Geospatial Startups: Recent Episodes
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Computer vision is everywhere! But teaching an algorithm to identify objects requires a lot of data and this is definitely the case when we think about GeoAI
But it is not enough to have a lot of data we also need data that is labeled
If we are looking for cars in images we need a lot of images of cars and we need to know which pixels are the car!
Of course, I am oversimplifying but I hope you get the idea,
Now imagine that you can automatically generate a large labeled data set of realistic images of cars based on the specifications of a specific sensor.
These data sets are often referred to as synthetic data or fake data and to help us understand more about this I have invited Chris Andrews from Rendered AI on the podcast.
Here are a few previous episodes you might find interesting
Computer Vision And GeoAI
https://mapscaping.com/podcast/computer-vision-and-geoai/
In this episode, the discussion is aimed at an increased understanding of the differences between computer vision and the AI that is used in the Earth Observation world.
Labels Matter
https://mapscaping.com/podcast/labels-matter/
What it takes to create labeled training data manually. If you are new to the idea of labeled data sets this is a good place to start.
Fake Satellite Imagery
https://mapscaping.com/podcast/fake-satellite-imagery/
This is a good episode if you want to know more about Generative AI and Generative Adversarial Networks.
Also, check out this website https://thisxdoesnotexist.com/ to get an idea of where and how these Generative Adversarial Networks can be used. Look for a website called This City Does Not Exist http://thiscitydoesnotexist.com/
On a silently similar note try uploading an image to https://bard.google.com/ … it's pretty interesting!
This is an interview with a senior data scientist from Hub Ocean, a platform that aims to unlock and unite ocean data.
Hub Ocean - as the name suggests is a hub for ocean data
Now we have talked about these kinds of data hubs before on the podcast - Sentinal Hub - a data hub for earth observation data, Microsoft Planetary Computer, Google Earth Engine, Open Topography is data but for topography data …. The concept is not new but also not easy to implement and if they work, these types of data hubs have a gravity to them that becomes more powerful over time.
One of the guiding concepts behind these data hubs seems to be the idea of FAIR data - Findable, Accessible, Interoperable, and Reuseable data
…. But its not enough to ensure that the data is fair I think we should also consider how we can make the results of our research Findable, Accessible, Interoperable, and Reuseable data
If you are not already familiar with Cloud Optimised Geospatial formats it is worth checking out these two episodes.
https://mapscaping.com/podcast/cloud-optimized-point-clouds/
https://mapscaping.com/podcast/cloud-native-geospatial/
My guest on the show today is Mike. Today Mike is the founder of a software startup called ChroneChards, but he started as a cartographer for an adventure race and Patagonia.
So he has come a long way.
A couple of other really interesting points about Mike.
He is a self-taught software developer and he is a self-taught businessman.
The reason why I mentioned this means that if he can teach himself these things, then you can do it too.
And as you'll discover later on in the episode, all you have to do is to get really, really comfortable with uncertainty.
You can connect with Mike here https://chrono.cards/
or on Twitter https://twitter.com/get_ChronoCards
It's probably worth riffing on this idea of uncertainty just for a minute.
I think this is one thing that we all have in common. There'll be something about our lives, professional or private that we are uncertain about.
I've had the pleasure over the last three, four, or five years of talking with a few different people that have overcome a lot of uncertainty.
People that are self-taught software developers like Mike, people that have started their own GIS geospatial consultancies, and build their own businesses around their skills, none of those people have overcome uncertainty.
None of those people are now immune to uncertainty!
They have simply learned to live with it.
So as someone who has experienced and continues to experience a lot of uncertainty, these stories have really helped me they've really had a positive impact. It's been great to know that other people go through this too.
So here are some links to those episodes and hopefully, they will inspire you as well.
From GIS Analyst to Software Engineer
https://mapscaping.com/podcast/from-gis-analyst-to-software-engineer/
Starting your own geospatial consultancy
https://mapscaping.com/podcast/starting-your-own-geospatial-consultancy/
Self-employment in the GIS / Geospatial industry
https://mapscaping.com/podcast/self-employment-in-the-gis-geospatial-industry/
Being self-employed in the earth observation sector
https://mapscaping.com/podcast/being-self-employed-in-the-earth-observation-sector/
Mid-career change
https://mapscaping.com/podcast/mid-career-change/
I quit my job
https://mapscaping.com/podcast/i-quit-my-job/
Applications of thermal imaging from space include monitoring wildfires, urban heat islands, economic activity, and the built environment.
But it's not easy ;)
Connect with Robin Cole at
https://robmarkcole.com/
Check out the Earth Observation Hub!
https://geoawesomeness.com/eo-hub/
More Geospatial Podcasts episodes
Recommended Podcast Earth Observation Podcasts
Fake Satellite Imagery
https://mapscaping.com/podcast/fake-satellite-imagery/
The LandSat Program
https://mapscaping.com/podcast/the-landsat-program/
How To Keep Your Satellite Pointing At Earth
https://mapscaping.com/podcast/the-landsat-program/
This is a story about a hobby project called Scribble Maps that grew into business… but it's also a story about the opportunities and challenges of creating geospatial tools for non-geospatial professionals.
Jonathan Wagner
“Its easy to get people to make a map today, but how do you get them to come back and make a map tomorrow?”
Special Offer for Listeners for the MapScaping Audience
ScibbleMaps.com/mapscaping
More podcast episodes on GIS and GIS careers can be found on our website https://mapscaping.com/podcasts/ Consider supporting this podcast on Patreon https://www.patreon.com/MapScaping?
Or go to MapScaping.com to find out about sponsoring our website
reach out on Twitter https://twitter.com/MapScaping
or LinkedIn https://www.linkedin.com/in/danielodonohue/
SAR Technology: Looking Beneath the Earth from Space
The guest on today’s show is Lauren Guy, the CTO and founder of Asterra. He has a background in Geophysics and discovered the technology on which Asterra is built while during his masters. Lauren was involved in a project that used radar sensors orbiting Mars to search for water on the planet. The Synthetic Aperture Radar (SAR) signals used penetrate the ground to give a clearer view of what lies beneath and whether there is any indication of the presence of water.
How Bad Are Water Leakages?
Most of our drinking water is transported from far-off locations like reservoirs or even desalination plants near the oceans.
About 30-40% of the water that is moved around the world is lost through leaky pipes.
It is not only water that is lost in leakages – a huge amount of energy (used to pump the water) is lost as well. Considering the growing impacts of climate change, and looming future water scarcity issues, this is incredibly significant.
How Does Synthetic Aperture Radar (SAR ) Find Water Leakages on Earth?
Different materials have varying dielectric constants and therefore, electrical conductivity. These properties cause materials to reflect SAR signals differently. Treating drinking water gives it a distinct salinity level from other makeups of water.
Since salinity affects conductivity, it reflects a distinct SAR signal that differentiates drinking water from other kinds of water sources in the ground.
The assumption made is that there is no other source of drinking water in the ground – it has to come from pipes. This makes it possible to use SAR to create an underground map illustrating leakages.
Even with the capability to accurately isolate drinking water from other kinds of water, there are still possibilities for false positives as the same water is used for a lot of different uses like watering lawns, gardens, or filling swimming pools. The isolation has to go a notch higher to be able to distinguish the drinking water that is coming from pipes.
One way to do this is by calibrating the algorithm to only show moisture in the ground that has been accumulating for more than 48 hours. The thinking behind this is that most people do not water their lawn for more than 48 hours at once. This helps to avoid wasting time on false triggers.
How Far Can SAR Penetrate into the Ground?
SAR can only penetrate a few meters into the ground, depending on the soil type, and the top covering (i.e. asphalt, pavement, etc.). Generally, the depth of SAR penetration is about 2m in cities, 5m in more rural locations, and up to 10m in very sandy soils. The penetration depth of SAR is suitable for this application since water pipes are usually laid at a depth of 1m.
Georeferencing SAR Images
Georeferencing is a critical part of working with SAR images. The images need to be georeferenced in order to figure out where they are on the surface. Finding the exact location where there is a leak as shown in a SAR image is very important to avoid sending a crew to the wrong place.
Since SAR sensors are usually pointed at Earth at an oblique angle, georeferencing SAR images can be difficult. Georeferencing algorithms have to undergo a robust training phase in order to achieve the level of accuracy required. As we continue to see the popularity of SAR technology grow, we may see this get easier.
Tackling Signal Noise in Urban Environments
Telecommunications in urban environments creates a lot of noise for SAR sensors as they use the same frequencies. Reflective surfaces also create a lot of noise. This problem can be overcome by using different polarizations. A SAR signal can be sent in three ways: Vertical, horizontal, or as an alternating combination of the two in some cases.
When the signal is bounces off different materials or noises, the polarised signal goes from vertical to horizontal and vice versa. Detecting these polarization changes, and measuring their magnitude makes it possible to identify the source of noise that caused the change of polarizations and correct for it.
Building a Business in Around SAR Tech
The problems that Asterra faced while building a business around SAR technology are quite the same for many companies that are developing new solutions in tech. Despite putting in a lot of effort to convince clients that the technology actually works, it is even more difficult to convince a client to create a new budget to buy that solution.
For Asterra, these were passive utility companies that were not actively looking for leakages in their infrastructure, but primarily relied on citizens to report suspected leakages. One of the more common ways a customer might notice a leak is a sudden spike or even gradual increase in their water bill, without having changed their habits. As utility companies did not have an existing budget for a field team that looked for leakages, it was difficult for them to justify a new expense.
Why You Should “Speak the Same Language” As Your Clients
The best kind of clients are the ones that are already solving a problem. It is easier to convince a client to buy your solution if you can acknowledge their existing ideas and solutions, and then offer your ‘new’ solution as a complement to theirs. It will not sound realistic to them to ask them to throw everything out – what is often very expensive equipment – and replace it with your solution. A general good tip in convincing anyone of something, is to make them feel like they came up with it themselves.
For Asterra, it was easier to convince utilities that already had a field team that were actively looking for leakages in their infrastructure, and already had a budget for it. The companies could just reappropriate the budget towards buying the new solution, and even save costs as Asterra’s solution is often cheaper than the original way.
There were also advanced utilities that not only have a field team, but also very expensive IoT equipment for finding leakages. Due to the high costs involved, it is not economical to install the equipment throughout an entire city. For these cases, Asterra’s solution could be adopted as a complement to these devices in order to identify the most problematic areas in the city, and shift the more costly equipment to those locations where it is needed most.
Embracing Competition in Tech Businesses
For most businesses, the thought of competitors may be dreadful, but in tech businesses, competition might just be the force that drives the business forward. Being the only player in the game may be viewed by clients and investors to mean that the market is not viable. It leaves them with many questions of why there are no other solutions in that area already if there is so much money to be made. Competition fuels more discussion around a technology, which is an opportunity for the newest solutions to gain exposure.
Other Applications of SAR Technology
SAR technology is also useful in monitoring other important infrastructure like highways and railways for potential issues. Since SAR is looking underground, the issues it identifies may not be apparent yet from ground level. Accumulated water causes most of the issues in infrastructure. Pinpointing locations with very high soil moisture can help railway companies, or a country’s Department of Transportation to identify infrastructure that may fail soon. SAR’s ability to penetrate the ground at night and in any kind of weather can be harnessed in many other applications, such as mineral explorations, defence, and identifying contaminated soils. Who will be the ones to make it happen?
Recommended Podcast episodes
The Open Geospatial Consortium (OGC) is an international consortium of more than 500 businesses, government agencies, research organizations, and universities ... but why should you care?
Maybe because this community is defining the future of geospatial infrastructure across all verticals!
Maybe because they are determining a set of "the best practices" when it comes to solving big problems like climate change.
Or ... if you have a business ... maybe because joining the OGC membership might just be the greatest marketing hack in the geospatial industry ;)
Here is a list of current members https://www.ogc.org/ogc/members
Recommended Episodes
Open Geospatial Standards – shared standards to solve shared problems
https://mapscaping.com/podcast/open-geospatial-standards-shared-standards-to-solve-shared-problems/
Cloud Native Geospatial
https://mapscaping.com/podcast/cloud-native-geospatial/
Building a Business from an Open Source Project: A Case of White Box Tools The guest on the show is John Lindsay, the creator of Whitebox Tools and a professor of Geomatics at the University of Guelph. John introduced us to Whitebox Tools in a previous episode and described it as a collection of open source geospatial analysis tools that can be embedded in other applications. In this episode, John is sharing with us how they are building ways to generate revenue from Whitebox Tools, while maintaining its status as an open source project - yes, this is possible! When is a Business the Right Solution for an Open Source Project? Being a developer for an open source project could be an experience of two extremes. On one hand, while it may be immensely rewarding to encounter day to day users of the software you have developed, but the experience could be quite stressful as well, especially as the user community expands.
Usually, open source developers have their day job, and only spare their personal time to work on the open source project. When the user community grows, the demands of this larger community may take a toll on the time of the developer. It may be a daunting and potentially draining task to have to respond to too many requests from users. This could lead to developer burnout, which could lead to a project dying out.
A growing user community is a good thing, but for the developer this growing demand can be taxing. At some point, it may be difficult for the developer to provide a satisfactory level of support to the user community as it scales. This means that the project would need more hands to support its userbase.
Generating revenue for an open source project builds more stability for the project, and means that it might be there in the future, with the right support and resources.
If you are having doubts about the idea of building a business from an open source project, then think of the 1000s of users of open source software who not only find them useful for education and research, but also in generating revenue for companies. If there are companies that can use open source tools to generate revenue, then it makes sense that the developer of the project should be able to leverage it in generating revenue as well. The Process of Building a Business from an Open Source Project Building a business from an open source project is not very different from how enterprises build their businesses. The only may be the challenge of preserving the integrity of the project as strictly open source. Outside of this, the business world presents a lot of the same challenges. Finding a Co-Founder Doing business alone could be really lonely, especially for a developer who is already overwhelmed by the demands of the project and community. It may be useful to find a co-founder who can help with the business side of things. At this point, it is important to know what your limitations are, and use them as a guide for the things you should be looking for in a co-founder. The right partnership is one in which the strengths of the partners fill in on the weaknesses of the other and contributes to achieving the goals of the company. Laying Out the Business Foundation In exploring the ways to generate revenue for the project, there are several things that should are imperative for the project’s success: maintaining its integrity and defining its success Keeping the Integrity of Your Goals A growing user community may be a good indication that the original goals of the project are serving the users well. When developing a business model for the project, it is critical to prioritize maintaining the integrity of those goals as much as possible, especially in the regards of it being an open source project. If the user community feels short changed, the project users may shrink and the possibility of the business being a success will diminish. It is very important to uphold the goals that keep the project intact, even when setting new goals. Defining Your Own Success For businesses built from open source projects, success may not mean the same thing as those built in commercial enterprise. Founders can have their own definition of what success is for the business. Sometimes this could mean the ability to sustain a workforce that supports the user community, and keeps the project alive.
Whitebox Tools are exploring ways to generate revenue that will be useful in keeping the project alive in the long term with adequate user support, learning materials, and improving and developing new tools. To them, success is being able to maintain and develop the Whitebox toolsets, and support the community that has gathered around it. This has helped Whitebox keep its focus on the user community, and maintain much of its original framework of the project. Ways to Earn Revenue from an Open Source Project One way to generate revenue from an open source project is by creating new paid tools. These paid tools could be those that extend the functionality of the free tools as in the case of Whitebox Tools Extension. In this way, the status of the free tools would still be maintained as open source as revenue is generated from the paid extension. In order for this to be successful, the paid tools should be compelling. Creating Compelling Products A compelling product is one that users are interested in. It may be a challenging task to know what tools the people want, or whether they will be willing to pay for them. There are some things that can help guide the creation of paid tools. One is looking at various thematic areas that your tools are geared towards and figuring out some tools that would have a great interest in those application areas. This will give an idea of where to focus development efforts. If you can create a toolset that fixes all the problems a certain type of user has, you become essential to that user.
Engaging with existing users of your product can also be a great resource for knowing where to focus development efforts. There is much that can be extracted from the conversations where users describe how they use a product, and how they would like to use it.
Gaps in a particular field can also provide an opportunity for developing a paid tool. A good place to look is in areas of recent advancements. Spotting a gap will enable you to create a solution that will be used by people working in a particular application area, and its more likely you’ll beat someone else to it. The “Pay as Much as You Can” Pricing Model “Pay as much as you can” is a pricing model that lets people donate to free tools. The Whitebox Tools website has this pricing model in the form of buttons displaying amounts between $0 and $100 on their tools download page. This presents an opportunity for users to support the project, even if they may not be able to afford the paid tools. It may also help to put in a note explaining how the donations will be used in support of the project. Steering the Business towards Success Thinking of the right tools to create, and having the right pricing model is not all that there is to succeed in this business. Increasing Product Visibility In marketing, the ideas that spread are the ones that win. It’s hard to achieve success if the project you are working on is invisible. It is unexpected for people to care about things they do not know exist or that they cannot find. This is an especially big challenge for products that are predominantly backend.
Usually, it is the frontends that get more attention than the backends that power them. Opting to create your own frontend may be a way of making your project more visible, but if your solution is designed to power other applications, this could be the wrong use of time. Alternatively, entering strategic partnerships with essential popular frontends may be useful in growing your appeal.
Cultivating various types of non-financial support may also help increase user awareness. For instance, reaching out to long term users and asking them if they could support you by mentioning your business on their website, blog, or social medias. You could also simply ask for permission to showcased them as users of your tools on your business website. Effective Communication Communicating effectively is a key part of the success of any business. Although you may create a really wonderful tool that provides an innovative solution to a problem you know people have, if it is not communicated properly, it still may not be successful. Effective communication means using the right words and images, or packaging them in a other way that helps people to understand what the tools can do for them. Try different communication styles gracefully, while acknowledging that many businesses find it more difficult to communicate a tool to users than creating a tool itself. Commitment and Confidence Commitment is super important. If you put something out in the world and it fails, have the confidence to try again. Repackage it, find other creative ways to communicate it and try once more. If you are using avenues like Twitter, LinkedIn, or even a blog or newsletters, it will help to think that you're speaking to different, if not overlapping groups of people in each of these avenues. It is important to reach out as inclusively as possible. The Website A website can be quite central in telling the story about a business. It is the first place where people from other avenues and social media will learn about you. A lot of effort should be put into the website to make sure it effectively communicates what the business offers. Imagine that people know absolutely nothing about your business and be as specific as possible about all the capabilities offered. How a User Community Kill, or Keep an Open Source Project Alive? Without doubt, a developer has a certain responsibility that comes with creating a software and making it available for people to use. After all, a project lives and dies by its user community. Its users, whether in an educational, government, or commercial setting, have a certain responsibility to ensure that the project thrives. If the developer is responsible for everything, it can result in burnout and risk the continuity of the project in the long term. Thriving open source projects are the ones which gain the support user community. Building a Business Is an Iterative Process One thing to always have in mind when building a business is that success does not usually happen the first time. If it does not turn out well the first time, try it again with a different approach and an open mind. Iterate and improve upon your process and eventually it gets better. There may be many struggles along the way but part of the journey is learning from mistakes.
Our guest today is Jakub Dziwisz, the CEO and founder of Orbify, a web-based SaaS solution for earth observation applications. Although he does not come from a GIS background, Jakub has always enjoyed problem-solving through technology. Originally, this consisted of being a software engineer focused on expanding people’s horizons and perspectives through the travel industry. Now, Orbify helps expand the geospatial capabilities of everyday people, solving not-so everyday problems.
Why Merge GIS and SaaS? First of all, what is Software as a Service (SaaS)? Well,
SaaS products are traditionally web-based software that greatly reduce the amount of time it takes for customers to get up and running with their own products by utilizing the SaaS product’s infrastructure.
Generally, these products follow a ‘pay only for what you use’ format, very similar to how some cell phone providers offer custom mobile data plans.
SaaS products can be great for GIS because they leverage the SaaS provider’s hardware and software resources, allowing customer applications to live and run in the cloud. This lowers the barrier to entry in terms of resources for creating an application. Most SaaS products allow users to select their application’s function or design from a series of preset templates, or DIY in some other modular way. This also lowers the barrier by reducing the amount of time and expertise necessary to get started on a project.
Another huge time saver with SaaS products is that, due to being web-based, there is no installation needed. Organization administrators can configure all their user settings on the backend, and easily regulate access to their application. This makes it a very popular platform with large companies who have a huge and constantly changing employment pool.
Although the pay-as-you-go method has been popularized in cloud storage, and to a certain degree in the ArcGIS platform for some analysis using credits, SaaS providers that are creating infrastructure for GIS workflows are few and far between.
The Need for SaaS in EOS: An Analogy In the 1920s, Henry Ford introduced the world to the raw efficiency of the assembly line. Before this, the process of building a car was slow, and expensive. By introducing the assembly line, cars could now be built in a streamlined fashion which was faster and easier, ultimately making vehicles accessible to a much wider market.
In the 1990s, it was customary to go to a travel agency if you needed to go on a trip. The travel agent would list for you the often limited available flights and fares, and you could take it or leave it. With the introduction of budget travel services like Expedia and Hotwire, consumers were provided with options to modify their plans to their needs. This resulted in a more competitive airline market, and democratized the space by putting the consumer in control of what they consumed.
Finally, in 2007, Steve Jobs unveiled the iPhone. People had been familiar with the telephone, even the cell phone, for decades. Similarly, they had been familiar with MP3 players for years. The idea, however, of being able to have both of these things in one changed how people judged the capabilities of technology.
For decades, GIS users and earth scientists have been working across dozens of applications, tools, script, and data sources.
By bringing SaaS to this niche, geospatial data workflows can become faster, easier, and more accessible. As it succeeds and more players enter the space, consumers will find they have more competitive options, and that their needs and dollars are in control of what happens next, and they shouldn’t be afraid to ask for what they want.
Creating a SaaS User Experience The best SaaS products are intuitive, and feel almost effortless to navigate. This is in stark contrast to the alternatives- environment-specific scripts, custom desktop installations, and coordinating and managing server resources. Planning and designing a great SaaS product is heavily dependent on knowing what your clients need, and what their customers want.
In order to build an app, there are four main elements, data, functionality, the output, and the packaging/user interface.
Normally, it takes quite a lot of time, code, and infrastructure to build an application like this. It often even requires a full team of developers. Using SaaS software, something like this can be configured by only one developer, and relatively quickly.
Let’s take a look at an example, using Orbify as our SaaS platform.
Orbify was developed with low tech skilled end users in mind, who need to solve a spatial question on a regular basis.
The Orbify platform is a bit complicated for someone with little technology experience to configure, so the most likely situation is that a developer has been contracted to build this application. Our end user in this case is an ecology graduate student who needs an application to monitor shipping vessel activity to better understand how this overlaps with known whale migration paths.
A user-friendly experience is key to the speed here. This starts with the data aspect. An interface like Orbify comes packaged with access to a catalog of existing cloud data that the developer can connect to and use in their application.
As the source code is completely customizable, they have the flexibility to connect to their own data as well.
For our scenario, the developer is able to connect to hosted AIS ship tracking data, and import their own data for their whale migration paths.
The functionality needed for our application is to visualize the ship and whale data in the context of time. This is easily accomplished in Orbify by selecting the ship tracking application template, and enabling the time slider. The output for this project is a map, which is accomplished through the template. Finally, the user interface will largely be directed by the template, but the developer can select from a number of existing no-code buttons and tools to include in the interface, and customize the look of the application as desired.
In the end, our graduate student has a simple, custom application that was created with minimal man-hours, and will only be billed for what they use.
This scenario can be extended to all kinds of potential customers for whom the traditional custom application would be too expensive, farmers, foresters, firefighters, etc.
By reducing the barriers to entry for using custom GIS applications, more people can be exposed to the wonders of geospatial, and we can collectively work towards solving problems that weigh on everyone from the individual, to the global organization.
You don't have to be a big organization to create a business or side hustle around your geospatial skills. If you are looking for examples and ideas ... this episode is for you.
If you enjoyed this episode check out "Geospatial Side hustles"
https://mapscaping.com/podcast/geospatial-side-hustles/
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Our guest today is Matt Pietryszyn, the CEO and co-founder of Qwhery, a company looking to use smart devices to streamline interactions between citizens and their municipalities. After years in the public GIS sector, Patrician recognized a strain on 311 resources and wanted to help. As a tinkerer with a skillset in developing open data solutions, his response was Q11, a smart speaker application that is looking to improve ease of access to location information for everyday questions. Voice Assistants and Spatial Applications In the modern world, voice technology is becoming more and more commonplace. In 2019, 20% of Google searches were voice queries and in general, a hefty share of searched questions are users looking for information on things in their local area. To complement this, over one-third of Americans now own a smart speaker. Understanding the current landscape, it is unsurprising that some innovators are looking to give the people what they want, a smart speaker compatible application that will answer their spatial questions.
Smart speakers, such as Amazon’s Alexa, and Google Home, are interactive speakers that allow users to control their smart homes. This largely involves tasks such as turning lights on or off, playing music, or telling a silly joke on demand.
These platforms also offer app stores with custom libraries of functions for users to take advantage of. Amazon’s applications are called skills, where Google’s are called actions. Independent companies and developers can contribute to these app stores to add even more targeted functionality.
Although there are already a plethora of skills and actions on the market, smart voice assistance is still a very under explored space. Spatial queries in particular leave a lot to be desired, but hold a great amount of potential.
As smart devices store a user profile of home address, phone number, email, and a number of other preferences, the figurative distance to be traveled to start answering people’s spatial questions is shorter than one might think.
The trick lies in translating how humans ask questions, to how computers understand questions, then encouraging humans to continue to take advantage of this emerging technology as new capabilities are released. A significant part of this is porting web page based applications to voice based interactions.
Where a web map may be the driving force behind answering a user’s question, that simply cannot be communicated in the same way strictly through words. This requires rethinking how people interact with spatial information at its core. How Do Voice Skills and Actions Work? As everyone here may know, humans and computers speak different languages. Computer scientists have spent a long time navigating how to better translate between the two, and now we benefit from an extensive catalog of options. The people over at Q11 in particular are focused on adding geographical questions to this growing dictionary to allow you to ask “Alexa, when will my garbage be picked up?” or “Hey Google, what is going on downtown tonight?” and get back a quick and useful result.
Accomplishing this task is simple in theory, but takes time to implement correctly. The general workflow involves first converting the user’s question to a query, pushing it to the appropriate municipality’s API and backend, then returning an understandable response to the user.
Converting user questions into actionable queries has been the mission of smart speakers from the beginning. The process, called natural language processing (NLP) involves converting the spoken word into text, then extracting information from that text to build a query or command. The phrases people use for requests are called ‘utterances’.
Lists of synonyms are created for the words used in utterances. These lists are expanded in order to help train the program for the many language variations that the application will likely encounter from the public.
While applications like Q11 will respond to specific requests, for example “Alexa, what construction projects are there within 2 miles of me?”, it is also engineered to create queries from more general questions like “Hey Google, what construction projects are there near my house?”.
Once the utterance has become a query, it gets fed into the relevant locality’s API. As there is no set standard for how GIS services are administered, stored, and accessed, it is necessary for this API setup to be done manually using Qwhery.cloud by the municipality’s GIS or IT department. This allows them to take advantage of the potential features of the Q11 application, as long as they have a feature service available that matches the user’s needs.
Considering the discontinuity between various governments’s backend GIS systems, it is unlikely that we will see Amazon or Google themselves swoop in with their own custom spatial skills and actions.
It is simply more efficient for each organization to integrate their own APIs, REST endpoints, and services. When the localities themselves are involved in this step, it also allows them to better regionally adapt their queries and outputs. Where “nearby” may mean 10 minutes in a small town, it may mean an hour in a larger city. The Future of Spatial Voice Querying Voice assistants and artificial intelligence in general have come a long way very quickly, but of course, there is still ground to cover. We have already seen next gen features incorporated, like Q11 notifying users when the garbage truck should be expected, but there are both technical, and social challenges in the way of future uses of geospatial voice apps.
A broad goal that GIS departments have in implementing tools like voice and web applications is to reduce calls they get to 311 centers, and to generally produce better informed citizens. This mission began with geospatial web apps, and the issues began with promoting awareness of these resources to the target audience.
Geospatial voice tasks and actions face the same obscurity problem. If people are not aware they can ask Alexa what the zoning limitations of their property are, they probably will not think to. By the time they have researched the answer to their question, they may not have the need to ask it again in the future. This conundrum is why developers want to facilitate reusable content - questions that need to be asked over and over again. This produces returning customers who may be more willing to invest the time to explore additional capabilities.
A huge market for potential use of spatially-aware voice apps is commercial applications. A user might be able to ask “Alexa, what is there to do downtown tonight?” and get a number of events to attend. These can be sourced from the municipality’s Economic Development office, or even go down the path of sponsored messages.
Further opportunities in the private sector lie in integrations with things like the Yelp API, where a user could ask for recommendations of where to find the best pizza in their city or neighborhood.
Once the word gets out on the possibilities behind spatial voice queries, there will be no looking back.
This episode might not be for you, it might not be what you signed up for. It's a solo episode all about ideas, being an advocate for our ideas, and how we get them to spread.
I hope your 2022 is off to the best possible start!
Our guest today is Anthony Antonio, CEO and cofounder of UrbanSky, based out of Denver, CO. UrbanSky is a remote sensing startup with a primary focus on the use of zero pressure stratospheric balloons as the UAS/UAV for sensor payloads. Anthony’s background is in business, obtaining his degree in Business Management from Washington College before he joined the StratEx project. After helping to facilitate the world record setting space dive from an stratospheric balloon, he and his partner, Jared Leidich, set out to present the “cubesat of the stratosphere” to the world. The Rise of Stratospheric Balloons Balloons are not generally the first thing that comes to mind when considering the cutting edge, in fact, the earliest remote sensing projects were conducted with balloons. The real excitement comes from thinking outside the traditional sphere of uses of balloons, and of the stratosphere itself.
Atmospheric balloons have already carried weather sensors to great heights for data collection. It is a relatively simple process, using small latex balloons which will pop when they hit a certain altitude, dropping their data payload back to Earth to begin a proverbial Easter egg hunt for scientists on the ground. Larger stratospheric balloons have been used to carry much heavier payloads, including the former Senior Vice President of Google who set a world record jumping from one at 136,000 feet. The presence of only very large, or very small balloons on the market is being challenged by the advent of mid-sized zero pressure balloons. The balloons can be launched from the back of a pickup truck. This is a huge improvement from the previous need to launch large balloons from airports, or even space ports due to the need for special infrastructure.
Zero pressure balloons are made from a thin plastic bubble that opens at the bottom, and is partially filled with helium at launch. As the balloon rises, the helium expands and fills the balloon. Once it reaches between 60,000 and 70,000 feet, excess helium will leak out from vents, keeping the balloon at a very stable altitude. Zero pressure balloons can maintain this altitude for about 6 to 10 hours, as colder temperatures associated with nighttime will compress the helium in the balloon, triggering its descent. This can be combated to a degree by strategically dropping ballasts (generally sandbags) to reduce weight, and gain more airtime.
Balloons are significantly cheaper than traditional remote sensing vehicles, but they do still face limitations. The FAR 101 rules of the FAA apply to High Altitude Balloons with payloads above 6lbs. If a balloon keeps its payload under this limitation, they are subject to far fewer FAA regulations, and gain a lot of flexibility with their flights. Balloons as an Earth Observation System The low cost and high flexibility of stratospheric balloons is enticing enough, but learning how stable these balloons can be at high altitudes unlocks a lot of doors in remote sensing. Furthermore, the stratosphere is an untapped “market” as generally the only aircraft found there are weather balloons, or the occasional spy plane. Stability of the balloon may not be an obstacle anymore, but there is still a great deal of thought put into how to steer the balloon to ensure it collects the target mission. Traditionally with large balloons, this involved navigating layers of wind in the atmosphere in very much the same way you would steer a sailboat. This left pilots very dependent on the weather and winds near their launch infrastructure.
Smaller balloons, like those produced by UrbanSky, can be transported and launched from a pickup truck in about 10 minutes, allowing them to travel to ideal conditions. Once a targeted area for collection is planned, atmospheric modeling algorithms can be run which output the ideal launch location for the desired flight plan. Each balloon can collect 20-22km of imagery , and can be launched in close proximity to widen the collection area. This wide range means there is a very safe margin of error (1-2km) for balloon missions. When collection is complete, the balloon and its camera can be disengaged, and recovered in a predictable location.
Currently, due to the 6lb limits, only one sensor is generally attached to a balloon at a time. The most commonly used sensor is an RGB, 3-band camera. Flying significantly closer to the Earth than a satellite means equally improved image resolution. UrbanSky’s system allows for a 10cm ground sampling distance (GSD) with their RGB camera, and 3.5m for their infrared sensor. The future likely holds continued innovation as high resolution sensors are made smaller and smaller. Future and Uses of Remote Sensing Balloons The reimagining and miniaturization of low cost stratospheric balloons has the potential to change the landscape of the aerial imagery market. The significantly lower costs mean it becomes much more feasible to collect imagery at smaller intervals. Instead of waiting every 3 months, 6 months, or even a full year for collection by a competing UAV, balloons can be flown as often as daily over areas of interest, yielding huge amounts of high resolution data.
The unprecedented amount of data that could be made available by balloons has some applications right out of the gate, but many have historically considered this resolution out of range, leaving a lot of space open for brainstorming new, innovative uses. Some of the best known applications are for the insurance industry, and creating input data for deep learning extraction. Benefits such as ease of deployment, cost unlocked opportunities for collection of lesser natural disasters in localized areas. The market for large natural disasters is currently pretty well covered by a variety of market players and governments, so expanding the scale of collectable events is groundbreaking. One especially engaging use case for balloons is imaging wildfires. Infrared cameras can be flown over areas of interest without interfering with aircraft fighting the fire below in lower airspace. Currently, balloon data is not downlinked, meaning it must be collected with the flight system once it has landed. UrbanSky, however, foresees real time data streaming where onboard photogrammetry software, paired with infrared, can broadcast data directly to firefighters on the scene, allowing them to respond more effectively to emergencies.
Other potential uses for stratospheric balloons are not limited to imagery workflows, but can encompass communications, and emergency applications. As time goes on, even more uses will be innovated and implemented. As we have seen, the ceiling is rising for the widening range of balloon and remote sensing technologies, and the sky is no longer the limit.
Our guest today is Carly Morris of Geovation at Ordnance Survey, a London-based organization that provides resources for geotech and proptech startups. While Carly has minimal experience with GIS technology, she has plenty of background helping to seed successful startups. Having spent several years as the Head of Innovation with one of the world’s largest airline groups, she knows what it takes to help an idea take off. She has since shifted to supporting geospatial entrepreneurs in their early stages to enable future success. Getting Help with Your Geospatial Startup Building a startup from the ground up is no doubt an intimidating process, so it can be an excellent jumpstart to have specialized resources at hand when beginning such an adventure. There are organizations out there that exist to help startups in their early stages. It is less common for them to support geospatial startups in particular, but in the UK, Geovation has served this niche well.
A geospatial startup resource like Geovation can help by providing funding, guidance, and connections for blossoming business owners. Their accelerated program is a 12 month process. The first six months consist of hands on support, while the final six are more hands off. All along the way, founders and their teams maintain autonomy over decisions, but are directed to evaluate their moves critically to help set themselves up for the best possible outcome for their business as a whole.
Most organized resources for startups do not care what particular industry you are breaking into and will help you ramp up regardless, so if you are outside the UK, there are still great options. SCORE acts as, and provides, a holistic list of resources for entrepreneurs to reference. The US Small Business Administration website also acts as a hub for planning and financial resources for US-based small businesses. To round it out, Esri’s startup program provides ArcGIS software resources to new businesses that qualify if you demonstrate a desire for long-term commitment with them. What Does a GIS Startup Need? First and foremost, a startup needs to identify a problem that genuinely needs solving. This does not mean that no one else is trying to solve it, but the problem should be well-defined, prevalent and significant enough to justify a solution. A great way to understand need is to talk to the people with that problem. Find out what impacts them, and how. Collect data on if your proposed solution would work for their cases, and if they are willing to pay for it. Always keep an open mind and be willing to change course if your original hypothesis is off.
Commonly, entrepreneurs set out to create a new business once they have identified a gap in their industry. If someone else is already in this area, identify areas that could be improved upon, and make those changes to provide the superior product.
An essential element of building a great startup is having the right founder. The ideal founder will have a palpable passion for whatever problem they are trying to solve, even to the point of it being an obsession. This drive and enthusiasm will be necessary to help carry the young business through the inevitable lows that the team will encounter as it grows. There should be highs as well, but these inherently carry less risk and should only fuel the fire. A good startup founder should also be open to feedback. The right attitude and a willingness to learn and adapt is invaluable, and impossible to teach.
It is a common misconception that founders need to be highly technical people, and have intimate knowledge of every facet of their business. This is not the case. Startup founders come from a wide variety of backgrounds, and the best ones generally have stronger background and interest in the primary problem they are looking to solve over the technical skills to do it all themselves. The best leaders know how to delegate. For this reason, it is more important to be able to identify strong contenders for building their team, rather than carrying it all themselves. Planning for a Startup’s Success A wise man once said, “If you fail to plan, you are planning to fail”. This is equally true in the world of entrepreneurship. If you find that you hold the key qualities for being a great founder, and you have a problem you are fully dedicated to solving, it is time to start laying groundwork for your geospatial business.
A good first step is to create a value proposition canvas. A value proposition canvas is a tool to help better understand the needs of your customers, and how you might add value to their situation and ultimately help resolve their issue. Creating a VPC is not a terribly complicated process. Through the course of preparing one, you can discover gaps in your understanding and preparation, as well as realize questions you have not yet asked.
As is true for many situations, it is highly valuable to build and maintain a quality network of people that you can talk to and collaborate with. In the early stages of the startup, you can go to your cohort with ideas to solicit feedback. Open a discussion with a trusted individual or mentor to discuss your business plan. Give them chances to ask questions, and make special note of questions you had not considered so you can explore how to best answer them in the future as the stakes increase.
Working with location data is tricky business. Due to its highly sensitive nature, we must be on guard to put our best foot forward in enforcing best practices as far as ethics, and privacy. The Benchmark Initiative has developed The Locus Charter to help build global guidelines for this space.
When you are fresh on the startup scene, it is easy to feel like an imposter. If all of this is new, you probably are one. Lean into the opportunity for a unique perspective and explore your questions with those more experienced in the industry, and know when to take their advice.
Overall, some great advice for setting out with your startup- * Make sure you have fallen in love with the problem you are looking to solve. Passion holds power. * Once you have made the decision to get started, do something. Create the momentum that will help drive you throughout the process. * Do not be afraid to ask for help. You cannot be expected to know all the answers, and that’s okay. Reach out to your network, and be open to insight.
Our guest today is Shay Strong, Ph.D. Dr. Strong is the recently appointed Vice President of ICEYE, based out of Espoo, Finland. While she is somewhat new to the world of SAR, she has vast experience in remote sensing, and brings valuable cross-disciplinary insight via her P.hD in astrophysics from the University of Texas at Austin. Beginning a shift out of academia, she worked for Johns Hopkins University, developing national security satellite systems. This evolved into an interest in cloud-based imagery data pipelines, leading to her current role with ICEYE where the focus is optimizing these data pipelines, and how to efficiently extract the most useful information from them. ICEYE is a SAR satellite company that utilizes their own constellation of 14 satellites to respond to and monitor flooding events. Monitoring Flooding - Why Is It So Hard? There are quite a few challenges in the pursuit of monitoring and mapping flooding. For ICEYE, these challenges begin with determining where collection needs to be to begin with. The nature of catastrophic events is that they happen quickly, and this reduces the timeline available to activate resources. Considering that boots on the ground have the time-based priority of protecting themselves and others in immediate danger, ICEYE has built their own team of meteorologists and analysts to help predict where and when the next event may be.
Having an idea of where and when the next flooding event may be is invaluable, but it is still difficult to make predictions reliably enough to capture the peak of an event. The peak of a flooding event would look like the deepest and widest extent of flooding, or destruction of critical infrastructure.
Determining locations with the greatest potential for impact can be further enabled by referencing other classic GIS resources, such as demographics and maps of existing infrastructure. Analysts can combine this information with historical data and weather models to understand where the areas of highest risk are. This means that when there are multiple potential events that need to be monitored, it is easier to make the difficult decision of where resources should be allocated.
The key element of monitoring a natural disaster is being able to monitor change. In a flooding event, this change happens quickly. In order for information to be useful and valuable, it must also be timely. Repeated collections over an area allows the creation of time-series products, allowing more accurate and relevant solutions for stakeholders. SAR and Flooding SAR, synthetic aperture radar, is highly versatile and capable of providing timely and valuable information about the geography of a study area. As an active system, SAR has the benefit of being able to penetrate clouds and haze, as well as being able to continue collection through both the day and night. There are a variety of image collection options out there, including optical, infrared, thermal, etc. but this round-the-clock collection aspect of SAR makes it especially useful for responding to emergencies.
Collecting SAR data is only the first part of the puzzle. Once the imagery is collected, it must enter the data pipeline to be assimilated, processed, and analyzed before useful information can be derived from its products. The trick is that these are real-life events being monitored, with very high stakes. The derived information is most needed within 24 hours of the event to inform responders and the public, creating added pressure on analysts for swift and accurate work.
Before one can evaluate the results of the collected data, it must first go through ground truthing. Ground truthing is the process of relating collected imagery to its real life location. In GIS, we frequently see this as georeferencing. Validating SAR data in a flooding event is quite challenging. Flood gauges that already exist are most likely near water bodies, such as rivers, which have likely overflowed as part of the event, and are not visible, or producing useful information under the circumstances. Additionally, previously easily identifiable locations, such as street or building corners, maybe inundated by the flood, and no longer act as useful landmarks for ground-truthing.
Any information collected via SAR is only as useful as the DTM (digital terrain model) it is overlaid on. This is complicated by the fact that high-quality DTMs are expensive, and narrowly available in many locations. In rough areas with even moderate variability in terrain, the standard 30m DTM is going to be minimally informative. SAR raster data can have a resolution of up to 25 cm. In order to calculate the 3D extent of the flood (the depth) the DTM must be subtracted from the ground-truthed SAR readings, so detail in the terrain model is imperative to getting useful results. The Business of Monitoring Flooding Satellite collection in general carries a hefty price tag, so it is important that there be a consumer market for imagery out there to support it. When it comes to flooding, in particular, those who see the most value so far are insurance agencies and governments. Insurance companies will use the products to help evaluate claims and update the risk level of various territories. Governments will primarily find value in the context of emergency aid response, and more so, to assess future risks due to climate change.
A big part of understanding where the viable market is for SAR data on flooding is knowing where the information will be most valued. For some places, like India in the monsoon season, flooding is seasonally routine, and residents have adapted to it for thousands of years. For these reasons, they probably will not see as much value in satellite monitoring as, say, a tourist district in southern Louisiana.
Another high-cost point in the flood imaging pipeline is the manual labor involved. Although automation has come a long way, there are still a significant amount of human eyes (and brains) needed to complete an analysis. It is likely we will see the number of humans in the mix reduced, but never eliminated.
As we explored earlier, one of the difficult aspects of making SAR data usable in a flood situation is ground-truthing. One way the team at ICEYE has been able to bypass this is by tapping into social media resources. Videos posted in places like YouTube or TikTok of flooding events can be used to help verify collected imagery. Considering how far sensors in cell phones have come, there is a lot of room for improving how citizen scientists can contribute to collection efforts.
Overall, when looking to create a geospatial solution, it is vital to make sure you are answering the right questions. Do not be afraid to be specific, as broad questions can have even broader answers. A business of this kind will have technical, as well as cultural challenges, and the more you understand them before encountering them, the better.
There is no guest today, just me, Daniel O'Donohue. The inspiration for departing from the norm today is a Reddit discussion on a scenario that may resonate with many.
Are you unhappy in your current GIS job, or feel stagnant in your development? Are you thinking that maybe you are not exploring your full professional potential in the geospatial field? If you are looking for a way to manage these feelings, while taking on very little startup risk, a geospatial side hustle may be the thing for you. If you are completely satisfied with your day-to-day work, that’s great! You will still benefit from keeping aware of market demand, and where the future industry opportunities may lie. Selling Maps Online As a map-enthusiast, although it may feel a bit obvious, creating maps may be the perfect fit. You are already making maps, why not go the extra mile and take the opportunity to share them (for profit!).
Others have of course already entered this niche. Etsy is an online marketplace for those who are looking for something you cannot buy off the store shelf. This platform for unique content is an excellent environment to sell maps in.
To get started, take some time to play around with the search function, and figure out what gets hits for the keywords you would expect customers to be searching. ‘Maps’, ‘Geography’, and ‘Landscape’, possibly plus the word ‘Gift’ are some good options to check out. Once you get some results, go ahead and put that analytical brain to work and see if you can find some patterns as to what works. Etsy can allow you to figure out what people want to buy, it will also give you an idea as to what they are willing to pay. Some other insights can include cartographic style, preferred colors, and even feedback as to what would have made those products even better.
Once you have a template for your content, you can plug any location into it to maximize the diversity of your offerings.
As a mapping professional, you have an advantage over those without that extra skillset, embrace it!
Now that you have the content, it may seem a bit intimidating to take on the arduous tasks of finding a printer, testing the products, figuring out shipping, etc.. The modern era actually allows you to outsource a lot of this. If you would like to avoid print altogether, you can choose to make your prints available as PDFs, and shift the content delivery aspect to the consumer.
If you don’t love the idea of someone being able to download (and potentially resell) your content, you can outsource all the physical production to a third-party printing and shipping service like Printful, and facilitate your digital storefront through Etsy or Shopify. Geospatial Content Creation Geospatial content is not limited to just maps. This podcast is geospatial content, these show notes are geospatial content, this stain that looks like Africa is geospatial content, well, you get the idea.
Content, whether it is audio, visual, or written, especially in the context of social media, is in high demand in the marketing sector. When it comes to geospatial content, the candidate pool those employers have to pull from narrows.
For the highest quality and most effective content, they need someone with a GIS/Geography background, as well as the desire and ability to combine those skills with the content medium.
Companies want to drive growth, and better content means a better chance to be discovered. The right content creator will know how to optimize keywords, resulting in better organic search rankings, and having the background knowledge to know what those words are is invaluable.
If this side hustle sounds like your kind of thing, here are some ways you can break into it. The first thing you will need to do is identify who would benefit from your services.
Take some time to figure out who is already spending money on content creation, as this means they see the value in the results.
You can do this by checking out the quality of their existing content (website, social media feed, etc.) and seeing if they are already running ads. The Facebook Ad Library is a good resource for scoping out their presence and investment in the platform.
Also, look to see how is sponsoring podcasts, online events, conferences. When you visit a geospatial blog do you see companies advertising on it? What ads do you see when searching for geospatial topics on google? What you are looking for here is who is already prepared to invest in getting traffic to their website and who has the budget to invest in content.
Now that you have narrowed down some potential clients, it’s time to sell yourself. Determine what you can bring to the table, and begin those conversations. Keep in mind that it is best to present tangible outcomes. In your discussion, describe how you can accomplish the company’s goals (likely some form of higher engagement, resulting in sales) by completing XYZ projects using ZYX skill set. Online Web Maps and Apps If your forte is in development, web or otherwise, you are in luck- business is booming and the space is full of potential. You do not need to be capable of programming the next Google Maps to be successful in this side hustle, simple web tools, such as https://www.gps-coordinates.net/ ( estimated monthly traffic = 443,000, estimated monthly revenue = $6600) or https://www.freemaptools.com/ which is less than polished, but still, its working and has been for awhile.
If you are struggling to find some inspiration for what to create, just know you do not need to reinvent the wheel here.
If something is working in another space, and you have the skills to adapt it for a geospatial purpose, do it!
If you find that an existing tool is lacking in some way, build a better one! Don’t forget to include your contact information in the end product, it will open you up to custom work from particularly impressed visitors.
The trick in creating evergreen content here is to solve a problem that needs to be solved over and over.
If you fix someone’s problem in one visit, you have limited your revenue potential. If you create a tool that someone can add to their toolbox, it will get used whenever something needs fixing. To get an idea of how much revenue a site may be generating, you can use WorthofWeb, and to get an estimate of traffic, try ahrefs. Please note, neither of these sites are perfect, so use some discretion when interpreting the results. GIS Freelancing If none of the side hustles above cut it for you, and you would rather be doing raw GIS work, there is still a market for you. Online freelancing platforms have increased dramatically in popularity over the years. Some of the two most popular at this point are Upwork, and Fiverr, although there are plenty of others that we’re sure would love your business.
Freelancing platforms offer a wide variety of work, including GIS work. Clients generally advertise for jobs, and freelancers will submit proposals as to why they are the best candidate. If you want to prove yourself to be the best candidate, you would be wise to back it up with evidence.
Hosting a polished portfolio on your profile will help you get noticed, and increases your chances of landing work.
That first job is always the most difficult one. Be persistent, and have confidence in your abilities, and you will be winning jobs in no time.
You do not need dozens of clients to succeed. Realistically, you only need 3-4 core clients to be sustainable. It will take some time to find these clients, so be sure to value them once you do get them. Clients are looking for someone who can do the work, show up, and can communicate accordingly. Online freelancing platforms host a lot of competition, which can make it feel like a race to the bottom. You will see plenty of freelancers out there with low rates. Just remember that you get what you pay for, and quality talent will always be in demand to those who value it. Do not undervalue your skills, and approach jobs with confidence-- you’ll do great.
Our guest today is Joe Morrison. Joe is currently the Vice President of Commercial Products at Umbra, a satellite and synthetic aperture radar (SAR) start up. Far from what you may expect, he went to university for religious studies. From there, he got a taste of entrepreneurship manufacturing backpacks. When he began to find this unsatisfying, he connected with Azavea, an ethical company with a quality team that inspired him to break into the satellite imagery industry. After spending five years apprenticing and learning, he migrated into his current role and foresees this fascinating industry keeping him (and many others) busy for the remainder of their professional careers. Is Satellite Imagery a Commodity? In preparation for the geospatial economics lesson we will be traversing, let’s go ahead and define what a commodity is. A commodity is a standard, interchangeable product or good which may be used as the input for creation of another product or service. While imagery absolutely satisfies the second part of this definition, we will see that it is far from standardized, or interchangeable. In short, no, Satellite imagery is not a commodity. Commodities are commodities because you can buy them, and good luck buying satellite imagery. You will need to call in a series of favors, and go through a highly classified number of miles of red tape, including lawyers, contracts, and assorted investigations into your intentions before you may have the privilege of spending a huge amount of money, months after your initial inquiry.
Even though there is a remarkable amount of oversight associated with imagery collection, this is not enough to have established an industry standard format for storage, or documentation for indexing.
If imagery is so clearly not a commodity, why are we having this discussion? Well, aerial and satellite imagery are absolutely essential for a wide variety of applications, and have been for some time. Imagery is needed for mapping, monitoring, and all the knowledge and research it enables, and there is no real substitute for it. Despite the financial restrictions, it is still infinitely more practical, in terms of time and finances, to collect imagery than it is to build that information from a manual survey of assets. Comparing Satellite and Aerial Imagery Let’s go ahead and continue our lesson by quickly differentiating between satellite, and aerial imagery. Satellite imagery is, of course, collected by satellites.
The image footprints collected are very large, collected from very high elevations (hundreds of miles), and generally of lower resolution than aerial imagery. Aerial imagery, in contrast, has smaller footprints, comes from lower elevations, and is of higher detail. Aerial is also easier to collect on demand, as you can get it from manned, or unmanned aircraft, which are much more available and flexible than satellites.
Here is a very cool live interactive map provided by Esri of all the satellites currently in orbit (Spoiler: 75% of them are space garbage).
The space age only recently blessed us with satellite imagery, but aerial images have been collected since 1860 (the first was this image of Boston collected by hot air balloon). Ongoing regular collection by various government, and more recently, commercial and private, agencies has created the illusion of a wealth of spatial data.
While there certainly is a great deal of imagery out there, it is not all created equal.
The lifecycle of imagery is much more complicated than most people realize. It is not as simple as snapping the photographs, georeferencing them, and moving on to analysis. Collected imagery must go through pre-processing, including simplification, transformation, and combination, in order to begin to become a usable product. This preprocessing is subject to a series of executive decisions about how to form the final product, and there are no standard guidelines being used. Different organizations may have their own unique processes. This means that even if two groups are provided the same base set of images, their imagery products may look very different.
This lack of standardization is a major issue. It makes it difficult to share data between organizations, and can cause issues in larger workflows as plug and playing with a wonky data format may grind everything to a halt. There is a grassroots movement looking to help fix this. The Spatio-temporal Asset Catalog (SPAC) has had success promoting a standard for online access, which has been adopted by the Open Geospatial Consortium. This can help enable a standard directory structure which would allow indexing and a streamlined search of finished products, improving accessibility overall. Economics and the Imagery Industry The military will always have the newest and most advanced technologies in this space (pardon the pun). In fact, there are even restrictions on the quality of imagery that can be collected commercially (at least in the US) to avoid conflict with military interests. As time goes on, however, the technology may potentially be released to the commercial industry.
The history of GPS technology provides some context here. Although the technology was released to the public in the 1980s, the accuracy of the data provided was scrambled to prevent people from matching the US military’s resources. This scrambling was ended by President Bill Clinton in 2000, and allowed the commercial space to blossom. It is possible that military-grade satellite and aerial imagery technology will follow the same path, but for now there are too many unknowns to be sure.
There are three big names in the commercial satellite imagery business, Maxar, Airbus, and Planet. When it comes to government sponsored programs, in the US you will be looking at the Landsat series of satellites, whereas Europe’s counterpart project is Sentinel. Landsat 9 will launch September 16th. If you are looking to invest in the commercial imagery industry, Satelogic, Planet Labs, and Black Sky have all recently gone, or made announcements that they will be going public.
Although imagery is in high demand, there are not currently enough high-quality providers to stimulate the competition needed to drive down the price.
There are currently a couple hundred players in the space, and there likely will not be enough market pressure until that number reaches the thousands. Some will satisfy the high quality data needs, but many more will provide the lower quality resolution that is pretty standard today. Assuming the industry can inch towards standardization of how data products are presented (not necessarily how they are preprocessed), it will start to matter less and less where the imagery came from. As long as the end-use case can be reliably served, no one is going to be too concerned about what is going on behind the scenes, only what is on the ground. Synthetic Aperture Radar (SAR) The basic functionality of synthetic aperture radar is that a satellite moves along a linear course, taking a series of returns at a known interval. By understanding the satellite’s position in space, and the exact distance it and the returns have traveled, a number of triangulation measurements can be calculated. These measurements allow for the correction of images in a way that allows them to be combined to obtain resolution in the single digits of centimeters.
Optical imagery can only be successfully collected under certain conditions. Optical sensors are also passive sensors, this means they need the light of the sun in order to illuminate the study area, for this reason, they follow a sun synchronous orbit, generally passing over the equator at 10am and 2am every day. The thing about the equator is that this small band of space harbors a disproportionate share of the Earth’s population. Coupled with this, it is also covered in clouds 60-70% of the time. This means optimal conditions for the collection of optical imagery are rare in the place that it is needed most.
SAR is unique in that it does not care about any of the obstacles faced by optical imagery sensors. Since the data is ultimately collected by radar, rather than a camera - darkness, clouds, and haze all become issues of antiquity. This remarkable flexibility is why SAR is so groundbreaking.
It is, however, not without fault. Pre-processing of the data is still necessary, and this is time and resource consuming. In fact, it can be more resource consuming than with traditional forms of satellite imagery because SAR is so new on the scene. There has not been enough time to diagnose and standardize working around common issues. Speaking of standardization, on theme with the rest of the industry, there is not even a standard format for sharing and representing SAR data.
While there are still a number of obstacles in front of the imagery industry, it continues to hold great promise for helping us create a better and brighter future.