B41D-0467
Repeat, Low Altitude Measurements of Vegetation Status and Biomass Using Manned Aerial and UAS Imagery in a Piñon-Juniper Woodland

Thursday, 17 December 2015
Poster Hall (Moscone South)
Daniel J Krofcheck, University of New Mexico Main Campus, Albuquerque, NM, United States
Abstract:
Measuring the above ground biomass of vegetation is a critical component of any ecological monitoring campaign. Traditionally, biomass of vegetation was measured with allometric-based approach. However, it is also time-consuming, labor-intensive, and extremely expensive to conduct over large scales and consequently is cost-prohibitive at the landscape scale. Furthermore, in semi-arid ecosystems characterized by vegetation with inconsistent growth morphologies (e.g., piñon-juniper woodlands), even ground-based conventional allometric approaches are often challenging to execute consistently across individuals and through time, increasing the difficulty of the required measurements and consequently the accuracy of the resulting products. To constrain the uncertainty associated with these campaigns, and to expand the extent of our measurement capability, we made repeat measurements of vegetation biomass in a semi-arid piñon-juniper woodland using structure-from-motion (SfM) techniques. We used high-spatial resolution overlapping aerial images and high-accuracy ground control points collected from both manned aircraft and multi-rotor UAS platforms, to generate digital surface model (DSM) for our experimental region. We extracted high-precision canopy volumes from the DSM and compared these to the vegetation allometric data, s to generate high precision canopy volume models. We used these models to predict the drivers of allometric equations for Pinus edulis and Juniperous monosperma (canopy height, diameter at breast height, and root collar diameter). Using this approach, we successfully accounted for the carbon stocks in standing live and standing dead vegetation across a 9 ha region, which contained 12.6 Mg / ha of standing dead biomass, with good agreement to our field plots. Here we present the initial results from an object oriented workflow which aims to automate the biomass estimation process of tree crown delineation and volume calculation, and partition standing biomass into live and dead pools, in a change detection context.