UAS Senior Capstone Proposal Abstract and Presentation

Below is the first abstract for my group's senior capstone project. Myself, Thomas Gonya, and Todd Horn have designed the following multifaceted project to have significant implications to forest management, manned-unmanned aircraft joint missions, and high-resolution remote sensing. Underneath the abstract is a link to a presentation on this initial proposal that can be accessed directly. The roles that each of the members will have on this project are detailed in the presentation.

The Impacts of Altitude on High-Resolution Multispectral Remote Sensing for Hardwood Forest Species Delineation

    Hardwood forest inventory is a time consuming and expensive process, especially for small forest owners (Butler et al., 2004). To expedite the process, satellite remote sensing techniques have been used with limited success due to low spatial resolution; unless expensive high-resolution satellite data is purchased (Immitzer et al., 2012). Recent studies have shown that unmanned aerial systems (UAS) can be a means to collect affordable high-resolution forestry data that is as accurate as  ground surveys in the Central Hardwood Forest region of the United States (Hockridge, 2018). However, to fully match the quality of ground surveys, UAS remote sensing methods will need to successfully delineate species of trees in the imagery.

    Our project seeks to identify tree species through UAS multispectral imagery utilizing the RedEdge Altum sensor integrated on the C-Astral Bramor ppX airframe. The sensor’s access to the LWIR and NIR bands and aircraft’s low altitude flight capability should allow for species specific spectral signatures to be identifiable. The aircraft will be flown at forested sites local to the West Lafayette, IN region at approximately 300 feet. It is unknown how much flight altitude’s effect on spatial resolution will impact the accuracy of the species delineation, so the Altum sensor will also be mounted on a fixed wing manned airplane that will fly surveying transects at altitudes of 2,000 and 3,000 feet so that data can be compared. The airborne datasets will be processed into multi-band orthomosaics and then analyzed to determine indices that can be used to identify tree species. From there, maps of tree species will be generated for both manned and unmanned aircraft data, and the accuracy associated with different spatial resolutions will be assessed when compared with ground surveys of tree species. From this, an ideal altitude for tree identification can be determined. 

References

Butler, B.J., J.H. Hewes, B.J. Dickinson, et al. 2016. Family Forest Ownerships of the United States, 2013: Findings from the USDA Forest Service’s National Woodland Owner Survey. Journal of Forestry 114: 638–647.

Hockridge E. (2018, April). Exploring the use of unmanned aerial systems (UAS) for hardwood tree inventory. Poster session presented at: Purdue Undergraduate Research Conference. West Lafayette, IN.

Immitzer, M., Atzberger, C., & Koukal, T. (2012). Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data. Remote Sensing, 4(9), 2661-2693. doi:10.3390/rs4092661 

 Proposal presentation link Here