Development of a multicriteria spatial decision support system with application to the economic optimization of aircraft based weather data collection

This research is motivated by the economic optimization of the Troposherical Airborne Meteorological Data Reporting (TAMDAR), an aircraft-based meteorological data collection system. In the envisioned TAMDAR system, meteorological data collected by the onboard sensors of selected aircraft are transmitted to the ground as aircraft fly their missions. The data is processed by a national center, which disseminates the data to diverse users such as weather forecasters and aviation control centers. Substantial government funding is required for the implementation and operation of this new data acquisition system and data transmission expenditures constitute the largest portion of the costs. To achieve economic optimization of the data gathering activities, the TAMDAR system requires a multicriteria spatial decision support system (MC-SDSS) that facilitates the efficient selection of the most desirable data points to collect based on a limited budget. To optimize the data collection each data point must be assigned a value by the TAMDAR DSS and a specialized data valuation technique is developed for this purpose.; This work presents a design methodology for practical integrated application of multi-attribute utility, simulation and spatial decision analysis techniques in the optimization of aircraft-based weather data collection systems. The TAMDAR DSS demonstrates tools to address a number of challenging decision support design problems such as inherent uncertainty, required subject-matter knowledge, geo-spatial data dimension, resolution of conflicting goals, reduction of complexity and, qualitative judgment. The developed model has wide application to other weather information and data gathering problems.