cesium克里金插值示例，html,三维开发实例前端开发_cesium插值,cesium克里金插值资源-CSDN下载

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克里金插值

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在IT行业中，尤其是在前端开发和三维可视化领域，`Cesium`是一个非常重要的开源库，它提供了强大的3D地球渲染和地理空间数据展示功能。本文将深入探讨`Cesium`库中的克里金（Kriging）插值方法，并结合HTML前端开发的实例，帮助你理解和应用这一技术。克里金插值是一种统计学上的空间插值方法，广泛用于地理信息系统（GIS）中，用于估算未知点的数据值，基于已知点的数据分布。它通过考虑数据间的空间相关性（即“距离衰减”），提供了一种预测空间变量的方法。在`Cesium`中，克里金插值可以帮助我们创建连续的、平滑的3D地形或数据表面，这对于环境分析、地质建模、气候研究等具有重要意义。我们需要了解如何在`Cesium`中引入克里金插值。通常，这需要借助JavaScript库，如`geostat-js`，它提供了克里金插值算法的实现。在HTML文件中，我们可以通过`<script>`标签引入这些库，并确保它们在`Cesium`加载后执行，以避免加载顺序问题。 ```html <script src="https://unpkg.com/cesium@latest/Cesium.js"></script> <script src="https://unpkg.com/geostat-js@latest/dist/index.min.js"></script> ``` 接下来，我们需要准备数据。克里金插值需要一组已知位置和值的点数据。这些数据可以是JSON格式，包含坐标（经度、纬度和高度）和对应的值。例如： ```json [ { "lon": -122.084, "lat": 37.421, "height": 50, "value": 10 }, { "lon": -122.083, "lat": 37.422, "height": 60, "value": 12 }, ... ] ``` 然后，我们可以使用`geostat-js`的`kriging`函数进行插值计算，得到一个插值模型。这个模型可以根据新的坐标点进行预测： ```javascript const data = ... // 从JSON加载数据 const krigingModel = geostat.kriging(data, 'value', { variogramModel: 'linear', maxDistance: 100000, // 设置最大距离 }); // 预测新的点 const prediction = krigingModel.predict([-122.085, 37.421, 55]); console.log(prediction); ``` 我们将插值结果应用到`Cesium`的3D场景中。我们可以创建一个新的`Cesium.Entity`，其`position`属性由预测值确定，并使用`Cesium.Color`表示插值结果的强度： ```javascript const viewer = new Cesium.Viewer('cesiumContainer'); const entity = new Cesium.Entity({ position: Cesium.Cartesian3.fromDegrees(...prediction.lonlat, prediction.value), point: { color: Cesium.Color.fromBytes(255, 0, 0, Math.floor(prediction.value * 255)), pixelSize: 10, }, }); viewer.entities.add(entity); viewer.zoomTo(entity); ``` 这个例子展示了如何在HTML前端环境中使用`Cesium`和克里金插值技术来创建一个3D点，其位置和颜色根据插值结果动态调整。当然，实际应用可能需要更复杂的插值表面，这需要对多个点进行预测并绘制在`Cesium`的3D地形上。通过这种方式，你可以实现更精细的空间数据分析和视觉化效果。在实践中，还可以根据需求调整克里金插值的参数，比如选择不同的变异性模型（如线性、指数、高斯等），设置最大插值距离，以及处理异常值等。这将影响插值的精度和结果的平滑程度。同时，结合GIS数据处理工具，如`GeoJSON`、`TopoJSON`等，可以进一步优化数据输入和输出流程，使整个过程更加高效和灵活。

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cesium克里金插值.zip （6个子文件）

克里金插值

克里金插值.rar 28KB

克里金插值

bounds.geojson 24KB

kriging.js 14KB

data.js 112KB

bounds.js 22KB

温度插值.html 6KB

<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=Edge,chrome=1"> <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, minimum-scale=1, user-scalable=no"> <title>温度插值</title> <script src="https://cesiumjs.org/releases/1.57/Build/Cesium/Cesium.js"></script> <link href="https://cesiumjs.org/releases/1.57/Build/Cesium/Widgets/widgets.css" rel="stylesheet"> <style> html, body, #cesiumContainer { width: 100%; height: 100%; margin: 0; padding: 0; overflow: hidden; background-color: #000000; } </style> <script src="kriging.js"></script> <script src="data.js"></script> <script src="bounds.js"></script> </head> <body> <canvas id="canvasMap" style="display:none;"></canvas> <div id="cesiumContainer"> </div> <script> var viewer = new Cesium.Viewer('cesiumContainer', { imageryProvider: new Cesium.UrlTemplateImageryProvider({ url: 'http://www.google.cn/maps/vt?lyrs=s@716&x={x}&y={y}&z={z}' }) }); Cesium.Camera.DEFAULT_VIEW_RECTANGLE = Cesium.Rectangle.fromDegrees(73.0, 3.0, 135.0, 53.0); viewer.camera.flyHome(5); viewer.dataSources.add(Cesium.GeoJsonDataSource.load('./bounds.geojson', { stroke: Cesium.Color.HOTPINK, fill: Cesium.Color.PINK.withAlpha(0.1), strokeWidth: 1 })); function loadkriging() { var canvas = document.getElementById("canvasMap"); canvas.width = 2000; canvas.height = 2000; var n = tempture.length; var t = []; var x = []; var y = []; for (var i = 0; i < n; i++) { t.push(tempture[i].properties.Temperatur); // 权重值 x.push(tempture[i].geometry.coordinates[0]); // x y.push(tempture[i].geometry.coordinates[1]); // y } var variogram = kriging.train(t, x, y, "exponential", 0, 100); var grid = kriging.grid(bounds, variogram, 0.05); var colors = ["#00A600", "#01A600", "#03A700", "#04A700", "#05A800", "#07A800", "#08A900", "#09A900", "#0BAA00", "#0CAA00", "#0DAB00", "#0FAB00", "#10AC00", "#12AC00", "#13AD00", "#14AD00", "#16AE00", "#17AE00", "#19AF00", "#1AAF00", "#1CB000", "#1DB000", "#1FB100", "#20B100", "#22B200", "#23B200", "#25B300", "#26B300", "#28B400", "#29B400", "#2BB500", "#2CB500", "#2EB600", "#2FB600", "#31B700", "#33B700", "#34B800", "#36B800", "#37B900", "#39B900", "#3BBA00", "#3CBA00", "#3EBB00", "#3FBB00", "#41BC00", "#43BC00", "#44BD00", "#46BD00", "#48BE00", "#49BE00", "#4BBF00", "#4DBF00", "#4FC000", "#50C000", "#52C100", "#54C100", "#55C200", "#57C200", "#59C300", "#5BC300", "#5DC400", "#5EC400", "#60C500", "#62C500", "#64C600", "#66C600", "#67C700", "#69C700", "#6BC800", "#6DC800", "#6FC900", "#71C900", "#72CA00", "#74CA00", "#76CB00", "#78CB00", "#7ACC00", "#7CCC00", "#7ECD00", "#80CD00", "#82CE00", "#84CE00", "#86CF00", "#88CF00", "#8AD000", "#8BD000", "#8DD100", "#8FD100", "#91D200", "#93D200", "#95D300", "#97D300", "#9AD400", "#9CD400", "#9ED500", "#A0D500", "#A2D600", "#A4D600", "#A6D700", "#A8D700", "#AAD800", "#ACD800", "#AED900", "#B0D900", "#B2DA00", "#B5DA00", "#B7DB00", "#B9DB00", "#BBDC00", "#BDDC00", "#BFDD00", "#C2DD00", "#C4DE00", "#C6DE00", "#C8DF00", "#CADF00", "#CDE000", "#CFE000", "#D1E100", "#D3E100", "#D6E200", "#D8E200", "#DAE300", "#DCE300", "#DFE400", "#E1E400", "#E3E500", "#E6E600", "#E6E402", "#E6E204", "#E6E105", "#E6DF07", "#E6DD09", "#E6DC0B", "#E6DA0D", "#E6D90E", "#E6D710", "#E6D612", "#E7D414", "#E7D316", "#E7D217", "#E7D019", "#E7CF1B", "#E7CE1D", "#E7CD1F", "#E7CB21", "#E7CA22", "#E7C924", "#E8C826", "#E8C728", "#E8C62A", "#E8C52B", "#E8C42D", "#E8C32F", "#E8C231", "#E8C133", "#E8C035", "#E8BF36", "#E9BE38", "#E9BD3A", "#E9BC3C", "#E9BB3E", "#E9BB40", "#E9BA42", "#E9B943", "#E9B945", "#E9B847", "#E9B749", "#EAB74B", "#EAB64D", "#EAB64F", "#EAB550", "#EAB552", "#EAB454", "#EAB456", "#EAB358", "#EAB35A", "#EAB35C", "#EBB25D", "#EBB25F", "#EBB261", "#EBB263", "#EBB165", "#EBB167", "#EBB169", "#EBB16B", "#EBB16C", "#EBB16E", "#ECB170", "#ECB172", "#ECB174", "#ECB176", "#ECB178", "#ECB17A", "#ECB17C", "#ECB17E", "#ECB27F", "#ECB281", "#EDB283", "#EDB285", "#EDB387", "#EDB389", "#EDB38B", "#EDB48D", "#EDB48F", "#EDB591", "#EDB593", "#EDB694", "#EEB696", "#EEB798", "#EEB89A", "#EEB89C", "#EEB99E", "#EEBAA0", "#EEBAA2", "#EEBBA4", "#EEBCA6", "#EEBDA8", "#EFBEAA", "#EFBEAC", "#EFBFAD", "#EFC0AF", "#EFC1B1", "#EFC2B3", "#EFC3B5", "#EFC4B7", "#EFC5B9", "#EFC7BB", "#F0C8BD", "#F0C9BF", "#F0CAC1", "#F0CBC3", "#F0CDC5", "#F0CEC7", "#F0CFC9", "#F0D1CB", "#F0D2CD", "#F0D3CF", "#F1D5D1", "#F1D6D3", "#F1D8D5", "#F1D9D7", "#F1DBD8", "#F1DDDA", "#F1DEDC", "#F1E0DE", "#F1E2E0", "#F1E3E2", "#F2E5E4", "#F2E7E6", "#F2E9E8", "#F2EBEA", "#F2ECEC", "#F2EEEE", "#F2F0F0", "#F2F2F2"]; kriging.plot(canvas, grid, [73.4766, 135.088], [18.1055, 53.5693], colors); } function returnImgae() { var mycanvas = document.getElementById("canvasMap"); return mycanvas.toDataURL("image/png"); } loadkriging(); var temptureLayer = viewer.imageryLayers.addImageryProvider(new Cesium.SingleTileImageryProvider({ url: returnImgae(), rectangle: new Cesium.Rectangle( Cesium.Math.toRadians(73.4766), Cesium.Math.toRadians(18.1055), Cesium.Math.toRadians(135.088), Cesium.Math.toRadians(53.5693) ) })); temptureLayer.alpha = 0.4 </script> </body> </html>

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