Heat Maps: Perfect Maps for Quick Reading? Comparing Usability of Heat Maps with Different Levels of Generalization

正确性 一般化 光栅图形 阅读(过程) 计算机科学 可用性 数据挖掘 人机交互 人工智能 数据库 情报检索 数学 算法 政治学 数学分析 法学
作者
Katarzyna Słomska-Przech,Tomasz Panecki,Wojciech Pokojski
出处
期刊:ISPRS international journal of geo-information [Multidisciplinary Digital Publishing Institute]
卷期号:10 (8): 562-562 被引量:12
标识
DOI:10.3390/ijgi10080562
摘要

Recently, due to Web 2.0 and neocartography, heat maps have become a popular map type for quick reading. Heat maps are graphical representations of geographic data density in the form of raster maps, elaborated by applying kernel density estimation with a given radius on point- or linear-input data. The aim of this study was to compare the usability of heat maps with different levels of generalization (defined by radii of 10, 20, 30, and 40 pixels) for basic map user tasks. A user study with 412 participants (16–20 years old, high school students) was carried out in order to compare heat maps that showed the same input data. The study was conducted in schools during geography or IT lessons. Objective (the correctness of the answer, response times) and subjective (response time self-assessment, task difficulty, preferences) metrics were measured. The results show that the smaller radius resulted in the higher correctness of the answers. A larger radius did not result in faster response times. The participants perceived the more generalized maps as easier to use, although this result did not match the performance metrics. Overall, we believe that heat maps, in given circumstances and appropriate design settings, can be considered an efficient method for spatial data presentation.
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