SPADE

Therefore, the hazard posed by heavy rain and subsequent flood events is significant and is gradually leading to increased vulnerability for communities worldwide.
There is a large number of data provided by satellites that can be used to predict flood areas in any place in the world. The combination of elements such as Digital Terrain models (DTM) and satellite images can generate prediction models for water flow and accumulation in a heavy rain event. Moreover, this information is already available in an open-source format, provided by space agencies like NASA and ESA.
However, to put the pieces of the puzzle together, it takes specialized knowledge that non-specialized audiences usually don't have. Therefore, these studies are usually conducted by governmental bodies and/or universities.  For this reason, their findings are communicated through academic or governmental reports, with the use of many technical terms, not suited for a broader audience.
Moreover, given the effort required to conduct these analyses, they are often limited to large urban centers and other interest areas, leaving small communities and rural areas uncovered. Furthermore, although a lot of time and effort need to be invested in producing these reports, they are quickly outdated by the pace of topography changes.

A study from Davenport et al. (2021) revealed that there is an increase in precipitation levels and historical changes in precipitation contributed to about one-third of flood damages from 1988 to 2017, which represents an additional impact of 73 billion dollars in damage during this period.

Therefore, the hazard posed by heavy rain and subsequent flood events is significant and is gradually leading to increased vulnerability for communities worldwide.

There is a large number of data provided by satellites that can be used to predict flood areas in any place in the world. The combination of elements such as digital elevation models (DEM) and satellite images can generate prediction models for water flow and accumulation in a heavy rain event. Moreover, this information is already available in an open-source format, provided by space agencies like NASA and ESA.

However, to put the pieces of the puzzle together, it takes specialized knowledge that non-specialized audiences usually don't have. Therefore, these studies are usually conducted by governmental bodies and/or universities.  For this reason, their findings are communicated through academic or governmental reports, with the use of many technical terms, not suited for a broader audience.

Moreover, given the effort required to conduct these analyses, they are often limited to large urban centers and other interest areas, leaving small communities and rural areas uncovered. Furthermore, although a lot of time and effort need to be invested in producing these reports, they are quickly outdated by the pace of topography changes.

Our solution is called Simulator for Predicting Accumulation and Drainage through Elevation (SPADE). It is an easy-to-use platform that provides insights in an iterative map about rainwater flow paths and areas susceptible to floods.

In summary, SPADE is a platform that provides insights into the effects of heavy precipitation in an area. By using location-based data and advanced algorithms, SPADE can accurately predict water flow paths and areas susceptible to floods and provide real-time information to everyone. This solution can assist in minimizing the impact of flooding on people and communities in urban and rural areas, as well as predict the effects of human activities on rainwater flow and accumulation.

From a technology perspective  SPADE applies open-data Digital Terrain Model (DTM), satellite images, and user's input regarding the precipitation and desired study area location to provide a representation of rainwater behavior on an interactive map.

Initially, our solution applies DTM to create a point cloud of city elevations. The cloud is later used to define local water basins and the elevation neighborhood of each point. This data serves as input for an algorithm that calculates probable rainwater flow based on the difference in elevation of the cloud points. The algorithm also determines points with a lower elevation within a group of neighbor points, indicating a potential water accumulation area and, therefore, a region at risk of flood.

The system also applies image recognition techniques to analyze satellite images to classify the area's different types of surface cover. Each type of coverage has an associated permeability index, that indicates how much will be absorbed by the soil and how much will flow to lower areas. The data provided by SPADE makes it possible to study the dimensioning and positioning of drainage mechanisms to analyze their impact in situations of heavy precipitation.

SPADE uses open data, such as those provided by the GeoE3 platform, ESA's Copernicus program, and the CGIARCSI consortium. Our algorithm works with no pre-processing, calculating the information at the moment it is requested by the user. This means that it can work with the most recent data available. This characteristic is vital for providing an assertive analysis of the ever-changing urban landscape.

The data provided by SPADE makes it possible to study the dimensioning and positioning of drainage mechanisms to analyze their impact in situations of heavy precipitation. 

A prototype of SPADE is already online at: SPADE prototype

The functionality of the system can also be checked in: Video of SPADE in action

SPADE is easy to use. The user inputs the desired city and the prediction of the amount of rain and presses the process button. After a short wait, SPADE provides the probable water flow, possible accumulation points, and the volume of water accumulated. Right now, our prototype can study the areas of Coimbra and Porto (Portugal) and apply simplified satellite images for determining the surface cover, like the ones from the OpenStreetMap database.

SPADE serves a broad and diverse audience, each benefiting in tailored ways:

• Residents in Flood Hazard and Risk Areas: Individuals living in zones historically prone to flooding, as well as those in areas more recently      at risk due to climate change, use SPADE to understand their flood hazard and risk better. This knowledge empowers them to take preventive measures, safeguarding their homes and families.
• Rescue Services: SPADE enables these teams to predict flood-prone areas in advance, enhancing their preparedness and efficiency in emergency responses, potentially saving lives and resources.
• Government Agencies: By leveraging SPADE, governments can improve urban planning and infrastructure projects, creating more effective and therefore safer drainage systems, authorizing construction in safer zones, and foreseeing environmental impact changes, thus bolstering community resilience.
• Insurance Companies: SPADE's detailed flood hazard mapping allowing insurers to more accurately gauge property flood risks. This leads to fairer premiums and more informed coverage decisions.
• Individuals and Businesses: Prospective property buyers or renters can make informed decisions to protect their investments and safety. Businesses gain insights into operational risks due to weather, aiding in disruption planning.

SPADE’s user-friendly design significantly enhances safety, economic stability, and planning efficiency for its users, contributing to resilience against climate change’s impacts.

The impacts resulting from heavy rainfall can be felt by virtually anyone living in a flood prone area. Unfortunately, given the increase in heavy rainfalls due to climate change and some urbanization processes  that involve high levels of soil sealing, increasing flood risks, the number of people living in flood risk areas is increasing, which includes our team, As people who have lived in different cities, including Florianópolis, Fortaleza, São José (Brazil), Coimbra, Porto (Portugal), and Calgary (Canada), we have experienced first hand the effects that heavy rainfall can have on cities and surrounding localities.

The SPADE team is composed of three doctoral students. Armando Dauer and Tiago Tamagusko have a background in civil engineering and experience in optimization, artificial intelligence, and, especially, scientific research. The third team member, Juliana Carvalho, has a  background in international relations and spatial planning. Juliana has worked with rights-based policy projects and institutions, and with several projects related to climate change and citizen engagement. As a team, we combine skills in technological tools and evidence-based territorial analysis, with competences to effectively communicate our results to a broad range of stakeholders, including citizens living in hazard flood areas.

Applying our background in addition to personal experiences, we were able to perceive how these problems may impact the overall population through a bibliographic review of academic papers and governmental reports. This analysis was extremely important to direct the development of SPADE. This way, we could collect the knowledge produced by other researchers and add their perceptions to our own.

At this point, SPADE had the validity of its idea attested by a second place in the 2023 Location Intelligence for Smart Cities Hackathon. In the Hackathon, SPADE was praised for its versatility, being able to be applied in a great number of applications, all of them of great importance. The jury for this event was made up of specialists in urban planning, geoprocessing, and government representatives. The award of second place was seen by us as an indication that we are in the right direction to help solve a problem that affects the social, economic, and political aspects of the population.

Furthermore, throughout the maturity and development of the prototype, we intend to work with governments, insurers, emergency services entities, and the population in general. This close contact will serve to evaluate new possible applications of SPADE and implement a wider range of tools.

The basic coding for predicting rainwater flow, water accumulation, and soil cover identification is ready. Those are integrated and functional in a platform available at: SPADE

Anyone can access our platform and test our algorithm. Right now, their calculations are available for the Portuguese cities of Porto and Coimbra, but SPADE's cover area can be easily expanded. 

Moreover, we consider that our ideas, methods, and platform were validated after we got second place in the 2023 Location Intelligence for Smart Cities Hackathon.

We are applying to MIT Solve because being part of the Solve community can provide us with valuable resources, partnerships, and support to help us overcome our current barriers. Our project aims to prepare communities and cities for the changes and extreme weather events that will occur in the coming years, and we need partners interested in expanding our solution worldwide.

 While we can expand in Europe due to the availability of open DTM data, we are looking to reach out to other countries and regions interested in using our technology, such as insurance companies, cities at risk, and areas with potential flood risks. Climate change-induced flooding is a real and growing phenomenon that increasingly affects urban regions worldwide.

We believe that Solve can connect us with potential partners, grants, or investors who can provide financial support to develop our solution further and expand its reach, especially outside the EU, where we would like to offer our services in regions with available data. As we work with open data, our financial costs mainly involve maintaining cloud servers for storing and computing data, as well as the costs associated with developing and integrating new databases into the solution.

In addition to financial support, we face challenges with legal issues, establishing ourselves as a company or organization, and navigating the complexities of growth. Solve can provide guidance and resources to help us overcome these legal hurdles and ensure a strong foundation for our solution as it grows. By becoming a Solver team, we want to leverage the diverse resources, expertise, and network that the MIT Solve community offers to overcome these challenges, scale our solution, and make a lasting impact in the fight against climate-induced flooding.

In simple terms, SPADE can analyze and transform complex open-source data into a simple and interactive format, with an easy to understand spatial visualization. This allows the use of this information for the most diverse applications, from a family analyzing where to build their house to governments preparing rescue routes and citizen awareness campaigns for flood events.

One of the main aspects that make SPADE innovative is to present a simple and dynamic interface to the user, making it accessible to different types of users (governments, companies, and ordinary people), allowing access and dissemination of knowledge about the area they inhabit, as well as its application in diverse areas and purposes.

Another point that should be highlighted is the constant updating of the information presented. The speed with which humanity modifies the environment can disassociate older studies from reality. SPADE can carry out new studies in an easy and fast way, from the supply of new updated input data.

Our solution, SPADE, simplifies complex data into an easy-to-use platform, allowing users from various backgrounds, including governments, businesses, and individuals, to understand and address flood risks effectively.

By analyzing open-source data such as Digital Terrain Models and satellite images, SPADE predicts rainwater flow paths and identifies flood-prone areas, empowering users to make informed decisions.

For residents in risk areas, SPADE provides crucial insights into flood risks, enabling them to take preventive measures to protect their homes and families. Rescue services benefit from SPADE's ability to predict flood-prone areas in advance, enhancing emergency response preparedness and potentially saving lives.

Moreover, governments can utilize SPADE to improve urban planning and infrastructure projects, creating safer drainage systems and bolstering community resilience against the impacts of climate change. Insurance companies benefit from SPADE's detailed risk assessments, leading to fairer premiums and better-informed coverage decisions. 

Overall, SPADE's user-friendly design and constant updating of information contribute to safety, economic stability, and planning efficiency, making it a vital tool in mitigating the impacts of flooding and climate change.

Some UN's SDG that relates directly to SPADE are:

• 11.5 By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to the global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations
• 13.1 Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries
• 13.2 Integrate climate change measures into national policies, strategies, and planning.

The correct way to measure the impact of our system is to compare historical data regarding heavy precipitation impacts with new ones in the areas where SPADE is available and used. Some indicators that may be used:

• Number of flooded areas during heavy precipitation;
• Average time for rescue services to reach areas in need;
• The yearly value of material losses related to heavy precipitation events;
• The yearly number of life losses related to heavy precipitation events.

The core of our solution is powered by a combination of Digital Terrain Models (DTMs) and satellite imagery analysis. We leverage advanced GIS technologies and artificial intelligence to create a predictive tool, named SPADE (Simulator for Predicting Accumulation and Drainage through Elevation).

SPADE analyzes elevation data and satellite images to calculate probable rainwater flow, pinpoint areas prone to flooding, and assess the extent of rainwater infiltration. In the next phase of our development, we plan to incorporate Artificial Intelligence for satellite image segmentation. Currently, we use computer vision models and process images on a pixel-by-pixel basis. By integrating AI into our solution, we aim to further enhance the accuracy of our terrain analysis.

Our system, built using Python 3.10.9, operates in the cloud and can easily adapt to platforms like AWS, Azure, or Google Cloud. This flexibility enhances scalability and reliability, ensuring optimal performance for users worldwide.

Part-Time Staff: 3 members

1 year

The impacts of heavy precipitation, rainwater flow, and floods can be seen in all communities, affecting especially vulnerable populations.

Initially, we thought of applying it to assist drainage projects in governments and route planning for rescue teams in an emergency. Its use for the general public (for analysis of places to live), as well as for insurance companies, was later proposed by a professional from another country who, due to his experience and knowledge different from ours, was able to see new applications in which our platform could be used.

Currently, SPADE's team is small, formed by three people who, despite adding knowledge and experiences from different lives, are still close (sharing countries of birth, residence, and academic backgrounds). However, with the growth of our team, we intend to make it as diverse as possible, so that the life experience, knowledge, and views of these people can propose new uses and applications of the system, directing our development towards something that can be useful for everyone. all people. 

Since SPADE is a virtual platform, and our team is used to working remotely, we intend to diversify our team with professionals from different countries, forming a multidisciplinary and diverse team.

Our business model is crafted to address the urgent need for effective flood risk management in the face of climate change. By utilizing cloud-based servers, open-source DTM data, satellite imagery, and machine learning algorithms, our platform, SPADE, provides comprehensive flood risk assessments. Our solutions cater to a wide audience including local governments, urban planners, insurance companies, and citizens, especially those in flood-prone areas, offering them critical insights to prepare for and mitigate the effects of flooding. 

Local governments and urban planners leverage SPADE to bolster community resilience through informed infrastructure development. Insurance companies benefit from our premium API service, integrating real-time flood risk data into their systems for enhanced risk management. Citizens and communities gain access to predictive information, empowering them to take proactive measures. Additionally, SPADE aids rescue services by identifying high-risk zones and optimal rescue routes. 

To ensure accessibility for all, especially communities and individuals most in need, we employ a tiered pricing model. Basic access remains free, supported by request limits to manage processing costs. Revenue from premium services, aimed at larger corporate users, supports this model, making it sustainable. We actively seek partnerships with international organizations, governments, NGOs, and philanthropic institutions for grants and funding to further subsidize our services for vulnerable groups. 

In our quest to refine SPADE and widen its impact, we engage closely with local communities. Workshops and feedback mechanisms allow us to incorporate local knowledge and crowdsourced data, enriching our risk assessments and recommendations. This community-driven approach not only enhances the accuracy of our service but also fosters a collaborative effort in combating flood risks. 

We are actively working to maintain low costs for our project and promote an innovative solution that can significantly improve people's lives. Our overarching goal is to have a positive impact on individuals and communities by enhancing climate resilience. By intertwining technological innovation with community engagement and strategic partnerships, our model is designed to provide vital services to those at the forefront of climate change challenges, ensuring our solutions remain accessible and impactful. As we evolve, our focus remains steadfast on empowering users with the knowledge to safeguard their futures against the threat of floods, contributing to a more resilient society.

Our strategy for financial sustainability hinges on a diversified revenue model that supports both our expansion and the continuous enhancement of our services. We aim to strike a balance between generating income and providing invaluable support to communities facing the risks of climate-induced flooding. Our revenue streams are designed to not only cover our operating costs but also to invest in further innovation and accessibility of our flood risk assessment platform, SPADE. Therefore, our forecast revenue streams are:

• Premium Services for Businesses: We target insurance companies and large corporations with our premium API service, offering real-time flood risk data integration. This service caters to businesses needing precise risk management solutions, with options for highly detailed data resolutions. The income from these premium services forms a crucial pillar of our financial strategy.
• Service Contracts with Governments and Institutions: Recognizing the necessity for accurate flood risk data among local governments and urban planners, we pursue service contracts that provide a reliable income source. Our contracts are tailored to meet the specific needs of these entities, including advanced simulations incorporating drainage systems.
• Partnerships for Donations and Grants: To ensure our solution reaches those in critical need, we actively seek funding from international organizations, NGOs, and philanthropic bodies. These funds are essential for subsidizing our services for at-risk communities and supporting our mission to enhance climate resilience.
• Accessible Community Services: Committed to community service, we offer SPADE for free to individuals and communities, with certain usage limitations to manage cloud processing costs effectively. This approach ensures widespread accessibility while maintaining operational sustainability. Our commitment to a mixed revenue model—encompassing premium business services, government contracts, and philanthropic support—ensures we stay true to our dual mission of achieving financial sustainability and making a significant positive impact on climate resilience. This approach positions us to continue our work, focusing on innovation, accessibility, and the wellbeing of communities globally in the face of escalating flood risks.