Connecting the Dots between Waveform Lidar , Woody and Herbaceous Biomass , and Fractional Cover for Assessment of Land Degradation Using Small-footprint Waveform Lidar Data

Content Provider	Semantic Scholar
Author	Wu, Jingwen Aardt, Jan Van Asner, Gregory P. Mathieu, Rolland Kennedy-Bowdoin, Ty Knapp, D. Wessels, Konrad J. Penson John B. Érasmus Smit, Izak P. J.
Copyright Year	2009
Abstract	Land degradation, defined as a persistent reduction in the capacity of the ecosystem to deliver ecosystem services such as grazing, fuelwood or habitat for wildlife, is regarded as one of the most important environmental issues facing Sub-Saharan Africa. In South Africa it is especially prevalent in the communal lands of the former segregated “homelands”. Land degradation assessment has been a topic of intense research, e.g., [1], but is approaching a point at which regional modelling and monitoring are limited by the capabilities of traditional remote sensing technology. One of the limiting factors is the reliance on high frequency, low spatial resolution, multi-spectral (3-20 wavebands) remote sensing data (e.g. 1km/pixel AVHRR or 500m/pixel MODIS), which are intended to develop regional indicators of vegetation production. This spectrally-and spatially coarse resolution data cannot unravel changes in the land surface at the scale at which the processes actually occur (a few meters). Nor can they identify vegetation composition, structure, and function. It has become evident that improved monitoring of land degradation requires measurements of the ecosystem with (i) a broader wavelength range, defined in narrower wavelength bins (imaging spectroscopy) [2] and (ii) sensors capable of describing the 3-dimensional vegetation structure, e.g. light detection and ranging (lidar). Lidar has been applied extensively in forested environments to describe structural parameters (e.g., volume and biomass; [3, 4]). However, waveform lidar, which records and digitizes the full-backscattered signal with high resolution (~1ns), is a relatively recent technology that holds much promise for detailed vertical characterization of vegetation structure (e.g., [3, 5]). The Carnegie Airborne Observatory (CAO; http://cao.stanford.edu) is a truly unique remote sensing platform in that it combines both the hyperspectral and waveform lidar technologies described above to study regional ecosystems anywhere in the world.
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Alternate Webpage(s)	http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IGARSS_2009/pdfs/1149.pdf
Language	English
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Content Type	Text
Resource Type	Article