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Integrating the UAS in Undergraduate Teaching and Research – Opportunities and Challenges at University of North Georgia [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 The University of North Georgia (UNG) has begun to evaluate both fixed and rotary UAS platforms across the departments to evaluate their potential for furthering both student learning experiences and undergraduate research.
J. B. Sharma, D. Hulsey
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Detection of Hotspot for Korea Earthquake Data using Echelon Analysis and Seismic Wave Energy [PDF]
, 2008 Echelon analysis (Myers et al., 1997) is a method to investigate the phase-structure of spatial data systematically and objectively. This method is also useful to prospect the areas of interest in regional monitoring of a surface variable.
Ishioka, Fumio +2 more
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Regularized Principal Component Analysis for Spatial Data
, 2016 In many atmospheric and earth sciences, it is of interest to identify dominant spatial patterns of variation based on data observed at $p$ locations and $n$ time points with the possibility that $p>n$. While principal component analysis (PCA) is commonly
Huang, Hsin-Cheng, Wang, Wen-Ting
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Annual Review of Public Health, 2016 With increasing accessibility to geographic information systems (GIS) software, statisticians and data analysts routinely encounter scientific data sets with geocoded locations. This has generated considerable interest in statistical modeling for location-referenced spatial data. In public health, spatial data routinely arise as aggregates over regions,
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Modelling urban networks using Variational Autoencoders
Applied Network Science, 2019 A long-standing question for urban and regional planners pertains to the ability to describe urban patterns quantitatively. Cities’ transport infrastructure, particularly street networks, provides an invaluable source of information about the urban ...
Kira Kempinska, Roberto Murcio
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Functional principal component analysis of spatially correlated data [PDF]
, 2016 This paper focuses on the analysis of spatially correlated functional data. We propose a parametric model for spatial correlation and the between-curve correlation is modeled by correlating functional principal component scores of the functional data ...
Hooker, Giles, Liu, Chong, Ray, Surajit
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AN AGENT-BASED MODEL TO REPRESENT SPACE-TIME PROPAGATION OF FOREST-FIRE SMOKE [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Agent-based modeling approaches have been used for various case studies related to the geospatial dynamics of complex systems. The proliferation of forest-fire smoke and the associated airborne particulate matter that behaves as complex systems make it ...
A. K. Smith, S. Dragicevic
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A spatial analysis of multivariate output from regional climate models [PDF]
, 2011 Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output.
Cressie, Noel +2 more
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, 1999 Series: Discussion Papers of the Institute for Economic Geography and ...
Thornton, P.K. +2 more
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A spatial likelihood analysis for MAGIC telescope data
, 2018 Context. The increase in sensitivity of Imaging Atmospheric Cherenkov Telescopes (IACTs) has lead to numerous detections of extended $\gamma$-ray sources at TeV energies, sometimes of sizes comparable to the instrument's field of view (FoV). This creates
Fruck, C., Strzys, M., Vovk, Ie.
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