Urban Density Clustering app
Authors: Sergio A Maldonado
Abstract: App that clusters ubran buildings based on density. Data of buildings comes from AI satelite images taken form HDX and facebook to provide rapid response to natural disasters, as many other uses.
Since the data is so big and the app consumes too much computing resoureses, I implemented basic reactivity to the server.
The method used to cluster the buildings is KNN and the app allows the user to define clustering sensitivity based on: 1. the minimum points inside the cluster radius, 2. Epsilon which defines the cluster radius. The app allows theuser to select a nighborhood in La Paz,Bolivia.
Full Description: App that clusters ubran buildings based on density. Data of buildings comes from AI satelite images taken form HDX and facebook to provide rapid response to natural disasters, as many other uses.
Since the data is so big and the app consumes too much computing resoureses, I implemented basic reactivity to the server.
The method used to cluster the buildings is KNN and the app allows the user to define clustering sensitivity based on: 1. the minimum points inside the cluster radius, 2. Epsilon which defines the cluster radius. The app allows theuser to select a nighborhood in La Paz,Bolivia.
Keywords: Urban, Density, ML, KNN, clustering, Safety, Contingency_plan, leaflet, reactivity, visualization, HDX, facebook_hdx
Shiny app: https://datapaip.shinyapps.io/herramienta_densidades/
Repo: GitHub - srgmld/herramienta_densidades: Densidades
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