Related Experiment Video
Updated: Jun 26, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Uncertainty of block estimates introduced by mis-allocation of point samples: on the example of spatial indoor Radon
1European Commission, Joint Research Centre, Institute for Environment and Sustainability, TP441, Via Fermi 1, I-21020 Ispra (VA), Italy. peter.bossew@jrc.it
Abstract:
The European indoor Radon map which is currently under production is based on gridded data supplied by the contributing countries. Each grid node represents the arithmetic mean (among other statistics) of the individual measurements within 10 x 10 km(2), called cells, pixels or blocks, which are aligned to a common metric coordinate system. During work the question emerged, if uncertainty in the geo-referencing of individual data might affect the aggregated "block" statistics to an extent that the statistics have an unpredictably high additional uncertainty, which makes them unusable. In this note we try to quantify the effect, based on simulations. The overall result is that the relevant statistics should not be affected too badly in most cases, in particular if the rate of mis-allocations, and the mean uncertainty of coordinates are not too high, so that also cell statistics which are to some degree distorted by mis-allocated data, can still be used for the purpose of the European Radon map.
Related Concept Videos
Propagation of Uncertainty from Systematic Error
Uncertainty in Measurement: Accuracy and Precision
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random Error
Contaminants and Errors
Another key consideration is determining the appropriate number of samples required to...
Propagation of Uncertainty from Random Error
