- Author: Sean Hogan
- Author: Shane Feirer
IGIS was pleased to attend an excellent “Forest and Shrubland LiDAR Derived Products Workshop” jointly held by the California Natural Resources Agency (CNRA) and California Department of Conservation (DOC), on March 17th.
CNRA has a budget for supporting the development of useful/high value data products that can support forest and shrubland planning and management decisions, including for emergency response. In the interest of seeking feedback from experts and potential users of such data products across the state of California, the goal of this workshop was to gather information for prioritizing LiDAR derived products for fire, vegetation, biodiversity, hydrology, climate change, and public safety decisions in California's forests and shrublands.
The workshop began with an outstanding presentation by Dr. Nathaniel (Nate) Roth (DOC), which provided a brief introduction to LiDAR (light detection and ranging), and operation derived products of this technology. Kass Green and Mark Tukman, from Tukman Geospatial, then presented several excellent use case examples of LiDAR in California, including for: topographic and hydrologic mapping, fine scale vegetation mapping, forest health and management, and vegetation/fuel mapping for forest fire planning and assessing impacts. Next came another impressive presentation by David (DJ) Bandrowski from the Yurok Tribe Fisheries Department, which cited multiple examples of how LiDAR and aerial imagery have been used for management and restoration of forest ecosystems within the Klamath River Basin. These examples include for: Sediment flux, transport and change following dam removal, point cloud classifications of vegetation vs. bare ground, designing and modeling river systems for planning and assessment, and finally for construction projects.
The workshop concluded with a series of surveys, conducted in ESRI's Survey 123 application, to assess and prioritize the needs of the 179 attendees at the workshop, as a representative sample of prospective users. The results of these surveys will undoubtedly be used to steer the allocation of funds provided to CNRA by the California State Legislature to have the most efficient and valuable impacts possible.
A great thanks is owed to Dr. Nathaniel (Nate) Roth, and all the people at DOC and CNRA, for hosting this workshop, as well as the outstanding contributors from Tukman Geospatial and the Yurok Tribe.
Sean Hogan and Shane Feirer
University of California
Division of Agriculture and Natural Resources
Informatics and GIS Statewide Program
- Author: Glen Martin
Reprinted from California Magazine
Vista View at North Sonoma Mountain Regional Park // Detail of photo courtesy of harminder dhesi / flickr
When the Tubbs and Nuns wildfires exploded across Sonoma County in 2017, firefighters found they lacked critical information. Details on the vegetation, structures, and roads distributed across the landscape would have helped them better evacuate residents and allocate fire suppression resources.
It was only after the fires were extinguished that authorities realized much of that data was available—in the form of “veg maps.” Created by the Sonoma County Agricultural Preservation and Open Space District, Ag + Open Space as it's known locally, the maps deconstruct the terrain, depicting slope, aspect, soil type, hydrological qualities, buildings, roads and driveways—even the density of trees and brush—in exquisite detail.
Fine-scale vegetation map of Sonoma County // Image courtesy of Sonoma County Ag + Open Space
Such maps, officials realized, could be an immense asset when responding to wildfires. They could even serve a preventative purpose: helping “fireproof” undeveloped land by turning open space from a wildfire liability to a fire-prevention asset.
The maps are produced through LiDAR, or Light Detection and Ranging, which is kind of like radar, except it uses pulsed lasers emitted from aircraft or satellites instead of radio waves. The process yields precise 3-D maps of the earth's surface, detailing vegetation type and density. Researchers can look at a LiDAR map and evaluate “fuel ladders”—deadwood on the forest floor combined with the limbs and branches running from the ground to the tree tops—in any given stand of trees, down to resolutions of one centimeter.
“Using the maps for wildfire response wasn't our original intent,” says Karen Gaffney, a UC Berkeley alumna and the conservation planning manager for Ag + Open Space. Originally part of a project supported by the Sonoma County Water Agency and grants from NASA, the maps were created for land and wildlife conservation purposes. “But it just so happens much of that data is proving valuable for disaster planning.”
The maps are being used to flag the best fire evacuation routes and the sites most susceptible to contamination or erosion post-fire.
When it comes to wildfire, it's largely about fuel. While the forests of the West were once subject to regular low-intensity fires that produced large, well-spaced trees and light accumulations of deadwood, more than a century of overzealous wildfire suppression and rising temperatures from climate change have reversed this dynamic. Combine the current dense, thicket-like stands of trees and piles of dead branches with hot, dry autumn winds, and the result is wildfires of devastating ferocity—wildfires like the 2017 North Bay fires and the 2018 Camp Fire in the town of Paradise.
Like many areas, Sonoma County has been attempting to use “prescribed” fire and tree thinning to reduce fuel loads, says Gaffney. Shortly before the Nuns Fire ripped through Glen Ellen, an experimental prescribed burn conducted at a nearby ranch demonstrated the effectiveness of such efforts. The encroaching wildfire immolated nearby woodlands and structures, but dropped to low, flickering flames when it hit the prescribed burn zone. There simply wasn't the fuel to sustain it.
The message was clear to the county's disaster response planners: the more wildlands that can be burned under controlled conditions, the better.
The district's veg maps are now being used by county officials to identify candidate open spaces for thinning and prescribed fire, with prioritization going to the most vulnerable areas.
“In conjunction with our partners at Pepperwood Preserve and Tukman Geospatial, we've created fuel loading maps from our LiDAR data that identify areas where heavy ladder fuels are located close to structures,” says Gaffney, who declined to comment on specific sites. “And because we can map development footprints down to resolutions of one centimeter, we can even identify risks for individual buildings.”
Ladder fuels maps of Sonoma County // Image courtesy of Sonoma County Ag + Open Space
The maps are also being used to flag the best fire evacuation routes and the sites most susceptible to contamination or erosion post-fire.
“For example, we can determine if a [burned] structure that contained toxic materials is at significant risk of contaminating a nearby stream,” Gaffney says. “While the maps first responders and firefighters typically use show all the major and secondary roads, our data let us create maps that show the much smaller routes that could also be used for evacuation.”
The veg map approach to wildfire response and planning is gaining fans beyond the borders of Sonoma County.
“Marin County and San Mateo County have acquired LiDAR technology and are creating their own veg maps,” says Allison Schichtel, the conservation GIS coordinator for Ag + Open Space, “and Monterey and Santa Cruz Counties are looking into it. I did a presentation at a forestry and GIS workshop, and there were folks from [far] northern California and southern Oregon who wanted to know all about it. Interest is growing—kind of like an amoeba.”
- Author: Bryon J. Noel
First of all, Pearl Street Mall is just as lovely as I remember, but OMG it is so crowded, with so many new stores and chains. Still, good food, good views, hot weather, lovely walk.
Welcome to Day 2! http://neondataskills.org/data-institute-17/day2/
Our morning session focused on reproducibility and workflows with the great Naupaka Zimmerman. Remember the characteristics of reproducibility - organization, automation, documentation, and dissemination. We focused on organization, and spent an enjoyable hour sorting through an example messy directory of misc data files and code. The directory looked a bit like many of my directories. Lesson learned. We then moved to working with new data and git to reinforce yesterday's lessons. Git was super confusing to me 2 weeks ago, but now I think I love it. We also went back and forth between Jupyter and python stand alone scripts, and abstracted variables, and lo and behold I got my script to run.
The afternoon focused on Lidar (yay!) and prior to coding we talked about discrete and waveform data and collection, and the opentopography (http://www.opentopography.org/) project with Benjamin Gross. The opentopography talk was really interesting. They are not just a data distributor any more, they also provide a HPC framework (mostly TauDEM for now) on their servers at SDSC (http://www.sdsc.edu/). They are going to roll out a user-initiated HPC functionality soon, so stay tuned for their new "pluggable assets" program. This is well worth checking into. We also spent some time live coding with Python with Bridget Hass working with a CHM from the SERC site in California, and had a nerve-wracking code challenge to wrap up the day.
Fun additional take-home messages/resources:
- ISO International standard for dates = YYYY-MM-DD
- Missing values in R = NA, in Python = -9999
- For cleaning messy data - check out OpenRefine - a FOS tool for cleaning messy data http://openrefine.org/
- Excel is cray-cray, best practices for spreadsheets: http://www.datacarpentry.org/spreadsheet-ecology-lesson/
- Morpho (from DataOne) to enter metadata: https://www.dataone.org/software-tools/morpho
- Pay attention to file size with your git repositories - check out: https://git-lfs.github.com/. Git is good for things you do with your hands (like code), not for large data.
- Funny how many food metaphors are used in tech teaching: APIs as a menu in a restaurant; git add vs git commit as a grocery cart before and after purchase; finding GIS data is sometimes like shopping for ingredients in a specialty grocery store (that one is mine)...
- Markdown renderer: http://dillinger.io/
- MIT License, like Creative Commons for code: https://opensource.org/licenses/MIT
- "Jupyter" means it runs with Julia, Python & R, who knew?
- There is a new project called "Feather" that allows compatibility between python and R: https://blog.rstudio.org/2016/03/29/feather/
- All the NEON airborne data can be found here: http://www.neonscience.org/data/airborne-data
- Information on the TIFF specification and TIFF tags here: http://awaresystems.be/, however their TIFF Tag Viewer is only for windows.
Thanks for everyone today! Megan Jones (our fearless leader), Naupaka Zimmerman (Reproducibility), Tristan Goulden (Discrete Lidar), Keith Krause (Waveform Lidar), Benjamin Gross (OpenTopography), Bridget Hass (coding lidar products).
Our home for the week
First of all, Pearl Street Mall is just as lovely as I remember, but OMG it is so crowded, with so many new stores and chains. Still, good food, good views, hot weather, lovely walk.
Welcome to Day 2! http://neondataskills.org/data-institute-17/day2/
Our morning session focused on reproducibility and workflows with the great Naupaka Zimmerman. Remember the characteristics of reproducibility - organization, automation, documentation, and dissemination. We focused on organization, and spent an enjoyable hour sorting through an example messy directory of misc data files and code. The directory looked a bit like many of my directories. Lesson learned. We then moved to working with new data and git to reinforce yesterday's lessons. Git was super confusing to me 2 weeks ago, but now I think I love it. We also went back and forth between Jupyter and python stand alone scripts, and abstracted variables, and lo and behold I got my script to run.
The afternoon focused on Lidar (yay!) and prior to coding we talked about discrete and waveform data and collection, and the opentopography (http://www.opentopography.org/) project with Benjamin Gross. The opentopography talk was really interesting. They are not just a data distributor any more, they also provide a HPC framework (mostly TauDEM for now) on their servers at SDSC (http://www.sdsc.edu/). They are going to roll out a user-initiated HPC functionality soon, so stay tuned for their new "pluggable assets" program. This is well worth checking into. We also spent some time live coding with Python with Bridget Hass working with a CHM from the SERC site in California, and had a nerve-wracking code challenge to wrap up the day.
Fun additional take-home messages/resources:
- ISO International standard for dates = YYYY-MM-DD
- Missing values in R = NA, in Python = -9999
- For cleaning messy data - check out OpenRefine - a FOS tool for cleaning messy data http://openrefine.org/
- Excel is cray-cray, best practices for spreadsheets: http://www.datacarpentry.org/spreadsheet-ecology-lesson/
- Morpho (from DataOne) to enter metadata: https://www.dataone.org/software-tools/morpho
- Pay attention to file size with your git repositories - check out: https://git-lfs.github.com/. Git is good for things you do with your hands (like code), not for large data.
- Funny how many food metaphors are used in tech teaching: APIs as a menu in a restaurant; git add vs git commit as a grocery cart before and after purchase; finding GIS data is sometimes like shopping for ingredients in a specialty grocery store (that one is mine)...
- Markdown renderer: http://dillinger.io/
- MIT License, like Creative Commons for code: https://opensource.org/licenses/MIT
- "Jupyter" means it runs with Julia, Python & R, who knew?
- There is a new project called "Feather" that allows compatibility between python and R: https://blog.rstudio.org/2016/03/29/feather/
- All the NEON airborne data can be found here: http://www.neonscience.org/data/airborne-data
- Information on the TIFF specification and TIFF tags here: http://awaresystems.be/, however their TIFF Tag Viewer is only for windows.
Thanks for everyone today! Megan Jones (our fearless leader), Naupaka Zimmerman (Reproducibility), Tristan Goulden (Discrete Lidar), Keith Krause (Waveform Lidar), Benjamin Gross (OpenTopography), Bridget Hass (coding lidar products).
Our home for the week
- Author: Bryon J. Noel
Our third GIF Spatial Data Science Bootcamp has wrapped! We had an excellent 3 days with wonderful people from a range of locations and professions and learned about open tools for managing, analyzing and visualizing spatial data. This year's bootcamp was sponsored by IGIS and GreenValley Intl (a Lidar and drone company). GreenValley showcased their new lidar backpack, and we took an excellent shot of the bootcamp participants. What is Paparazzi in lidar-speak? Lidarazzi?
Here is our spin: We live in a world where the importance and availability of spatial data are ever increasing. Today’s marketplace needs trained spatial data analysts who can:
- compile disparate data from multiple sources;
- use easily available and open technology for robust data analysis, sharing, and publication;
- apply core spatial analysis methods;
- and utilize visualization tools to communicate with project managers, the public, and other stakeholders.
At the Spatial Data Science Bootcamp we learn how to integrate modern Spatial Data Science techniques into your workflow through hands-on exercises that leverage today's latest open source and cloud/web-based technologies.