Crown delineation using multispectral point cloud data

Authors: Nicholas Kolarik*,
Topics: Remote Sensing, Land Use and Land Cover Change
Keywords: Unmanned Aerial Systems, UAS, UAV, land cover, drone, vegetation, remote sensing
Session Type: Poster
Day: 4/13/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Napoleon Foyer/Common St. Corridor, Sheraton, 3rd Floor
Presentation File: No File Uploaded

Unmanned Aerial Systems (UAS) are an emerging platform capable of providing valuable data on vegetation structure, health, and productivity. With output products having much finer spatial resolutions than traditional satellite or aircraft imagery there is great potential for the application of UAS technology for mapping and monitoring vegetation conditions which often exhibit high spectral and structural heterogeneity. This study uses derived point clouds and imagery collected from UAS-mounted sensors at a test site in Louisville, KY. We compare multiple approaches for extracting woody vegetation structure from the UAS imagery and assess whether multispectral data improves estimates of vegetation structure. We found that leveraging height, texture, and where applicable, color or multispectral reflectance information aids in crown delineation, areal estimates, and fractional cover of woody and non-woody vegetation within the study area. A comparison and overall efficacy of various crown delineation techniques with in situ field measurements is also presented in order to guide field sampling protocols and methods for autonomous crown delineation of UAS imagery in further research.These findings advance research for field and remote sensing analyses assessing degradation in heterogeneous landscapes where varying levels of vegetation structure have implications on land use and land functions.

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