概述：
在前面的博文中讲述过基于Arcgis for js如何实现聚类统计展示，在本文中讲述如何基于openlayers实现聚类统计的效果，Arcgis for js聚类统计的博文地址为：
http://blog.csdn.net/gisshixisheng/article/details/40867989
效果：
实现关键点：
实现代码：
1、数据格式
2、设置显示样式
var style = new OpenLayers.Style({
fillColor: "#ffcc66",
strokeColor: "#ff9933",
strokeWidth: 2,
label: "${count}",
fontColor: "#333333",
fontFamily: "sans-serif",
fontWeight: "bold"
}, {
rules: [
new OpenLayers.Rule({
minScaleDenominator: 100000000,
symbolizer: {
pointRadius: 7,
fontSize: "9px"
}
}),
new OpenLayers.Rule({
maxScaleDenominator: 100000000,
minScaleDenominator: 50000000,
symbolizer: {
pointRadius: 10,
fontSize: "11px"
}
}),
new OpenLayers.Rule({
maxScaleDenominator: 50000000,
symbolizer: {
pointRadius: 13,
fontSize: "13px"
}
})
]
});3、添加矢量图层
var features = new Array();
for (var i=0; i<data.length; i++) {
features[i] = new OpenLayers.Feature.Vector(
new OpenLayers.Geometry.Point(data[i].x, data[i].y),
{
count:data[i].count,
name:data[i].name
}
);
}
var clusterLayer = new OpenLayers.Layer.Vector("Points", {
styleMap: new OpenLayers.StyleMap(style)
});
clusterLayer.addFeatures(features);
map1.addLayer(clusterLayer);程序完整代码为；
<!DOCTYPE html>
<html>
<head lang="en">
<meta charset="UTF-8">
<title>openlayers map</title>
<link rel="stylesheet" href="http://localhost/olapi/theme/default/style.css" type="text/css">
<style>
html, body{
padding:0;
margin:0;
height:100%;
width:100%;
overflow: hidden;
font-size: 12px;
}
#map1{
width: 100%;
height: 100%;
float: left;
border-right: 1px solid #000000;
}
</style>
<script src="http://localhost/olapi/OpenLayers.js"></script>
<script src="http://localhost/olapi/lib/OpenLayers/Lang/zh-CN.js"></script>
<script src="http://localhost/jquery/jquery-1.8.3.js"></script>
<script>
var map1, vectors;
OpenLayers.Feature.Vector.style['default']['strokeWidth'] = '2';
$(function(){
var bounds = new OpenLayers.Bounds(
73.45100463562233, 18.16324718764174,
134.97679764650596, 53.531943152223576
);
var options = {
controls: [],
maxExtent: bounds,
maxResolution: 0.2403351289487642,
projection: "EPSG:4326",
units: 'degrees'
};
map1 = new OpenLayers.Map('map1', options);
map1.addLayer(getWms("china"));
map1.addControl(new OpenLayers.Control.Zoom());
map1.addControl(new OpenLayers.Control.Navigation());
map1.zoomToExtent(bounds);
addCluster();
});
function getWms(layer){
return new OpenLayers.Layer.WMS(
"Geoserver layers - Tiled",
"http://localhost:8081/geoserver/lzugis/wms",
{
"LAYERS": layer,
"STYLES": '',
format: 'image/png'
},
{
buffer: 0,
displayOutsideMaxExtent: true,
isBaseLayer: true,
yx : {'EPSG:4326' : true}
}
);
}
function addCluster(){
var style = new OpenLayers.Style({
fillColor: "#ffcc66",
strokeColor: "#ff9933",
strokeWidth: 2,
label: "${count}",
fontColor: "#333333",
fontFamily: "sans-serif",
fontWeight: "bold"
}, {
rules: [
new OpenLayers.Rule({
minScaleDenominator: 100000000,
symbolizer: {
pointRadius: 7,
fontSize: "9px"
}
}),
new OpenLayers.Rule({
maxScaleDenominator: 100000000,
minScaleDenominator: 50000000,
symbolizer: {
pointRadius: 10,
fontSize: "11px"
}
}),
new OpenLayers.Rule({
maxScaleDenominator: 50000000,
symbolizer: {
pointRadius: 13,
fontSize: "13px"
}
})
]
});
var data = [{name:"乌鲁木齐",x:87.5758285931,y:43.7822116460,count:10},
{name:"拉萨",x:91.1629975040,y:29.7104204643,count:30},
{name:"西宁",x:101.797302689,y:36.5936423859,count:50},
{name:"兰州",x:103.584297498,y:36.1190864503,count:70},
{name:"成都",x:104.035508297,y:30.7141790950,count:90},
{name:"重庆",x:106.519115206,y:29.4789248520,count:60},
{name:"贵阳",x:106.668071385,y:26.4573115457,count:20}];
var features = new Array();
for (var i=0; i<data.length; i++) {
features[i] = new OpenLayers.Feature.Vector(
new OpenLayers.Geometry.Point(data[i].x, data[i].y),
{
count:data[i].count,
name:data[i].name
}
);
}
var clusterLayer = new OpenLayers.Layer.Vector("Points", {
styleMap: new OpenLayers.StyleMap(style)
});
clusterLayer.addFeatures(features);
map1.addLayer(clusterLayer);
}
</script>
</head>
<body>
<div id="map1"></div>
</body>
</html>
