About: Choropleth map is a research topic. Over the lifetime, 369 publications have been published within this topic receiving 8331 citations. The topic is also known as: blot map.
TL;DR: A new automatic method of determining class intervals in representing knowledge of population distribution based on population distribution Lorenz curve, which can determine the number of classes by requirement of knowledge transfer as well as determine the class interval via the Douglas-Peucker simplification method.
Abstract: Different from traditional researches which focus on statistics accuracy and representation effects of choropleth map,a new automatic method of determining class intervals in representing knowledge of population distribution is proposed in this paper.Based on population distribution Lorenz curve,the method can determine the number of classes by requirement of knowledge transfer as well as determine the class interval via the Douglas-Peucker simplification method.Experiments of the method demonstrate the potential of representing population distribution patterns and the improvement of map information transfer.During simplification,the two class interval map shows the approximate outline of "Hu line".The population distribution patterns and knowledge of particular cases are easily understood from maps of three or more class intervals.
TL;DR: The creation of a database drawing primarily on the parish evidence contained in the 1524/15251aysubsidyrolls for Devon is discussed in order to generate choropleth maps which depict patterns of population and prosperity in early sixteenth-century Devon.
Abstract: This paper discusses the creation of a database drawing primarily on the parish evidence contained in the 1524/15251aysubsidyrollsforDevon.Thisislinkedto ARC/INFO in order to generate choropleth maps which depict patterns ofpopulation and prosperity in early sixteenth-century Devon. The methods are capable of replication in other counties, and the database can be extended to include further variables.
TL;DR: An efficient algorithm for computing the choropleth map classification scheme known as equal area breaks or geographical quantiles is introduced and is compared with the quantiles and Jenks natural breaks algorithms and found to be superior from a visual standpoint by a user study.
Abstract: An efficient algorithm for computing the choropleth map classification scheme known as equal area breaks or geographical quantiles is introduced. An equal area breaks classification aims to obtain a coloring for the map such that the area associated with each of the colors is approximately equal. This is meant to be an alternative to an approach that assigns an equal number of regions with a particular range of property values to each color, called quantiles, which could result in the mapped area being dominated by one or a few colors. Moreover, it is possible that the other colors are barely discernible. This is the case when some regions are much larger than others (e.g., compare Switzerland with Russia). A number of algorithms of varying computational complexity are presented to achieve an equal area assignment to regions. They include a pair of greedy algorithms, as well as an optimal algorithm that is based on dynamic programming. The classification obtained from the optimal equal area algorithm is compared with the quantiles and Jenks natural breaks algorithms and found to be superior from a visual standpoint by a user study. Finally, a modified approach is presented which enables users to vary the extent to which the coloring algorithm satisfies the conflicting goals of equal area for each color with that of assigning an equal number of regions to each color.