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Evaluation of sampling tool efficacy in support of capturing variability in building occupancy

Authors: Zachary Palmer*, Oak Ridge Institute for Science and Education, Marie Urban, Oak Ridge National Laboratory
Topics: Population Geography, Quantitative Methods, Applied Geography
Keywords: Population Modeling, Demographics, Sampling, Hospitals
Session Type: Paper
Presentation File: No File Uploaded

Population Density Tables (PDT) is a project being developed at Oak Ridge National Laboratory (ORNL) that seeks to develop worldwide ambient building occupancies (people per 1000 sq. feet of built space) for over 50 different building types. This is done at the building-level using a wide variety of open-source qualitative and quantitative datasets that range from academic cultural studies and news articles, to official census statistics and government reports on living standards. These input sources focus on informing a population model through cultural analysis of building usage supported by hard numbers. To aid in data collection efforts for PDT, a Smart Sampling Tool (SST) was created. The SST runs tests concerning distribution, mean change, and margin of error on a chosen dataset as it is being completed to determine when the sample is large enough to be statistically sound. Validation of the SST has proved difficult due to the amount of effort necessary for manual data collection and the lack of complete datasets to compare samples to. However, newly acquired data regarding hospital occupancy in Japan has provided virtually complete datasets that allow for validation testing of the SST. This talk will discuss the use of the Smart Sampling Tool in the PDT project, difficulties in validating the tool’s mechanisms, the results of the validation tests, and future directions for its usage.

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