Progress 10/01/20 to 09/30/21
Outputs
Target Audience:The target audience was Welton with Alaska State Division of Forestry. Changes/Problems:The PI took another position, so we completed the field work in 2020. The data is being processed as part of another project, as these projects are related to each other. What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?This is the end of the project and there is nothing left to report.
Impacts
What was accomplished under these goals?
This year was part of a no-cost-extension due to COVID. The field work on the project was wrapped up in the prior year's reporting period. Additionally, this project's original PI took another position, so while the field work was completed, the analysis of the data is taking longer to complete. However, these data are being incorporated into an ongoing inventory project.
Publications
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Progress 03/18/19 to 09/30/21
Outputs
Target Audience:The target audiences of this project are medium- to large-forest land owners and managers who need forest inventory data. The technique is also useful to researchers who need more efficient data acquisition. Additionally, the Alaska State Division of Forestry utilizes and collects inventory data and will move in the direction of using UAVs to assist in field measurements. Changes/Problems:The original PI took a new job after the first year. In addition, COVID limited our ability to conduct fieldwork. As a result, we did not accomplish as much as we originally planned. The data will be analyzed and published as time permits. What opportunities for training and professional development has the project provided?A technician on the project received training on how to operate the new UAV. How have the results been disseminated to communities of interest?An article has been published in the Boreal Forest Newsletter published by UAF Cooperative Extension Service. The results were presented at two professional conferences (Society of American Forester National Convention and American GeophysicalUnion). What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
In the first year, Morimoto sampled two broadleaf stands (mix of birch and other species) and two black spruce stands in Caribou Poker Creeks Research Watershed, and two white spruce stands along Parks Highway. In broadleaf and white spruce stands, a 17.84 m radius circular plot and in black spruce stands, a 12.62 m radius circular plot were used. In each plot, distance and azimuth from the center of the plot, species, status (live or dead), crown position (open, dominant, co-dominant, intermediate, and shaded), diameter at breast height (DBH) and height are recorded for all stems larger than 2 cm in DBH. Morimoto flew the Phantom 4 Pro over the two broadleaf and two black spruce plots a few times after the field measurements with Matthew Robertson's help. The flight path was either single or double grid pattern with over 70% side and front overlaps. Flight altitude was between 40 and 80m. Ground control points (GCPs; large and reflective materials) were used to georeference the images. The images acquired by the drone were aligned using Structure from Motion algorithm in Agisoft Metahsape. The images obtained from the first few flights, especially from the broadleaf stands, had issues with aligning. This is likely due to a low flight altitude which made the images too similar between each other for the algorithm to detect similarities and differences. Georeferencing using GCPs was challenging due to low accuracy of GPS data at each GCPs. If GCPs were used to georeference, the 3D point cloud and orthomosaic were significantly distorted resulting in large errors. As a result, Morimoto aligned the images without GCPs in Agisoft and then georeferenced the 3D point cloud manually in ArcGIS. Canopy height models were produced in ArcGIS followed by individual crown detections using local maxima algorithm. Individual tree detections appeared to work well for black spruce stands but not so well for broadleaf stands because of simpler crown shape of black spruce compared to broadleaf. Better tree location data will help evaluate the accuracy and precision of tree detection and height estimate using photogrammetry. In the second year, we worked with ACUASI to attach new sensors to the UAV with improved capacity to estimate aboveground biomass and learn to fly the UAV. In fall 2020, Robertson flew UAV over 2 more plots on Tanana Valley State Forest about 30 miles southwest of Fairbanks. Alaska Division of Forestry conducted ground measurements of the trees on those plots. We have not completed processing and analyzing of the UAV data yet which will be done in the future. Additional flights were halted due to COVID restrictions.
Publications
- Type:
Other
Status:
Published
Year Published:
2020
Citation:
Miho Morimoto Welton (2020) UAF Research: Drone Use in the Boreal Forest. The Boreal Forest Newsletter Summer 2020. Editor Glen Holt. Published by University of Alaska Fairbanks Cooperative Extension Service.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Miho Morimoto (2019) REVOLUTIONIZE FOREST RESEARCH AND MANAGEMENT:FAST AND ACCURATE DATA COLLECTION USING UAV PHOTOGRAMMETRY. Society of American Forester National Convention. Louisville, Kentucky.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Miho Morimoto (2019) REVOLUTIONIZE FOREST RESEARCH AND MANAGEMENT:FAST AND ACCURATE DATA COLLECTION USING UAV PHOTOGRAMMETRY. American Geophysical Union. San Francisco, California
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Progress 10/01/19 to 09/30/20
Outputs
Target Audience:In this reporting period, we conducted additional UAV flights to increase replication for statistical analyses over long-term vegetation monitoring plots in collaboration with the State Forestry Division. The UAV sensors and flights will be used to quantify tree height, species composition, and tree density in the plots. We worked with the UAF UAV group ACUASI to build a new UAF with multi-sensor capacity, and we received training on the new UAV to develop new protocols for plot sampling. Changes/Problems:The original PI has taken a job with State Forestry, but we are continuing to collaborate with her and get her input on data collection and analysis. Additionally, COVID restricted our ability to meet all the goals in the prior year but we were able to conduct some flights and develop the new UAV. What opportunities for training and professional development has the project provided?A technician on the project received training on how to operate the new UAV. How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?We plan to fly a couple more plots and analyze the data and share the information with stakeholders. Once the data are analyzes, we plan to determine the next steps with this project to secure future funding. The original PI has taken a new position outside of the university.
Impacts
What was accomplished under these goals?
We focused on Goal 1 due to COVID restrictions limiting our research capacity over the past year. Under Goal 1, we worked with ACUASI to attach new sensors to the UAV with improved capacity to estimate aboveground biomass and learn to fly the new UAV.
Publications
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Progress 03/18/19 to 09/30/19
Outputs
Target Audience:
Nothing Reported
Changes/Problems:Morimoto encounteredtechnical challenges with building drone and equipping sensors on it. Morimoto originally planned to use a DJI S1000 octocopter. However, Morimoto ended up buying Phantom 4 Proto collect data for the reporting period. The DJI S1000 was given to Morimoto by another researcher at UAF who bought it about 5 years ago. This drone was not built at all and discontinued when given and the flight controller is outdated. As a result, Morimoto had issues with updating the firmware and such. Morimoto was not sure if she could get the drone going in time and collect data with it, so she bought much simpler drone (Phantom 4 Pro) which has a built-in camera. Morimoto also intended to collect LiDAR data using the DJI S1000. However, collecting useful LiDAR data turned out to be much more challenging than anticipated and required more parts. Phantom 4 Pro also can't carry other sensors than a built-in camera. As a result, Morimoto only collected aerial images during the reporting period. What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?Goal 1 -Morimoto plan to collect more field data and aerial images. Field data will be collected in new plots and existing plots. In existing plots, Morimoto will collect location data of each tree in the plots at a higher accuracy to be able to georeference photogrammetry outcomes at a higher accuracy and precision. Additional sample will increase the accuracy and precision of aboveground biomass estimations. Morimoto will use other algorithms, such as watershed delineation, for individual tree detections and try plot level aboveground biomass estimations. Orthomosaics and their RGB data will be used for species identification which will then be used for aboveground biomass estimations. Although Phantom 4 Pro isinexpensive and reliable to collect aerial images, it cannot carry other sensors than the built-in camera. A drone like Tarot X4 needs to be built but is inexpensive andhas a larger payload capacity allowing more flexibility. As a result, Morimoto plans to build a Tarot X4 with a help of Professor Michael Hatfield at UAF who is very knowledgeable with drones andhas built Tarot X4.With this drone, thermal, normalized difference vegetation index (NDVI) and LiDAR data will be collected to increase the accuracy of aboveground biomass estimation. Goal 2 - Morimoto will write proposals to secure funding. One project will focus on post-harvest regeneration and a use of UAV photogrammetry for regeneration survey. Another project will look at forest hydrology with UAV remote sensing technology (e.g. thermal images and NDVI). Goal 3 - Morimoto will attend and present at a UAV workshop held locally (pre-conference event of National Indian Timber Symposium). Morimoto will also create digital contents, such as videos and online articles, which shows how to use UAV remote sensing for forest management.
Impacts
What was accomplished under these goals?
In spring and early summer, Morimoto tried to build a drone (DJI S1000) and LiDAR system. However, due to technical difficulties, Morimoto decided to use Phantom 4 Pro which is much simpler to fly and collect aerial images. Morimoto sampled two broadleaf stands (mix of birch and other species) and two black spruce stands in Caribou Poker Creeks Research Watershed, and two white spruce stands along Parks Highway. In broadleaf and white spruce stands, a 17.84 m radius circular plot and in black spruce stands, a 12.62 m radius circular plot were used. In each plot, distance and azimuth from the center of the plot, species, status (live or dead), crown position (open, dominant, co-dominant, intermediate, and shaded), diameter at breast height (DBH) and height are recorded for all stems larger than 2 cm in DBH. Morimoto flew the Phantom 4 Pro over the two broadleaf and two black spruce plots a few times after the field measurements with Matthew Robertson's help. The flight path was either single or double grid pattern with over 70% side and front overlaps. Flight altitude was between 40 and 80m. Ground control points (GCPs; large and reflective materials) were used to georeference the images. The images acquired by the drone were aligned using Structure from Motion algorithm in Agisoft Metahsape.The images obtained from the first few flights, especially from the broadleaf stands, had issues with aligning. This is likely due to a low flight altitude which made the images too similar between each other for the algorithm to detect similarities and differences. Georeferencing using GCPs was challenging due to low accuracy of GPS data at each GCPs. If GCPs were used to georeference, the 3D point cloudand orthomosaic were significantly distorted resulting in large errors. As a result, Morimoto aligned the images without GCPs in Agisoft and then georeferenced the 3D point cloud manually in ArcGIS. Canopy height models were produced in ArcGIS followed by individual crown detections using local maxima algorithm. Individual tree detections appeared to work well for black spruce stands but not so well for broadleaf stands because of simpler crown shape of black spruce compared to broadleaf.Better tree location data will help evaluate the accuracy and precision of tree detection and height estimate using photogrammetry.
Publications
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