Modeling training-site vegetation-coverage probability with a random optimization procedure: an artificial neural network approach

Biing T. Guan; George Z. Gertner; David G. Kowalski

doi:10.1117/12.152571

2 September 1993 Modeling training-site vegetation-coverage probability with a random optimization procedure: an artificial neural network approach

Biing T. Guan, George Z. Gertner, David G. Kowalski

Author Affiliations +

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152571
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

The main objective of this study is to examine the feasibility of applying feed-forward neural networks to estimate training site vegetation coverage probability based on past disturbance pattern and vegetation coverage history.

Citation Download Citation

Biing T. Guan, George Z. Gertner, and David G. Kowalski "Modeling training-site vegetation-coverage probability with a random optimization procedure: an artificial neural network approach", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152571

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