Progress 10/01/19 to 09/30/20
Outputs
Target Audience:Target audiences of this project include those who are interested in natural resource management. During this period, they ranged from students and faculty of forestry and nature resources schools, forest professionals, forest landowners, forestry consultants, and government agencies. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Although the COVID-19 reduced the face-to-face contact between faculty, staff and students, we maintained the interaction following public health guidelines. With several faculty and staff members at Stephen F. Austin State University working together as a team, we engaged our students, both undergraduate and graduates, in multiple courses on different projects. We took a two-way approach where the instructors and the students interacted actively throughout the process. From formulating a scientific question, designing and conducting an experiment, analyzing the data statistically, to professionally delivering the outcome. Many of the projects resulted in presentations in professional conferences such as East Texas GIS & GPS User Group annual conference. It keeps us, both instructors and students, up to date with the technology. How have the results been disseminated to communities of interest?The results from this project have been incorporated into the curriculum at Stephen F. Austin State University (SFASU). The outcome information was made available to the public through the University's website and local news outlets. The findings were also presented as paper and/or poster in conferences such as SFASU Undergraduate Research Conference, SFASU Graduate Research Conference, East Texas GIS & GPS User Group meeting, Southern Forestry and Natural Resource Management GIS Conference, and the Society of American Foresters Convention. Specific topics encompassed Texas roadkill through citizen science, 3D printing for education, suitability analysis for wind farm, positional accuracy of trees, etc. Manuscripts of the results are in development, in review, or published in scientific journals. What do you plan to do during the next reporting period to accomplish the goals?Our recent effort in applying deep learning algorithms to identify individual trees on a drone derived image has shown some promising results. A manuscript titled Measuring Loblolly Pine Crowns with Drone Imagery through Deep Learning is in review where it indicated that deep learning is a cost-effective approach with high accuracy compared to ground measurement. We will continue this line of research and expand the data source to include thermal and multispectral imagery and lidar. Our ultimate goal is to estimate timber volume of a plantation through geospatial technology.
Impacts
What was accomplished under these goals?
We continued to explore the ever-emerging geospatial technologies that can be applied for natural resource management. A new drone equipped with a thermal sensor was added to the fleet. Initial test flights proved that it is a practical tool for detecting animals in night time. The thermal sensor was also used to detect heat reflected from building roofs that can be used for energy efficiency assessment. A planned drone mission was flown over a loblolly pine stand that was recently clearcut. An orthomosaic aerial photo was produced from photos taken by the drone. The aerial photo was then used to detect tree stumps on the clearcut site. It is to evaluate the image processing approach compared to traditional ground measurements in locating and measuring stumps after clearcut. Since the cost of site preparation is highly correlated with the number and size of stumps, quantifying stumps with a drone could be a cost-effective alternative to ground measurements. In comparing the positional accuracy for pecan tree locations in a forested city park, different technologies including drone, Pictometry, Google Earth, and What3Words, were used to attain the geographic coordinates of each tree. The accuracy was assessed by comparing the actual coordinates of each tree surveyed with a total station.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Kulhavy, D., R. Reynolds, D. Unger, M. McBroom, I. Hung, and Y. Zhang. 2020. Use of Altmetrics to Analyze ScholarWorks in Natural Resource Management. Journal of Altmetrics, Vol. 3, No. 1, P. 6.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Kulhavy, D., D. Unger, R. Viequt, I. Hung, and Y. Zhang. 2020. Integration of CITYgreen Landscape Ecological Analysis into a Capstone Environmental Science Course. International Journal of Higher Education, Vol. 9, No. 6, P. 259-267.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2020
Citation:
Kulhavy, D., I. Hung, D. Unger, R. Viegut, and Y. Zhang. 2020. Measuring Building Height Using Point Cloud Data Derived from Unmanned Aerial System Imagery in an Undergraduate Geospatial Science Course. Higher Education Studies, accepted.
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2020
Citation:
Zhang, Y. Kulhavy, D. L. Unger, D. R. Hung, I.-K. Academic 3D Printing and Digital Fabrication Conference for K12, Higher Ed., and Informal Ed. Conference, "UAS and 3D Printing for Conservation and Modeling Education," K12, Higher Ed., and Informal Ed. Conference, Houston, Texas. (February 15, 2020).
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2020
Citation:
Viegut, R. Kulhavy, D. L. Schalk, C. M. Unger, D. R. Hung, I.-K. Zhang, Y. Texas Chapter of the Wildlife Society Conference, "Spatial Analysis and Reporting Biases of Texas Roadkills Using Citizen Science," Texas Chapter of the Wildlife Society, Corpus Christi, TX. (February 15, 2020).
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2020
Citation:
Milecz, R. Hung, I.-K. Farrish, K. W. Unger, D. R. 12th Southern Forestry and Natural Resource Management GIS Conference, "Land Suitability Analysis for Wind Farm Development in Texas," University of Georgia, Athens, Georgia. (December 9, 2019).
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2020
Citation:
Hung, I.-K. Unger, D. R. Kulhavy, D. L. Zhang, Y. 12th Southern Forestry and Natural Resource Management GIS Conference, "Positional Accuracy Assessment on Drones Return to Home Landing in a Wooded Area," University of Georgia, Athens, Georgia. (December 9, 2019).
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