Kernel Density Estimation Maps
Kernel Density Estimation Maps is a spatial visualization method that estimates the intensity of point patterns across a continuous surface by applying a kernel function to aggregate point densities, distinguishing it from other point pattern visualization techniques through its use of smoothed, continuous surface interpolation to represent the underlying probability density of point events.
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565
Institutions
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2017–2026
152
Variants
Kde Maps
Parents
264
Andrew Maroko, Juliana Maantay, Nancy Sohler et al. · International Journal of Health Geographics · 2009 · 232 citations · Full text
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Wuhan University
Wuhan, China
7 h-index
15 publications
932 citations
University of Oxford
Oxford, United Kingdom
6 h-index
10 publications
371 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
22 publications
858 citations
University of California San Diego
San Diego, United States
4 h-index
16 publications
399 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
14 publications
257 citations

Pennsylvania State University
State College, United States
4 h-index
9 publications
479 citations

University of British Columbia
Vancouver, Canada
4 h-index
7 publications
223 citations
University College London
London, United Kingdom
4 h-index
8 publications
361 citations
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15 publications · 387 citations
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IJGI · 11 publications · 268 citations
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9 publications · 452 citations
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5 publications · 116 citations
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5 publications · 543 citations
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