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OpenLayers集成ECharts

开发技术 开发技术 2022-07-29 次浏览

1. 引言

OpenLayers是WebGIS中常用的开源JavaScript前端库,ECharts是常用的可视化开源JavaScript前端库

OpenLayers官网:OpenLayers - Welcome

ECharts官网:Apache ECharts

OpenLayers中可视化效果欠佳,集成ECharts能提升地图可视化效果

ol3Echarts是一个集成ECharts到OpenLayers中的开源JavaScript库,支持了大部分的ECharts地图

ol3Echarts的GitHub站点:sakitam-fdd/ol3Echarts: ol3Echarts | a openlayers extension to echarts (github.com)

本文基于ol3Echarts,实现在OpenLayers中使用ECharts绘制空间数据

2. 加载CDN

参考GitHub的README中的示例:sakitam-fdd/ol3Echarts: ol3Echarts | a openlayers extension to echarts (github.com)

使用以下CDN导入:

<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.css">
<script src="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.js"></script>
<script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.js"></script>
<script src="https://cdn.jsdelivr.net/npm/ol3-echarts/dist/ol3Echarts.js"></script>

3. 构建基础底图

构建基础页面,使用OpenLayers加载底图:

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.css">
    <script src="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/ol3-echarts/dist/ol3Echarts.js"></script>
    <style>
        html, body, #map {
            height: 100%;
            margin: 0;
            padding: 0;
        }
    </style>
</head>

<body>
    <div id="map"></div>
    <script>
        const map = new ol.Map({
            target: 'map',
            layers: [
                new ol.layer.Tile({
                    source: new ol.source.XYZ({
                        url: 'https://s{1-5}.geohey.com/s/mapping/midnight/all?x={x}&y={y}&z={z}&retina=&ak=ZmI0YmI5MWE4NjEyNDlkNTkxY2NmNmQ1NDYwOWI5ZmU'
                    })
                })
            ],
            view: new ol.View({
                center: [120.13066322374, 30.240018034923],
                projection: 'EPSG:4326',
                zoom: 4,
            })
        })
    </script>
</body>

</html>

实现效果如下:

OpenLayers集成ECharts

4. 构建ECharts图层

构建ECharts图层主要就是设置配置项(option)

参考官方的全国AQI示例,直接把配置项(option)复制过来使用:

var data = [
    { name: '海门', value: 9 },
    { name: '鄂尔多斯', value: 12 },
	......
];
var geoCoordMap = {
    '海门': [121.15, 31.89],
    '鄂尔多斯': [109.781327, 39.608266],
    ......
};

var convertData = function (data) {
    var res = [];
    for (var i = 0; i < data.length; i++) {
        var geoCoord = geoCoordMap[data[i].name];
        if (geoCoord) {
            res.push({
                name: data[i].name,
                value: geoCoord.concat(data[i].value)
            });
        }
    }
    return res;
};

option = {
    title: {
        text: '全国主要城市空气质量 - 百度地图',
        subtext: 'data from PM25.in',
        sublink: 'http://www.pm25.in',
        left: 'center'
    },
    tooltip: {
        trigger: 'item'
    },
    bmap: {
        center: [104.114129, 37.550339],
        zoom: 5,
        roam: true,
        mapStyle: {
            styleJson: [{
                'featureType': 'water',
                'elementType': 'all',
                'stylers': {
                    'color': '#d1d1d1'
                }
            }, {
                'featureType': 'land',
                'elementType': 'all',
                'stylers': {
                    'color': '#f3f3f3'
                }
            }, {
                'featureType': 'railway',
                'elementType': 'all',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'highway',
                'elementType': 'all',
                'stylers': {
                    'color': '#fdfdfd'
                }
            }, {
                'featureType': 'highway',
                'elementType': 'labels',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'arterial',
                'elementType': 'geometry',
                'stylers': {
                    'color': '#fefefe'
                }
            }, {
                'featureType': 'arterial',
                'elementType': 'geometry.fill',
                'stylers': {
                    'color': '#fefefe'
                }
            }, {
                'featureType': 'poi',
                'elementType': 'all',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'green',
                'elementType': 'all',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'subway',
                'elementType': 'all',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'manmade',
                'elementType': 'all',
                'stylers': {
                    'color': '#d1d1d1'
                }
            }, {
                'featureType': 'local',
                'elementType': 'all',
                'stylers': {
                    'color': '#d1d1d1'
                }
            }, {
                'featureType': 'arterial',
                'elementType': 'labels',
                'stylers': {
                    'visibility': 'off'
                }
            }, {
                'featureType': 'boundary',
                'elementType': 'all',
                'stylers': {
                    'color': '#fefefe'
                }
            }, {
                'featureType': 'building',
                'elementType': 'all',
                'stylers': {
                    'color': '#d1d1d1'
                }
            }, {
                'featureType': 'label',
                'elementType': 'labels.text.fill',
                'stylers': {
                    'color': '#999999'
                }
            }]
        }
    },
    series: [
        {
            name: 'pm2.5',
            type: 'scatter',
            coordinateSystem: 'bmap',
            data: convertData(data),
            symbolSize: function (val) {
                return val[2] / 10;
            },
            encode: {
                value: 2
            },
            label: {
                formatter: '{b}',
                position: 'right',
                show: false
            },
            itemStyle: {
                color: 'yellow',
            },
            emphasis: {
                label: {
                    show: true
                }
            }
        },
        {
            name: 'Top 5',
            type: 'effectScatter',
            coordinateSystem: 'bmap',
            data: convertData(data.sort(function (a, b) {
                return b.value - a.value;
            }).slice(0, 6)),
            symbolSize: function (val) {
                return val[2] / 10;
            },
            encode: {
                value: 2
            },
            showEffectOn: 'render',
            rippleEffect: {
                brushType: 'stroke'
            },
            hoverAnimation: true,
            label: {
                formatter: '{b}',
                position: 'right',
                show: true
            },
            itemStyle: {
                color: 'purple',
                shadowBlur: 10,
                shadowColor: '#333'
            },
            zlevel: 1
        }
    ]
};

使用ol3Echarts创建ECharts图层并添加到Map中:

const echartsLayer = new ol3Echarts(option)
echartsLayer.appendTo(map)

5. 完整代码

这里笔者修改了一下代码(配置项option),当然不修改也可以直接使用:

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Document</title>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.css">
    <script src="https://cdn.jsdelivr.net/npm/openlayers/dist/ol.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.js"></script>
    <script src="https://cdn.jsdelivr.net/npm/ol3-echarts/dist/ol3Echarts.js"></script>
    <style>
        html,
        body,
        #map {
            height: 100%;
            margin: 0;
            padding: 0;
        }
    </style>
</head>

<body>
    <div id="map"></div>
    <script>
        const map = new ol.Map({
            target: 'map',
            layers: [
                new ol.layer.Tile({
                    source: new ol.source.XYZ({
                        url: 'https://s{1-5}.geohey.com/s/mapping/midnight/all?x={x}&y={y}&z={z}&retina=&ak=ZmI0YmI5MWE4NjEyNDlkNTkxY2NmNmQ1NDYwOWI5ZmU'
                    })
                })
            ],
            view: new ol.View({
                center: [120.13066322374, 30.240018034923],
                projection: 'EPSG:4326',
                zoom: 4,
            })
        })
        var data = [
            { name: '海门', value: 9 },
            { name: '鄂尔多斯', value: 12 },
            { name: '招远', value: 12 },
            { name: '舟山', value: 12 },
            { name: '齐齐哈尔', value: 14 },
            { name: '盐城', value: 15 },
            { name: '赤峰', value: 16 },
            { name: '青岛', value: 18 },
            { name: '乳山', value: 18 },
            { name: '金昌', value: 19 },
            { name: '泉州', value: 21 },
            { name: '莱西', value: 21 },
            { name: '日照', value: 21 },
            { name: '胶南', value: 22 },
            { name: '南通', value: 23 },
            { name: '拉萨', value: 24 },
            { name: '云浮', value: 24 },
            { name: '梅州', value: 25 },
            { name: '文登', value: 25 },
            { name: '上海', value: 25 },
            { name: '攀枝花', value: 25 },
            { name: '威海', value: 25 },
            { name: '承德', value: 25 },
            { name: '厦门', value: 26 },
            { name: '汕尾', value: 26 },
            { name: '潮州', value: 26 },
            { name: '丹东', value: 27 },
            { name: '太仓', value: 27 },
            { name: '曲靖', value: 27 },
            { name: '烟台', value: 28 },
            { name: '福州', value: 29 },
            { name: '瓦房店', value: 30 },
            { name: '即墨', value: 30 },
            { name: '抚顺', value: 31 },
            { name: '玉溪', value: 31 },
            { name: '张家口', value: 31 },
            { name: '阳泉', value: 31 },
            { name: '莱州', value: 32 },
            { name: '湖州', value: 32 },
            { name: '汕头', value: 32 },
            { name: '昆山', value: 33 },
            { name: '宁波', value: 33 },
            { name: '湛江', value: 33 },
            { name: '揭阳', value: 34 },
            { name: '荣成', value: 34 },
            { name: '连云港', value: 35 },
            { name: '葫芦岛', value: 35 },
            { name: '常熟', value: 36 },
            { name: '东莞', value: 36 },
            { name: '河源', value: 36 },
            { name: '淮安', value: 36 },
            { name: '泰州', value: 36 },
            { name: '南宁', value: 37 },
            { name: '营口', value: 37 },
            { name: '惠州', value: 37 },
            { name: '江阴', value: 37 },
            { name: '蓬莱', value: 37 },
            { name: '韶关', value: 38 },
            { name: '嘉峪关', value: 38 },
            { name: '广州', value: 38 },
            { name: '延安', value: 38 },
            { name: '太原', value: 39 },
            { name: '清远', value: 39 },
            { name: '中山', value: 39 },
            { name: '昆明', value: 39 },
            { name: '寿光', value: 40 },
            { name: '盘锦', value: 40 },
            { name: '长治', value: 41 },
            { name: '深圳', value: 41 },
            { name: '珠海', value: 42 },
            { name: '宿迁', value: 43 },
            { name: '咸阳', value: 43 },
            { name: '铜川', value: 44 },
            { name: '平度', value: 44 },
            { name: '佛山', value: 44 },
            { name: '海口', value: 44 },
            { name: '江门', value: 45 },
            { name: '章丘', value: 45 },
            { name: '肇庆', value: 46 },
            { name: '大连', value: 47 },
            { name: '临汾', value: 47 },
            { name: '吴江', value: 47 },
            { name: '石嘴山', value: 49 },
            { name: '沈阳', value: 50 },
            { name: '苏州', value: 50 },
            { name: '茂名', value: 50 },
            { name: '嘉兴', value: 51 },
            { name: '长春', value: 51 },
            { name: '胶州', value: 52 },
            { name: '银川', value: 52 },
            { name: '张家港', value: 52 },
            { name: '三门峡', value: 53 },
            { name: '锦州', value: 54 },
            { name: '南昌', value: 54 },
            { name: '柳州', value: 54 },
            { name: '三亚', value: 54 },
            { name: '自贡', value: 56 },
            { name: '吉林', value: 56 },
            { name: '阳江', value: 57 },
            { name: '泸州', value: 57 },
            { name: '西宁', value: 57 },
            { name: '宜宾', value: 58 },
            { name: '呼和浩特', value: 58 },
            { name: '成都', value: 58 },
            { name: '大同', value: 58 },
            { name: '镇江', value: 59 },
            { name: '桂林', value: 59 },
            { name: '张家界', value: 59 },
            { name: '宜兴', value: 59 },
            { name: '北海', value: 60 },
            { name: '西安', value: 61 },
            { name: '金坛', value: 62 },
            { name: '东营', value: 62 },
            { name: '牡丹江', value: 63 },
            { name: '遵义', value: 63 },
            { name: '绍兴', value: 63 },
            { name: '扬州', value: 64 },
            { name: '常州', value: 64 },
            { name: '潍坊', value: 65 },
            { name: '重庆', value: 66 },
            { name: '台州', value: 67 },
            { name: '南京', value: 67 },
            { name: '滨州', value: 70 },
            { name: '贵阳', value: 71 },
            { name: '无锡', value: 71 },
            { name: '本溪', value: 71 },
            { name: '克拉玛依', value: 72 },
            { name: '渭南', value: 72 },
            { name: '马鞍山', value: 72 },
            { name: '宝鸡', value: 72 },
            { name: '焦作', value: 75 },
            { name: '句容', value: 75 },
            { name: '北京', value: 79 },
            { name: '徐州', value: 79 },
            { name: '衡水', value: 80 },
            { name: '包头', value: 80 },
            { name: '绵阳', value: 80 },
            { name: '乌鲁木齐', value: 84 },
            { name: '枣庄', value: 84 },
            { name: '杭州', value: 84 },
            { name: '淄博', value: 85 },
            { name: '鞍山', value: 86 },
            { name: '溧阳', value: 86 },
            { name: '库尔勒', value: 86 },
            { name: '安阳', value: 90 },
            { name: '开封', value: 90 },
            { name: '济南', value: 92 },
            { name: '德阳', value: 93 },
            { name: '温州', value: 95 },
            { name: '九江', value: 96 },
            { name: '邯郸', value: 98 },
            { name: '临安', value: 99 },
            { name: '兰州', value: 99 },
            { name: '沧州', value: 100 },
            { name: '临沂', value: 103 },
            { name: '南充', value: 104 },
            { name: '天津', value: 105 },
            { name: '富阳', value: 106 },
            { name: '泰安', value: 112 },
            { name: '诸暨', value: 112 },
            { name: '郑州', value: 113 },
            { name: '哈尔滨', value: 114 },
            { name: '聊城', value: 116 },
            { name: '芜湖', value: 117 },
            { name: '唐山', value: 119 },
            { name: '平顶山', value: 119 },
            { name: '邢台', value: 119 },
            { name: '德州', value: 120 },
            { name: '济宁', value: 120 },
            { name: '荆州', value: 127 },
            { name: '宜昌', value: 130 },
            { name: '义乌', value: 132 },
            { name: '丽水', value: 133 },
            { name: '洛阳', value: 134 },
            { name: '秦皇岛', value: 136 },
            { name: '株洲', value: 143 },
            { name: '石家庄', value: 147 },
            { name: '莱芜', value: 148 },
            { name: '常德', value: 152 },
            { name: '保定', value: 153 },
            { name: '湘潭', value: 154 },
            { name: '金华', value: 157 },
            { name: '岳阳', value: 169 },
            { name: '长沙', value: 175 },
            { name: '衢州', value: 177 },
            { name: '廊坊', value: 193 },
            { name: '菏泽', value: 194 },
            { name: '合肥', value: 229 },
            { name: '武汉', value: 273 },
            { name: '大庆', value: 279 }
        ];
        var geoCoordMap = {
            '海门': [121.15, 31.89],
            '鄂尔多斯': [109.781327, 39.608266],
            '招远': [120.38, 37.35],
            '舟山': [122.207216, 29.985295],
            '齐齐哈尔': [123.97, 47.33],
            '盐城': [120.13, 33.38],
            '赤峰': [118.87, 42.28],
            '青岛': [120.33, 36.07],
            '乳山': [121.52, 36.89],
            '金昌': [102.188043, 38.520089],
            '泉州': [118.58, 24.93],
            '莱西': [120.53, 36.86],
            '日照': [119.46, 35.42],
            '胶南': [119.97, 35.88],
            '南通': [121.05, 32.08],
            '拉萨': [91.11, 29.97],
            '云浮': [112.02, 22.93],
            '梅州': [116.1, 24.55],
            '文登': [122.05, 37.2],
            '上海': [121.48, 31.22],
            '攀枝花': [101.718637, 26.582347],
            '威海': [122.1, 37.5],
            '承德': [117.93, 40.97],
            '厦门': [118.1, 24.46],
            '汕尾': [115.375279, 22.786211],
            '潮州': [116.63, 23.68],
            '丹东': [124.37, 40.13],
            '太仓': [121.1, 31.45],
            '曲靖': [103.79, 25.51],
            '烟台': [121.39, 37.52],
            '福州': [119.3, 26.08],
            '瓦房店': [121.979603, 39.627114],
            '即墨': [120.45, 36.38],
            '抚顺': [123.97, 41.97],
            '玉溪': [102.52, 24.35],
            '张家口': [114.87, 40.82],
            '阳泉': [113.57, 37.85],
            '莱州': [119.942327, 37.177017],
            '湖州': [120.1, 30.86],
            '汕头': [116.69, 23.39],
            '昆山': [120.95, 31.39],
            '宁波': [121.56, 29.86],
            '湛江': [110.359377, 21.270708],
            '揭阳': [116.35, 23.55],
            '荣成': [122.41, 37.16],
            '连云港': [119.16, 34.59],
            '葫芦岛': [120.836932, 40.711052],
            '常熟': [120.74, 31.64],
            '东莞': [113.75, 23.04],
            '河源': [114.68, 23.73],
            '淮安': [119.15, 33.5],
            '泰州': [119.9, 32.49],
            '南宁': [108.33, 22.84],
            '营口': [122.18, 40.65],
            '惠州': [114.4, 23.09],
            '江阴': [120.26, 31.91],
            '蓬莱': [120.75, 37.8],
            '韶关': [113.62, 24.84],
            '嘉峪关': [98.289152, 39.77313],
            '广州': [113.23, 23.16],
            '延安': [109.47, 36.6],
            '太原': [112.53, 37.87],
            '清远': [113.01, 23.7],
            '中山': [113.38, 22.52],
            '昆明': [102.73, 25.04],
            '寿光': [118.73, 36.86],
            '盘锦': [122.070714, 41.119997],
            '长治': [113.08, 36.18],
            '深圳': [114.07, 22.62],
            '珠海': [113.52, 22.3],
            '宿迁': [118.3, 33.96],
            '咸阳': [108.72, 34.36],
            '铜川': [109.11, 35.09],
            '平度': [119.97, 36.77],
            '佛山': [113.11, 23.05],
            '海口': [110.35, 20.02],
            '江门': [113.06, 22.61],
            '章丘': [117.53, 36.72],
            '肇庆': [112.44, 23.05],
            '大连': [121.62, 38.92],
            '临汾': [111.5, 36.08],
            '吴江': [120.63, 31.16],
            '石嘴山': [106.39, 39.04],
            '沈阳': [123.38, 41.8],
            '苏州': [120.62, 31.32],
            '茂名': [110.88, 21.68],
            '嘉兴': [120.76, 30.77],
            '长春': [125.35, 43.88],
            '胶州': [120.03336, 36.264622],
            '银川': [106.27, 38.47],
            '张家港': [120.555821, 31.875428],
            '三门峡': [111.19, 34.76],
            '锦州': [121.15, 41.13],
            '南昌': [115.89, 28.68],
            '柳州': [109.4, 24.33],
            '三亚': [109.511909, 18.252847],
            '自贡': [104.778442, 29.33903],
            '吉林': [126.57, 43.87],
            '阳江': [111.95, 21.85],
            '泸州': [105.39, 28.91],
            '西宁': [101.74, 36.56],
            '宜宾': [104.56, 29.77],
            '呼和浩特': [111.65, 40.82],
            '成都': [104.06, 30.67],
            '大同': [113.3, 40.12],
            '镇江': [119.44, 32.2],
            '桂林': [110.28, 25.29],
            '张家界': [110.479191, 29.117096],
            '宜兴': [119.82, 31.36],
            '北海': [109.12, 21.49],
            '西安': [108.95, 34.27],
            '金坛': [119.56, 31.74],
            '东营': [118.49, 37.46],
            '牡丹江': [129.58, 44.6],
            '遵义': [106.9, 27.7],
            '绍兴': [120.58, 30.01],
            '扬州': [119.42, 32.39],
            '常州': [119.95, 31.79],
            '潍坊': [119.1, 36.62],
            '重庆': [106.54, 29.59],
            '台州': [121.420757, 28.656386],
            '南京': [118.78, 32.04],
            '滨州': [118.03, 37.36],
            '贵阳': [106.71, 26.57],
            '无锡': [120.29, 31.59],
            '本溪': [123.73, 41.3],
            '克拉玛依': [84.77, 45.59],
            '渭南': [109.5, 34.52],
            '马鞍山': [118.48, 31.56],
            '宝鸡': [107.15, 34.38],
            '焦作': [113.21, 35.24],
            '句容': [119.16, 31.95],
            '北京': [116.46, 39.92],
            '徐州': [117.2, 34.26],
            '衡水': [115.72, 37.72],
            '包头': [110, 40.58],
            '绵阳': [104.73, 31.48],
            '乌鲁木齐': [87.68, 43.77],
            '枣庄': [117.57, 34.86],
            '杭州': [120.19, 30.26],
            '淄博': [118.05, 36.78],
            '鞍山': [122.85, 41.12],
            '溧阳': [119.48, 31.43],
            '库尔勒': [86.06, 41.68],
            '安阳': [114.35, 36.1],
            '开封': [114.35, 34.79],
            '济南': [117, 36.65],
            '德阳': [104.37, 31.13],
            '温州': [120.65, 28.01],
            '九江': [115.97, 29.71],
            '邯郸': [114.47, 36.6],
            '临安': [119.72, 30.23],
            '兰州': [103.73, 36.03],
            '沧州': [116.83, 38.33],
            '临沂': [118.35, 35.05],
            '南充': [106.110698, 30.837793],
            '天津': [117.2, 39.13],
            '富阳': [119.95, 30.07],
            '泰安': [117.13, 36.18],
            '诸暨': [120.23, 29.71],
            '郑州': [113.65, 34.76],
            '哈尔滨': [126.63, 45.75],
            '聊城': [115.97, 36.45],
            '芜湖': [118.38, 31.33],
            '唐山': [118.02, 39.63],
            '平顶山': [113.29, 33.75],
            '邢台': [114.48, 37.05],
            '德州': [116.29, 37.45],
            '济宁': [116.59, 35.38],
            '荆州': [112.239741, 30.335165],
            '宜昌': [111.3, 30.7],
            '义乌': [120.06, 29.32],
            '丽水': [119.92, 28.45],
            '洛阳': [112.44, 34.7],
            '秦皇岛': [119.57, 39.95],
            '株洲': [113.16, 27.83],
            '石家庄': [114.48, 38.03],
            '莱芜': [117.67, 36.19],
            '常德': [111.69, 29.05],
            '保定': [115.48, 38.85],
            '湘潭': [112.91, 27.87],
            '金华': [119.64, 29.12],
            '岳阳': [113.09, 29.37],
            '长沙': [113, 28.21],
            '衢州': [118.88, 28.97],
            '廊坊': [116.7, 39.53],
            '菏泽': [115.480656, 35.23375],
            '合肥': [117.27, 31.86],
            '武汉': [114.31, 30.52],
            '大庆': [125.03, 46.58]
        };

        var convertData = function (data) {
            var res = [];
            for (var i = 0; i < data.length; i++) {
                var geoCoord = geoCoordMap[data[i].name];
                if (geoCoord) {
                    res.push({
                        name: data[i].name,
                        value: geoCoord.concat(data[i].value)
                    });
                }
            }
            return res;
        };

        option = {
            title: {
                text: '全国主要城市空气质量',
                subtext: 'data from PM25.in',
                sublink: 'http://www.pm25.in',
                left: 'center'
            },
            series: [
                {
                    name: 'pm2.5',
                    type: 'scatter',
                    coordinateSystem: 'bmap',
                    data: convertData(data),
                    symbolSize: function (val) {
                        return val[2] / 10;
                    },
                    encode: {
                        value: 2
                    },
                    label: {
                        formatter: '{b}',
                        position: 'right',
                        show: false
                    },
                    itemStyle: {
                        color: 'yellow',
                    },
                    emphasis: {
                        label: {
                            show: true
                        }
                    }
                },
                {
                    name: 'Top 5',
                    type: 'effectScatter',
                    data: convertData(data.sort(function (a, b) {
                        return b.value - a.value;
                    }).slice(0, 6)),
                    symbolSize: function (val) {
                        return val[2] / 10;
                    },
                    encode: {
                        value: 2
                    },
                    showEffectOn: 'render',
                    rippleEffect: {
                        brushType: 'stroke'
                    },
                    hoverAnimation: true,
                    label: {
                        formatter: '{b}',
                        position: 'right',
                        show: true
                    },
                    itemStyle: {
                        color: 'purple',
                        shadowBlur: 10,
                        shadowColor: '#333'
                    },
                    zlevel: 1
                }
            ]
        };
        const echartsLayer = new ol3Echarts(option)
        echartsLayer.appendTo(map)

    </script>
</body>

</html>

实现的结果如下:

OpenLayers集成ECharts

6. 参考资料

[1]sakitam-fdd/ol3Echarts: ol3Echarts | a openlayers extension to echarts (github.com)

[2]ol echarts 9/12, 19:34 (sakitam.com)

[3]Examples - Apache ECharts

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