将圆的半径(以米为单位)缩放到D3.js d3.geo.mercator map

时间:2015-07-22 20:34:56

标签: javascript d3.js svg maps geo

我正在使用D3.js和TopoJSON库在网页上的小div中呈现世界的平面SVG地图。我还拍摄了一些地理对象(多边形和圆形),并通过纬度/经度坐标在地图上绘制它们。这一切看起来都很好,但是,我在地图上绘制的圆形对象包含一个以米为单位的半径元素。我无法找到或弄清楚如何将此测量值适当地转换/缩放到SVG地图上。任何帮助将不胜感激。

绘制圆圈和设置的代码片段为:

if (formattedGeoObjects[a].shape.indexOf('circle') >= 0) {
  //plot point for circle
  svg.selectAll('.pin')
    .data(formattedGeoObjects).enter().append('circle', '.pin')
    .attr({fill: formattedGeoObjects[a].color.toString()})
    .attr('r', 5) //formattedGeoObjects[a].radius is in meters
    .attr('transform', 'translate(' +
      projection([
        formattedGeoObjects[a].location[0],
        formattedGeoObjects[a].location[1]
      ]) + ')'
    );
}

JSFiddle链接,用于代码的精简版:https://jsfiddle.net/vnrL0fdc/7/

以下是完整的参考代码...

完成大部分工作的功能:

setupMap: function(mapJson, theElement, geoObject, colorCb, normalizeCb) {
    var width = 200;
    var height = 120;

    //define projection of spherical coordinates to Cartesian plane
    var projection = d3.geo.mercator().scale((width + 1) / 2 / Math.PI).translate([width / 2, height / 2]);

    //define path that takes projected geometry from above and formats it appropriately
    var path = d3.geo.path().projection(projection);

    //select the canvas-svg div and apply styling attributes
    var svg =
      d3.select('#' + theElement + ' .canvas-svg').append('svg')
        .attr('width', width)
        .attr('height', height)
        .attr('class', 'ocean');

    //convert the topoJSON back to GeoJSON
    var countries = topojson.feature(mapJson, mapJson.objects.countries).features;

    //give each country its own path element and add styling
    svg.selectAll('.countries')
      .data(countries).enter().append('path')
      .attr('class', 'country')
      .attr('d', path);

    //add borders around all countries with mesh
    svg.append('path')
      .datum(topojson.mesh(mapJson, mapJson.objects.countries, function() {
        return true;
      }))
      .attr('d', path)
      .attr('class', 'border');

    //if shape data exists, draw it on the map
    if (geoObject !== null && geoObject.length !== 0) {
      //normalize geoObject into format needed for d3 arc functionality and store each shapes color
      var formattedGeoObjects = normalizeCb(geoObject, colorCb);

      for (a = 0; a < formattedGeoObjects.length; a++) {
        if (formattedGeoObjects[a].shape.indexOf('polygon') >= 0) {
          for (b = 0; b < formattedGeoObjects[a].lines.length; b++) {
            //plot point for polygon
            svg.selectAll('.pin')
              .data(formattedGeoObjects).enter().append('circle', '.pin')
              .style({fill: formattedGeoObjects[a].color.toString()}).attr('r', 2)
              .attr('transform', 'translate(' +
                projection([
                  formattedGeoObjects[a].lines[b].coordinates[0][0],
                  formattedGeoObjects[a].lines[b].coordinates[0][1]
                ]) + ')'
              );
          }
          //draw lines for polygon
          svg.append('g').selectAll('.arc')
            .data(formattedGeoObjects[a].lines).enter().append('path')
            .attr({d: path})
            .style({
              stroke: formattedGeoObjects[a].color.toString(),
              'stroke-width': '1px'
            });
        }
        if (formattedGeoObjects[a].shape.indexOf('circle') >= 0) {
          //plot point for circle
          svg.selectAll('.pin')
            .data(formattedGeoObjects).enter().append('circle', '.pin')
            .attr({fill: formattedGeoObjects[a].color.toString()})
            .attr('r', 5)
            .attr('transform', 'translate(' +
              projection([
                formattedGeoObjects[a].location[0],
                formattedGeoObjects[a].location[1]
              ]) + ')'
            );
        }
      }
    }
  }

以下是formattedGeoObjects的缩写版本:

[
  {
    "shape": "polygon0",
    "color": "#000000",
    "lines": [
      {
        "type": "LineString",
        "coordinates": [
          [
            -24.9609375,
            36.5625
          ],
          [
            -24.9609375,
            55.1953125
          ]
        ]
      }
      ..... more coords
    ]
  },
  {
    "shape": "polygon1",
    "color": "#006600",
    "lines": [
      {
        "type": "LineString",
        "coordinates": [
          [
            -42.1875,
            26.3671875
          ],
          [
            -71.71875,
            7.734375
          ]
        ]
      }
      ..... more coordindates
    ]
  },
  {
    "shape": "circle2",
    "color": "#FF0000",
    "location": [
      13.359375,
      31.640625
    ],
    "radius": 1881365.33
  }
]

最后,CSS / HTML:

.canvas-svg {
  .ocean {
    background: #85E0FF;
  }
  .country {
    fill: #FFFFFF;
  }
  .border {
    fill: none;
    stroke: #777;
    stroke-width: .5;
  }
}

<div class="canvas-svg"></div>

2 个答案:

答案 0 :(得分:1)

我的一位同事通过向我展示一种更为简单的方法来帮助我(仅供参考 - 圈子中心的纬度/经度有更新)。在画布上绘制两个点并计算距离以找到比例的工作并且是准确的 - 但是使用图像中的总像素和世界的总面积,使用下面的代码片段和JSFiddle,有一种更简单的方法。 :

this.changeName

使用JSFiddle:https://jsfiddle.net/vnrL0fdc/15/

答案 1 :(得分:0)

所以,我“想”我找到了一种方法来将半径(以米为单位)缩放到笛卡尔平面d3地图上的像素。我可能会比这更复杂 - 但我不知道该怎么做。

地图的高度,宽度和投影定义为:

var width = 200;
var height = 120;
var projection = 
    d3.geo.mercator()
    .scale((width + 1) / 2 / Math.PI)
    .translate([width / 2, height / 2]);

我在地图上绘制的地理对象包含多个点的纬度/经度坐标。通过搜索stackoverflow,我找到了一个距离公式:

d = sqrt((x2 - x1)^2 + (y2 - y1)^2)

公式需要笛卡尔平面(x1,y1)和(x2,y2)两个点。我选择了圆的点和一个多边形点,纬度/经度坐标如下:

Lat/Long for polygon1, point1: 36.5625, -24.9609375
Lat/Long for circle: 31.640625, 13.359375

我使用以下网站查看上面两个坐标之间的距离 - http://www.freemaptools.com/how-far-is-it-between.htm

Miles between the two coordinates on the map are: 3020.207

然后我通过以下方法找到了笛卡尔平面上两个纬度/经度坐标的投影坐标(x,y):

projection([long,lat])
X/Y for polygon1, point1: 86.0634765625, 38.040230671805666
X/Y for circle: 107.458984375, 41.36090550209383

因此,我将这些值插入公式中以计算两点之间的像素距离:

d = sqrt ( (107.458984375 - 86.0634765625)^2 + (41.36090550209383 - 38.040230671805666)^2  )
result = 21.651665891641176 pixels
miles per pixel = 139.49074473599643 (calculated by: 3020.207/21.651665891641176)
meters per pixel = 224488.5930964074505 (calculated by 139.49074473599643 * 1609.34)

使用JSFiddle:https://jsfiddle.net/vnrL0fdc/8/

这似乎是将米缩放到墨卡托地图投影的极其迂回的方式。如果有人有一个更简单的解决方案 - 请分享!