ui.Chart.array.values
函数提供了一种从 ee.Array
和 ee.List
对象渲染图表的方法。
以下示例依赖于使用 ee.Reducer.toList()
Reducer 对图像波段和图像元数据进行缩减生成的数组和列表数据。请注意,ui.Chart.array.values
可以绘制沿给定轴具有相同长度的任意一组列表和/或数组。
ee.Array
区域散点图
ee.Reducer.toList()
通过缩减图片区域生成一个像素值列表字典,其中每个列表对应给定图片中的每个波段。在这里,它用于从 MODIS 图像中提取与森林生态区域相交的像素的红色、近红外和短波红外反射率值列表。红色反射率值绘制到 x 轴,近红外和短波红外值绘制到 y 轴。
projects/google/charts_feature_example 素材资源在此示例中用于描绘森林生态区,仅供演示之用。它由三个生态区多边形组成,其中包含用于描述气候正常值的属性。
Code Editor (JavaScript)
// Import the example feature collection and subset the forest feature. var forest = ee.FeatureCollection('projects/google/charts_feature_example') .filter(ee.Filter.eq('label', 'Forest')); // Define a MODIS surface reflectance composite. var modisSr = ee.ImageCollection('MODIS/006/MOD09A1') .filter(ee.Filter.date('2018-06-01', '2018-09-01')) .select('sur_refl_b0[0-7]') .mean(); // Reduce MODIS reflectance bands by forest region; get a dictionary with // band names as keys, pixel values as lists. var pixelVals = modisSr.reduceRegion( {reducer: ee.Reducer.toList(), geometry: forest.geometry(), scale: 2000}); // Convert NIR and SWIR value lists to an array to be plotted along the y-axis. var yValues = pixelVals.toArray(['sur_refl_b02', 'sur_refl_b06']); // Get the red band value list; to be plotted along the x-axis. var xValues = ee.List(pixelVals.get('sur_refl_b01')); // Define the chart and print it to the console. var chart = ui.Chart.array.values({array: yValues, axis: 1, xLabels: xValues}) .setSeriesNames(['NIR', 'SWIR']) .setOptions({ title: 'Relationship Among Spectral Bands for Forest Pixels', colors: ['1d6b99', 'cf513e'], pointSize: 4, dataOpacity: 0.4, hAxis: { 'title': 'Red reflectance (x1e4)', titleTextStyle: {italic: false, bold: true} }, vAxis: { 'title': 'Reflectance (x1e4)', titleTextStyle: {italic: false, bold: true} } }); print(chart);
ee.List
区域散点图
您可以使用 ui.Chart.array.values
函数绘制两个列表对象。基于上一个示例,表示红色和 SWIR 反射率的 x 轴和 y 轴值列表将呈现为散点图。
Code Editor (JavaScript)
// Get Red and SWIR value lists; to be plotted along x and y axes, respectively. // Note that the pixelVals object is defined in the previous code block. var x = ee.List(pixelVals.get('sur_refl_b01')); var y = ee.List(pixelVals.get('sur_refl_b06')); // Define the chart and print it to the console. var chart = ui.Chart.array.values({array: y, axis: 0, xLabels: x}).setOptions({ title: 'Relationship Among Spectral Bands for Forest Pixels', colors: ['cf513e'], hAxis: { title: 'Red reflectance (x1e4)', titleTextStyle: {italic: false, bold: true} }, vAxis: { title: 'SWIR reflectance (x1e4)', titleTextStyle: {italic: false, bold: true} }, pointSize: 4, dataOpacity: 0.4, legend: {position: 'none'}, }); print(chart);
ee.List
样线图
ee.Reducer.toList()
通过图片区域缩减功能生成一个像素值列表字典,每个图像波段对应一个列表。如果区域是线条(如本例所示),则可以在感兴趣的图片中将纬度和经度带作为带添加时生成地理横断面。在这里,沿着样条线提取经度和海拔像素值列表作为单独的变量,并分别绘制到 x 轴和 y 轴。
Code Editor (JavaScript)
// Define a line across the Olympic Peninsula, USA. var transect = ee.Geometry.LineString([[-122.8, 47.8], [-124.5, 47.8]]); // Define a pixel coordinate image. var latLonImg = ee.Image.pixelLonLat(); // Import a digital surface model and add latitude and longitude bands. var elevImg = ee.Image('JAXA/ALOS/AW3D30/V2_2').select('AVE_DSM').addBands(latLonImg); // Reduce elevation and coordinate bands by transect line; get a dictionary with // band names as keys, pixel values as lists. var elevTransect = elevImg.reduceRegion({ reducer: ee.Reducer.toList(), geometry: transect, scale: 1000, }); // Get longitude and elevation value lists from the reduction dictionary. var lon = ee.List(elevTransect.get('longitude')); var elev = ee.List(elevTransect.get('AVE_DSM')); // Sort the longitude and elevation values by ascending longitude. var lonSort = lon.sort(lon); var elevSort = elev.sort(lon); // Define the chart and print it to the console. var chart = ui.Chart.array.values({array: elevSort, axis: 0, xLabels: lonSort}) .setOptions({ title: 'Elevation Profile Across Longitude', hAxis: { title: 'Longitude', viewWindow: {min: -124.50, max: -122.8}, titleTextStyle: {italic: false, bold: true} }, vAxis: { title: 'Elevation (m)', titleTextStyle: {italic: false, bold: true} }, colors: ['1d6b99'], lineSize: 5, pointSize: 0, legend: {position: 'none'} }); print(chart);
应用 .setChartType('AreaChart')
以在线条下方添加阴影:
print(chart.setChartType('AreaChart'));
ee.List
元数据散点图
ee.Reducer.toList()
通过集合属性缩减功能会生成一个包含属性值列表的字典,每个所选属性对应一个列表。在这里,系统会根据一组 Landsat 8 图像生成云量和几何 RMSE 属性列表,并将其作为单独的变量。云量变量沿 x 轴绘制,几何 RMSE 沿 y 轴绘制。
Code Editor (JavaScript)
// Import a Landsat 8 collection and filter to a single path/row. var col = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2') .filter(ee.Filter.expression('WRS_PATH == 45 && WRS_ROW == 30')); // Reduce image properties to a series of lists; one for each selected property. var propVals = col.reduceColumns({ reducer: ee.Reducer.toList().repeat(2), selectors: ['CLOUD_COVER', 'GEOMETRIC_RMSE_MODEL'] }) .get('list'); // Get selected image property value lists; to be plotted along x and y axes. var x = ee.List(ee.List(propVals).get(0)); var y = ee.List(ee.List(propVals).get(1)); // Define the chart and print it to the console. var chart = ui.Chart.array.values({array: y, axis: 0, xLabels: x}) .setChartType('ScatterChart') .setOptions({ title: 'Landsat 8 Image Collection Metadata (045030)', colors: ['96356f'], hAxis: { title: 'Cloud cover (%)', titleTextStyle: {italic: false, bold: true} }, vAxis: { title: 'Geometric RMSE (m)', titleTextStyle: {italic: false, bold: true} }, pointSize: 5, dataOpacity: 0.6, legend: {position: 'none'}, }); print(chart);
ee.List
映射的函数散点图和折线图
对 x 值列表应用函数,以计算对应的 y 值列表。在这里,sin()
函数会映射到 x 轴值列表,以生成相应的 y 轴值列表。绘制 x 列表和 y 列表后,系统会显示正弦波的示例。
Code Editor (JavaScript)
// Define a sequence from -2pi to +2pi in 50 increments. var start = -2 * Math.PI; var end = 2 * Math.PI; var points = ee.List.sequence(start, end, null, 50); // Evaluate the sin() function for each value in the points sequence. var values = points.map(function(val) { return ee.Number(val).sin(); }); // Define the chart and print it to the console. var chart = ui.Chart.array.values({array: values, axis: 0, xLabels: points}) .setOptions({ title: 'Sine Function', hAxis: { title: 'radians', viewWindowMode: 'maximized', ticks: [ {v: start, f: '-2π'}, {v: -Math.PI, f: '-π'}, {v: 0, f: '0'}, {v: Math.PI, f: 'π'}, {v: end, f: '2π'} ], titleTextStyle: {italic: false, bold: true} }, vAxis: { title: 'sin(x)', titleTextStyle: {italic: false, bold: true} }, colors: ['39a8a7'], lineWidth: 3, pointSize: 7, viewWindow: {min: start, max: end}, legend: {position: 'none'} }); print(chart);