Paper
3 May 2012 Lidar flecks: modeling the influence of canopy type on tactical foliage penetration by airborne, active sensor platforms
Richard Massaro, Julie Zinnert, John Anderson, Jarrod Edwards, Edward Crawford, Donald Young
Author Affiliations +
Abstract
Our research focuses on the Army's need for improved detection and characterization of targets beneath the forest canopy. By investigating the integration of canopy characteristics with emerging remote data collection methods, foliage penetration-based target detection can be greatly improved. The objective of our research was to empirically model the effect of pulse return frequency (PRF) and flight heading/orientation on the success of foliage penetration (FOPEN) from LIDAR airborne sensors. By quantifying canopy structure and understory light we were able to improve our predictions of the best possible airborne observation parameters (required sensing modalities and geometries) for foliage penetration. Variations in canopy openness profoundly influenced light patterns at the forest floor. Sunfleck patterns (brief periods of direct light) are analogous to potential "LIDAR flecks" that reach the forest floor, creating a heterogeneous environment in the understory. This research expounds on knowledge of canopy-specific characteristics to influence flight geometries for prediction of the most efficient foliage penetrating orientation and heading of an airborne sensor.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard Massaro, Julie Zinnert, John Anderson, Jarrod Edwards, Edward Crawford, and Donald Young "Lidar flecks: modeling the influence of canopy type on tactical foliage penetration by airborne, active sensor platforms", Proc. SPIE 8360, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX, 836008 (3 May 2012); https://doi.org/10.1117/12.918519
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CITATIONS
Cited by 6 scholarly publications and 1 patent.
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KEYWORDS
LIDAR

Sensors

Vegetation

Active sensors

Electro optical modeling

Target detection

Clouds

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