OpenLayers集成ECharts
作者：互联网
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：
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：
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)
标签：集成,featureType,name,stylers,value,OpenLayers,elementType,data,ECharts 来源： https://www.cnblogs.com/jiujiubashiyi/p/16530884.html