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首页> 美国政府科技报告 >Unsupervised Classification of Lidar-based Vegetation Structure Metrics at Jean Lafitte National Historical Park and Preserve.
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Unsupervised Classification of Lidar-based Vegetation Structure Metrics at Jean Lafitte National Historical Park and Preserve.

机译：Jean Lafitte国家历史公园和自然保护区基于激光雷达的植被结构度量的无监督分类。

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The objective of this study is to classify the major types of vegetation assemblages in the Barataria Preserve at Jean Lafitte National Historical Park and Preserve (JELA), Louisiana, using metrics derived from the Experimental Advanced Airborne Research Lidar (EAARL) system. The EAARL is a raster-scanning, waveform-resolving, green-wavelength (532 nm) lidar system designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor was developed (circa 2000) by the National Aeronautics and Space Administration (NASA) at its Wallops Flight Facility, Virginia. The EAARL instrument records the time history of the return waveform within a small footprint (20-cm diameter on the ground) for each laser pulse, enabling characterization of vegetation canopy structure and bare earth (BE) topography beneath a variety of vegetation types. The EAARL system also acquires concurrent, high-resolution geolocated color infrared (CIR) imagery at a 1-second interval. A collection of individual waveforms is combined to create a synthesized large-footprint waveform that is used to define three canopy metrics: canopy height (CH), canopy reflection ratio (CRR), and height of median energy (HOME). For this study, a 5-m footprint size was used, but in general, the appropriate size of the synthesized footprint is derived based on a combination of the lidar sampling density and the nature of the terrain (Nayegandhi and others, 2006). The lidar-based vegetation canopy metrics, along with BE elevation data, were then used in an unsupervised classification procedure to determine the boundaries or patches of vegetation structural communities within the Barataria Preserve.

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