Research


Modeling Habitat and Upscaling TLS to ALS

Work with Washington DNR to quantify ground level vegetation structure with terrestrial lidar to then upscale the plot level metrics to a landscape level using airborne lidar. This work is focusing on identifying understory forest conditions that are critical habitat for Canada Lynx. Work is focused in north-central Washington state using metrics derived from single-point TLS scans.

https://doi.org/10.3390/rs15184434


Terrestrial Lidar for Vegetation Moisture Content

Many terrestrial lidar units use 1550nm lasers to derive distance information. This wavelength of EM radiation is highly absorbed by water. We have shown that the intensity returned from each laser pulse corresponds with the moisture content of the vegetation the pulse reflected off. This relationship can be used to quantify moisture contents across an area in near real-time. This information can inform fire behavior models and can be used to determine optimal conditions for prescribed burns.

https://doi.org/10.3390/rs15061482


Drone Multispectral Photogrametery for Fire Effects

Three-dimensional images can be created with drone photographs. This drone Digital Aerial Photogrammetry (dDAP also known as structure from motion) can produce accurate models of forest structure. This same process can be done using multispectral images beyond just RGB. With NIR images, 3D NDVI models can be created allowing for the quantification of fire effects at different height strata and the effective removal of upper canopy branches to look exclusively at the ground fire severity.


Riparian Self-Repair with the Removal of Cattle

Cattle grazing is a pervasive issue across the American west. In this study, we showed that passive restoration efforts alone can allow riparian systems to regenerate once cattle impacts are removed. Repeat photography was used as multiple sites within the Hart Mountain National Antelope Refuge.

https://link.springer.com/article/10.1007/s00267-014-0436-2

http://www.cof.orst.edu/cof/fr/research/hart/index.html

Rewilding a Mountain from Balance Media on Vimeo.


TLS Sampling of Forest Structure

Single-point terrestrial lidar scans can be used to generate effective metrics based on the depth and openness of forest stands. These metrics can quantify differences between forests of different ecosystems and disturbance events. Visibility polygons can also be created to quantify the area visible from the scanner position. These metrics have the potential to be used to quantify biomass, habitat quality, viewshed, and numerous other important ecological variables.

https://doi.org/10.3390/rs15010145


PUBLICATIONS

Peer-Reviewed Manuscripts

Batchelor, J.L., Hudak, A.T., Gould, P., Moskal, L.M., 2023. Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning. Remote Sensing 15, 4434. https://doi.org/10.3390/rs15184434

Batchelor, J.L.; Rowell, E.; Prichard, S.; Nemens, D.; Cronan, J.; Kennedy, M.C.; Moskal, L.M. Quantifying Forest Litter Fuel Moisture Content with Terrestrial Laser Scanning. Remote Sensing2023, 15, 1482, doi:10.3390/rs15061482.

Batchelor, J.L., Wilson, T.M., Olsen, M.J., Ripple, W.J., (2023). New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans. Remote Sensing 15, 145. https://doi.org/10.3390/rs15010145

Herzog, M.M., Hudak, A.T., Weise, D.R., Bradley, A.M., Tonkyn, R.G., Banach, C.A., Myers, T.L., Bright, B.C., Batchelor, J.L., Kato, A., (2022). Point cloud based mapping of understory shrub fuel distribution, estimation of fuel consumption and relationship to pyrolysis gas emissions on experimental prescribed burns. Fire 5, 118.

Kato, A., Moskal, L. M., Batchelor JL, Thau, D., & Hudak, A. T. (2019). Relationships between Satellite-Based Spectral Burned Ratios and Terrestrial Laser Scanning. Forests, 10(5), 444. doi.org/10.3390/f10050444

Batchelor JL, Ripple WJ, Wilson TM, Painter LE (2015) Restoration of Riparian Areas Following the Removal of Cattle in the Northwestern Great Basin. Environmental Management 55:930–942. doi.org/10.1007/s00267-014-0436-2

Manuscripts in Preparation

Batchelor JL, Hudak AT, Kato A, Moskal LM: Drone Based, Multispectral Photogrammetric Point Clouds to Classify Fire Severity at Differing Canopy Height Strata

Magazine Articles

Batchelor JL (2014) See the Forest for the Point Cloud: Tree Diameter Detection. LiDAR News Magazine. Vol4, No4.

Batchelor JL (2013) Cascading Importance: Wolves, Yellowstone, and the World Beyond. In: Trophic Cascades Program. http://www.cof.orst.edu/leopold/papers/CascadingImportance.pdf.