Web-based Assessment of Operator Performance and Variability in Remote Sensing Image Analysis

Soetkin Gardin1, Sebastien M.J.Van Laere2, Frieke M.B Van Coillie1. Frederik Anseel3, Wouter Duyck2, and Robert R. De Wulf1
1 Laboratory of Forest Management and Spatial Information Techniques
2 Department of Experimental Psychology
3 Department of Personnel Management, Work and Organizational Psychology Ghent University, Ghent, Belgium
{Soetkin.Gardin, Sebastien.Vanlaere, Frieke.VanCoillie, Frederik.Anseel, Wouter.Duyck, Robert.DeWulf}@UGent.be

Abstract: Human perception and interpretation is an indispensable component in many aspects of remote sensing image analysis. Human intervention is a requisite for visual image interpretation and even in computer-based digital image processing, human screening and interpretation is still needed at certain stages. Next to the remote sensing domain, human intervention plays an important role in other types of geodata processing such as GIS and cartography. Although it is crucial for adequately assessing automated systems' performance, virtually no research has focussed on operator functioning. Instead, it is implicitly assumed that operator performance approaches perfection, and that infrequent errors are randomly distributed across time, operators and image types. The goal of the present study is to test these assumptions, and to determine the human factors that influence operator functioning. To this end a web application has been developed including several experiments testing operator performance. In a first part a personal profile is made consisting of some demographics like age and gender. Next, a personality questionnaire is presented and an interactive tool measures the capacity of the visual working memory. The second part consists of a long series of digitizing tasks. So far, a try-out took place in a controlled environment. The results of this control group already showed significant variability amongst operators that could partly be explained by human factors.

Keywords: image analysis; accuracy; human factors

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