Hugo, from IMMAP, shares his expert insights on how GIS technologies are leveraged to analyze data, visualize scenarios, and facilitate rapid decision-making during emergencies.

Here are the key tools mentioned:

1. Kobo Toolbox: An open-source tool used for data collection in humanitarian contexts. Kobo Toolbox allows for both quantitative and qualitative data collection and is operational offline, which is crucial in areas with limited internet connectivity. It supports geospatial data collection and can be used for needs assessments in settings like refugee camps.
2. ODK Collect: Similar to Kobo Toolbox, ODK Collect is an open-source mobile application used for field data collection. It is widely used in humanitarian efforts for its ease of use and the capability to work offline.
3. QGIS: A free and open-source geographic information system used for viewing, editing, and analyzing geospatial data. Hugo notes that QGIS is core for mapping and data analysis in humanitarian operations.
4. Tableau and Power BI: Business intelligence tools mentioned for their use in analyzing and visualizing data. These tools help in making data-driven decisions during humanitarian operations.
5. Humanitarian Data Exchange (HDX): An open platform for sharing data across crises and organizations, which helps in avoiding duplication of efforts and enhances coordination among humanitarian actors.
6. Humanitarian OpenStreetMap Team (HOT): Provides crowdsourced geospatial data which is extremely valuable in humanitarian settings for its accuracy and timeliness.
7. Esri’s Living Atlas and other Esri tools: While not open-source, Esri’s tools are sometimes used for their comprehensive geospatial data, particularly in natural disaster contexts like earthquakes.
8. Humanitarian Spatial Data Center: Managed by IMMAP, this tool aggregates and processes data, providing access to data, analytics, and visualization tools all in one place. It has been particularly successful in deployments like Afghanistan.

This episode was sponsored by scribblemaps.com

Recommended Listening

• Geospatial Support For Humanitarian Emergencies
• A Self-Contained Environment For Open-Source Geospatial Tools
• QGIS Offline And In The Field
• The Business Of Web Maps
• Peer to Peer Mapping And Digital Democracy

I am working on a new project over at QuickMapTools.com and any feedback is really appreciated!

In Conversation

The Global Surge Team

Daniel: Your title is Junior Information Management Officer with the Global Surge Team at iMMAP. What does the team do?

Hugo: The Global Surge Team has a core group of six or seven managers, and we manage an information management roster of 200-plus cross-disciplinary experts — from information management and GIS to full-stack web development. During a humanitarian crisis, man-made or natural, we deploy an expert to the field to support the humanitarian activities, mostly within the UN cluster system — one of the UN agencies we’re partnered with makes a request, and we find appropriate profiles to go and support them.

Daniel: Just to clarify — this is a geospatial podcast. Is there geo involved here?

Hugo: A huge component of information management is GIS. A GIS expert can do the data analysis, visualization, and prep; an information management officer can do those things too, but also looks at the data holistically — not just from a technical point of view. Entering a crisis, they need to know we’re getting data from six different stakeholders, make sure it’s all in the same format, and figure out how to contact them so the data keeps coming in regularly. With humanitarian crises, geospatial data is key, so GIS comes under the umbrella of an information management officer’s duties.

From Congo Park Ranger to Humanitarian GIS

Daniel: How did you get involved in geospatial at all?

Hugo: Almost by accident — when I first started doing GIS things, I didn’t even know I was doing GIS. I was about 24 and moved to the eastern Democratic Republic of Congo to work as executive assistant to the head warden of Virunga National Park. One of my roles was supporting the park rangers in mapping various aspects of the park, more specifically the poaching camps within the park boundaries — and what was being poached was actually charcoal; people took wood from the forest to build big kilns. I’d go up in tiny fixed-wing planes with the rangers, take down coordinates and snap photos of where the encampments were — you could spot them by the smoke from the kilns — and bring it back to HQ to map for the rangers to go and clear up.

Daniel: How did you get from that to what you do today?

Hugo: After I came back from the DRC I was at a bit of a loss for what to do. It was my sister — a marine biologist who’d done a lot of GIS — who suggested an Oxford University continuing-education course, a seven-week online course on the basics of GIS. And I went, “oh, that’s what I was doing.” My end-of-course project was mapping the topology of Virunga National Park. I grew up in a humanitarian family — my mom worked for the Red Cross, my dad for the WHO — so little by little I built up the skills and understanding of both the humanitarian and GIS worlds.

Being Deployed: What the Work Looks Like

Daniel: Have you been deployed yourself?

Hugo: A couple of times. The two most notable: in February 2023 I was deployed in support of DEEP, a knowledge and data analytics platform, with the OCHA analysis cell during the Turkey-Syria earthquake; and more recently in support of UNDSS Jerusalem — the UN Department for Safety and Security — to help with their incident reporting system. An incident, in a humanitarian or conflict context, can be anything from a protester arrested by police up to rocket fire landing in a particular district. Incident reporting is essentially what happened, who, and where — and from that you start making decisions about what support is needed, where, and how it can best be provided in the safest way possible for the people delivering the aid.

Daniel: What does a typical task look like — one very specific job, or something broad?

Hugo: It varies. For the UNDSS Jerusalem deployment we had a very specific task — they had an outdated data collection system of Excel files feeding into each other that crashed every time they ran the analytics, and we were brought in because it was untenable. But it’s not uncommon for a crisis to just need a generic GIS officer whose expertise is mapping, because there’s a surge in demand for those products — you say “you’re with the health cluster, I know the health cluster uses these templates, we’re going to create the contact list, build a surveying tool, create a dashboard,” boom, boom, boom. Within the humanitarian realm there’s the cluster system, which ensures there’s no duplication of work and that one central agency coordinates all the others. In the Ukraine crisis, 260 humanitarian organizations arrived in the field within three days of the fighting breaking out — so you need that holistic view of who’s doing what, where.

Working Offline: The Humanitarian Toolstack

Daniel: When I worked for a big corporation I could apply for any software, use cloud processing. My guess is that’s not always possible responding to a crisis.

Hugo: Oh, sweet summer child. Having internet when you’re deployed is a massive deal. One of the big things you do before deploying is make sure you have all the readily available data for the region on a USB stick or your laptop, so you can immediately create baseline situation reports from offline data. I don’t think I could go to any organization I’ve been deployed with and say “I need an FME license” and get it within the timeframe of a crisis. For the vast majority it’s open source — QGIS for mapping and data analysis is fairly core, business analytics tools like Power BI and Tableau get thrown around a lot, and for field data collection there’s ODK Collect, an open-source Android app, and Kobo Toolbox. ODK, Tableau, and QGIS were the three core humanitarian GIS and information management tools, without a doubt.

Daniel: Could you go into a bit more depth on ODK Collect and Kobo Toolbox?

Hugo: Kobo Toolbox is not far off from Survey123 — a spreadsheet-based surveying tool with geospatial capacity, so you can map quantitative and qualitative data alongside each other. That’s super helpful for needs assessments — you go into a refugee camp tent by tent and ask people their name, where they’re from, family size, what their needs are, and then map it with simple heatmaps or choropleth maps to understand the layout of the camp and how the needs are reflected in where people are placed. It’s open source, so you can make changes you need, it works offline, and it can link to servers so multiple enumerators gather the same information and upload it once they reach connectivity.

Where the Data Comes From

Daniel: Where do you get your data — what’s a typical pack of data you’d take on that USB stick?

Hugo: The first place you go is HDX — the Humanitarian Data Exchange, run by OCHA, the UN Office for the Coordination of Humanitarian Affairs. Humanitarians love a good acronym. HDX is a widely available database focused on humanitarian relief; iMMAP both contributes data to it and gathers data from it. If a humanitarian organization has a GIS or data component and isn’t uploading to HDX — shame on you, you should be; it’s one of the most important tools for information sharing within the community. Then there’s the Humanitarian OpenStreetMap Team — mostly volunteer-based, with incredibly powerful crowdsourced data that can be more accurate than normal data-gathering. If you have access to the Esri suite, Living Atlas has a lot of natural disaster data — for earthquakes it’s almost immediately available as a comprehensive layer. My personal recommendation is the PDC, the Pacific Disaster Center, based in Hawaii. And there’s our own — the Humanitarian Spatial Data Center, a data aggregate that also does processing and analysis built into dashboards, deployed most successfully in Afghanistan.

AI, Edge Computing, and Why On-Site Is Different

Daniel: Cloud-native formats, cloud processing, edge computing, AI — do you see benefits from those technologies in your work?

Hugo: I wish we did. It wasn’t long ago that most of this data was still collected with pen and paper, simply because there wasn’t access to even an Android phone — so moving from pen and paper, collated manually, to a digital system straight away with a telephone is already huge. AI and image processing are really great in the preparedness phase, but during a crisis, where the Surge Team works, it’s borderline impossible to deploy a neural network or edge processing — people won’t necessarily know how to use it, and what benefit does it bring compared to physically doing the work quickly? Remotely it changes a bit — during the Turkey-Syria earthquake my support was mostly remote, doing more complex data gathering and processing. Image analysis can measure change — comparing a satellite image of a city from before and after an earthquake to define the percentage of buildings destroyed — but is that useful in the first 48 hours, when reducing human suffering is the goal? Over the longer rebuilding phase, yes. And a neural network trained in one context won’t transfer — a building in Antalya doesn’t have the same bird’s-eye footprint as a building in Ouagadougou. You can get the same result with open-source citizen science — volunteers who spend three hours a day confirming “this building was here on the 6th of December, destroyed on the 7th.”

Localizing the Response: The Refugee Camp Water Story

Daniel: You used a great example before about water distribution in a refugee camp — localizing the response. Could you share that again?

Hugo: During the Rohingya crisis there was a massive influx of refugees into the Cox’s Bazar region of Bangladesh, and as the camps were set up, water sites — huge 5,000-litre containers — were placed throughout the camp. Our enumerators went through asking what people needed, and found that even though the water sites were all over the camp, certain people said they didn’t have enough water. With the survey data we knew where people were and the population density; with satellite imagery we knew the camp’s footprint; with the water-site points we knew the containers were placed equidistant in a perfect grid. It turned out the people in the centre of the camp were the ones short of water — because the earliest arrivals packed densely into the core, while later arrivals on the outside had more space and smaller families. If you’d only had the remote-sensing data and the water-point locations, you’d have looked at it and said it was perfectly balanced — everyone has access to the same amount of water. It took someone in the field going family by family, asking the question, for it to be mapped. That’s what I mean by localizing the information — and without it, people would have suffered.

Daniel: And the people doing this work — are they Westerners, or local to that environment?

Hugo: A vast majority of the people we deploy are from the global South — sub-Saharan Africa, South America. It’s the most diverse roster I’ve come across, and that adds a layer of localization: a crisis in South Sudan, you can send someone Sudanese who understands the context. And the enumerators going out to gather the data are from the local community, so you’re transferring very particular skills — step by step training up people in the local area who can gain enough experience to one day apply to be an information management officer themselves.

The Future, and How to Get Involved

Daniel: What’s the biggest problem — the thing you’d solve first with a magic wand?

Hugo: I’d stop wars — you don’t need the most developed GIS tools if there are fewer conflicts. But not to be facetious: a global, properly functioning local network connection — 5G everywhere — would go a long way. It would make cloud computing feasible on the go: you wouldn’t need the most powerful machine, just your little workhorse laptop accessing a supercomputer in Switzerland to process huge amounts of raster data. And from a security standpoint, being able to tell HQ in real time “completed the survey of this quadrant, moving to the next, the enumerator is safe,” rather than waiting for a three-and-a-half-hour drive back to internet connectivity — those increments of time saved matter.

Daniel: Are we getting better at responding to humanitarian crises?

Hugo: Almost certainly. The humanitarian world has a mantra of “do no harm” — the moment something goes wrong it’s hellfire, so organizations have to be careful. A rudimentary example: it makes sense to give food to people who are starving, but in a protracted crisis going on for years, you have to make sure they don’t become reliant on the food being given out. Those lessons have been learned slowly, sometimes painfully, over the last 100 or 200 years, and once the juggernaut of the humanitarian world starts turning, it’s efficient and has the local context to do more good than harm. A fun anecdote: the founder of the International Committee of the Red Cross, in his book about witnessing the atrocities of a Napoleonic-era battle in northern Italy — the first page is a map. That’s such a powerful image for GIS in the humanitarian sphere.

Daniel: If a geospatial expert wants to get involved, what should they do?

Hugo: I’d be remiss not to put iMMAP forward — once a year we do an open call for people to apply to join our roster, after which you receive alerts when someone with your profile is needed for a location, with the terms of reference. Deployments are often short — one month, six weeks, three to six months. The other place to start is just volunteering — there are loads of volunteer-based humanitarian GIS activities. There’s a group called GISCorps with a volunteer network that groups regularly call upon; when I was at the ICRC we needed the location of all the National Society offices around Ukraine, activated GISCorps, and within three days 21 volunteers had built a dataset of about 600 points by trawling the internet. Just search “GIS humanitarian volunteer” and something will come up.