercluster.org/sites/default/files/docs/flood_response_preparedness_plan_of_bangladesh_june_2014.pdf
EU Science Hub. (2021).“Earth observation”. https://ec.europa.eu/jrc/en/research-topic/earth-observation
Harbaugh, J. (2017, August 7). Bangladesh Announces Nationwide Use of SERVIR Satellite-based Flood Fo. NASA. https://www.nasa.gov/mission_pages/servir/bangladesh-warning-system.html
Hossain, A., & Arifuzzaman Bhuiyan, Md. (2016). Application of Satellite Radar Altimeter Data in Operational Flood Forecasting of Bangladesh. Springer Remote Sensing/Photogrammetry, 287, 269–284. https://doi.org/10.1007/978-3-319-33438-7_10
Humanitarian Coordination Task Team. (2018). Response Preparedness Plan Bangladesh: Floods Humanitarian Coordination Task Team Final Draft. https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/2019/07/HCTT-Response-Preparedness-Plan-Bangladesh.pdf
Jason-2 - eoPortal Directory - Satellite Missions. (2014). Esa.int. https://earth.esa.int/web/eoportal/satellite-missions/j/jason-2
Patel, K. (2020, August). Intense Flooding in Bangladesh. Nasa.gov; NASA Earth Observatory. https://earthobservatory.nasa.gov/images/147057/intense-flooding-in-bangladesh
Rahman, M., Chen, N., Islam, M. M., Dewan, A., Pourghasemi, H. R., Washakh, R. M. A., ... & Ahmed, N. (2021). Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh. Geoscience Frontiers, 12(3), 101095. Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh - ScienceDirect
Rejaul Karim Byron & Refayet Ullah Mirdha. (2021). “Becoming A Developing Nation: Bangladesh reaches A Milestone”. https://www.thedailystar.net/frontpage/news/becoming-developing-nation-bangladesh-reaches-milestone-2052161
Satellite flood forecasts save lives, livelihoods in Bangladesh - Bangladesh. (2007, August 10). ReliefWeb. https://reliefweb.int/report/bangladesh/satellite-flood-forecasts-save-lives-livelihoods-bangladesh
SERVIR. (2019). NASA. https://www.nasa.gov/mission_pages/servir/index.html
Servir Global. (2015, September 30). Satellite Data Is Saving Lives with Flood Forecasting in Bangladesh. Climatelinks.org. https://www.climatelinks.org/blog/satellite-data-saving-lives-flood-forecasting-bangladesh
Uddin, K., & Matin, M. A. (2021). Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology. Progress in Disaster Science, 11, 100185. https://doi.org/10.1016/j.pdisas.2021.100185
Young, O. R., & Onoda, M. (2017). Satellite Earth Observations in Environmental Problem-Solving. Satellite Earth Observations and Their Impact on Society and Policy, 3–27. https://doi.org/10.1007/978-981-10-3713-9_1
Schumann, G. J-P., et al. (2016), Unlocking the full potential of Earth observation during the 2015 Texas flood disaster, Water Resour. Res., 52, 3288–3293, https://doi.org/10.1002/2015WR018428
Tags
#satellite #earthobservingsatellite #disastermanagement #flooding #data #remote-sensed #Bangladesh #water #impactassessmentframework #spacerangers #sarawak #earthobservationdata #satellitedata #disaster #SDG #unitednations
Global Judging
This project has been submitted for consideration during the Judging process.