Cartography

Cartography (kɑːrˈtɒgrəfi; from χάρτης chartēs, "papyrus, sheet of paper, map"; and γράφειν graphein, "write") is the study and practice of making and using maps. Combining science, aesthetics and technique, cartography builds on the premise that reality (or an imagined reality) can be modeled in ways that communicate spatial information effectively. The fundamental objectives of traditional cartography are to: Set the map's agenda and select traits of the object to be mapped. This is the concern of map editing. Traits may be physical, such as roads or land masses, or may be abstract, such as toponyms or political boundaries. Represent the terrain of the mapped object on flat media. This is the concern of map projections. Eliminate characteristics of the mapped object that are not relevant to the map's purpose. This is the concern of generalization. Reduce the complexity of the characteristics that will be mapped. This is also the concern of generalization. Orchestrate the elements of the map to best convey its message to its audience. This is the concern of map design. Modern cartography constitutes many theoretical and practical foundations of geographic information systems (GIS) and geographic information science (GISc). History of cartography and List of cartographers Surveying#HistoryCadastre#History and Topographic mapping#History What is the earliest known map is a matter of some debate, both because the term "map" is not well-defined and because some artifacts that might be maps might actually be something else. A wall painting that might depict the ancient Anatolian city of Çatalhöyük (previously known as Catal Huyuk or Çatal Hüyük) has been dated to the late 7th millennium BCE. Among the prehistoric alpine rock carvings of Mount Bego (France) and Valcamonica (Italy), dated to the 4th millennium BCE, geometric patterns consisting of dotted rectangles and lines are widely interpreted in archaeological literature as depicting cultivated plots.

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Hybrid Simulator for Capturing Dynamics of Synthetic Populations

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Hybrid Simulator for Capturing Dynamics of Synthetic Populations