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谷歌markercluster

2024-11-13 11:36:02   202人阅读

我们有时候需要观察地图 不同地方数据的所在范围和分布密集情况，热力图和聚合点的使用无疑是最好的选择。

1.首先说说百度地图，只做国内的地图可以使用百度地图的海量点和热力图还是蛮好用的。

a.海量点的最大好处是加载很多数据点的情况下不卡顿。

b.如果是画mark在地图上，当点多的时候，会很卡。

c.我之所以用谷歌地图的热力图，是因为我发现百度地图的热力图没有叠加功能，满足不了我的需求。比如说我想了解全国姓张，李，王的人的对比分布，我想要姓张的区域显示红色，姓李的显示蓝色，姓王的显示橙色。这个需求百度地图无法满足我，但是谷歌可以。

2.说说谷歌地图，谷歌地图的热力图我就不说了，https://developers.google.com/maps/documentation/javascript/examples/        这里面有实例的。

a.谷歌地图支持热力图叠加，但是没有海量点，这一点让我很难过，如果全部画marker的话，数据点太多，加载太卡

b.这就用到了谷歌聚合点，如图

技术分享

技术分享

3.代码实例，主要看看引用了哪些个文件，我是从      https://github.com/Leaflet/Leaflet.markercluster    找到的下载包和实例

 

<!DOCTYPE html>
<html>
<head>
<title>Leaflet debug page</title>

<link rel="stylesheet" href="https://unpkg.com/leaflet@1.0.3/dist/leaflet.css" integrity="sha512-07I2e+7D8p6he1SIM+1twR5TIrhUQn9+I6yjqD53JQjFiMf8EtC93ty0/5vJTZGF8aAocvHYNEDJajGdNx1IsQ==" crossorigin="" />
<script src="https://unpkg.com/leaflet@1.0.3/dist/leaflet-src.js" integrity="sha512-WXoSHqw/t26DszhdMhOXOkI7qCiv5QWXhH9R7CgvgZMHz1ImlkVQ3uNsiQKu5wwbbxtPzFXd1hK4tzno2VqhpA==" crossorigin=""></script>
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" href="http://www.mamicode.com/screen.css" />

<link rel="stylesheet" href="http://www.mamicode.com/dist/MarkerCluster.css" />
<link rel="stylesheet" href="http://www.mamicode.com/dist/MarkerCluster.Default.css" />
<script src="http://www.mamicode.com/dist/leaflet.markercluster-src.js"></script>
</head>
<body>

<div id="map"></div>
<button id="populate">Populate 1 marker</button>
<button id="remove">Remove 1 marker</button>

<script type="text/javascript">

var tiles = L.tileLayer(‘https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png‘, {
maxZoom: 18,
attribution: ‘&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors‘
}),
latlng = new L.LatLng(50.5, 30.51);

var map = new L.Map(‘map‘, {center: latlng, zoom: 15, layers: [tiles]});

var markers = new L.MarkerClusterGroup();
var markersList = [];

function populate() {
for (var i = 0; i < 100; i++) {
var m = new L.Marker(getRandomLatLng(map));
markersList.push(m);
markers.addLayer(m);
}
return false;
}
function populateRandomVector() {
for (var i = 0, latlngs = [], len = 20; i < len; i++) {
latlngs.push(getRandomLatLng(map));
}
var path = new L.Polyline(latlngs);
map.addLayer(path);
}
function getRandomLatLng(map) {
var bounds = map.getBounds(),
southWest = bounds.getSouthWest(),
northEast = bounds.getNorthEast(),
lngSpan = northEast.lng - southWest.lng,
latSpan = northEast.lat - southWest.lat;

return new L.LatLng(
southWest.lat + latSpan * Math.random(),
southWest.lng + lngSpan * Math.random());
}

markers.on(‘clusterclick‘, function (a) {
alert(‘cluster ‘ + a.layer.getAllChildMarkers().length);
});
markers.on(‘click‘, function (a) {
alert(‘marker ‘ + a.layer);
});

populate();
map.addLayer(markers);

L.DomUtil.get(‘populate‘).onclick = function () {
var bounds = map.getBounds(),
southWest = bounds.getSouthWest(),
northEast = bounds.getNorthEast(),
lngSpan = northEast.lng - southWest.lng,
latSpan = northEast.lat - southWest.lat;
var m = new L.Marker(new L.LatLng(
southWest.lat + latSpan * 0.5,
southWest.lng + lngSpan * 0.5));
markersList.push(m);
markers.addLayer(m);
};
L.DomUtil.get(‘remove‘).onclick = function () {
markers.removeLayer(markersList.pop());
};
</script>
</body>
</html>

谷歌markercluster


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