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Spatializations are computer visualizations in which nonspatial information is depicted spatially. Spatializations of large databases commonly use distance as a metaphor to depict semantic (nonspatial) similarities among data items. By analogy to the " first law of geography " , which states that closer things tend to be more similar, we propose a " first(More)
Dimensionality reduction algorithms are applied in the field of information visualization to generate low-dimensional, visuo-spatial displays of complex, multivariate databases—spatializa-tions. Most popular dimensionality reduction algorithms project relatedness in data content among entities in an information space (e.g., semantic similarity) onto some(More)
As GIScientists we know that " Everything is related to everything else, but near things are more related than distant things " (Tobler, 1970: 236). Unfortunately this law does not tell the spatially aware researcher how to conceptualize " nearness " or which proximity measure to utilize to quantify " relatedness ". One of the main challenges in GIScience(More)
Using CO2 in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce sequestration costs in the absence of emissions policies that include incentives for carbon capture and storage. This study develops a multiscale statistical framework to perform CO2 accounting and risk analysis in an EOR(More)
This study develops a probability framework to evaluate subsurface risks associated with commercial-scale carbon sequestration in the Kevin Dome, Montana. Limited knowledge of the spatial distribution of physical attributes of the storage reservoir and the confining rocks in the area requires using regional data to estimate project risks during the pre-site(More)