TY - JOUR

T1 - HEXAGONAL GRIDS APPLIED TO CLUSTERING LOCATIONS IN WEB MAPS

AU - Beresnev, A.

AU - Panidi, E.

N1 - Publisher Copyright: © 2022 A. Beresnev et al.

PY - 2022/5/30

Y1 - 2022/5/30

N2 - One of the popular ways to clutter reduction techniques is to combine neighboring points into one marker that somehow shows that it contains multiple entities - this way is called clustering. In this paper, we present a JavaScript library to define optimal size of clusters and render them. Moreover, markers have to present heterogeneous data inside of clusters. The presented library relies on server side clustering, no matter if is it a real-time clustering or a static bunch of hexagonal grids. For the library, a server provides the bunch of grid layers by different cell sizes - from smaller to larger. The library relies on data fetching provided by external library, such as Mapbox/Maplibre, so it can work with both GeoJSON and vector tiles. Using the HTML Canvas to render the marker allows to full customizing the marker image: manage the colors and proportions of cluster fractions and the size.

AB - One of the popular ways to clutter reduction techniques is to combine neighboring points into one marker that somehow shows that it contains multiple entities - this way is called clustering. In this paper, we present a JavaScript library to define optimal size of clusters and render them. Moreover, markers have to present heterogeneous data inside of clusters. The presented library relies on server side clustering, no matter if is it a real-time clustering or a static bunch of hexagonal grids. For the library, a server provides the bunch of grid layers by different cell sizes - from smaller to larger. The library relies on data fetching provided by external library, such as Mapbox/Maplibre, so it can work with both GeoJSON and vector tiles. Using the HTML Canvas to render the marker allows to full customizing the marker image: manage the colors and proportions of cluster fractions and the size.

KW - Clustering

KW - Geographic Data

KW - Hexagonal Grid

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=85132199375&partnerID=8YFLogxK

U2 - 10.5194/isprs-archives-XLIII-B4-2022-435-2022

DO - 10.5194/isprs-archives-XLIII-B4-2022-435-2022

M3 - Conference article

AN - SCOPUS:85132199375

VL - 43

SP - 435

EP - 440

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

SN - 1682-1750

IS - B4-2022

T2 - 2022 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission IV

Y2 - 6 June 2022 through 11 June 2022

ER -