Access, Signal, Action: Data Stewardship Lessons from Valencia’s Floods

Curated on Posted on by Stefaan Verhulst

Article by Marta Poblet, Stefaan Verhulst, and Anna Colom: “Valencia has a rich history in water management, a legacy shaped by both triumphs and tragedies. This connection to water is embedded in the city’s identity, yet modern floods test its resilience in new ways.

During the recent floods, Valencians experienced a troubling paradox. In today’s connected world, digital information flows through traditional and social media, weather apps, and government alert systems designed to warn us of danger and guide rapid responses. Despite this abundance of data, a tragedy unfolded last month in Valencia. This raises a crucial question: how can we ensure access to the right data, filter it for critical signals, and transform those signals into timely, effective action?

Data stewardship becomes essential in this process.

In particular, the devastating floods in Valencia underscore the importance of:

  • having access to data to strengthen the signal (first mile challenges)
  • separating signal from noise
  • translating signal into action (last mile challenges)…(More)”.

Proactive Mapping to Manage Disaster

Curated on Posted on by Stefaan Verhulst

Article by Andrew Mambondiyani: “..In March 2019, Cyclone Idai ravaged Zimbabwe, killing hundreds of people and leaving a trail of destruction. The Global INFORM Risk Index data shows that Zimbabwe is highly vulnerable to extreme climate-related events like floods, cyclones, and droughts, which in turn destroy infrastructure, displace people, and result in loss of lives and livelihoods.

Severe weather events like Idai have exposed the shortcomings of Zimbabwe’s traditional disaster-management system, which was devised to respond to environmental disasters by providing relief and rehabilitation of infrastructure and communities. After Idai, a team of climate-change researchers from three Zimbabwean universities and the local NGO DanChurchAid (DCA) concluded that the nation must adopt a more proactive approach by establishing an early-warning system to better prepare for and thereby prevent significant damage and death from such disasters.

In response to these findings, the Open Mapping Hub—Eastern and Southern Africa (ESA Hub)—launched a program in 2022 to develop an anticipatory-response approach in Zimbabwe. The ESA Hub is a regional NGO based in Kenya created by the Humanitarian OpenStreetMap Team (HOT), an international nonprofit that uses open-mapping technology to reduce environmental disaster risk. One of HOT’s four global hubs and its first in Africa, the ESA Hub was created in 2021 to facilitate the aggregation, utilization, and dissemination of high-quality open-mapping data across 23 countries in Eastern and Southern Africa. Open-source expert Monica Nthiga leads the hub’s team of 13 experts in mapping, open data, and digital content. The team collaborates with community-based organizations, humanitarian organizations, governments, and UN agencies to meet their specific mapping needs to best anticipate future climate-related disasters.

“The ESA Hub’s [anticipatory-response] project demonstrates how preemptive mapping can enhance disaster preparedness and resilience planning,” says Wilson Munyaradzi, disaster-services manager at the ESA Hub.

Open-mapping tools and workflows enable the hub to collect geospatial data to be stored, edited, and reviewed for quality assurance prior to being shared with its partners. “Geospatial data has the potential to identify key features of the landscape that can help plan and prepare before disasters occur so that mitigation methods are put in place to protect lives and livelihoods,” Munyaradzi says…(More)”.

Emerging technologies in the humanitarian sector

Curated on Posted on by Stefaan Verhulst

Report and project by Rand: “Emerging technologies have often been explored in the humanitarian sector through small scale pilot projects, testing their application in a specific context with limited opportunities to replicate the testing across various contexts. The level of familiarity and knowledge of technological development varies across the specific types of humanitarian activities undertaken and technology areas considered.

The study team identified five promising technology areas for the humanitarian sector that could be further explored out to 2030:

  • Advanced manufacturing systems are likely to offer humanitarians opportunities to produce resources and tools in an operating environment characterised by scarcity, the rise of simultaneous crises, and exposure to more intense and severe climate events.
  • Early Warning Systems are likely to support preparedness and response efforts across the humanitarian sector while multifactorial crises are likely to arise.
  • Camp monitoring systems are likely to support efforts not only to address security risks, but also support planning and management activities of sites or the health and wellbeing of displaced populations.
  • Coordination platforms are likely to enhance data collection and information-sharing across various humanitarian stakeholders for the development of timely and bespoke crisis response.
  • Privacy-enhancing technologies (PETs) can support ongoing efforts to comply with increased data privacy and data protection requirements in a humanitarian operating environment in which data collection will remain necessary.

Beyond these five technology areas, the study team also considered three innovation journey opportunities:

  • The establishment of a technology horizon scanning coalition
  • Visioning for emerging technologies in crisis recovery
  • An emerging technology narrative initiative.

To accompany the deployment of specific technologies in the humanitarian sector, the study team also developed a four-step approach aimed to identify specific guidance needs for end-users and humanitarian practitioners…(More)”.

The Power of Volunteers: Remote Mapping Gaza and Strategies in Conflict Areas

Curated on Posted on by Stefaan Verhulst

Blog by Jessica Pechmann: “…In Gaza, increased conflict since October 2023 has caused a prolonged humanitarian crisis. Understanding the impact of the conflict on buildings has been challenging, since pre-existing datasets from artificial intelligence and machine learning (AI/ML) models and OSM were not accurate enough to create a full building footprint baseline. The area’s buildings were too dense, and information on the ground was impossible to collect safely. In these hard-to-reach areas, HOT’s remote and crowdsourced mapping methodology was a good fit for collecting detailed information visible on aerial imagery.

In February 2024, after consultation with humanitarian and UN actors working in Gaza, HOT decided to create a pre-conflict dataset of all building footprints in the area in OSM. HOT’s community of OpenStreetMap volunteers did all the data work, coordinating through HOT’s Tasking Manager. The volunteers made meticulous edits to add missing data and to improve existing data. Due to protection and data quality concerns, only expert volunteer teams were assigned to map and validate the area. As in other areas that are hard to reach due to conflict, HOT balanced the data needs with responsible data practices based on the context.

Comparing AI/ML with human-verified OSM building datasets in conflict zones

AI/ML is becoming an increasingly common and quick way to obtain building footprints across large areas. Sources for automated building footprints range from worldwide datasets by Microsoft or Google to smaller-scale open community-managed tools such as HOT’s new application, fAIr.

Now that HOT volunteers have completely updated and validated all OSM buildings in visible imagery pre-conflict, OSM has 18% more individual buildings in the Gaza strip than Microsoft’s ML buildings dataset (estimated 330,079 buildings vs 280,112 buildings). However, in contexts where there has not been a coordinated update effort in OSM, the numbers may differ. For example, in Sudan where there has not been a large organized editing campaign, there are just under 1,500,000 in OSM, compared to over 5,820,000 buildings in Microsoft’s ML data. It is important to note that the ML datasets have not been human-verified and their accuracy is not known. Google Open Buildings has over 26 million building features in Sudan, but on visual inspection, many of these features are noise in the data that the model incorrectly identified as buildings in the uninhabited desert…(More)”.

Collaborating with Journalists and AI: Leveraging Social Media Images for Enhanced Disaster Resilience and Recovery

Curated on Posted on by Stefaan Verhulst

Paper by Murthy Dhiraj et al: “Methods to meaningfully integrate journalists into crisis informatics remain lacking. We explored the feasibility of generating a real-time, priority-driven map of infrastructure damage during a natural disaster by strategically selecting journalist networks to identify sources of image-based infrastructure-damage data. Using the REST Twitter API, 1,000,522 tweets were collected from September 13-18, 2018, during and after Hurricane Florence made landfall in the United States. Tweets were classified by source (e.g., news organizations or citizen journalists), and 11,638 images were extracted. We utilized Google’s AutoML Vision software to successfully develop a machine learning image classification model to interpret this sample of images. As a result, 80% of our labeled data was used for training, 10% for validation, and 10% for testing. The model achieved an average precision of 90.6%, an average recall of 77.2%, and an F1 score of .834. In the future, establishing strategic networks of journalists ahead of disasters will reduce the time needed to identify disaster-response targets, thereby focusing relief and recovery efforts in real-time. This approach ultimately aims to save lives and mitigate harm…(More)”.

This free app is the experts’ choice for wildfire information

Curated on Posted on by Stefaan Verhulst

Article by Shira Ovide: “One of the most trusted sources of information about wildfires is an app that’s mostly run by volunteers and on a shoestring budget.

It’s called Watch Duty, and it started in 2021 as a passion project of a Silicon Valley start-up founder, John Mills. He moved to a wildfire-prone area in Northern California and felt terrified by how difficult it was to find reliable information about fire dangers.

One expert after another said Watch Duty is their go-to resource for information, including maps of wildfires, the activities of firefighting crews, air-quality alerts and official evacuation orders…

More than a decade ago, Mills started a software company that helped chain restaurants with tasks such as food safety checklists. In 2019, Mills bought property north of San Francisco that he expected to be a future home. He stayed there when the pandemic hit in 2020.

During wildfires that year, Mills said he didn’t have enough information about what was happening and what to do. He found himself glued to social media posts from hobbyists who compiled wildfire information from public safety communications that are streamed online.

Mills said the idea for Watch Duty came from his experiences, his discussions with community groups and local officials — and watching an emergency services center struggle with clunky software for dispatching help.

He put in $1 million of his money to start Watch Duty and persuaded people he knew in Silicon Valley to help him write the app’s computer code. Mills also recruited some of the people who had built social media followings for their wildfire posts.

In the first week that Watch Duty was available in three California counties, Mills said, the app had tens of thousands of users. In the past month, he said, Watch Duty has hadroughly 1.1 million users.

Watch Duty is a nonprofit. Members who pay $25 a year have access to extra features such as flight tracking for firefighting aircraft.

Mills wants to expand Watch Duty to cover other types of natural disasters. “I can’t think of anything better I can do with my life than this,” he said…(More)”.

Routledge Handbook of Risk, Crisis, and Disaster Communication

Curated on Posted on by Stefaan Verhulst

Book edited by Brooke Fisher Liu, and Amisha M. Mehta: “With contributions from leading academic experts and practitioners from diverse disciplinary backgrounds including communication, disaster, and health, this Handbook offers a valuable synthesis of current knowledge and future directions for the field. It is divided into four parts. Part One begins with an introduction to foundational theories and pedagogies for risk and crisis communication. Part Two elucidates knowledge and gaps in communicating about climate and weather, focusing on community and corporate positions and considering text and visual communication with examples from the US and Australia. Part Three provides insights on communicating ongoing and novel risks, crises, and disasters from US and European perspectives, which cover how to define new risks and translate theories and methodologies so that their study can support important ongoing research and practice. Part Four delves into communicating with diverse publics and audiences with authors examining community, first responder, and employee perspectives within developed and developing countries to enhance our understanding and inspire ongoing research that is contextual, nuanced, and impactful. Offering innovative insights into ongoing and new topics, this handbook explores how the field of risk, crisis, and disaster communications can benefit from theory, technology, and practice…(More)”

People with Lived Experience and Expertise of Homelessness and Data Decision-Making

Curated on Posted on by Stefaan Verhulst

Toolkit by HUD Exchange: “People with lived experience and expertise of homelessness (PLEE) are essential partners for Continuums of Care (CoCs). Creating community models that acknowledge and practice inclusivity, while also valuing the agency of PLEE is essential. CoCs should work together with PLEE to engage in collection, review, analyzation, and use of data to make collaborative decisions impacting their local community.

This toolkit offers suggestions on how PLEE, community partners, and CoCs can partner on data projects and additional local data decision-making efforts. It includes resources on partnership practices, compensation, and training…(More)”

Lethal AI weapons are here: how can we control them?

Curated on Posted on by Stefaan Verhulst

Article by David Adam: “The development of lethal autonomous weapons (LAWs), including AI-equipped drones, is on the rise. The US Department of Defense, for example, has earmarked US$1 billion so far for its Replicator programme, which aims to build a fleet of small, weaponized autonomous vehicles. Experimental submarines, tanks and ships have been made that use AI to pilot themselves and shoot. Commercially available drones can use AI image recognition to zero in on targets and blow them up. LAWs do not need AI to operate, but the technology adds speed, specificity and the ability to evade defences. Some observers fear a future in which swarms of cheap AI drones could be dispatched by any faction to take out a specific person, using facial recognition.

Warfare is a relatively simple application for AI. “The technical capability for a system to find a human being and kill them is much easier than to develop a self-driving car. It’s a graduate-student project,” says Stuart Russell, a computer scientist at the University of California, Berkeley, and a prominent campaigner against AI weapons. He helped to produce a viral 2017 video called Slaughterbots that highlighted the possible risks.

The emergence of AI on the battlefield has spurred debate among researchers, legal experts and ethicists. Some argue that AI-assisted weapons could be more accurate than human-guided ones, potentially reducing both collateral damage — such as civilian casualties and damage to residential areas — and the numbers of soldiers killed and maimed, while helping vulnerable nations and groups to defend themselves. Others emphasize that autonomous weapons could make catastrophic mistakes. And many observers have overarching ethical concerns about passing targeting decisions to an algorithm…(More)”