CANAPI: Canopy Analysis with Panchromatic Imagery for Validation of Moderate Resolution Canopy Structure Products
Mark
James
Chopping, Montclair State University, chopping@pegasus.montclair.edu
(Presenting)
Xiaoyuan
Yang, Boston University, xiaoyuan@bu.edu
Crystal
Schaaf, Boston University, schaaf@bu.edu
Alan
Strahler, Boston University, alan@bu.edu
The validation of remotely-sensed canopy structural parameters derived from moderate resolution imaging is a perennial problem because it is too expensive to undertake field measurements at scales of 250 m and above. High resolution imaging from the air and space and airborne lidar systems are widely used sources of reference data, with the former used to delineate crowns and the latter to estimate crown heights and other statistics. A simple yet effective method that provides tree crown extent, radii, and heights maps from high resolution panchromatic images of large dimensions – CANAPI (CANopy Analysis from Panchromatic Imagery) – is presented here, together with comparisons with QuickBird 0.6 m spatial resolution imagery, EVI field lidar, and lidar height estimates from the NASA Laser Vegetation Imaging Sensor (LVIS) for forest sites in the Sierra Nevada mountain range in California. The method was developed as an ImageJ macro using simple image processing functions and is easily modified and extended, for example to obtain estimates of crown shape. CANAPI has some limitations -- for example it is not adapted for closed and/or tropical forest canopies -- but is useful in obtaining cover and height estimates for extensive areas in open and semi-open forest and shrub canopies where illumination is oblique. The results can also be used to establish and evaluate background reflectance magnitude and anisotropy metrics predicted using multiangle bidirectional reflectance factors or a bidirectional reflectance distribution function (BRDF) model.
Presentation Type: Poster
Poster Session: Orbital and Suborbital Missions
NASA TE Funded Awards Represented:
Chopping, Mark
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