The First Law of Geography, according to Waldo Tobler, is "everything is related to everything else, but near things are more related than distant things." This first law is the foundation of the fundamental concepts of spatial dependence and spatial autocorrelation and is utilized specifically for the inverse distance weighting method for spatial interpolation and to support the regionalized variable theory for kriging. The first law of geography is the fundamental assumption used in all spatial analysis.
Tobler first presented his seminal idea during a meeting of the International Geographical Union's Commission on Qualitative Methods held in 1969 and later published by him in 1970. Tobler was probably not extremely serious when he originally invoked the first law and instead was explaining limitations brought about by computers of the 1970s. He certainly did not think it would be as prominent in geography as it is today. Though simple in its presentation, this idea is profound. Without it, "the full range of conditions anywhere on the Earth's surface could be packed within any small area. There would be no regions of approximately homogeneous conditions to be described by giving attributes to area objects. Topographic surfaces would vary chaotically, with infinite slopes everywhere, and the contours of such surfaces would be infinitely dense and contorted. Spatial analysis, and indeed life itself, would be impossible."
While Tobler is the first to present the concept as the first law of geography, it existed in some form as a concept before him. In 1935, an R. A. Fisher said "the widely verified fact that patches in close proximity are commonly more alike, as judged by the yield of crops, than those which are further apart." Tobler was made aware of this by a peer-reviewer, and seems to have come up with the first law independently.
Tobler's law was proposed towards the end of the quantitative revolution in geography, which saw a shift towards using systematic and scientific methods in geography.
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Inverse distance weighting (IDW) is a type of deterministic method for multivariate interpolation with a known scattered set of points. The assigned values to unknown points are calculated with a weighted average of the values available at the known points. This method can also be used to create spatial weights matrices in spatial autocorrelation analyses (e.g. Moran's I). The name given to this type of method was motivated by the weighted average applied, since it resorts to the inverse of the distance to each known point ("amount of proximity") when assigning weights.
The First Law of Geography, according to Waldo Tobler, is "everything is related to everything else, but near things are more related than distant things." This first law is the foundation of the fundamental concepts of spatial dependence and spatial autocorrelation and is utilized specifically for the inverse distance weighting method for spatial interpolation and to support the regionalized variable theory for kriging. The first law of geography is the fundamental assumption used in all spatial analysis.
The second law of geography, according to Waldo Tobler, is "the phenomenon external to a geographic area of interest affects what goes on inside." This is an extension of his first. He first published it in 1999 in reply to a paper titled "Linear pycnophylactic reallocation comment on a paper by D. Martin" and then again in response to criticism of his first law of geography titled "On the First Law of Geography: A Reply." Much of this criticism was centered on the question of if laws were meaningful in geography or any of the social sciences.
This course is the second part of a course dedicated to the theoretical and practical bases of Geographic Information Systems (GIS).It offers an introduction to GIS that does not require prior compu
This course is the second part of a course dedicated to the theoretical and practical bases of Geographic Information Systems (GIS).It offers an introduction to GIS that does not require prior compu
Explores the evolution of air travel, analyzing global figures and reasons for flying, emphasizing the dominance of leisure purposes and the impact of social and spatial attributes.
Covers discrete geographic variables and their geometric properties, including how to characterize them using indices like the Gravelius compactness index.