Color is a vivid factor among map visual variables. Map color has information value and aesthetic value. Because of the complexity of color design, color using becomes one of the most interesting and challenging aspects of cartography. In thematic map designing, basic tone of color is firstly taken into account, which is the essence attribute of color. This study is mainly about the design of b...

Thematic maps have a central and often unquestioned role in geographical information systems (GIS) (Woodcock and Gopal, 2000). They are one of the most common ways of representing spatial data and are unsurprisingly, therefore, a common input and output of analyses undertaken in GIS. They are, however, only a model or simplification and hence a flawed representation of reality. Consequently, it...

This paper de s c ribes a context based technique for smoothing digital thematic maps produced by multispec tral classification of Landsat Thematic Mapper data . The output of this technique i s a "maplike" product which can be directly used as input to a geographic information system.

In this paper, fuzzy-based multisensor data fusion is studied and an iterative fuzzy classifier is proposed. Obtained results are given as a set of two maps: a thematic map, and a confidence map (a classification certainty map representing the degree of certainty in the thematic map). The application of this classifier using ERS-1/JERS-1 SAR composites is shown to very promising.

A total of 21 maps were produced that together form a type of atlas of the Nokia Mobile Data Challenge. Like in a traditional geographic atlas, we present a limited number of base map configurations, onto which various thematic elements are then overlaid. Two of those base maps are derived from MDC data, the third is placed in geographic space. Thematic overlays serve several purposes, includin...

Overstory vegetation maps of species and canopy cover were developed from Landsat 7 Thematic Enhanced Thematic Mapper satellite imagery. Ecosystem Monitoring plot data, collected during the 1997-2001 field seasons, were used as training sites for the image classification. Sixty-two species classes and four canopy cover classes were mapped. The maps will be used to support a Joint Fire Science P...

No thematic map is perfect. Some pixels or polygons are not accurately classified, no matter how well the map is crafted. Therefore, thematic maps need metadata that sufficiently characterize the nature and degree of these imperfections. To decision-makers, an accuracy assessment helps judge the risks of using imperfect geospatial data. To analysts, an accuracy assessment helps describe the rel...