The model, “Remote Sensing Communication Model” (RSCM), which permits the estimation of the timeliness of remote sensing systems (RSS) is tested (Lippitt, Stow, & Clarke, 2014). This model conceptualizes RSS as having capacities that determine the timeliness of the systems, where a system is comprised of three segments, each with a capacity that determines the timeliness of that segment: acquisition capacity, transmission capacity, and receiver capacity (i.e., the capacity of a human and/or machine analyst to produce information) (Lippitt et al., 2014). Acquisition and transmission capacity analyses are run to aid in the optimization of a flexible time-sensitive remote sensing system being designed for emergency response in Bernalillo County, NM. Modeled timeliness is validated using empirical tests of airborne acquisitions, the model modified to improve fit, and then used for a variety of manned and unmanned platform and sensor combinations to infer the timeliness of data delivery to emergency managers, based on both currently available and potential airborne assets. In doing so, this research assesses the accuracy of capacity based estimates of timeliness for airborne RSSs and demonstrate a method for the optimization of platform, sensor, and transmission configurations for emergency response.
Level of Degree
First Committee Member (Chair)
Second Committee Member
Third Committee Member
National Science Foundation Award # CMMI-1360041
Remote Sensing, Disaster, Emergency Management, RSCM, Remote Sensing Communication Model, Remote Sensing Systems
Loerch, Andrew. "Modeling the Timeliness of Airborne Remote Sensing Data." (2016). https://digitalrepository.unm.edu/geog_etds/31