The automated Tree Identification and Delineation Algorithm (TIDA) was developed for application to high spatial resolution digital imagery of Australian native eucalypt forest. The algorithm is based on contiguous, threshold-based spatial clustering of pixels and was designed to cope with the complex asymmetric crowns typical of eucalypts. / To facilitate systematic algorithm evaluation, a forest scene simulation model was created for the simulation of visually realistic remotely sensed images. The model is based on the principles of ray-tracing and the geOll1etric description of scene objects and background. The model simulates the appearance of a forest scene viewed and illuminated from specific directions and under known atmospheric conditions. The distinctive 'modular' structure of eucalypts was represented by modelling crowns as small (branch-scale) spheroids distributed over a larger spheroidal envelope. / Using the simulation model, TIDA performance was evaluated in terms of forest structure (canopy cover, crown cover and canopy structural variability) and the remote sensing environment (view zenith angle, solar zenith angle and aerosol optical thickness). Prior to the evaluation, a methodology was developed for objectively estimating the optimum spatial resolution for TIDA application in a given image. The methodology was based on incremental Gaussian smoothing and exploited TIDA's sensitivity to changes in image spatial resolution. This process demonstrated the importance of individual crown cover, rather than crown size, as the main factor determining the optimum spatial resolution for tree delineation. / Results indicate that TIDA is most suited for application in forests with high canopy cover and high crown cover. The structural complexity of forest canopies, represented by the diameter and overlap of crowns and tree height, had a relatively small impact on TIDA performance. Increasing view zenith angle consistently caused a decrease in TIDA performance. A small phase angle between the sun and sensor produces optimum TIDA performance when both canopy and crown cover is high. As crown or canopy cover decrease, high positive and negative sun zenith angles yield superior TIDA results by decreasing the brightness of the background relative to the canopy and improving the identification of tree peaks. For both dense and sparse canopies, back-scattered radiation from the forest canopy was more suited to automated tree crown delineation than forward-scattered radiation. Imagery acquired under an optically thick atmosphere was found to increase TIDA performance compared to scene illumination under strong direct light. The advantage stemmed from a strengthening of the relationship between geometric and radiometric crown shape. / Through an awareness of limitations imposed by the remote sensing environment, the potential for manipulation of image characteristics, and preferential selection of acquisition conditions, TIDA performance can be optimised to suit various structural forest types. Canopy cover, crown cover, view zenith angle, sun zenith angle, background brightness and image spatial resolution are key criteria in assessing the suitability of automated tree crown delineation as an image interpretation procedure.
| Identifer | oai:union.ndltd.org:ADTP/245797 |
| Date | January 2000 |
| Creators | Culvenor, Darius Samuel |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
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