OpenLayers集成ECharts
2022/7/29 6:22:50
本文主要是介绍OpenLayers集成ECharts,对大家解决编程问题具有一定的参考价值,需要的程序猿们随着小编来一起学习吧!
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)
[3]Examples - Apache ECharts
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