Josh von Nonn
Josh von Nonn is a Geographer with the Western Geographic Science Center in Moffett Field, CA.
Josh’s current research examines post-fire ecological recovery and invasive species management through remote sensing techniques, often scaling very high resolution UAS imagery to satellite. Josh designs free and open-source software workflows for the geospatial analyses to promote open science and reproducibility.
Professional Experience
2022 - Current: Geographer, Western Geographic Science Center, U.S. Geological Survey
Education and Certifications
M.S. 2023 - Geographic Information Science, San Francisco State University
B.S. 2021 - Environmental Science, San Francisco State University
B.A. 2021 - Geography, San Francisco State University
FAA Part 107 license
A-450 Certification
Science and Products
Remote Sensing of Invasive Annual Grasses -- Greater Yellowstone Ecosystem
Exotic annual grasses such as cheatgrass ( Bromus tectorum) have heavily invaded portions of the western United States, rapidly degrading habitats and increasing wildfire risk. Cheatgrass and other ESIs (desert alyssum [Alyssum desertorum], and annual wheatgrass [Eremopyrum triticeum]) are an emerging threat to the Greater Yellowstone Ecosystem (GYE); climatic changes including earlier snowmelt...
Characterizing high-resolution soil burn severity, erosion risk, and recovery using Uncrewed Aerial Systems (UAS)
The western United States is experiencing severe wildfires whose observed impacts, including post-wildfire floods and debris flows, appear to be increasing over time.
Remote Sensing of Invasive Annual Grasses
One of the major ecological consequences of increasing global connectivity is the introduction, establishment, and spread of non-native species into new ecosystems. The rate and extent of biological invasions continues to increase globally, often at considerable environmental and economic costs. Once established, non-native species can transform ecosystems, complicating land management decision...
Data for: UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape Data for: UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape
We mapped cheatgrass at different scales in the Greater Yellowstone Ecosystem using 10-m Sentinel-2 imagery, 3-m PlanetScope, and 10-cm Unoccupied Aerial Systems (UAS) imagery. We compared these maps to field-collected data to address 1) variation in seasonal phenological signals of native and cheatgrass patches, 2) the influence of scale on detectability and map accuracy across our...
High-resolution digital surface model (DSM) and true-color image orthomosaic collected by Uncrewed Aircraft System (UAS) within the Los Planes Watershed, Baja California Sur, Mexico, 2024 High-resolution digital surface model (DSM) and true-color image orthomosaic collected by Uncrewed Aircraft System (UAS) within the Los Planes Watershed, Baja California Sur, Mexico, 2024
These data are structure from motion products from UAS providing high topographical and true-color imagery detail over a subregion within the Los Planes Watershed in La Paz, Mexico. This is part of an ongoing research partnership with the U.S. Geological Survey (Aridland Water Harvesting Study), U.S. Water Partnership (USWP), and Innovaciones Alumbra to monitor eco-hydrological feedbacks...
UAS lidar Digital Terrain Model of a southern subset in Palo Alto Battlefield National Historic Park, Texas, March 2024 UAS lidar Digital Terrain Model of a southern subset in Palo Alto Battlefield National Historic Park, Texas, March 2024
This is a 4cm resolution Digital Terrain Model (DTM) raster derived from an Unoccupied Aerial System (UAS; a DJI M600 equipped with a YellowScan Mapper+), lidar collected on March 26, 2024 by the U.S. Geological Survey (USGS) National Uncrewed Systems Office (NUSO). It covers a southern portion of Palo Alto Battlefield National Historic Park in the Lower Rio Grande Valley of South Texas.
UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape
Context Cheatgrass (Bromus tectorum L.) is a problem across the western United States, where it outcompetes and replaces native grass species, alters habitats, and increases the risk of wildfires. Cheatgrass greens up earlier in the growing season compared to native grasses, making it classifiable with multi-temporal and multi-spectral remote sensing. Objectives We mapped cheatgrass at...
Authors
Jason Kreitler, Joshua Von Nonn, Seth Munson, Alex Zaideman, Steven Bekedam, Ann Rodman, Miguel Villarreal
The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions
Context The relationship between slope and terrestrial animal locomotion is key to landscape ecology but underexplored across species. This is partly due to a lack of scalable methodology that applies to a diversity of wildlife. Objectives This study investigates the slope-speed relationship for two species, Texas tortoise (Gopherus berlandieri) and pronghorn (Antilocapra americana)...
Authors
Samuel Chambers, Joshua Von Nonn, Matthew Burgess, Lance R. Brady, Jeffrey Bracewell, Daniel A. Guerra, Miguel Villarreal
Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities
Context Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial...
Authors
Miguel Villarreal, Tara B.B. Bishop, Temuulen Ts. Sankey, William Smith, Matthew Burgess, Trevor Caughlin, Jeffrey Gillan, Caroline Havrilla, Tao Huang, Raymond LeBeau, Cindy L. Norton, Joel B. Sankey, Victoria Scholl, Joshua Von Nonn, Erika Yao
An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management
Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post...
Authors
Joshua Von Nonn, Miguel Villarreal, Leonhard Blesius, Jerry Davis, Skye Corbett
UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python
Classifying UAS soil burn severity and scaling up to satellite with Python
Science and Products
Remote Sensing of Invasive Annual Grasses -- Greater Yellowstone Ecosystem
Exotic annual grasses such as cheatgrass ( Bromus tectorum) have heavily invaded portions of the western United States, rapidly degrading habitats and increasing wildfire risk. Cheatgrass and other ESIs (desert alyssum [Alyssum desertorum], and annual wheatgrass [Eremopyrum triticeum]) are an emerging threat to the Greater Yellowstone Ecosystem (GYE); climatic changes including earlier snowmelt...
Characterizing high-resolution soil burn severity, erosion risk, and recovery using Uncrewed Aerial Systems (UAS)
The western United States is experiencing severe wildfires whose observed impacts, including post-wildfire floods and debris flows, appear to be increasing over time.
Remote Sensing of Invasive Annual Grasses
One of the major ecological consequences of increasing global connectivity is the introduction, establishment, and spread of non-native species into new ecosystems. The rate and extent of biological invasions continues to increase globally, often at considerable environmental and economic costs. Once established, non-native species can transform ecosystems, complicating land management decision...
Data for: UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape Data for: UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape
We mapped cheatgrass at different scales in the Greater Yellowstone Ecosystem using 10-m Sentinel-2 imagery, 3-m PlanetScope, and 10-cm Unoccupied Aerial Systems (UAS) imagery. We compared these maps to field-collected data to address 1) variation in seasonal phenological signals of native and cheatgrass patches, 2) the influence of scale on detectability and map accuracy across our...
High-resolution digital surface model (DSM) and true-color image orthomosaic collected by Uncrewed Aircraft System (UAS) within the Los Planes Watershed, Baja California Sur, Mexico, 2024 High-resolution digital surface model (DSM) and true-color image orthomosaic collected by Uncrewed Aircraft System (UAS) within the Los Planes Watershed, Baja California Sur, Mexico, 2024
These data are structure from motion products from UAS providing high topographical and true-color imagery detail over a subregion within the Los Planes Watershed in La Paz, Mexico. This is part of an ongoing research partnership with the U.S. Geological Survey (Aridland Water Harvesting Study), U.S. Water Partnership (USWP), and Innovaciones Alumbra to monitor eco-hydrological feedbacks...
UAS lidar Digital Terrain Model of a southern subset in Palo Alto Battlefield National Historic Park, Texas, March 2024 UAS lidar Digital Terrain Model of a southern subset in Palo Alto Battlefield National Historic Park, Texas, March 2024
This is a 4cm resolution Digital Terrain Model (DTM) raster derived from an Unoccupied Aerial System (UAS; a DJI M600 equipped with a YellowScan Mapper+), lidar collected on March 26, 2024 by the U.S. Geological Survey (USGS) National Uncrewed Systems Office (NUSO). It covers a southern portion of Palo Alto Battlefield National Historic Park in the Lower Rio Grande Valley of South Texas.
UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape
Context Cheatgrass (Bromus tectorum L.) is a problem across the western United States, where it outcompetes and replaces native grass species, alters habitats, and increases the risk of wildfires. Cheatgrass greens up earlier in the growing season compared to native grasses, making it classifiable with multi-temporal and multi-spectral remote sensing. Objectives We mapped cheatgrass at...
Authors
Jason Kreitler, Joshua Von Nonn, Seth Munson, Alex Zaideman, Steven Bekedam, Ann Rodman, Miguel Villarreal
The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions The tortoise and the antilocaprid: Adapting GPS tracking and terrain data to model wildlife walking functions
Context The relationship between slope and terrestrial animal locomotion is key to landscape ecology but underexplored across species. This is partly due to a lack of scalable methodology that applies to a diversity of wildlife. Objectives This study investigates the slope-speed relationship for two species, Texas tortoise (Gopherus berlandieri) and pronghorn (Antilocapra americana)...
Authors
Samuel Chambers, Joshua Von Nonn, Matthew Burgess, Lance R. Brady, Jeffrey Bracewell, Daniel A. Guerra, Miguel Villarreal
Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities
Context Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial...
Authors
Miguel Villarreal, Tara B.B. Bishop, Temuulen Ts. Sankey, William Smith, Matthew Burgess, Trevor Caughlin, Jeffrey Gillan, Caroline Havrilla, Tao Huang, Raymond LeBeau, Cindy L. Norton, Joel B. Sankey, Victoria Scholl, Joshua Von Nonn, Erika Yao
An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management
Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post...
Authors
Joshua Von Nonn, Miguel Villarreal, Leonhard Blesius, Jerry Davis, Skye Corbett
UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python
Classifying UAS soil burn severity and scaling up to satellite with Python