ArcGIS

Sea Turtle Solutions: Using ArcGIS to Protect an Endangered Species

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Partnering with Quantam Spatial, Argis Solutions uses a JavaScript web application developed with the Leaflet library to minimize adverse impact to sea turtles during dredging. 

By Alyssa Grant 

Watching footage of baby sea turtles struggle out of their eggs and clumsily head for the ocean, you find yourself holding your breath, cheering for them as they face daunting odds of survival. An estimated one in 1000 to one in 10,000 hatchlings reach adulthood. There is even more to root for—some sea turtle species have incredibly long migrations that take them several years and thousands of miles. These statistics underline the challenges the sea turtle faces and why it is endangered. 

The Bureau of Ocean Energy Management (BOEM) has been working with scientists and the dredging industry to identify ways protect endangered sea turtles while still allowing the important work of dredging to continue. Dredging, a form of excavation, offers valuable environmental benefits: beach reclamation, flooding prevention, as well as contaminant remediation. The question to answer: How could dredging operations safely co-exist with minimal harm to sea turtles? Recognizing the value of a digital approach in answering this question, BOEM approached Quantum Spatial (QSI), partnering with Argis Solutions, to assist them in solving this unique problem.

A massive aggregation of data related to the turtles' behavior on the Atlantic coast was gathered from publicly available data sources and scientific turtle studies conducted by QSI. BOEM’s goal was to use this data to determine the best locations and times of year to dredge.

QSI and Argis Solutions worked together to standardize the data for use in the solution. Recognizing the adeptness of ArcGIS at communicating GIS data quickly and clearly, they created a JavaScript web-based application developed with the Leaflet library in which users could actually view the estimated population of any given species, in any given area, at any given time. Now BOEM is able to plan dredging projects based on data rather than using arbitrary dredging windows.

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It is a simple, intuitive solution that protects endangered sea turtle populations while allowing dredging companies to continue their work. Even better: Users with little experience operating technology of this kind can easily interpret the data, assess the risk, and adjust accordingly. Protecting endangered species like sea turtles will continue to be a  complex global challenge, but creative digital solutions like this one are a big step in the right direction.

DevSummit 2019 Talk: Augmented Reality Paired with Computer Vision

Argis Solutions’ CEO Brady Hustad presented on computer vision and augmented reality and how to use the Open Computer Vision Library with ArcGIS at Esri’s 2019 DevSummit. 

By Alyssa Grant 

At Esri’s 2019 DevSummit held in Palm Springs, CA on March 5-8, machine learning and ArcGIS REST JS created a big buzz. Another hot topic among DevSummit attendees was how developers are switching to 4X JavaScript libraries, which allows for more 3D capability and better functionality. This conference is the annual opportunity for Esri’s expert developers to share their technical knowledge with other software developers to help them write better code, build better systems, and create state-of-the-art apps that utilize ArcGIS mapping technology. While there are 8 rooms simultaneously hosting a full daily schedule of talks, there’s also a little time for dodgeball and beer! 

Argis Solutions’ CEO Brady Hustad had the honor of sharing how to integrate computer vision and Esri, explaining how to use the Open Computer Vision Library (Open CV) with ArcGIS. The presentation covered the technical setup of Open CV, some interesting tips on how to successfully connect it to ArcGIS, and coding tips that will help Open CV function properly for developers interested in using computer vision in their next project. Reflecting on his talk, Hustad remarked, “It was exciting to see how people are getting creative and how computer vision and machine learning are impacting the way they are doing business. People are seeing ways to go beyond doing maps and creating systems software.” 

Computer vision enables a computer to see something and make a decision that a human no longer has to make. For example, if hundreds of miles of roadways need to be analyzed for damage, computer vision could allow the computer to look through thousands of images and determine which images contain road damage. In robotics, computer vision has been one of the hardest problems for programmers to solve. Now with access to libraries such as OpenCV and some some finesse to connect it to ArcGIS, programmers are able to attempt to integrate this complex technology in ways that will shape the future of business. 

Big cities can be GPS black holes—their large volume of concrete and metal throws off GPS service and blocks signals. It can be difficult to get accurate geographic data. Using the rough satellite location of the mobile device, the computer can compare and compute location using two known points, giving improved accuracy in the city. Computer vision could enable the mobile device to detect an asset such as a manhole cover, storm drain, or hydrant. It just needs to be trained to see these known above-ground facilities, enabling the ability to generate accuracy where before none existed. 

Together, AR and computer vision could be used to document missing GIS assets. The computer could be programmed to be passively viewing in the background with the ability to notice an asset that is not documented in the ArcGIS data. The computer would then generate a basic record with spatial location. Its final step would be to ask the end user for further details, for instance: “This asset is not found in your data. Is this correct?” This would be an efficient way to quality check data. 

Computer vision could also be used to train a computer to look at an asset when a field worker is looking at it and then automatically pull up the right manual to work on that asset, streamlining field work. As AR visualizer improves with computer vision and image recognition this will all be possible. Computer vision is a game changer in improving accuracy and processes. 

How do we get there? Spatial referencing is required. Once you know where something is in space by way of dual cameras, you can extrapolate 3D space around it. Most mobile devices now come standard with dual cameras, paving the way for programming these functionalities. Argis Solutions has also made the code for Brady Hustad’s talk available on GITHub for developers interested in building projects using the OpenCV library and ArcGIS

What is needed to program computer vision? A knowledge of a modern programming language like Swift, C++, Java, Python, Kotlin, etc. A developer will also need to be savvy with mobile software like ARCOREARKitOpenCVEsri, etc. Lastly, a project using Open CV and ArcGIS will need decent software and high availability GIS data. If you would like tips and further information on programming, please visit GITHub, where our example is built in Android using Java and Esri’s ArcGIS Runtime SDK for Android.

ArcGIS and CAD Featured on Esri

ArcGIS and CAD Featured on Esri

Argis Solutions recent work with Silver Lake Construction Company has been highlighted in depth by Chris Andrews on Esri’s ArcGIS blog. Andrews recognizes the value augmented reality (AR) adds to GIS data, noting: 

 “As a product manager driving 3D, BIM, and other related software efforts at Esri, I’m always looking for applications of geospatial technology that can improve the lives of real users.  We get asked about AR a ton and whether through partner apps, such as Argis Solutions, or through development using our ArcGIS Runtime SDKs, it’s great to be able to report that real partners and customers are building AR applications that are transforming the experience of GIS in the field.  I expect to see much more like this in the future.”