Paper
17 August 2009 Hyperspectral-LIDAR system and data product integration for terrestrial applications
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Abstract
This manuscript details the development and validation of a unique forward thinking instrument and methodology for monitoring terrestrial carbon dynamics through synthesis of existing hyperspectal sensing and Light Detection and Ranging (LIDAR) technologies. This technology demonstration is directly applicable to linking target mission concepts identified as scientific priorities in the National Research Council (NRC, 2007) Earth Science Decadal Survey; namely, DESDynI and HyspIRI. The primary components of the Hyperspec-LIDAR system are the ruggedized imaging spectrometer and a small footprint LIDAR system. The system is mounted on a heavy duty motorized pan-tilt unit programmed to support both push-broom style hyperspectral imaging and 3-D canopy LIDAR structural profiling. The integrated Hyperspec-LIDAR sensor system yields a hypserspectral data cube with up to 800 bands covering the spectral range of 400 to 1000 nm and a 3-D scanning LIDAR system accurately measuring the vertical distribution of intercepted surfaces within a range of 150 m with an accuracy of 15 mm. Preliminary field tests of the Hyperspec-LIDAR sensor system were conducted at a mature deciduous mixed forest tower site located at the Smithsonian Environmental Research Center in Edgewater, MD. The goal of this research is to produce integrated science and data products from ground observations that will support satellite-based hybrid spectral/structural profile linked through appropriate models to monitor Net Ecosystem Exchange and related parameters such as ecosystem Light Use Efficiency.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lawrence A. Corp, Yen-Ben Cheng, Elizabeth M. Middleton, Geoffrey G. Parker, K. Fred Huemmrich, and Petya K. Entcheva Campbell "Hyperspectral-LIDAR system and data product integration for terrestrial applications", Proc. SPIE 7457, Imaging Spectrometry XIV, 745705 (17 August 2009); https://doi.org/10.1117/12.825515
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KEYWORDS
LIDAR

Reflectivity

Imaging systems

Vegetation

Sensors

Ecosystems

Hyperspectral imaging

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