poinproc wherecamp berlin

Marker clustering and cartographic generalizationBerlin, november 2014.

About map scales

Classic cartographic generalization

Base maps are prepared to be represented at a certainscale. Design scale and view scale must match.

Large scale: + detail. Small scale: - detail.

Small scale view Large scale viewSmall scale view Large scale view

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Cartographic sources are drawn at a detailed scales. Thenthey’re submitted to cartographic generalization to obtaincartography at smaller scales.

3D featuredigitizingenvironment forArcGIS from geo-referenced aerialor space-borneimagery (Purview).


About map scales


3D featuredigitizingenvironment forArcGIS from geo-referenced aerialor space-borneimagery (Purview).

Base maps are outlined from aerial photography.

Base maps for web map viewers are prepared following thesame approach as classic (paper) map series.


About map scales


Google Maps street map: its design is road map like.

Maps to be shown at different scales are drawn differently

Tools to obtain base mapsat less detailed scales:cartographic generalizationtools.

Sometimes the applicationwill require some amountof work.

Simplification.

Classification.


About map scales


Tools to obtain base mapsat less detailed scales:cartographic generalizationtools.

Sometimes the applicationwill require some amountof work.

Aggregation.

Collapsing.

Selection.

But that’s not the case with Douglas-Peuker classic algorithmto remove vertices automatically for line simplification, whichis fully automatic.


About map scales


It is internally implemented in all internet map viewers.

Douglas-Peuker method applied to polyline with a single line.

About internet mapping

Marker clustering

A set of markers is embedded into a vector layer. It can bedisplayed as a map overlay for internet viewers. The viewerhandles scale changes in a way that we’re grown used to.


We’re relying somewhat in the Maps API’s functionalityand somewhat in the web designer’s criteria to have a mapcustomized.

Some vector layer shown at two different zoom levels

This was Google Maps API’s incorporated marker clusteringprocedure.


Marker clustering


http://www.mapadacachaca.com.br/guia/

Pushpin markers and cluster markers behave differently under a click event

Thematic maps are an elegant alternative approach. It isbeing used a lot with cartographic data base servers(Google’s Fusion Tables, etc.)


Marker clustering


http://www.cartovista.com/

Thematic maps require polygon boundary layers and a data summary for each administrative entity.

Another approach to overlay geometries to customize maps isto convert zoom dependant vector overlays into tile layers forweb map servers.


Marker clustering


http://www.skimap.org/

Rasterizing vectors into tiles overcomes (maps APIs) restricitions to map different layers at different zoom levels.

PoinProc’s marker clustering service. It is a cartographicgeneralization-like approach to swap sets of markers foranother zoom dependant geometries.


Marker clustering


For low zoom levels, results are thematic map alike. Provides flexibility in click event handling.

About PoinProc

Search by map


1 Use map controls

2 Select a place from a list

4 Select location and navigate3 Preview location info

PoinProc services


About PoinProc Additional services other than marker clustering.

Lines from points Paths (lines) clustering Orthodromics generalization

You can use the internet service by filling the convenient webform. A data table is required in csv, tab, text format.

How to use PoinProc: web


About PoinProc

Latitude and longitude are required. It is desirable to give a name to eachmarker, as well as geographical entities names to summarize and separate.

The desktop application is under development.

How to use PoinProc: desktop


About PoinProc

Campos latitud, longitud

Javascript API

Scripts for Web maps APIs: easily loading different geometriesfor each zoom level.

var mapViewer = new ZoomDepViewer (mapdivID, MapClick, LoadIcons, getColour);

function MapClick(descrip) {var expla = document.getElementById('expla');var descripItems = descripTxt.split('.');var descripHtml = descripItems.join('<br/>');expla.innerHTML = descripHtml;

}

var LoadIcons = function(viewer) {var iconfolder = "www.poinproc.com/Schemas/";var icons;icons[0] = { icon: iconfolder+'point0.png',height:15,width:15 };icons[1] = { icon: iconfolder+'point1.png',height:22,width:22 };icons[2] = { icon: iconfolder+'point2.png',height:32,width:32 };return icons:

}

function getColour(code) {var fillColor = ["#963296", "#C86432", "#329696", "#48C848", "#6432C8"];var index = code % 5;return fillColor[index];

}

mapViewer.showXMLData(xmlData, viewer, useIDs); // viewer :'gmapsv3', 'bing', 'ol'


About PoinProc



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poinproc wherecamp berlin

Data & Analytics

map overlay

internet map viewers

view scale

road map

design scale

web map viewers

maps apis functionalityand

internet viewers