OOS 39-6 - Using lidar remote sensing to characterize habitat quality and diversity

Thursday, August 5, 2010: 9:50 AM
306-307, David L Lawrence Convention Center
Ralph Dubayah, Department of Geography, University of Maryland, College Park, MD and Scott Goetz, Woods Hole Research Center, Falmouth, MA
Background/Question/Methods

Vegetation canopy vertical and spatial structure have been hypothesized to be important factors that affect species diversity, abundance, as well as being overall indicators of habitat quality and its changes through time. The vertical dimension in particular is difficult to measure and most studies have been limited to small plot-level experiments that restrict our ability to explore landscape level variability in structure, to understand how this structure forms and evolves, and ultimately its implications for biodiversity and habitat characterization. The relatively recent introduction of lidar remote sensing is a potential breakthrough in terms of methodological advances because it allows for landscape level mapping of canopy structure at unprecedented spatial and vertical resolutions, on the order of centimeters to tens of meters. Lidar remote sensing has been used to retrieve canopy structure characteristics such as height and height variability; vertical foliar/canopy profiles, LAI and canopy cover vertical profiles, stem density, and biomass. As such, lidar provides a novel and unique perspective for exploring habitat.  In this paper we present an overview of lidar remote sensing for habitat characterization and biodiversity studies. We first give a brief background on discrete return and waveform lidar. We then explain the methods used to derive various types of canopy structure, and the accuracies observed thus far.

Results/Conclusions

We show a series of examples taken from our own work on the application of this technology to habitat and biodiversity studies. Lidar remote sensing is used to accurately retrieve many aspects of canopy structure, and these are shown to be significantly related to bird biodiversity and abundance for three examples we present in western and eastern US forests. Additionally, we show how lidar remote sensing was deployed to help map potential habitat for the presumably rediscovered ivory-billed woodpecker.  Lastly, we touch on future space missions that promise to provide lidar data globally. Based on these and other studies, we conclude that lidar remote sensing should play an increasingly large role in habitat characterization for landscape and regional studies of biodiversity.

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