Cognitive Reconstructive Remote Sensing for Decision Support in Environmental Resource Management

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Miniatura

Fecha

2006

Autores

Villalón-Turrubiates, Iván E.
Shkvarko, Yuriy

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Editor

Information Resources Management Association

Resumen

Descripción

In this paper, the problem of reconstruction of different characteristic signatures (CSs) of the monitored environmental scenes from the multi-spectral remotely sensed data is cast in the unified framework of the statistically optimal Bayesian inference making strategy aggregated with the proposed cognitive descriptive regularization paradigm. The reconstructed CS maps are then treated as sufficient statistical data required for performing the environmental resource management tasks. Simulation examples with the real-world remote sensing data are provided to illustrate the efficiency of the proposed approach.

Palabras clave

Environmental Remote Sensing, Resource Management, Decision Support, Regularization

Citación

Ivan E. Villalon-Turrubiates, Yuriy V. Shkvarko, “Cognitive Reconstructive Remote Sensing for Decision Support in Environmental Resource Management”, in Proceedings of the 18th International Conference of the Information Resources Management Association (IRMA): Emerging Trends and Challenges in Information Technology Management, Washington D.C. EE.UU., 2006, pp. 978-980.