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

Here are the key tools mentioned:

1. **Kobo Toolbox**: An open-source tool used for data collection in humanitarian contexts. Kobo Toolbox allows for both quantitative and qualitative data collection and is operational offline, which is crucial in areas with limited internet connectivity. It supports geospatial data collection and can be used for needs assessments in settings like refugee camps.

2. **ODK Collect**: Similar to Kobo Toolbox, ODK Collect is an open-source mobile application used for field data collection. It is widely used in humanitarian efforts for its ease of use and the capability to work offline.

3. **QGIS**: A free and open-source geographic information system used for viewing, editing, and analyzing geospatial data. Hugo notes that QGIS is core for mapping and data analysis in humanitarian operations.

4. **Tableau and Power BI**: Business intelligence tools mentioned for their use in analyzing and visualizing data. These tools help in making data-driven decisions during humanitarian operations.

5. **Humanitarian Data Exchange (HDX)**: An open platform for sharing data across crises and organizations, which helps in avoiding duplication of efforts and enhances coordination among humanitarian actors.

6. **Humanitarian OpenStreetMap Team (HOT)**: Provides crowdsourced geospatial data which is extremely valuable in humanitarian settings for its accuracy and timeliness.

7. **Esri’s Living Atlas and other Esri tools**: While not open-source, Esri’s tools are sometimes used for their comprehensive geospatial data, particularly in natural disaster contexts like earthquakes.

8. **Humanitarian Spatial Data Center**: Managed by IMAP, this tool aggregates and processes data, providing access to data, analytics, and visualization tools all in one place. It has been particularly successful in deployments like Afghanistan.

This episode was sponsored by scribblemaps.com

https://youtu.be/CDkG9eS6H2M

Recommended Listening

Geospatial Support For Humanitarian Emergencies

A Self-Contained Environment For Open-Source Geospatial Tools

GGIS Offline And In The Field

The Business Of Web Maps

Peer to Peer Mapping And Digital Democracy

I am working on a new project over at QuickMapTools.com

and any feedback is really appreciated!

AI Autocomplete for QGIS

Brendan Ashworth the CTO and co-founder of https://buntinglabs.com/ focuses on integrating AI with QGIS, and today on the podcast we are talking about Autocomplete for vectorization.

Along the way Brendan will share with us why Bunting Labs chose to build this on top of QGIS, the Challenges in Map Digitization, what the development process was like and how this is different from tools like Segment Anything ( from meta )

Here's what we discussed:

1. Introduction to Bunting Labs: Get to know more about Brendan and Bunting Labs, whose mission revolves around enhancing QGIS with AI, especially focusing on automating vectorization processes.

2. AI Autocomplete for Vectorization: We explored the AI autocomplete feature developed by Bunting Labs that simplifies the vectorization of maps in QGIS, streamlining the digitization process for better efficiency.

3. Brendan’s Background and Motivation: Brendan shared his journey from a software engineer to a pivotal player in the geospatial sector, spurred by a project that showcased the potential of merging geospatial data with machine learning.

4. Why Choose QGIS?: Discover why Bunting Labs opted for QGIS over other GIS platforms, with an emphasis on its open-source nature and vibrant community ecosystem.

5. Challenges in Map Digitization: Our conversation covered the technical challenges involved in developing AI capable of accurately understanding and digitizing maps.

6. Iterative Development and Learning: Brendan highlighted the evolutionary process of their AI model, which has significantly improved from its early versions.

7. AI vs. Segment Anything: Brendan explained how their AI autocomplete tool differs from existing solutions like Segment Anything, particularly in handling specific digitizing challenges.

8. The Future of AI in Geospatial Data Analysis: We discussed potential future applications of AI in geospatial data, including automatic georeferencing and metadata extraction.

9. Privacy Considerations: We also touched on the importance of privacy in the development and deployment of AI technologies in geospatial data analysis.

10. Changing the Geospatial Landscape: Brendan shared his vision for using geospatial data not just to map the current world but to plan and improve future landscapes.

Sponsored by https://www.scribblemaps.com/

Recommended Listening

https://mapscaping.com/podcast/the-business-of-web-maps/

https://mapscaping.com/podcast/the-business-of-qgis-development/

https://mapscaping.com/podcast/qgis-offline-and-in-the-field/

https://mapscaping.com/podcast/computer-vision-and-geoai/

GNSS receivers - why precise positioning will not be coming to your phone any time soon

Igor is the CEO and cofounder of Emlid.com a company that started out making high-precision GNSS receivers in his kitchen and crowd-funded the first batch on Kickstarter.

But that was over ten years ago so today on the podcast Igor is going to tell us about the innovations that made this possible, give a great explanation of RTK and PPP and explain why we should expect to see high precision positioning on your phone any time soon.

Connect with Igor here: https://www.linkedin.com/in/igor-vereninov-52a73ab0/

Or visit https://emlid.com/

In this episode, we cover:

1. **Introduction to Emlid and its Focus**: Introduction to the company Emlid, its CEO and co-founder Igor, and their focus on high precision GNSS receivers and software designed for centimeter accuracy positioning.

1. **Startup Story and Crowdfunding**: The origin story of Emlid, starting from working with drones in university, the need for accurate maps, the initial challenges with high precision GPS technology, the development of their own GNSS receiver, and their successful crowdfunding campaign on Kickstarter.

1. **Innovations in GNSS Technology**: How Emlid managed to make high precision GNSS technology more affordable and accessible, the role of open-source software, and the technical innovations that allowed them to reduce the cost and size of GNSS receivers.

1. **Market and Technology Evolution**: The discussion on how the market for GNSS technology has evolved, including the impact of autonomous cars on the development and availability of multi-frequency GNSS chips, and how these advancements benefited broader applications beyond surveying and construction.

1. **Precision vs. Accuracy in GNSS**: An explanation of the difference between precision and accuracy in the context of GNSS technology, and the significance of each in various applications like drone mapping and volume measurements.

1. **RTK and PPP Explained**: A detailed explanation of Real-Time Kinematic (RTK) and Precise Point Positioning (PPP), including how they work, their applications, and their advantages and limitations.

1. **The Future of GNSS Technology**: Insights into the future directions of GNSS technology, including the challenges and potentials for achieving sub-centimeter accuracy with smartphones, the complementarity of GNSS and visual positioning systems, and the potential for GNSS technology to replace traditional surveying methods.

1. **Global Utility of GNSS**: A discussion on the importance of GNSS as a global utility, its indispensable role in modern technology and everyday life, and the potential consequences of GNSS failures.

More GNSS-related podcast episodes!

From GNSS to VPS

Reimaging GPS

How Google Knows Your Location

Past, Present and Future of GNSS

SBAS - A base station in the sky