makepath attended the National State Geographic Information (NSGIC) Annual Conference in Portland, Oregon. The theme of the meeting this year was “Where Geospatial Collaboration Works”.
Leaders from the public and private sectors came together to discuss geospatial trends and issues, with a focus this year on Next Generation 911 (NG911), Spatial Data Infrastructure (SDI), 3D Hydrography (3DHP), and Machine Learning for geospatial data.
This post will provide:
- Highlight sessions from NSGIC 2022
- Resources to help you learn more about NSGIC
Connecting Open Source Tools and Machine Learning for Geospatial Applications
Dr. Dylan Stewart, Senior Machine Learning Engineer at makepath, presented makepath’s recent work on Open Source machine learning for change detection, as well as work done in collaboration with the Texas Natural Resources Information System (TNRIS) for georeferencing historical archives with deep learning.
The two main takeaways from the talk were:
1. How to connect ML to geospatial applications
2. Which Open Source ML tools can be leveraged to build pipelines for geospatial projects
Dr. Dylan Stewart shared educational resources available for machine learning projects, such as:
- Kaggle for competitions and notebooks
- TensorFlow and PyTorch for getting “into the weeds” of Deep Learning
Richard Wade (right) Deputy Executive Administrator of the Texas Natural Resources Information System at the Texas Water Development Board, co-presented.
Keynote: Former Oregon Governor Dr. John Kitzhaber
Dr. Kitzhaber highlighted his plan for a Common Operating Picture.
The Common Operating Picture would consolidate datasets that appear unrelated but are connected spatially.
This would enable regional, state, and federal levels of government to make policy decisions that incorporate social and environmental factors simultaneously.
State of Utah: Rating Systems to Improve Data Quality
Greg Bunce, Geospatial Data Coordinator for the Utah Geospatial Resource Center (UGRC) and Nathan Kota, Project and Staff Manager for the UGRC shared how they implemented a rating system to enhance data quality.
Data contained in the recently-renamed State Geographic Information Datasource (SGID) were rated on 9 metrics with a 0 – 3 weighted score.
- Business Systems
- Data Quality
- Foundational Layer
- System of Record
- Update Cycle
Ratings systems like this one will ensure future and continued data quality at the state level.
For more details on how the SGID is kept updated, check out this SGID Data Flow Diagram.
NSGIC helps coordinate the application of Geographic Information Systems (GIS) to better serve the nation.
Local, state, federal, and private sector partners work together to shape public policy.
Want to learn more about NSGIC? Here are resources to get you started.
3DEP for the Nation Information Hub
NSGIC 2022 Annual Conference Homepage
NSGIC 2022 Annual Conference Agenda
Get in Touch
To learn more about makepath’s involvement in NSGIC, check out our previous posts from the NSGIC 2021 Annual Conference and the NSGIC 2021 Midyear Meeting.
If you have any more questions about Dr. Dylan Stewart’s presentation or about the NSGIC conference, reach out on Twitter @makepathGIS or send us an email at email@example.com
- Machine Learning for Change Detection: Part 1
- GPU-Enhanced Geospatial Analysis
- Open Source Machine Learning Tools (Updated for 2023)
- Getting Started with Open Source (Updated for 2023)
- The History of Open Source GIS: An Interactive Infographic (Updated for 2023)
- Superpowered GIS: ESRI’s ArcGIS + Open Source Spatial Analysis Tools.
- Seniors at Risk: Using Spatial Analysis to Identify Pharmacy Deserts
- Open Source Spatial Analysis Tools for Python: A Quick Guide (Updated for 2022)