Source: UNIV OF IDAHO submitted to
ACQUISITION OF A UAS-MOUNTED AERIAL LIDAR SYSTEM TO SUPPORT AGRICULTURAL AND NATURAL-RESOURCES RESEARCH.
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
OTHER GRANTS
Reporting Frequency
Annual
Accession No.
1031484
Grant No.
2023-70410-41214
Cumulative Award Amt.
$123,163.00
Proposal No.
2023-05393
Multistate No.
(N/A)
Project Start Date
Sep 1, 2023
Project End Date
Aug 31, 2027
Grant Year
2023
Program Code
[EGP]- Equipment Grants Program
Project Director
Karl, J. W.
Recipient Organization
UNIV OF IDAHO
875 PERIMETER DRIVE
MOSCOW,ID 83844-9803
Performing Department
(N/A)
Non Technical Summary
High-resolution remotely-sensed elevation measurements are critical inputs to addressing many pressing questions in sustainable agriculture and natural resource management. Light detection and ranging (Lidar) is an active sensor technology that measures distance with laser pulses, and because it can penetrate plant canopies, is commonly used to measure ground elevation and plant canopy height. Over the past decade, Lidar sensors have become smaller and lighter, enabling deployment via unmanned aerial systems (UAS, i.e., drones) for capturing on-demand, high-resolution elevation and height data. The University of Idaho (UI) is requesting an airborne Lidar system mounted to UAS to enhance institutional capabilities of UI researchers and research training. Specifically, we propose to purchase a YellowScan Mapper+ Lidar sensor mounted to a Freefly Systems AltaX UAS. The Lidar system will be used to further UI's research and teaching in precision agriculture, precision forestry, rangeland ecology and management, and hydrology. This Lidar system will be housed in and maintained by the UI Drone Lab, implemented in a selected set of ongoing or new projects, and available to faculty in the UI College of Agricultural and Life Sciences, College of Natural Resources, and College of Engineering for research and teaching. A UAS Lidar system will increase the UI's ability to compete for large, cross-disciplinary extramural grants and conduct high-impact research in sustainable agriculture and natural resource management. The UI does not own an aerial Lidar system, and must contract aerial Lidar data acquisitions, which is costly, inhibits flexibility and discourages projects needing frequent data acquisition.
Animal Health Component
50%
Research Effort Categories
Basic
25%
Applied
50%
Developmental
25%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1210799107020%
1220699310020%
1230699310020%
1120320205020%
2041599106020%
Knowledge Area
204 - Plant Product Quality and Utility (Preharvest); 112 - Watershed Protection and Management; 122 - Management and Control of Forest and Range Fires; 121 - Management of Range Resources; 123 - Management and Sustainability of Forest Resources;

Subject Of Investigation
0320 - Watersheds; 0799 - Rangelands and grasslands, general; 1599 - Grain crops, general/other; 0699 - Trees, forests, and forest products, general;

Field Of Science
2050 - Hydrology; 1060 - Biology (whole systems); 1070 - Ecology; 3100 - Management;
Goals / Objectives
The University of Idaho (UI) is requesting an airborne Lidar system mounted to an unpiloted-aerial system (UAS, i.e., drone) to facilitate many research projects requiring precise, high-resolution elevation measurements.We propose to purchase an aerial Lidar system consisting of a Lidar sensor mounted to an UAS (i.e., UAS Lidar system). Specifically, we propose to acquire a YellowScan Mapper+ Lidar sensor (https://www.YellowScan-lidar.com/products/mapper-plus/)integrated with a Freefly Systems AltaX UAS (https://freeflysystems.com/alta-x), a high-performance quad-rotor UAS designed for high reliability and heavy-lift applications.Our proposal consists of four main tasks to be completed over the project period.The first task is purchasing and testing the UAS Lidar system. Acquisition of the UAS Lidar system from Frontier Precision, Inc. will occur as soon as feasible in Fall 2023.The second task is training the Project Team (and associated graduate students) on the use of the UAS Lidar system and processing of the data. First, the Project Team will be trained by the vendor in use of the UAS Lidar system and data processing at a two-day training provided by Frontier Precision in Spring 2024.The third task will be to implement the UAS Lidar system in a selected set of ongoing or new projects, as described above in section B of the proposal.The final task is documenting the use and impacts of the UAS Lidar system on enhancing UI's research, teaching, and Extension activities.
Project Methods
Overall responsibility for the completion of the proposed project will be the PD, J. Karl. Co-PIs E. Brooks, J. Eitel, P. Gessler, J. Karl, R. Keefe, L. Kobziar, A. Smith, J. Ryu, O. Walsh, E. Winford will constitute the Project Team and be responsible for coordinating use of the UAS Lidar system. The Project Team will meet at least once per spring and fall semesters throughout the project period to discuss the progress of implementing the above timeline and review and resolve any issues that arise. At the first meeting, the Project Team will formalize the guidelines for use of the sensor, minimum training and qualifications, scheduling, and maintenance. Additionally, the Project Team will receive a report from the UI Drone Lab at each meeting on the status of the UAS Lidar system, usage since the last meeting, and any performed maintenance or repairs. On an ongoing basis, the Project Team will also review scheduling requests for use of the UAS Lidar system and will prioritize use to projects that: 1) have established funding, 2) demonstrate clear research objectives and methods, 3) involve strong multi-disciplinary collaborations or external partners, and 4) show the potential to contribute to agricultural and natural resource science and management. Projects will be scheduled on the Drone Lab's shared calendar equipment on a first-come, first-served basis. The Project Team will work with projects to find flexibility to accommodate as many projects as possible. Projects without an experienced pilot trained in using the UAS Lidar system will be asked to provide funding to cover salary and travel expenses for a qualified pilot identified by the Project Team.Our proposal consists of four main tasks to be completed over the project period. The first task is purchasing and testing the UAS Lidar system. Acquisition of the UAS Lidar system from Frontier Precision, Inc. will occur as soon as feasible in Fall 2023. Frontier Precision is an authorized distributor for YellowScan and Freefly Systems with offices in Boise and Jerome, Idaho. The UI Drone Lab will cover the costs of the required registration of the UAS Lidar system with the FAA, and the UI's Office of Risk will provide, at no cost to this project, liability insurance required by the State of Idaho.The second task is training the Project Team (and associated graduate students) on the use of the UAS Lidar system and processing of the data. First, the Project Team will be trained by the vendor in use of the UAS Lidar system and data processing at a two-day training provided by Frontier Precision in Spring 2024. The costs of the one-time vendor-provided training will be paid for through this grant. The Project Team will, in turn, train other UI faculty, staff, and students. Training will occur at the UI main campus in Moscow, Idaho for the Project Team. Subsequent UI trainings beginning in Spring 2024 will be completed through a combination of regular workshops, training videos, and checklists and will be provided to UI faculty, staff, and students at no cost for the duration of this project. Any UI faculty or student interested in using the UAS Lidar system must complete an initial training and/or use a trained and experienced operator. An additional component of this task will be to develop teaching modules using the UAS Lidar system for existing UI courses taught by the proposal team (e.g., ASM 305 precision agriculture, FOR 404 Lidar fundamentals, NRS 478/578 Lidar analysis, REM 476 drone operations) that expose students to collecting, processing, and analyzing Lidar data. Development and initial implementation of the UAS Lidar system in UI teaching efforts will commence in Fall 2024.The third task will be to implement the UAS Lidar system in a selected set of ongoing or new projects, as described above in section B. In addition to the collaborations described above, we will seek opportunities to engage the Lidar system in other cooperative projects in Idaho (e.g., Boise State University) and regionally (e.g., USDA-ARS, Washington State University). We anticipate the sensor being ready to deploy on projects starting in summer of 2024. Use of the UAS Lidar system on the various projects will be coordinated through the UI Drone Lab according to the guidelines set by the Project Team. Any use of the UAS Lidar system must be scheduled in advance through the UI Drone Lab's shared equipment calendar and approved by the Project Team. Users of the UAS Lidar system will be required to secure flight authorization from the UI's UAS-committee (which includes verification of FAA remote pilot license, landowner/manager approval, and flight hazards assessment) and provide documentation of flight records (e.g., number of take-offs, flight duration, battery health, incidents or flight anomalies) and research objectives, outcomes, and data availability. Research projects associated with this grant (described in section B) will not be charged for use of the UAS Lidar system during the grant but will request and schedule use following the procedures set by the Project Team. Other research projects and teaching uses of the UAS Lidar system will be subject to the UI Drone Lab's service center fees described below.The final task is documenting the use and impacts of the UAS Lidar system on enhancing UI's research, teaching, and Extension activities. This task will consist of direct measurements of system use and measures of impact, such as publications, new collaborations within and external to UI, secured extramural funding, and Extension programming.For this EGP proposal, we identified eight projects that can immediately use the UAS Lidar system. We anticipate interest in using the UAS Lidar system to be high based on the number of projects that currently contract for Lidar services and inquiries to the UI Drone Lab. We expect the UAS Lidar system to be used in approximately 12 projects per year in addition to the class uses described above. We will schedule UAS Lidar system maintenance and downtime for low-demand times when possible.To attract new users, we will promote the UAS Lidar system through the UI Office of Research and Economic Development (ORED), the UI Drone Lab website, and through the colleges of participating faculty. The UI Drone Lab hosts an annual UI Drone Summit, where we will feature the UAS Lidar system and host a workshop introducing the UAS Lidar system and opportunities for its use. Finally, the Project Team will initiate a Lidar sensor access award program and solicit applications for a limited number of flight days per year for new, innovative, or student-led research projects to use the UAS Lidar system without charge. Costs for this program will be offset by Drone Lab service fees or by participating Colleges at UI.

Progress 09/01/23 to 08/31/24

Outputs
Target Audience:This project has a primary and secondary target audience. The primary audience is the faculty and graduate students who would potentially use the drone-mounted lidar system. We have reached this target audience through direct contacts, announcements through UI internal email newsletters. Our secondary audience consists of partners, collaborators, and funders whose projects or research may benefit from access to the drone-collected lidar data. We have reached this secondary audience through our contacts with UI faculty. It has been surprising to us how quickly word has spread that we have the drone lidar system, and the number of requests we are receiving to use it in research projects and teaching. Changes/Problems:We have not experienced any changes or problems to date. What opportunities for training and professional development has the project provided?Since acquisition of the drone lidar system, we have had several formal and informal opportunities for trianing and professional development (excluding the vendor-provided training in June). On August 23, 2024, we hosted a drone lidar workshop at the University of Idaho's Parker Farm in Moscow, ID that was attended by 11 UI faculty and graduate students. This workshop was intended to train participants in the safe operation of the drone lidar system and post-processing of the raw data into lidar data products. The training included information and checklists for equipment needs, lidar mission planning, and safe (and legal) operation of the drone. Workshop participants each had a opportunity to fly the Freefly Astro drone to practice take-offs, basic maneuvers, and landings. Workshop participants then were able to perform a lidar data collection over a portion of the Farm. Following the data collection, we worked through how to process the raw data from the sensor and the GNSS base station to produce and evaluate the accuracy of the lidar data products. Additionally, we were able to collect drone lidar data to support a class exercise for the UAS Remote Sensing (REM 475) class. The lab for this class involves exploring and classifying the lidar point clouds and aligning the lidar data with other drone-collected data for UI's Parker Farm. A video walkthrough of this class exercise was posted to YouTube (https://youtu.be/QLqpbzZnp9s) and as of 11/25/24 has received almost 850 views. Training materials developed to support the drone lidar system as well as class materials for REM 475 have been posted on the Drone Lab's website (https://uidronelab.org).? How have the results been disseminated to communities of interest?To date, results of this project are primarily: 1) knowledge of the drone lidar system and its availability, 2)training materials developed to support the operation of the system and use of data it produces, and 2) distribution of drone lidar datasets. Knowledge of the drone lidar system with UI faculty and graduate students has been accomplished through direct contacts and announcements in UI internal email communications. Training materials are likewise also directly disseminated but also published on the Drone Lab's website and YouTube. Dissemination of drone lidar datasets is challenging due to their size. To date, we have disseminated datasets directly through UI file sharing links. However, we are exploring other options for easier (and where appropriate public) data distribution. As the project progresses and research projects that use the system reach completion and produce publications, these publications and other outputs will be distributed through the PI's academic departments, via the Idaho Forestry Cooperative and the Rangeland Center, and via the DroneLab website. What do you plan to do during the next reporting period to accomplish the goals?Most importantly, over the next reporting period, we will be collecting a lot of lidar data! Our main goal is to ensure we collect data for all of the projects listed in the original proposal. We are also partnering with other UI faculty to write drone lidar into new proposals. We are planninglidar data collection for new projects such as: 1) inventory of forest monitoring network sites on the UI Experimental Forest, 2) evaluation of riparian restoration projects on BLM lands in southern Idaho, and 3) evaluation of long-term burn severity and soil erosion following the 2024 wildfire at UI's Rinker Rock Creek Ranch. We are already scheduling out use of the drone lidar system for 2024. Based on the interest in the lidar system, and using available funds from other sources, we have hired a manager for the Drone Lab who will coordinate the scheduling and use of the drone lidar system as well as training and certification of all pilots/operators of the system. We will host additional trainings on the drone lidar system. Our goal is to host at least one drone lidar training per semester over the next year. Depending on demand, we may offer additional trainings or supplemental trainings on specific topics. Finally, we will continue to improve and implement techniques and technologies for documenting and sharing the drone lidar data we generate. This will include better project metadata and more robust options for disseminating the data to collaborators outside UI or the public.

Impacts
What was accomplished under these goals? Task 1 for this project was completed this spring. The drone-mounted lidar system was purchased from in April 2024 and assembled by Frontier Precision and shipped to uson May 21, 2024. Upon reciept of the drone and verification that all parts arrived in good condition, we performed initial test flights with the drone to ensure operation and begin familiarizing us with the new UAS platform. Task two consisted of training provided to the project team by the vendor and subsequent trainingsbythe project team for other potential users. Frontier Precision came to the Boise, Idaho area June 7th, 2024. Chris Jackson, UAS Training Specialists for Frontier Precision, provided initial setup and calibration of the Yellowscan Surveyor Ultra 3 lidar sensor on the Freefly Astro drone. Training included: A morning classroom session on sensor setup and mission planning A field session practicing safe flight operations for the Astro drone (without the sensor) and two lidar data collection missions An afternoon classroom session on processing the raw lidar and GNSS base station data into final lidar products The training was attended by project PI's Karl, Ryu, and Li as well as by three graduate students. Subsequent to the vendor-provided trainings, we developed our own training curriculum for the drone lidar system (described in the next section below). The third goal of the project was the implement the lidar system at a set of ongoing and new projects. Since delivery of the drone lidar system, we have flown 29 data collection missions for a variety of projects in agriculture and natural resources. These include lidar data acquisitions for: Study of the effects of dormant-season grazing on the abundance of annual grasses at the USFS Curlew National Grasslands Channel morphology change resulting from installation of beaver-dam analogs at UI's Rinker Rock Creek Ranch Evaluation of the use of drone-collected lidar data for forest stand inventories at the UI Experimental Forest Evaluating the short- and long-term effects of a 2024 wildland fire on soil erosion and channel morphology along Rock Creek at the UI's Rinker Rock Creek Ranch Collecting teaching datasets for the UAS Remote Sensing (REM 475) class Evaluating long-term effectiveness of a stage-zero stream restoration project in northern Idaho Additionally, we flew demonstration missions to illustrate how drone lidar can be used to evaluate fuel loading in forests as part of two Idaho congressional tours (Senator Crapo, Congressman Simpson). Potential future use of the drone lidar system has been written into at least one NSF and one NIFA proposals submitted in 2024, and one awarded project by the Bureau of Land Management (BLM). As part of the implementation of the drone lidar system, we committed to establishing the Drone Lab as a UI Service Center to allow for grant funds to be used for the operation and maintenance of the lidar system. The Drone Lab was given Service Center designation in December 2023. Throughout 2024, we have been able to recover costs for operating the drone lidar system for projects not described in the original proposal. According to the proposal, we have also provided free use of the drone lidar system to unfunded graduate student projects (n=2) as we have had capacity to do so. Finally, work on documenting the use and impacts of the drone lidar system are ongoing. We are using the 3rd-part application DroneLogBook.com to track all lidar acquisition flights (for legal compliance purposes as well as for project tracking) and ensure that routine maintenance of the drone and lidar sensor is performed on schedule. Drone-collected lidar units produce a large amount of data for each flight (a 10-minute flight will produce approximately 8GB of data). Data are being stored in the UI's Resource Computing Data Services hosting environment as described by the project data management plan. We are currently working on developing systems to adequately document metadata associated with each flight (e.g., flight mission parameters, weather conditions) and track progress on post-processing of all the collected datasets.

Publications