WEBVTT

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You're listening to a stage talk titled Monitoring

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the Environment from Space. This week we were

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joined by the technical director from Space for

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Good as they walked us through the possible practical

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applications for satellite imagery when it comes

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to environmental monitoring, explaining how and

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why satellite images may be the best way to oversee

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large -scale rapid impacts on our climate and

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wildlife. This talk was hosted by my colleague

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Giancarlo Fiorella on Thursday the 10th of April,

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2025 in the Bellingcat Discord server. Welcome

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everybody. My name is Giancarlo Fiorella and

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I'm the Director of Research and Training here

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at Bellingcat. I am filling in for Charlie this

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week. who is away at a conference. I'm really

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excited to introduce you to Lisa Bruckhausen.

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Lisa is the tech lead at Space for Good and is

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a remote sensing specialist. Lisa and her team

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use satellite imagery and remote sensing techniques

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to monitor changes in the environment from space.

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Now, previously we'd spoken about a tool from

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a Bellingcat contributor named Chris Giles. And

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the name of the tool, you might remember, was

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the OSINT Forest Area Tracker. This is a tool

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that looks at burned areas of forest in Ukraine.

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And the purpose of the tool is to give users

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the ability to look further afield about forest

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fires in this part of the world. Now, that tool

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uses something called Sentinel -2 data. You can

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find it on our GitHub. If you go to GitHub and

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you look for Bellingcat, this is one of the many

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wonderful tools you'll find there. Space for

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Good have just come out with their own application

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to help people on the ground monitor deforestation

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from space. And Lisa is here to talk about that

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application and more of her work at Space for

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Good. Now, if you'd like to ask a question, please

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do so in the chat as we talk. I'll be writing

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down your questions and then asking them to Lisa

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towards the end of the talk. If you don't want

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me to read your username when I ask your question

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to Lisa, please make a note of that in the chat.

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Lisa, thank you so much for being here this afternoon

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in the Netherlands. I'm going to hand over the

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microphone to you now. Thanks very much for having

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me. Thanks everyone for being here, for listening

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in and a special thanks for Giancarlo and Charlie

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for setting this up and of course everyone here

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for all the good work. So I'm here today to share

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some of the work that we are doing and share

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some ideas and some inspiration on hopefully

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open some eyes on how a lot more can be done

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with the eyes we have in the sky, the satellites.

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I'm Lisa. I'm technical director of Space for

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Good and today I will focus mostly on the practical

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use cases with satellites. So I'll talk a bit

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about that, like I do every day and hopefully

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after this so will all of you. At Space for Good

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we work with satellite data to monitor the earth.

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We do this for projects we believe have a positive

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impact on the planet. I'll talk through some

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of the work we've done, some big developments

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and some smaller ones which nevertheless I think

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have a good impact. and hopefully share some

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ideas and inspirations on what's possible out

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there. During this session I will not get technical,

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but rather provide with a satellite overview.

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However, you're more than welcome to ask technical

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questions at the end, hoping for those. And when

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I say monitor the planet with satellites, I don't

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just mean working with pictures from space. I

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mean uncovering the stories. Environmental stories,

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land use stories, sometimes very personal stories.

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where the start of the story starts with the

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data. So first of all I didn't want to talk about

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Forester, our product to help detect illegal

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logging near real time in the field. It's a tool

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to give rapid alerts and really help Foresters

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on the ground take action rapidly rather than

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having long -term visuals over trends or regional

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actions. We rolled this out first of all in Indonesia.

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We're working with local partners to take direct

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action. Sometimes we use Sentinel -2 and need

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the optical data. For this, we use Sentinel -1,

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which is a radar data set, which means we can

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penetrate the clouds. Now, if we look at tropical

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rainforest, then rain kind of in there. There's

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a lot of precipitation, a lot of cloud cover.

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That means that with optical data, we often have

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just see the clouds. With radar data, we can

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look through the clouds and see changes that

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are happening. It's a bit less intuitive to read

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the data, but that's what we have algorithms

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for. So we look for changes, rapid changes, within

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areas that we before classified as forest. Within

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those areas, we look whether it's likely illegal

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logging or a legal or natural event such as a

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landslide. If we think it's illegal logging,

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we send the WhatsApp alert out to people in the

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fields directly. They go and they take action.

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So what we've seen before is that they come up

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with security guards to show the people that

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they have been spotted and to get the people

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out. Sometimes they use the reports we generate

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to go to local authorities and get the police

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involved. And with that, they can remove the

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people before a big conversion to agriculture

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happens, which means that the forest can recover

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faster and better. We now have a system that's

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over 98 % accurate, so that's really nice. In

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this area at least. In other areas we always

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need to retrain and revalidate because it's not

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a globally applicable model, but it's a model

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that really needs to be trained locally because

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the patterns and the nature is different in different

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locations. A bit about the stories. So one of

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the things we hear from our clients is that they

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can finally detect deforestation that happens

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away from roads. Imagine here it's a tropical

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rainforest condition. It's about 200 ,000 hectares

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of area to monitor. Roads tend to be washed away

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with rainfall or any other events and suddenly

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the road is gone. And even if the roads are perfect,

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yeah, it's a rainforest. You can't look into

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the forest and see very far. So you can only

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see a few meters. So before it was almost impossible

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to see these events because they happen outside

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of the direct road network, outside of direct

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fuel. And one more thing that we've seen, which

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I really like talking about. I don't like the

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story behind it. But we detect a full satellite

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view of the whole area, which means that we detect

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all deforestation events. What they noticed is

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with that data that around one security guard

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was positioned at different security posts. Whenever

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he was positioned, there would be a peak in illegal

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logging. So likely he let some family members

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through illegally but that's very difficult to

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assess if you don't have the full data. So by

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having that full map it could pinpoint hey here

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we need to do some more research to identify

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what's exactly going on. Quite a nice case to

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see like how this information we never thought

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something to be pinned down to an individual

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but that actually was possible with the help

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of the data and of course merging it with all

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sorts of other data sets. Now what we do here

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differs quite a bit from EUDR compliance because

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we are focused on near real -time direct action

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and I am assuming directly that almost everyone

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knows what EUDR is but some of you might not

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hear about it as much as I do so let me quickly

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expand EUDR is the European regulation for deforestation

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free supply chain starting next year probably

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you never know with EU it's intended to ensure

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that agricultural products entering the EU are

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not causing deforestation so that you can eat

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your bar of chocolate guilt free. Deforestation

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wise I'm not talking about fair pricing or human

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rights or calories today, but that it doesn't

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cause deforestation. EODR has a single definition

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of forest deforestation land cover where we rather

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look at trees disappearing. So we don't look

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at is a plot of forest converted to agriculture,

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but we look at there were trees here, there are

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none now, take action. rather than saying there

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were trees here, there's agriculture, two years

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later, so you can't import. And then we really

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focus on enabling people in the field to take

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direct action. That's a bit about forest application,

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but deforestation, but it's not all bad. There's

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also afforestation, the growth of new forest,

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where new forests are being planted. So, nice

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story here. without naming specific names I'd

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like to come into a little case study we did

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where we got a request from a small tree planting

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NGO to compare how some of their different sites

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have been doing they used to do a lot of field

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work but with environmental more and more information

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about the flying but also safety concerns for

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quite a long period they couldn't go into their

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afforestation areas anymore so we did some analytics

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for them to compare how different sites were

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doing, which one was healthy, which one was managed

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well etc etc and in some sites we found that

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there were no trees left so the local partners

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had been receiving money to take care of the

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trees but had failed to report the death of several

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full plots so we're gonna go by mistakes happen

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but thanks to this data the project could be

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changed around gain additional management and

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it was made clear to the people locally that

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there were checkups being done which is, first

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is good, but validation is better. And of course

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it's bad that those trees didn't make it, but

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with satellite data, they could make early interventions

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and changes into the process. Now in this project,

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we also made some nice analytics, some quite

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nice algorithms we developed to compare the different

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sites, the missing trees. I would like to say

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that there was this amazing algorithm in -depth

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assessment. But basically it was looking at a

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picture and going to a colleague and, do you

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see trees? I don't see trees. And having figured

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out that there was a major issue here. Satellite

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data analytics can be rocket science, but often

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it's not. And then having that layer of extra

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accountability, especially in an industry where

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so much greenwashing is happening, can give that

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additional trust. And not having that layer...

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and lead to more scrutiny which at least leads

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to us all having something to do so that's also

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a win right? Looking at the current Belenka challenges

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there's also I also want to quickly point out

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some other things everything that has a location

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always grab a satellite image we did a project

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around illegal zoos small project there was no

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budget available so we had no commercial data

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but even looking at 10 meter resolution openly

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available satellite data It's the Sentinel -2

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program that's looking at only true color images.

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We could see the expansion of some of these wildlife

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breeding facilities as an extra source of information

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to help with the investigation of that party

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there. And animals or meat directly leads to

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biodiversity. We see a spike in biodiversity

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credits. where people are paying to support biodiversity

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within different areas, within different conservation

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sites or new nature developments. What is missing

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in a lot of cases is objective data. There is

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quite a lot we can see with satellites that relates

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to biodiversity. Very rarely you look at individual

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species, but often you get landscape features,

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diversity, landscape history, all those things

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can be mapped. That also brings us to an issue.

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If we can map multiple things, we can get different

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outcomes. And which outcome do you share when

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all of the different outcomes are correct, but

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also saying something different? I don't always

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have an answer to that, but I do know that the

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answer can't always be the most optimistic case

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or the most profitable case. Even if we don't

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look at the complexities of biodiversities, but

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look into carbon credits, which is something

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measurable theoretically, you can measure a tree.

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We see billions flowing into the carbon credit

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market, but are the protected areas even under

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threat? And that's why satellites are very important

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to generate a baseline to see what has been happening,

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because we can look back until the 70s of the

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last century to see evidence -based what has

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been going on. We can provide support whether

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a project is resulting in avoided deforestation

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or an aforestation, and identify good reference

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areas, or make strong claim why a reference area

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chosen, so an area where we compare the prediction

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site with chosen, is selected wrongly. And the

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net satellites can give a timeline rather than

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snapshots to tell the whole story instead of

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part of the story. We see that a lot with land

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cover conversion, where land is changing from

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forest to crop land, from pasture to urban, and

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we can detect whether that change is cyclic.

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So if you have shifting cultivation, every year

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part of a forest is cleared to convert to agriculture.

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That's not always the same as a fool on deforestation

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because maybe a year later a different area is

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cleared and it's part of the system that's being

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used within the region. But often it's not. Often

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it's just a cascade effect. Like we see in Indonesia,

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where we see in certain areas a pattern from

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primary forest. to the graded forest, to small

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water fields, to commercial palm oil. And that

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whole pattern can happen within a few years.

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Also, I want to quickly talk about invasive species

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monitoring. We do quite a lot of work in Indonesia.

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We now started just out the project to map invasive

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grasslands to support suitable afforestation

00:14:53.679 --> 00:14:56.659
areas. For us, that's pretty much the same as

00:14:56.659 --> 00:14:59.179
looking at making a land cover map, saying what's

00:14:59.179 --> 00:15:01.080
there. It's a bit more complex if we look at

00:15:01.080 --> 00:15:04.480
very specific species or species group. Almost

00:15:04.480 --> 00:15:07.440
everything you can see with the naked eye, especially

00:15:07.440 --> 00:15:10.100
if you can look from above and see it. You can

00:15:10.100 --> 00:15:12.259
also model and map on large scale with satellites,

00:15:12.340 --> 00:15:15.220
but also develop triggers, codes that give a

00:15:15.220 --> 00:15:18.159
trigger if something happens. That'd be quite

00:15:18.159 --> 00:15:21.259
nice to give warnings. And then I think my current

00:15:21.259 --> 00:15:24.220
favorite project to talk about is environmental

00:15:24.220 --> 00:15:28.320
risks. Imagine you spend a lot of time and resources

00:15:28.320 --> 00:15:32.649
to map a minefield in Ukraine. Imagine a dam

00:15:32.649 --> 00:15:37.490
breach or storm causing a flood. Mines get shifted

00:15:37.490 --> 00:15:39.690
with the water. They're relocated. You don't

00:15:39.690 --> 00:15:42.490
know where. You need to remap possibly a much

00:15:42.490 --> 00:15:45.529
larger area to figure out where the mines are

00:15:45.529 --> 00:15:47.769
in order to be cleaning them. With that we're

00:15:47.769 --> 00:15:50.149
working with the Halo Trust to map environmental

00:15:50.149 --> 00:15:52.870
risk to support in mine clearance priority setting.

00:15:53.769 --> 00:15:57.000
So where is a fire likely to happen? or a flood,

00:15:57.240 --> 00:15:59.379
like a fire you can't exactly send a fire truck

00:15:59.379 --> 00:16:02.799
into a minefield if there's a forest fire. Or

00:16:02.799 --> 00:16:04.500
where is a drought likely to happen and what

00:16:04.500 --> 00:16:07.759
communities will that affect? That's all information

00:16:07.759 --> 00:16:09.519
that can be helped in this case for better decision

00:16:09.519 --> 00:16:12.039
making but that's all information that can also

00:16:12.039 --> 00:16:14.559
be generated globally for different purposes.

00:16:15.340 --> 00:16:18.559
So really looking into the different risks based

00:16:18.559 --> 00:16:20.399
on the patterns that we've seen and based on

00:16:20.399 --> 00:16:23.139
the patterns that we expect in the future with

00:16:23.139 --> 00:16:27.129
for example climatic differences. And if a fire

00:16:27.129 --> 00:16:32.070
happens, where, how big, the faster the information

00:16:32.070 --> 00:16:34.830
can reach the right people, the better the action

00:16:34.830 --> 00:16:37.850
can be taken. So I can really recommend everyone

00:16:37.850 --> 00:16:39.870
to, if you haven't already, to look at the NASA

00:16:39.870 --> 00:16:43.549
Global Database firms. It provides information

00:16:43.549 --> 00:16:47.529
on patterns and trends and historic fires. So

00:16:47.529 --> 00:16:49.649
that way we can map and also make predictions.

00:16:49.889 --> 00:16:52.850
We can give alerts, we can map recovery, always

00:16:52.850 --> 00:16:56.340
globally and everywhere available. and objective.

00:16:57.919 --> 00:17:02.539
I say objective, but in this time of deep fakes

00:17:02.539 --> 00:17:05.960
and fake data, how can we be sure that satellite

00:17:05.960 --> 00:17:09.180
data can be trusted? Or how can we know when

00:17:09.180 --> 00:17:15.380
it can't? So far, large datasets have had very

00:17:15.380 --> 00:17:18.259
few large -scale issues, and I should be careful

00:17:18.259 --> 00:17:22.660
what I say with this audience, because the satellite

00:17:22.660 --> 00:17:25.630
data can feel inherently objective. It's from

00:17:25.630 --> 00:17:29.829
space. It looks like the truth. But as soon as

00:17:29.829 --> 00:17:33.750
it hits the ground or website, it can be framed,

00:17:33.869 --> 00:17:36.589
processed, and cherry -picked to give a particular

00:17:36.589 --> 00:17:40.430
story or a particular angle. And we can't pretend

00:17:40.430 --> 00:17:43.430
like the data is always going to be correct.

00:17:47.009 --> 00:17:51.490
So how to make sure the data is not manipulated

00:17:51.490 --> 00:17:54.640
or misrepresented and how to make sure that you

00:17:54.640 --> 00:17:58.920
don't accidentally misrepresent the data. Quite

00:17:58.920 --> 00:18:01.259
simply put, there's a lot of different satellites

00:18:01.259 --> 00:18:06.599
out there, so don't rely on a single image. Look

00:18:06.599 --> 00:18:10.640
at the time series, look at what change happened.

00:18:10.680 --> 00:18:13.119
Is it a sudden or gradual change? Is it a seasonal

00:18:13.119 --> 00:18:16.019
change? For example, if you look at the deforestation

00:18:16.019 --> 00:18:20.480
events, you can make very impressive images about

00:18:20.480 --> 00:18:23.740
European deforestation. by comparing summer and

00:18:23.740 --> 00:18:25.779
winter images, because the trees lose their leaves

00:18:25.779 --> 00:18:29.900
and everything looks dead. It's not. Guys, the

00:18:29.900 --> 00:18:35.039
forest survives. So really look at how does this

00:18:35.039 --> 00:18:38.079
thread, how is what we're seeing normally looking

00:18:38.079 --> 00:18:41.640
over time? And how is it looking with multiple

00:18:41.640 --> 00:18:44.900
sources? So there's a lot of different satellite

00:18:44.900 --> 00:18:47.460
constellations out there, both public and commercial.

00:18:48.859 --> 00:18:51.230
Satellites are a witness. and you don't rely

00:18:51.230 --> 00:18:53.210
on one witness when you've got a dozen out there.

00:18:53.829 --> 00:18:57.230
We have, for example, very nicely Sentinel and

00:18:57.230 --> 00:19:00.670
Landsat, where Landsat is hosted by the NASA.

00:19:01.170 --> 00:19:04.630
Sentinel is from the European Space Agency. So

00:19:04.630 --> 00:19:06.549
different sources that can look at the same thing,

00:19:07.650 --> 00:19:09.829
different sensors, different resolutions, et

00:19:09.829 --> 00:19:11.750
cetera, et cetera, but they can see the same

00:19:11.750 --> 00:19:14.430
trends. So always have a look at, hey, can I

00:19:14.430 --> 00:19:18.109
validate this with a different data set? And

00:19:18.109 --> 00:19:20.319
then if you're truly concerned about the validity

00:19:20.319 --> 00:19:23.200
of the data, heading back to the original source.

00:19:24.440 --> 00:19:26.380
So a lot of the data you can find in different

00:19:26.380 --> 00:19:29.740
places has been processed, which is freaking

00:19:29.740 --> 00:19:32.500
amazing because I can tell you atmospheric correction

00:19:32.500 --> 00:19:34.700
is really annoying to do. And usually you don't

00:19:34.700 --> 00:19:37.539
really need to do it yourself. You can quite

00:19:37.539 --> 00:19:42.559
easily get that done automatically. But if you

00:19:42.559 --> 00:19:44.680
have reason of doubt, it's good to check the

00:19:44.680 --> 00:19:49.349
original data source and go back into that. and

00:19:49.349 --> 00:19:51.930
to check the full data source. So we're all used

00:19:51.930 --> 00:19:54.690
to look at true color images, red, green, blue,

00:19:54.869 --> 00:19:57.529
make a very nice picture. People working a lot

00:19:57.529 --> 00:19:59.589
with satellite data tend to work a lot with the

00:19:59.589 --> 00:20:01.430
near infrared band as well, make false color

00:20:01.430 --> 00:20:03.789
composites. Looks really nice. You can see a

00:20:03.789 --> 00:20:07.369
lot more changes. But it's a lot harder to fake

00:20:07.369 --> 00:20:09.930
23 bands of sentinel imagery, including atmospheric

00:20:09.930 --> 00:20:12.029
effects, than it is to fake a single picture.

00:20:12.869 --> 00:20:18.269
You'll look back to that single image. that original

00:20:18.269 --> 00:20:20.329
data set and see, can you validate the whole

00:20:20.329 --> 00:20:25.609
processing chain or not? And with false position,

00:20:25.829 --> 00:20:28.750
I think that's more of a misrepresentation usually

00:20:28.750 --> 00:20:36.450
than a true hacking into the data. If people

00:20:36.450 --> 00:20:39.650
make strong claims about data, then the models,

00:20:40.930 --> 00:20:43.789
then the evidence should back that up. If they

00:20:43.789 --> 00:20:46.400
make a... If they don't share any uncertainty

00:20:46.400 --> 00:20:49.339
estimates, that's not that relevant. I now share

00:20:49.339 --> 00:20:52.059
the accuracy of our model in Eurasia and I can

00:20:52.059 --> 00:20:55.039
tell you that's tested on one side and it's amazing

00:20:55.039 --> 00:20:57.539
there. But I can also tell you that I can make

00:20:57.539 --> 00:21:00.559
a global deforestation detection algorithm that's

00:21:00.559 --> 00:21:05.819
99 % accurate. I would do that. I would say that

00:21:05.819 --> 00:21:08.700
in the sea, there will never be deforestation.

00:21:09.019 --> 00:21:12.890
So that's already 60 % done. I will say that

00:21:12.890 --> 00:21:14.630
outside the forest, there will never be deforestation.

00:21:14.750 --> 00:21:17.490
So then we only have a small area to check. And

00:21:17.490 --> 00:21:19.650
actually saying there's less than 1%, there's

00:21:19.650 --> 00:21:21.890
only a couple of percent of deforestation. That

00:21:21.890 --> 00:21:23.650
means that if I say there's zero deforestation

00:21:23.650 --> 00:21:26.670
globally, I have a global model that's going

00:21:26.670 --> 00:21:30.670
to be 99 % accurate. It's also going to be absolutely

00:21:30.670 --> 00:21:35.250
useless, but it's going to be accurate. So know

00:21:35.250 --> 00:21:38.869
when people stroll around accuracy metrics, what

00:21:38.869 --> 00:21:41.289
to ask for. I can share the accuracy metrics

00:21:41.289 --> 00:21:43.029
about our model as well if you want, by the way.

00:21:43.069 --> 00:21:48.529
Those are reliable. And ask those right questions.

00:21:48.690 --> 00:21:52.130
Or make sure you or someone you can depend on

00:21:52.130 --> 00:21:56.910
can do the actual analysis. And know that the

00:21:56.910 --> 00:22:00.250
data can be hacked. Processing pipelines can

00:22:00.250 --> 00:22:03.109
be tampered with. Cloud platforms can be compromised.

00:22:03.369 --> 00:22:08.950
Scripts can be manipulated. very easily putting

00:22:08.950 --> 00:22:11.529
in an altered timestamp, we've all seen that

00:22:11.529 --> 00:22:14.369
happening, is already giving a completely different

00:22:14.369 --> 00:22:18.250
view of what the data represents. So that's why

00:22:18.250 --> 00:22:21.970
open codes, audit trails, their reviewed methods

00:22:21.970 --> 00:22:26.869
are important. So satellite data is a powerful

00:22:26.869 --> 00:22:29.349
witness, but it does need cross -examination.

00:22:30.670 --> 00:22:33.990
It can be mayplated, it can be wrong, but it

00:22:33.990 --> 00:22:37.200
is objective. And with the right checks, it can

00:22:37.200 --> 00:22:40.839
also be a very strong ally in the truth. So to

00:22:40.839 --> 00:22:44.279
end a bit cheesy, the eyes in the sky are watching,

00:22:44.920 --> 00:22:46.980
but they're on our side if we know where to look.

00:22:47.700 --> 00:22:50.259
Where this forest lost ghost plantation or land

00:22:50.259 --> 00:22:54.200
grabbing satellite data can be an ally. So start

00:22:54.200 --> 00:22:57.920
exploring, ask your questions now or contact

00:22:57.920 --> 00:23:01.180
me later for more information. If you can't find

00:23:01.180 --> 00:23:03.200
me based on what I've just said then you shouldn't

00:23:03.200 --> 00:23:06.950
be in this group. So thank you all for listening.

00:23:08.390 --> 00:23:10.910
Thanks very much, Lisa, for your presentation,

00:23:11.869 --> 00:23:13.569
for sharing your knowledge and your experience

00:23:13.569 --> 00:23:16.710
with us. Folks, if you've got questions for Lisa

00:23:16.710 --> 00:23:19.990
based on what she just said, please type them

00:23:19.990 --> 00:23:22.190
in the chat. I'm watching the chat. I will copy

00:23:22.190 --> 00:23:26.690
your question and ask it to Lisa later on. Lisa,

00:23:26.710 --> 00:23:28.269
I've got a couple of questions here for you just

00:23:28.269 --> 00:23:32.650
right off the bat as people get warmed up here

00:23:32.650 --> 00:23:36.450
with their own questions. Can you tell us a bit

00:23:36.450 --> 00:23:40.329
about what got you personally interested in satellite

00:23:40.329 --> 00:23:43.650
data? What was your journey like into this field

00:23:43.650 --> 00:23:47.309
from maybe a young person in the university or

00:23:47.309 --> 00:23:49.549
high school to where you are today? How did you

00:23:49.549 --> 00:23:51.150
get interested in this and how did you end up

00:23:51.150 --> 00:23:54.809
working at Space for Good? Yeah, thanks. It's

00:23:54.809 --> 00:23:58.420
been a while since I thought about that. In high

00:23:58.420 --> 00:24:01.519
school I wanted to really go into nature conservation,

00:24:01.980 --> 00:24:04.039
going into biology, but then I saw that biology

00:24:04.039 --> 00:24:07.259
was going to be very much looking into cells

00:24:07.259 --> 00:24:09.460
in most universities and looking into the cell

00:24:09.460 --> 00:24:12.000
processes and that was not what drew me. I really

00:24:12.000 --> 00:24:15.259
wanted to look into ecology and the bigger processes

00:24:15.259 --> 00:24:18.420
and see how those things work. So then I started

00:24:18.420 --> 00:24:20.759
to study forest and nature conservation in Wageningen.

00:24:21.299 --> 00:24:23.900
I did my bachelor's there. I started my master

00:24:23.900 --> 00:24:26.940
and then I got a bit into GIS remote sensing

00:24:26.940 --> 00:24:29.859
and spatial modeling. And that was for me really

00:24:29.859 --> 00:24:33.039
what I was looking for. It's working with the

00:24:33.039 --> 00:24:35.660
computer, making some models, figuring out how

00:24:35.660 --> 00:24:37.700
things actually work and can we replicate that.

00:24:39.259 --> 00:24:41.799
Basically making major conservation into a game

00:24:41.799 --> 00:24:44.180
and seeing like, how can I alter that? And that's

00:24:44.180 --> 00:24:46.710
really drew me and then... slowly but surely

00:24:46.710 --> 00:24:49.049
I started to learn more about these satellites

00:24:49.049 --> 00:24:51.190
and everything I could see. And basically with

00:24:51.190 --> 00:24:53.289
everything I did, I was like, okay, but where

00:24:53.289 --> 00:24:56.150
can I see, what can I see that's going on? And

00:24:56.150 --> 00:24:58.730
that really got me excited to every time. But

00:24:58.730 --> 00:25:03.710
the data says, yeah, I'm kind of nerdy. Great.

00:25:03.710 --> 00:25:06.890
Thanks for that answer. And as a kind of a follow

00:25:06.890 --> 00:25:10.549
-up, if you're a person, maybe you're listening

00:25:10.549 --> 00:25:13.410
to this live here in our Discord server, you're

00:25:13.410 --> 00:25:15.660
listening to this later. and you are interested

00:25:15.660 --> 00:25:18.859
in getting into this kind of work or you're hearing

00:25:18.859 --> 00:25:20.640
for the first time, oh, wait a minute, there's

00:25:20.640 --> 00:25:22.859
these satellite imaging platforms and one of

00:25:22.859 --> 00:25:24.640
them is called Landsat and the other one is called

00:25:24.640 --> 00:25:28.480
Sentinel. If you're just learning about this

00:25:28.480 --> 00:25:30.279
now or you're becoming interested in this now,

00:25:31.160 --> 00:25:32.759
what are some recommendations that you have for

00:25:32.759 --> 00:25:35.579
somebody like that to learn more about this field

00:25:35.579 --> 00:25:37.900
and to maybe get their hands on some satellite

00:25:37.900 --> 00:25:41.890
imagery and start looking at them? Yeah, so the

00:25:41.890 --> 00:25:44.410
very, very first step is Google Earth, where

00:25:44.410 --> 00:25:46.329
you have the time view as well. So you can look

00:25:46.329 --> 00:25:48.329
back in the past and you can start playing around

00:25:48.329 --> 00:25:53.349
a bit and get hopefully excited. Then I would

00:25:53.349 --> 00:25:56.009
recommend to work mostly with Sentinel, Sentinel

00:25:56.009 --> 00:25:58.630
-2, which is optical data. It's a bit easy to

00:25:58.630 --> 00:26:01.289
work with and radar data, for example. And it's

00:26:01.289 --> 00:26:03.089
10 meter resolution, so you can see quite a lot

00:26:03.089 --> 00:26:05.849
of different things. You can download it either

00:26:05.849 --> 00:26:09.329
via one of the DS servers or Google Earth engine.

00:26:09.799 --> 00:26:14.380
Google Earth Engine is still freely available

00:26:14.380 --> 00:26:18.980
for certain use cases. So that's a nice win.

00:26:19.859 --> 00:26:21.819
Unfortunately for a lot, not anymore, which is

00:26:21.819 --> 00:26:23.259
too bad. But then Google Earth, you can, there's

00:26:23.259 --> 00:26:28.880
a lot of tutorials and a lot of different learnings

00:26:28.880 --> 00:26:31.660
out there to be looking at things. And yeah,

00:26:31.799 --> 00:26:34.980
start with seeing if you can map your own house

00:26:34.980 --> 00:26:38.700
and different bands in different views. Look

00:26:38.700 --> 00:26:42.079
at any article you're reading like, okay, what

00:26:42.079 --> 00:26:45.519
is the latest image I can get? Get really, really

00:26:45.519 --> 00:26:48.640
frustrated by cloud cover and figure out how

00:26:48.640 --> 00:26:50.140
to deal with it. And then at one point think,

00:26:50.140 --> 00:26:52.460
okay, now I'm going to need radar data to complement

00:26:52.460 --> 00:26:54.240
this or now I'm going to need Landsat data to

00:26:54.240 --> 00:26:57.380
complement this. Have a look and play around

00:26:57.380 --> 00:26:59.920
with it. It is coding based. You can also look

00:26:59.920 --> 00:27:02.539
at QGIS, Quantum GIS, which is a software you

00:27:02.539 --> 00:27:05.279
can install your computer and then just download

00:27:05.279 --> 00:27:07.779
the data and open it in there. But I recommend

00:27:07.779 --> 00:27:10.099
working coding based because you can all the

00:27:10.099 --> 00:27:14.039
things so much more easily. Thanks for all those

00:27:14.039 --> 00:27:16.339
tips there. By the way, I'm dropping the links

00:27:16.339 --> 00:27:19.859
to everything that Lisa's mentioning here in

00:27:19.859 --> 00:27:23.180
our Discord server chat. So if you take a look

00:27:23.180 --> 00:27:25.059
at the chat there, I've dropped a link to Google

00:27:25.059 --> 00:27:28.720
Earth Pro, which, yes, is maybe the most beloved

00:27:28.720 --> 00:27:31.559
and used tool of the open source researcher,

00:27:31.740 --> 00:27:33.240
whether you're working primarily with satellite

00:27:33.240 --> 00:27:37.250
imagery or... You're doing geolocations for human

00:27:37.250 --> 00:27:40.069
rights investigations. The Sentinel Google Earth

00:27:40.069 --> 00:27:42.750
Engine, I've also dropped a link in the chat

00:27:42.750 --> 00:27:45.950
there, and QGIS as well. If you're listening

00:27:45.950 --> 00:27:47.869
to this later and you don't have access to the

00:27:47.869 --> 00:27:50.910
chat, you just Google for those words that I

00:27:50.910 --> 00:27:52.430
just mentioned, and that Lisa just mentioned,

00:27:52.450 --> 00:27:54.730
and then you'll see links to these tools that

00:27:54.730 --> 00:27:57.730
you can download. We have a question from Fraser,

00:27:58.049 --> 00:28:00.309
community member Fraser. Hello Fraser, good to

00:28:00.309 --> 00:28:03.049
see you. Thanks for being here. Fraser has this

00:28:03.049 --> 00:28:06.740
question. Lisa, Fraser asks, have you had a look

00:28:06.740 --> 00:28:10.920
at the Leiden guidelines on digitally derived

00:28:10.920 --> 00:28:16.519
evidence and satellite imagery? Yes, I had a

00:28:16.519 --> 00:28:19.220
look at it, but not recently enough to be answering

00:28:19.220 --> 00:28:22.640
this in this. I do know there's a couple of different

00:28:22.640 --> 00:28:25.519
works out there at the moment, also with CivicSpace

00:28:25.519 --> 00:28:27.880
looking to launch their own satellite constellation

00:28:27.880 --> 00:28:33.640
that is not from any... any government or any

00:28:33.640 --> 00:28:35.640
agency or any commercial entity but it's really

00:28:35.640 --> 00:28:39.059
looking at evidence -based blockchain validated

00:28:39.059 --> 00:28:42.940
data. I've had a look at it and I definitely

00:28:42.940 --> 00:28:44.279
will have a look at it again and I recommend

00:28:44.279 --> 00:28:45.859
everyone to have a look at it and I will not

00:28:45.859 --> 00:28:48.160
go further into that. Yeah, oh great, that's

00:28:48.160 --> 00:28:49.960
an answer. Hey, that's a great answer. Thank

00:28:49.960 --> 00:28:52.180
you for that answer. Thanks for your question,

00:28:52.220 --> 00:28:54.920
Fraser. And by the way, if you have any questions,

00:28:55.019 --> 00:28:57.299
please type them in the chat here. I will ask

00:28:57.299 --> 00:29:00.309
them to Lisa. As we continue, we got about a

00:29:00.309 --> 00:29:03.329
half an hour left, so do not be shy. Lisa's an

00:29:03.329 --> 00:29:05.529
expert in this field. You don't often have a

00:29:05.529 --> 00:29:08.089
chance to talk to somebody like Lisa, so do not

00:29:08.089 --> 00:29:09.589
be shy. Ask your questions in the chat, please.

00:29:10.250 --> 00:29:14.490
I got another question for you here, Lisa. The

00:29:14.490 --> 00:29:19.930
question is this. Towards the end there, you

00:29:19.930 --> 00:29:22.250
talked about deep fakes and whatever we want

00:29:22.250 --> 00:29:25.130
to call AI -generated images and fake data being

00:29:25.130 --> 00:29:28.039
out there. You mentioned... that there were,

00:29:28.039 --> 00:29:30.380
I think you said, very few large -scale issues

00:29:30.380 --> 00:29:34.859
out there with imagery. I know in our own work

00:29:34.859 --> 00:29:37.059
at Bellingcat, we're often asked, can you think

00:29:37.059 --> 00:29:40.819
of examples of AI images in the wild that you've

00:29:40.819 --> 00:29:43.049
detected, that you've worked with? And certainly

00:29:43.049 --> 00:29:45.690
in our field, we've seen quite a few. So my question

00:29:45.690 --> 00:29:49.089
to you is, can you think of examples of AI -generated

00:29:49.089 --> 00:29:51.150
satellite imagery? Are they out there? Have you

00:29:51.150 --> 00:29:53.369
come across them? Are there people out there

00:29:53.369 --> 00:29:56.390
who are trying to trick others into looking at

00:29:56.390 --> 00:29:58.089
a satellite image and saying it shows something

00:29:58.089 --> 00:30:02.210
but really it's generated by AI? Is that something

00:30:02.210 --> 00:30:04.069
that you've come across? And if not, is that

00:30:04.069 --> 00:30:07.599
something that you fear might happen soon? Yeah,

00:30:07.599 --> 00:30:10.500
I have not come across any big ones I come came

00:30:10.500 --> 00:30:12.680
across when doing some research for this to also

00:30:12.680 --> 00:30:16.319
find some an area where someone made a nice fake

00:30:16.319 --> 00:30:24.380
post about a fire in In a big park which was

00:30:24.380 --> 00:30:27.619
like obviously fake as in it looked nice, but

00:30:27.619 --> 00:30:29.559
it was also more made with Photoshop So then

00:30:29.559 --> 00:30:33.200
there's no data behind it. I do think it's likely

00:30:33.200 --> 00:30:36.700
to be happening in the future if not now already,

00:30:36.900 --> 00:30:39.380
especially with high resolution data where there

00:30:39.380 --> 00:30:41.700
is active tasking. So there's often only one

00:30:41.700 --> 00:30:46.819
image or very few images to be altered basically.

00:30:47.380 --> 00:30:50.380
And then if you look at war zones, for example,

00:30:50.400 --> 00:30:52.720
there's very high stakes. So I can imagine it

00:30:52.720 --> 00:30:54.720
would be naive to say that it's never going to

00:30:54.720 --> 00:30:57.579
happen. It's likely to happen. But I think with,

00:30:58.200 --> 00:30:59.880
especially in the case where you have open data,

00:30:59.900 --> 00:31:02.700
we have time series of the same data sets, it's

00:31:02.700 --> 00:31:06.759
easy enough to disprove. oh wait that's not I

00:31:06.759 --> 00:31:08.380
think that are easy to disprove still get sometimes

00:31:08.380 --> 00:31:10.539
picked up by the crowd but it is at least easy

00:31:10.539 --> 00:31:13.039
to disprove so it is something to be conscious

00:31:13.039 --> 00:31:18.079
of but that's not yeah for the deforestation

00:31:18.079 --> 00:31:21.940
I don't see it as the direct biggest risk factor

00:31:21.940 --> 00:31:24.380
yeah thanks for that and you know it's interesting

00:31:24.380 --> 00:31:27.799
when you were going through the workflow or the

00:31:27.799 --> 00:31:31.779
suggestions on how to work with images satellite

00:31:31.779 --> 00:31:35.480
images in this time of fake images, of AI images

00:31:35.480 --> 00:31:37.640
being out there. The steps that you outlined

00:31:37.640 --> 00:31:40.460
are the same, many of them are the same as we

00:31:40.460 --> 00:31:42.839
recommend to people who ask us about, hey, how

00:31:42.839 --> 00:31:45.819
do I know that an image from a protest is really

00:31:45.819 --> 00:31:48.380
a real image and not an image from, or how do

00:31:48.380 --> 00:31:50.799
I know that this picture from a war zone really

00:31:50.799 --> 00:31:53.339
is an actual picture from a war zone and not

00:31:53.339 --> 00:31:55.279
a fake picture? You know, you talked about looking

00:31:55.279 --> 00:31:57.640
for other images, right? So you called it the

00:31:57.640 --> 00:31:59.960
time series, like look at other pictures that

00:31:59.960 --> 00:32:03.079
apparently show the same thing. Because I think

00:32:03.079 --> 00:32:07.779
I suspect that as with pictures from war zones

00:32:07.779 --> 00:32:10.420
or from protests or from anywhere that are generated

00:32:10.420 --> 00:32:13.519
by AI, the platforms can't, at least I'm not

00:32:13.519 --> 00:32:16.059
aware of this, can't replicate the same scene

00:32:16.059 --> 00:32:20.779
from different angles. But as you said, it's

00:32:20.779 --> 00:32:22.359
kind of naive to think it's not going to happen.

00:32:22.819 --> 00:32:25.420
I suppose for satellite imagery, something that'd

00:32:25.420 --> 00:32:30.599
be interesting to think about is satellite images

00:32:30.599 --> 00:32:34.009
are... They show intricate patterns right like

00:32:34.009 --> 00:32:39.309
roads and houses and and and I wonder if the

00:32:39.309 --> 00:32:41.769
AI image generation technology is so good that

00:32:41.769 --> 00:32:44.390
it can actually accurately mimic those and I'm

00:32:44.390 --> 00:32:47.650
thinking specifically about the cover of the

00:32:47.650 --> 00:32:51.700
Berkeley protocol book from the Human Rights

00:32:51.700 --> 00:32:53.539
Center at Berkeley. The cover of that book is

00:32:53.539 --> 00:32:57.420
actually an AI -generated image of a satellite

00:32:57.420 --> 00:32:59.819
view. But if you take a close look at it, and

00:32:59.819 --> 00:33:02.019
an expert eye like yours could definitely tell,

00:33:02.079 --> 00:33:03.940
hey, this is weird. I've looked at a million

00:33:03.940 --> 00:33:05.720
satellite images. None of them look like this.

00:33:06.819 --> 00:33:08.299
But as you say, it's one of those things you

00:33:08.299 --> 00:33:10.940
have to think about as being potentially possible

00:33:10.940 --> 00:33:14.200
in the next little while. There, indeed, my risk

00:33:14.200 --> 00:33:18.109
is there is especially with open satellite data,

00:33:18.170 --> 00:33:19.869
there is a lot of data available to train on.

00:33:20.869 --> 00:33:25.730
And a couple of years ago, the generation of

00:33:25.730 --> 00:33:28.730
deepfakes was very, very early on. And if you

00:33:28.730 --> 00:33:31.589
see how fast that goes, how good video material

00:33:31.589 --> 00:33:33.210
we can get. I'm not sure why I'm here. I could

00:33:33.210 --> 00:33:37.630
have just sent an AI. How good that all gets.

00:33:38.509 --> 00:33:40.529
Then I think, yeah, the satellite data, there

00:33:40.529 --> 00:33:42.619
is a lot of data out there. is going to be feasible

00:33:42.619 --> 00:33:44.680
as well. The patterns at the moment, I don't

00:33:44.680 --> 00:33:46.420
think yet, but I'm talking to some people who

00:33:46.420 --> 00:33:49.099
are working on how to connect the roads, which

00:33:49.099 --> 00:33:52.059
is also very useful if you want to map a road

00:33:52.059 --> 00:33:54.519
network in an area. It's nice to be able to map

00:33:54.519 --> 00:33:57.299
those roads. But yeah, it can be used to generate

00:33:57.299 --> 00:33:59.460
fakes as well. And if we talk about the wrong

00:33:59.460 --> 00:34:05.920
data, I see at the moment a bigger issue in misrepresented

00:34:05.920 --> 00:34:09.260
data. having a data set and saying it's and that's

00:34:09.260 --> 00:34:11.159
something that we do see what people say claim

00:34:11.159 --> 00:34:14.360
it's in a different area and again you can say

00:34:14.360 --> 00:34:16.619
or a different time and you can say no wait i've

00:34:16.619 --> 00:34:19.179
got the evidence that it's not but if the information

00:34:19.179 --> 00:34:21.619
is out there coming with the evidence isn't always

00:34:21.619 --> 00:34:25.320
enough yeah thanks for that lisa i have another

00:34:25.320 --> 00:34:27.019
question here since we're talking about you know

00:34:27.019 --> 00:34:29.099
we're talking about what may be coming in the

00:34:29.099 --> 00:34:32.639
future in terms of ai image generation you've

00:34:32.639 --> 00:34:35.420
just mentioned this ability to make realistic

00:34:35.420 --> 00:34:39.739
roads, for example. Are there any advances in

00:34:39.739 --> 00:34:42.179
remote sensing technology that you think are

00:34:42.179 --> 00:34:44.039
coming soon or in the next couple of years that

00:34:44.039 --> 00:34:49.159
you're really excited about? A lot, a lot. So

00:34:49.159 --> 00:34:52.719
what's happening right now is Google has just

00:34:52.719 --> 00:34:56.019
announced a better version of a system to be

00:34:56.019 --> 00:35:00.510
talking to maps, basically. So rather than doing

00:35:00.510 --> 00:35:02.389
all the investigation yourself, being able to

00:35:02.389 --> 00:35:05.030
just ask, hey, for this area of interest, how

00:35:05.030 --> 00:35:07.510
much deforestation has there been? I think there's

00:35:07.510 --> 00:35:08.969
a big risk there, but I also think there's a

00:35:08.969 --> 00:35:11.110
lot of opportunities there to take that first

00:35:11.110 --> 00:35:14.230
step into how can we actually see what's going

00:35:14.230 --> 00:35:17.969
on on our planet? I think the roads, that's for

00:35:17.969 --> 00:35:22.750
me to make the system of automatically connecting

00:35:22.750 --> 00:35:26.530
different features. based on a lot of data, but

00:35:26.530 --> 00:35:29.809
also based on quite complex models. Having a

00:35:29.809 --> 00:35:33.369
detailed road network can mean so, so much for,

00:35:33.369 --> 00:35:36.090
for example, detecting illegal logging, but also

00:35:36.090 --> 00:35:38.309
predicting it. We see that illegal logging almost

00:35:38.309 --> 00:35:41.250
always happens near roads and almost always first

00:35:41.250 --> 00:35:44.630
a new road is made and then logging happens and

00:35:44.630 --> 00:35:46.829
it expands. If you can see that earlier by having

00:35:46.829 --> 00:35:49.789
just a few points. then you can really map out

00:35:49.789 --> 00:35:52.690
a lot so that's really interesting to me and

00:35:52.690 --> 00:35:56.110
yeah biodiversity making some sort of integrated

00:35:56.110 --> 00:36:00.710
solution how can we map biodiversity to well

00:36:00.710 --> 00:36:03.050
it's not really clear what biodiversity there's

00:36:03.050 --> 00:36:05.690
not one definition of biodiversity but to be

00:36:05.690 --> 00:36:09.050
able to say hey this is going well and this is

00:36:09.050 --> 00:36:13.429
not going well Thanks, Lisa. We have a question

00:36:13.429 --> 00:36:15.269
from Chris. And if you have a question, folks,

00:36:15.429 --> 00:36:17.010
please type it in the chat. We've got about 20

00:36:17.010 --> 00:36:19.610
minutes left here with Lisa from Space for Good.

00:36:19.929 --> 00:36:22.989
Chris is asking this question here, Lisa. Now,

00:36:23.289 --> 00:36:25.909
there's some jargon in here that I don't know.

00:36:25.949 --> 00:36:27.670
So I'm going to read it out as it is written.

00:36:28.210 --> 00:36:31.610
And maybe this is the jargon that you know. And

00:36:31.610 --> 00:36:33.969
the question is this. I'm curious to hear more

00:36:33.969 --> 00:36:36.989
about how you are ground -truthing satellite

00:36:36.989 --> 00:36:42.739
data to help detect distortions. So we ourselves

00:36:42.739 --> 00:36:45.000
are not earlier, but let me first like phrases

00:36:45.000 --> 00:36:47.179
a bit for the rest. So ground rooting that's

00:36:47.179 --> 00:36:49.420
looking at what's on the ground and perceiving

00:36:49.420 --> 00:36:52.380
that as the truth and you can use that to retrain

00:36:52.380 --> 00:36:56.139
models. I think here the distortion, the distortions,

00:36:56.340 --> 00:37:00.760
but Chris, chat if it's wrong, is really looking

00:37:00.760 --> 00:37:04.559
at the distortions of the images, which is why

00:37:04.559 --> 00:37:07.300
you're looking at, for example, something that

00:37:07.300 --> 00:37:10.530
we've seen in the past quite a lot, the earlier

00:37:10.530 --> 00:37:14.809
generations of planet data had a lot of misalignment

00:37:14.809 --> 00:37:17.050
of different bands now i'm getting a bit technical

00:37:17.050 --> 00:37:20.369
here so that's when you have a picture of the

00:37:20.369 --> 00:37:23.690
red green and blue and they're all not exactly

00:37:23.690 --> 00:37:27.230
aligned so you could have a situation where the

00:37:27.230 --> 00:37:30.570
red value of a certain pixel was 10 meters below

00:37:30.570 --> 00:37:34.690
blue value so you would have a shift there with

00:37:34.690 --> 00:37:37.570
ground rooting you can basically align pictures

00:37:37.570 --> 00:37:40.570
so they're all exactly at the same spot. And

00:37:40.570 --> 00:37:42.170
then you can look for example, changes and then

00:37:42.170 --> 00:37:45.090
you know where something is exactly. Usually

00:37:45.090 --> 00:37:47.530
that is done by the satellite data providers.

00:37:47.590 --> 00:37:49.650
And I think right now, most of those have good

00:37:49.650 --> 00:37:52.829
enough on -train models that we can focus on

00:37:52.829 --> 00:37:57.389
our own strengths, which is mostly the data analytics

00:37:57.389 --> 00:38:03.369
and going into depth on the AI models. Thank

00:38:03.369 --> 00:38:05.190
you for that question. And thanks for that answer,

00:38:05.809 --> 00:38:11.150
Lisa. I have another question. What is your kind

00:38:11.150 --> 00:38:13.230
of biggest frustration about the limitations

00:38:13.230 --> 00:38:15.489
of the current technology? What's the thing that

00:38:15.489 --> 00:38:17.369
you run across the most that makes you go, oh

00:38:17.369 --> 00:38:20.789
my gosh, I wish it wasn't like this. I wish we

00:38:20.789 --> 00:38:23.130
could fix this issue with the technology. What's

00:38:23.130 --> 00:38:25.570
something that's missing in the technology or

00:38:25.570 --> 00:38:29.610
a capability that's missing at the moment? Yeah,

00:38:29.670 --> 00:38:32.590
it really depends on use case to use case. What

00:38:32.590 --> 00:38:36.699
is, for me, I think my biggest frustration is

00:38:36.699 --> 00:38:38.860
not as much in the technology, but in the technology

00:38:38.860 --> 00:38:42.019
communication. So I'm spending a lot of time

00:38:42.019 --> 00:38:43.719
with different users and different potential

00:38:43.719 --> 00:38:46.320
users talking about, hey, what can be done and

00:38:46.320 --> 00:38:48.599
what cannot be done. And then sometimes you have

00:38:48.599 --> 00:38:51.880
people who say, who think we're working with

00:38:51.880 --> 00:38:55.840
satellites and AI. So I want to see this individual

00:38:55.840 --> 00:38:58.260
tree and how well it's doing. And sometimes you

00:38:58.260 --> 00:39:00.360
have people who still think like satellites and

00:39:00.360 --> 00:39:02.159
AI, no, that's not working in forest, forest

00:39:02.159 --> 00:39:05.280
is special. It's somewhere in the middle and

00:39:05.280 --> 00:39:07.860
that's always really annoying. If we go back

00:39:07.860 --> 00:39:11.860
to really technical, I think a lot is possible.

00:39:12.480 --> 00:39:17.440
For me, the challenges with working on a large

00:39:17.440 --> 00:39:20.000
scale with high resolution data, especially with

00:39:20.000 --> 00:39:23.280
time series, are still really annoying because

00:39:23.280 --> 00:39:25.440
I know that there's a lot of data out there,

00:39:25.739 --> 00:39:28.019
but most of it is commercial and then it tends

00:39:28.019 --> 00:39:30.960
to be nuts. available for a lot of the applications

00:39:30.960 --> 00:39:33.659
that I feel need it most. You can do a lot if

00:39:33.659 --> 00:39:36.179
you want to go into oil and gas, but if you want

00:39:36.179 --> 00:39:39.980
to make sure there's a world left, then it's

00:39:39.980 --> 00:39:43.219
a constant uphill battle that way. Again, maybe

00:39:43.219 --> 00:39:46.639
not the most technical issue, so I think, yeah.

00:39:47.519 --> 00:39:49.360
I kind of like the technical challenges. Yeah,

00:39:49.559 --> 00:39:52.340
clouds are annoying, but it's part of the fun,

00:39:52.559 --> 00:39:56.110
right? Gives us a puzzle to solve. Yeah, whenever

00:39:56.110 --> 00:39:59.489
we work with, we have a really wonderful network

00:39:59.489 --> 00:40:04.150
of volunteers and sometimes we get satellite

00:40:04.150 --> 00:40:07.170
imagery from a satellite image provider that

00:40:07.170 --> 00:40:08.929
they request. They'll be working on a case and

00:40:08.929 --> 00:40:10.329
they'll go, hey, I need a picture from here.

00:40:10.769 --> 00:40:13.670
And if the volunteer, if the individual isn't

00:40:13.670 --> 00:40:16.449
familiar with satellite imagery, we have lots

00:40:16.449 --> 00:40:18.829
of folks who've never worked with it in the past

00:40:18.829 --> 00:40:21.090
and are now working with it for the first time

00:40:21.090 --> 00:40:23.909
at BellyCat. you know, 95 % of the time we get

00:40:23.909 --> 00:40:25.429
the image, we send it to them and we go, it's

00:40:25.429 --> 00:40:27.110
cloudy. Like we could, you know, here's the result,

00:40:27.170 --> 00:40:28.690
or you can't see anything. And they go, oh, of

00:40:28.690 --> 00:40:30.710
course, like there's clouds. Yeah, there's lots

00:40:30.710 --> 00:40:32.550
of clouds. And depending on the place, there's

00:40:32.550 --> 00:40:36.710
clouds like every day. So, yeah, definitely sympathize

00:40:36.710 --> 00:40:40.309
with that. We did a project in Ivory Coast and

00:40:40.309 --> 00:40:42.750
I think in a year's time we could get one image.

00:40:43.469 --> 00:40:46.449
Yeah, that sounds about right. Yeah. We have

00:40:46.449 --> 00:40:49.889
another question here from another community

00:40:49.889 --> 00:40:54.260
member named BQN. And BQN asks, Lisa, what is

00:40:54.260 --> 00:40:57.360
the most interesting or innovative or unusual

00:40:57.360 --> 00:41:01.079
or creative application of satellite image data

00:41:01.079 --> 00:41:09.460
that you have come across? So I kind of want

00:41:09.460 --> 00:41:11.880
to talk about this project we've done. It wasn't

00:41:11.880 --> 00:41:13.480
technically with satellite image because here

00:41:13.480 --> 00:41:16.780
we could get through a partner, really like the

00:41:16.780 --> 00:41:20.219
project as well, some aerial data. But basically

00:41:20.219 --> 00:41:22.280
for us, the processing is pretty much the same.

00:41:22.340 --> 00:41:23.820
It's a bit less atmospheric correction needed,

00:41:24.000 --> 00:41:28.199
but data is data, right? So I was working with

00:41:28.199 --> 00:41:31.820
aerial data and that was to map out latrines.

00:41:32.500 --> 00:41:34.900
Where MREF held Africa, this project, this wash

00:41:34.900 --> 00:41:39.260
intervention to support, to give out micro credits

00:41:39.260 --> 00:41:42.900
for people to build latrines. And they wanted

00:41:42.900 --> 00:41:46.659
to know how effective the project was. Now they

00:41:46.659 --> 00:41:48.739
needed to do a comparison to a different site.

00:41:49.150 --> 00:41:51.269
to see how many latrines people would normally

00:41:51.269 --> 00:41:55.309
build, at least would build us outhouses. And

00:41:55.309 --> 00:41:57.489
it's kind of invasive to be knocking on people's

00:41:57.489 --> 00:42:00.670
door and ask, hey, can I see your toilets? So

00:42:00.670 --> 00:42:02.750
they were looking for a different solution and

00:42:02.750 --> 00:42:05.250
then we developed a model to see, hey, where

00:42:05.250 --> 00:42:08.250
can we see outhouses and how can we distinguish

00:42:08.250 --> 00:42:10.869
latrines from chicken coops, which is very challenging.

00:42:12.349 --> 00:42:14.349
And I really like talking about that, like looking

00:42:14.349 --> 00:42:16.889
at the different angle, like, yeah, sure, sure,

00:42:16.949 --> 00:42:20.800
we can map latrines, why not? Yeah, I don't think

00:42:20.800 --> 00:42:22.099
I've ever heard of anything like that. That's

00:42:22.099 --> 00:42:25.440
fascinating. Thanks for sharing that. We have

00:42:25.440 --> 00:42:31.960
a question here from Aikan. Hello, Aikan. Thanks

00:42:31.960 --> 00:42:34.260
for your question. And the question is, do you

00:42:34.260 --> 00:42:36.880
have any tips for using platforms like Google

00:42:36.880 --> 00:42:41.500
Earth or Sentinel for identifying and confirming

00:42:41.500 --> 00:42:46.159
smaller scale environmental sites like artisanal

00:42:46.159 --> 00:42:51.150
mines, for example? So artisanal minds, we've

00:42:51.150 --> 00:42:54.489
also done some work in. I believe there might

00:42:54.489 --> 00:42:57.510
even be some tutorials using it in Google Earth

00:42:57.510 --> 00:43:01.190
Engine. Otherwise, what I would really look at

00:43:01.190 --> 00:43:05.429
is look for bare soil index. So really look at

00:43:05.429 --> 00:43:09.050
bare soil and mapping changes into that. So looking

00:43:09.050 --> 00:43:11.369
at the time series analysis, you can look into,

00:43:11.510 --> 00:43:18.500
for example, BFAST, B -F -A -S -T. that's normally

00:43:18.500 --> 00:43:21.179
done on the NDVI but you can also do it on for

00:43:21.179 --> 00:43:25.119
example bare soil index and using that to map

00:43:25.119 --> 00:43:27.659
where you see for example bare soils popping

00:43:27.659 --> 00:43:31.500
up in certain area sizes so you want to look

00:43:31.500 --> 00:43:33.820
at then quite small area sizes where there's

00:43:33.820 --> 00:43:38.500
quite a rapid change ideally you make some some

00:43:38.500 --> 00:43:40.119
smart selections about your area of interest

00:43:40.119 --> 00:43:42.500
where you expect it to happen so for example

00:43:42.500 --> 00:43:46.420
close to rivers and then Second point of advice

00:43:46.420 --> 00:43:50.079
is don't be afraid to get dirty and just click

00:43:50.079 --> 00:43:52.880
through images and look at things. So use these

00:43:52.880 --> 00:43:54.460
algorithms. If you don't have a lot of training

00:43:54.460 --> 00:43:57.079
data, don't spend too much time on building complex

00:43:57.079 --> 00:43:59.380
models. If you don't have the data to put in

00:43:59.380 --> 00:44:01.440
there and the model is not going to be great

00:44:01.440 --> 00:44:05.659
anyway and click through things, look at the

00:44:05.659 --> 00:44:08.420
different images and use your own eyes as well

00:44:08.420 --> 00:44:10.400
because our own eyes are very good at change

00:44:10.400 --> 00:44:15.179
detection and pattern recognition. Use the computer

00:44:15.179 --> 00:44:17.760
to take the first step, but don't try to get

00:44:17.760 --> 00:44:20.920
everything done perfectly Rather just look and

00:44:20.920 --> 00:44:23.480
click and do the dirty work yourself as well

00:44:23.480 --> 00:44:29.380
We have a question now from wit Fox and you've

00:44:29.380 --> 00:44:32.219
talked You know, we just talked a little bit

00:44:32.219 --> 00:44:35.360
about this. Let's let's see if we can get more

00:44:35.360 --> 00:44:39.320
On this Lisa. You've talked a bit about deforestation

00:44:39.320 --> 00:44:42.320
biodiversity fires mines. We talked about latrines

00:44:42.320 --> 00:44:45.739
a moment ago What are some things that you think

00:44:45.739 --> 00:44:49.400
satellites are being underutilized for? Or what

00:44:49.400 --> 00:44:53.039
are some other perhaps non -obvious use cases

00:44:53.039 --> 00:44:58.059
for satellite imagery data, either optical or

00:44:58.059 --> 00:45:06.960
multispectral? Thanks. Take your moment. Because

00:45:06.960 --> 00:45:10.119
I know satellite data is being used for loads

00:45:10.119 --> 00:45:13.420
of different things. even for mapping penguin

00:45:13.420 --> 00:45:15.480
colonies by looking at their shit you can do

00:45:15.480 --> 00:45:18.420
with satellite so what they're not being used

00:45:18.420 --> 00:45:26.920
for is kind of difficult to look at yeah I think

00:45:26.920 --> 00:45:30.960
a lot of places a lot more can be done I think

00:45:30.960 --> 00:45:35.440
for mapping these environmental claims for big

00:45:35.440 --> 00:45:38.340
organizations I think they can be used a lot

00:45:38.340 --> 00:45:41.139
more because I feel like for a lot of these cases

00:45:42.579 --> 00:45:46.559
companies will make a claim, for example, in

00:45:46.559 --> 00:45:49.320
the offsetting. They will share some sort of

00:45:49.320 --> 00:45:50.900
location with it or they will share some sort

00:45:50.900 --> 00:45:53.760
of report with it. But the data tends to be based

00:45:53.760 --> 00:45:56.739
on field work, which is nice, but which must

00:45:56.739 --> 00:45:58.920
be validated. We've seen it a lot where even

00:45:58.920 --> 00:46:01.760
companies we work with who do field work professionally

00:46:01.760 --> 00:46:06.099
and who do it for the project we asked them,

00:46:06.480 --> 00:46:08.619
give us data where there's just errors in there.

00:46:10.039 --> 00:46:14.039
That makes me wonder how much validation is being

00:46:14.039 --> 00:46:18.099
done to support these claims for, for example,

00:46:18.280 --> 00:46:21.039
the regulated carbon market. I know it's being

00:46:21.039 --> 00:46:23.699
done there, and I know it's kind of an open and

00:46:23.699 --> 00:46:26.599
short case, but I think more can be done there.

00:46:28.139 --> 00:46:30.519
Thanks, Lisa. We have about 10 minutes here left

00:46:30.519 --> 00:46:33.500
with Lisa Brughausen from Space for Good. If

00:46:33.500 --> 00:46:35.579
you have any questions, please type them in the

00:46:35.579 --> 00:46:39.190
chat. You've got 10 minutes to ask her. A question,

00:46:39.269 --> 00:46:42.489
we've got one here from SirSkippy. And SirSkippy

00:46:42.489 --> 00:46:46.909
asks, do you make the data that you collect available

00:46:46.909 --> 00:46:53.570
on OpenStreetMap for ECUs by others? No, we do

00:46:53.570 --> 00:46:56.289
not. And the data we collect, we don't have our

00:46:56.289 --> 00:46:58.650
own satellites. So the data we collect is the

00:46:58.650 --> 00:47:00.489
satellite data itself, the raw satellite data.

00:47:01.289 --> 00:47:04.070
And the data, the results, the information we

00:47:04.070 --> 00:47:08.269
generate We don't make available and I think

00:47:08.269 --> 00:47:10.329
so we also work for, for example, commercial

00:47:10.329 --> 00:47:14.409
entities to take their direct action. I think

00:47:14.409 --> 00:47:17.769
in most of those cases, it would not be beneficial

00:47:17.769 --> 00:47:19.829
to them to publish it. And then we also need

00:47:19.829 --> 00:47:21.949
to be cautious with that and rather focus on

00:47:21.949 --> 00:47:25.210
the direct action and on the mapping. Plus in

00:47:25.210 --> 00:47:27.269
OpenStreetMap, if we do, for example, deforestation

00:47:27.269 --> 00:47:30.329
detection. So like I said, what we do is we look

00:47:30.329 --> 00:47:33.900
at deforestation as there was a forest it's gone

00:47:33.900 --> 00:47:37.840
now there's no more forest if you look at most

00:47:37.840 --> 00:47:41.039
land cover maps they look at what is the land

00:47:41.039 --> 00:47:45.300
cover we the official land cover that's here

00:47:45.300 --> 00:47:48.119
the land use that's here so if you cut a forest

00:47:48.119 --> 00:47:51.480
and a new forest grows it is still the land cover

00:47:51.480 --> 00:47:55.619
class of forest and then there's no rapid change

00:47:55.619 --> 00:47:58.639
for change that we detect and then in the other

00:47:58.639 --> 00:48:00.360
land cover mapping we tend to have a bit more

00:48:00.360 --> 00:48:03.980
classes than are relevant for This road networks

00:48:03.980 --> 00:48:08.239
could make sense. But even then I think that

00:48:08.239 --> 00:48:10.440
working with the GPS tracker so people have locally

00:48:10.440 --> 00:48:14.880
are probably going to be more, uh, more directly

00:48:14.880 --> 00:48:17.099
applicable also because it's in private areas.

00:48:17.119 --> 00:48:18.739
So they don't want the date. They don't want

00:48:18.739 --> 00:48:22.199
people on the roads. So no, we do not. The short

00:48:22.199 --> 00:48:24.960
answer. Thanks, Lisa. We got another one here

00:48:24.960 --> 00:48:30.340
from, um, uh, this one's from Charlie. Um, are

00:48:30.340 --> 00:48:32.599
you Charlie from, from Bellingham? And Charlie

00:48:32.599 --> 00:48:36.440
asks, I'm going to paraphrase here. Imagine you're

00:48:36.440 --> 00:48:38.079
listening to this and you go, wow, Space for

00:48:38.079 --> 00:48:40.980
Good sounds incredible. I think I have some skills

00:48:40.980 --> 00:48:43.099
that might make me a candidate. I'm going to

00:48:43.099 --> 00:48:45.639
look for postings on the Space for Good website.

00:48:45.739 --> 00:48:47.179
Maybe if they're hiring somebody, I'm going to

00:48:47.179 --> 00:48:49.739
apply. And the question to you, Lisa, is what

00:48:49.739 --> 00:48:52.400
kinds of skill sets do you look for in team members?

00:48:52.739 --> 00:48:55.639
Just in case somebody in the audience here wants

00:48:55.639 --> 00:48:59.079
to maybe give a shot at working with Space for

00:48:59.079 --> 00:49:03.599
Good. Yeah, thanks. So what we're looking for

00:49:03.599 --> 00:49:08.360
is really in -depth remote sensing and modeling

00:49:08.360 --> 00:49:10.559
skills. So if we look for a data analyst or data

00:49:10.559 --> 00:49:12.360
scientist and we look for people who really have

00:49:12.360 --> 00:49:14.900
experience in the data, but also have experience

00:49:14.900 --> 00:49:19.119
in one or two fields of interest. So we have,

00:49:19.199 --> 00:49:21.619
I myself have a mixed background with forestry.

00:49:22.000 --> 00:49:23.860
We have someone who has a background in doing

00:49:24.639 --> 00:49:27.159
carbon projects in the fields, getting that access

00:49:27.159 --> 00:49:29.320
with someone who's done a lot of work around

00:49:29.320 --> 00:49:32.599
fires in the past, agriculture. So knowing, and

00:49:32.599 --> 00:49:35.719
that's where I think most value lays in, combining

00:49:35.719 --> 00:49:39.099
the data sites with direct action in the field

00:49:39.099 --> 00:49:41.019
with something, someone who knows the background.

00:49:41.980 --> 00:49:44.639
If you don't know how a tree grows, then monitoring

00:49:44.639 --> 00:49:47.179
from above is going to be a lot harder and monitoring

00:49:47.179 --> 00:49:50.099
it when it's gone is going to be very difficult

00:49:50.099 --> 00:49:54.440
to assess. So that's ready for the data. They're

00:49:54.440 --> 00:49:56.099
the analytics, they're the scientist position.

00:49:57.599 --> 00:50:00.559
Then we have, if we work with, we have, for example,

00:50:00.579 --> 00:50:03.539
at the moment, one full stack developer that

00:50:03.539 --> 00:50:06.579
was looking for someone with cloud experience,

00:50:06.760 --> 00:50:09.420
scalability, et cetera, et cetera. But for us,

00:50:09.559 --> 00:50:11.780
the soft side is also very important where you've

00:50:11.780 --> 00:50:15.719
got a very cool team, if I may say so, and really

00:50:15.719 --> 00:50:17.599
working together as a team to build something

00:50:17.599 --> 00:50:20.820
that's better. And then, of course, around commercial,

00:50:20.940 --> 00:50:22.440
well, we've got a very small team around that,

00:50:22.500 --> 00:50:24.719
but that's also always good to have people who

00:50:24.719 --> 00:50:29.280
can try to get it to the final users and clients.

00:50:31.360 --> 00:50:32.820
Thanks very much. We have about eight minutes

00:50:32.820 --> 00:50:35.380
left here with Lisa. Get your questions in, folks.

00:50:35.940 --> 00:50:38.599
We have a question from Dusty Wieners. By the

00:50:38.599 --> 00:50:42.119
way, Wieners, if you folks don't know. is the

00:50:42.119 --> 00:50:45.440
skin on your elbow is the weenus. I'm not sure

00:50:45.440 --> 00:50:48.059
if you are familiar with that term, but Dusty

00:50:48.059 --> 00:50:54.019
Weenus is asking the following question. They

00:50:54.019 --> 00:50:57.679
say, Dusty Weenus says, is there any way to verify

00:50:57.679 --> 00:51:00.159
direct carbon emissions from industrial sites

00:51:00.159 --> 00:51:06.340
from space? For example, A company claims a certain

00:51:06.340 --> 00:51:08.519
amount of scope one emissions, but the satellite

00:51:08.519 --> 00:51:11.539
data actually indicates a larger amount. Is that

00:51:11.539 --> 00:51:16.530
possible? For example, methane mapping. Thanks,

00:51:16.670 --> 00:51:19.329
Dusty or Venus, I'm not sure how to refer to

00:51:19.329 --> 00:51:22.090
you. For example, for methane, there's some satellites

00:51:22.090 --> 00:51:24.469
out there that can really map at different resolutions

00:51:24.469 --> 00:51:27.650
the direct methane emissions. It's always important

00:51:27.650 --> 00:51:30.429
to look at then the full scale of events. If

00:51:30.429 --> 00:51:32.630
they report CIRTOSCOPE -1 emissions, you need

00:51:32.630 --> 00:51:34.949
to have the correct overpass times, the correct

00:51:34.949 --> 00:51:36.829
models behind it. And there's always the issue

00:51:36.829 --> 00:51:38.909
that you look with the satellite at the full

00:51:38.909 --> 00:51:42.570
column. So at the entire atmosphere, basically.

00:51:42.880 --> 00:51:47.039
So there is a potential for a mix -up. However,

00:51:47.340 --> 00:51:49.039
these satellites have been used, for example,

00:51:49.159 --> 00:51:51.860
to identify when there have been methane leaks

00:51:51.860 --> 00:51:54.539
or large -scale methane emissions where they

00:51:54.539 --> 00:51:57.440
shouldn't have been due to any technical issues.

00:51:58.139 --> 00:52:01.559
So yes, it can be done for larger scale operations.

00:52:02.679 --> 00:52:06.480
The farmer next door with 20 cows doesn't exist

00:52:06.480 --> 00:52:08.320
anymore. But anyway, you're not going to be able

00:52:08.320 --> 00:52:12.000
to find that. But for the large factories, yes.

00:52:12.179 --> 00:52:17.300
And for the pipelines where there might be maybe

00:52:17.300 --> 00:52:21.500
slight issues with the maintenance as well. I'm

00:52:21.500 --> 00:52:24.719
being positive here. Thanks. Thanks Lisa. I think

00:52:24.719 --> 00:52:26.320
this is going to be the last question here. Somebody

00:52:26.320 --> 00:52:28.400
notices we're talking about, you know, work in

00:52:28.400 --> 00:52:31.400
the field and maybe working space for good. Somebody

00:52:31.400 --> 00:52:34.659
noticed that there's an astropreneur position

00:52:34.659 --> 00:52:36.320
on the website. Are you familiar with that one?

00:52:36.440 --> 00:52:38.599
I'm asking it because Chris is asking about this,

00:52:38.619 --> 00:52:40.679
but also I've never heard of that term. Do you

00:52:40.679 --> 00:52:42.619
know about the position, the vacancy? Can you

00:52:42.619 --> 00:52:47.099
talk about it? It might be a word we made up.

00:52:50.000 --> 00:52:55.059
More on the data side than that side. So let

00:52:55.059 --> 00:53:01.920
me quickly, where is that? It's in the, yeah,

00:53:02.000 --> 00:53:06.500
spaceforgo .com forward slash vacancies. Marketing

00:53:06.500 --> 00:53:10.179
and sales, market research and analysis, finance

00:53:10.179 --> 00:53:12.639
and investment. Oh yeah, talented and engaged

00:53:12.639 --> 00:53:16.500
entrepreneurs. So that's basically an open, always

00:53:16.500 --> 00:53:18.579
open vacancy where people who are interested

00:53:18.579 --> 00:53:21.380
can. let us know and we can see whether there

00:53:21.380 --> 00:53:23.900
is there is anything out there uh that always

00:53:23.900 --> 00:53:27.059
depends a bit on projects on current needs on

00:53:27.059 --> 00:53:29.840
skills whether we can fit something in or not

00:53:29.840 --> 00:53:33.820
um lately usually not i have to admit because

00:53:33.820 --> 00:53:36.360
we're with quite quite a strong team at the moment

00:53:36.360 --> 00:53:39.460
uh but quite frequently we can find figure out

00:53:39.460 --> 00:53:44.139
something so um yeah entrepreneur combination

00:53:44.139 --> 00:53:47.739
of uh astro and entrepreneur so also looking

00:53:47.739 --> 00:53:49.900
at people who want to We do work as well with

00:53:49.900 --> 00:53:52.860
a shell of freelancers who take specific projects

00:53:52.860 --> 00:53:56.500
or who we support in giving specific projects

00:53:56.500 --> 00:53:59.320
when there are specific skill sets we don't have

00:53:59.320 --> 00:54:01.539
in the team, but we need in certain projects

00:54:01.539 --> 00:54:05.059
or that just want to be somehow connected because

00:54:05.059 --> 00:54:08.860
we are a lot of fun. Great. Thank you so much

00:54:08.860 --> 00:54:10.579
for that. And we've got this last question here,

00:54:10.699 --> 00:54:12.900
folks, again, from SIRS -KP, has the change in

00:54:12.900 --> 00:54:16.219
US government funding priorities affected Space

00:54:16.219 --> 00:54:17.739
for good at all. We get that question about again

00:54:17.739 --> 00:54:21.159
all the time. We're passing it on to you Lisa

00:54:21.159 --> 00:54:23.780
space for good. Yeah, you don't have to ask the

00:54:23.780 --> 00:54:30.079
book Affected us. I mean emotionally financially

00:54:30.079 --> 00:54:32.780
directly or indirectly. I think it's affecting

00:54:32.780 --> 00:54:36.860
affecting the entire world At the moment, it

00:54:36.860 --> 00:54:39.579
has not affected any of the current of the projects

00:54:39.579 --> 00:54:41.519
that we do. And that's also where we try to have

00:54:41.519 --> 00:54:44.320
a mix between commercial projects, projects with

00:54:44.320 --> 00:54:47.280
NGOs and governmental projects. We do know that

00:54:47.280 --> 00:54:49.099
a lot of our partners have been affected quite

00:54:49.099 --> 00:54:52.619
strongly and we do see quite some risk here because

00:54:52.619 --> 00:54:56.199
the budgets are also affecting the data sets.

00:54:56.360 --> 00:54:58.159
And then we're looking at the climatological

00:54:58.159 --> 00:55:00.219
data sets, which we use if we make predictive

00:55:00.219 --> 00:55:03.260
models. It's important to have those available

00:55:03.260 --> 00:55:06.039
globally rather than only in certain regions

00:55:06.039 --> 00:55:09.719
because the climate is kind of a global thingy.

00:55:11.199 --> 00:55:15.219
So there we do expect it to affect us on the

00:55:15.219 --> 00:55:18.199
data set quite a bit and on the projects not

00:55:18.199 --> 00:55:22.000
on the active projects we have but on the yeah

00:55:22.000 --> 00:55:26.159
future ones unfortunately I think that's yeah

00:55:26.159 --> 00:55:31.650
that's great well On that depressing note, we're

00:55:31.650 --> 00:55:34.030
going to call it. Thank you so much, Lisa. Brooke

00:55:34.030 --> 00:55:37.429
Hellsend from Space for Good. Thanks for your

00:55:37.429 --> 00:55:39.369
wonderful presentation. I learned a lot. I know

00:55:39.369 --> 00:55:40.949
folks here learned a lot as well. Thank you very

00:55:40.949 --> 00:55:43.269
much, Lisa, for spending this hour with us. Thank

00:55:43.269 --> 00:55:45.289
you. And have a good evening and day, everyone.

00:55:45.829 --> 00:55:48.670
Thank you for listening to the Stage Talk. If

00:55:48.670 --> 00:55:51.670
you'd like to catch a Stage Talk live where you

00:55:51.670 --> 00:55:54.349
can ask the guest questions, join the Bell and

00:55:54.349 --> 00:56:02.639
Cat Discord server by visiting www. The music

00:56:02.639 --> 00:56:06.119
you've heard is titled Dawn by Newer Self and

00:56:06.119 --> 00:56:07.800
is courtesy of Artlist.
