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ee.Image.arrayFlatten
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
将形状相同的多维像素的单波段图片转换为标量像素的图片,其中每个数组元素对应一个波段。
用法 | 返回 |
---|
Image.arrayFlatten(coordinateLabels, separator) | 图片 |
参数 | 类型 | 详细信息 |
---|
此:image | 图片 | 要展平的多维像素的图片。 |
coordinateLabels | 列表 | 每个轴上每个位置的名称。例如,如果一个 2x2 数组的轴分别表示“天”和“颜色”,则其标签可能为 [['monday', 'tuesday'], ['red', 'green']],从而生成“monday_red”“monday_green”“tuesday_red”和“tuesday_green”等频段名称。 |
separator | 字符串,默认值:“_” | 每个频段名称中数组标签之间的分隔符。 |
示例
代码编辑器 (JavaScript)
// A function to print arrays for a selected pixel in the following examples.
function sampArrImg(arrImg) {
var point = ee.Geometry.Point([-121, 42]);
return arrImg.sample(point, 500).first().get('array');
}
// A 1D array image.
var arrayImg1D = ee.Image([0, 1, 2]).toArray();
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2]
// Define image band names for a 1D array image with 3 rows. You are labeling
// all rows and columns using a list of lists; the 1st sub list defines labels
// for array rows and the 2nd (if applicable) defines labels for array columns.
var bandNames1D = [['row0', 'row1', 'row2']];
// Flatten the 1D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 0 columns,
// so the result will be a 3-band image.
var imgFrom1Darray = arrayImg1D.arrayFlatten(bandNames1D);
print('Image from 1D array', imgFrom1Darray);
// Make a 2D array image by repeating the 1D array on 2-axis.
var arrayImg2D = arrayImg1D.arrayRepeat(1, 2);
print('2D array image (pixel)', sampArrImg(arrayImg2D));
// [[0, 0],
// [1, 1],
// [2, 2]]
// Define image band names for a 2D array image with 3 rows and 2 columns.
// Recall that you are labeling all rows and columns using a list of lists;
// The 1st sub list defines labels for array rows and the 2nd (if applicable)
// defines labels for array columns.
var bandNames2D = [['row0', 'row1', 'row2'], ['col0', 'col1']];
// Flatten the 2D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 2 columns,
// so the result will be a 6-band image.
var imgFrom2Darray = arrayImg2D.arrayFlatten(bandNames2D);
print('Image from 2D array', imgFrom2Darray);
Python 设置
如需了解 Python API 和如何使用 geemap
进行交互式开发,请参阅
Python 环境页面。
import ee
import geemap.core as geemap
Colab (Python)
# A function to print arrays for a selected pixel in the following examples.
def samp_arr_img(arr_img):
point = ee.Geometry.Point([-121, 42])
return arr_img.sample(point, 500).first().get('array')
# A 1D array image.
array_img_1d = ee.Image([0, 1, 2]).toArray()
print('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())
# [0, 1, 2]
# Define image band names for a 1D array image with 3 rows. You are labeling
# all rows and columns using a list of lists; the 1st sub list defines labels
# for array rows and the 2nd (if applicable) defines labels for array columns.
band_names_1d = [['row0', 'row1', 'row2']]
# Flatten the 1D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 0 columns,
# so the result will be a 3-band image.
img_from_1d_array = array_img_1d.arrayFlatten(band_names_1d)
print('Image from 1D array:', img_from_1d_array.getInfo())
# Make a 2D array image by repeating the 1D array on 2-axis.
array_img_2d = array_img_1d.arrayRepeat(1, 2)
print('2D array image (pixel):', samp_arr_img(array_img_2d).getInfo())
# [[0, 0],
# [1, 1],
# [2, 2]]
# Define image band names for a 2D array image with 3 rows and 2 columns.
# Recall that you are labeling all rows and columns using a list of lists;
# The 1st sub list defines labels for array rows and the 2nd (if applicable)
# defines labels for array columns.
band_names_2d = [['row0', 'row1', 'row2'], ['col0', 'col1']]
# Flatten the 2D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 2 columns,
# so the result will be a 6-band image.
img_from_2d_array = array_img_2d.arrayFlatten(band_names_2d)
print('Image from 2D array:', img_from_2d_array.getInfo())
如未另行说明,那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可,并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情,请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC):2025-07-26。
[null,null,["最后更新时间 (UTC):2025-07-26。"],[[["\u003cp\u003e\u003ccode\u003eImage.arrayFlatten\u003c/code\u003e transforms an image containing multidimensional pixel arrays into a multi-band image with scalar pixel values.\u003c/p\u003e\n"],["\u003cp\u003eEach element of the input array becomes a separate band in the output image.\u003c/p\u003e\n"],["\u003cp\u003eUsers can specify custom names for the output bands using the \u003ccode\u003ecoordinateLabels\u003c/code\u003e parameter.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eseparator\u003c/code\u003e parameter allows for customization of the delimiter used in band names derived from array indices.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for working with data structured as arrays within an image, such as time series or multi-spectral data organized in matrices.\u003c/p\u003e\n"]]],[],null,["# ee.Image.arrayFlatten\n\nConverts a single-band image of equal-shape multidimensional pixels to an image of scalar pixels, with one band for each element of the array.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-------------------------------------------------------|---------|\n| Image.arrayFlatten`(coordinateLabels, `*separator*`)` | Image |\n\n| Argument | Type | Details |\n|--------------------|----------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| this: `image` | Image | Image of multidimensional pixels to flatten. |\n| `coordinateLabels` | List | Name of each position along each axis. For example, 2x2 arrays with axes meaning 'day' and 'color' could have labels like \\[\\['monday', 'tuesday'\\], \\['red', 'green'\\]\\], resulting in band names'monday_red', 'monday_green', 'tuesday_red', and 'tuesday_green'. |\n| `separator` | String, default: \"_\" | Separator between array labels in each band name. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// A function to print arrays for a selected pixel in the following examples.\nfunction sampArrImg(arrImg) {\n var point = ee.Geometry.Point([-121, 42]);\n return arrImg.sample(point, 500).first().get('array');\n}\n\n// A 1D array image.\nvar arrayImg1D = ee.Image([0, 1, 2]).toArray();\nprint('1D array image (pixel)', sampArrImg(arrayImg1D));\n// [0, 1, 2]\n\n// Define image band names for a 1D array image with 3 rows. You are labeling\n// all rows and columns using a list of lists; the 1st sub list defines labels\n// for array rows and the 2nd (if applicable) defines labels for array columns.\nvar bandNames1D = [['row0', 'row1', 'row2']];\n\n// Flatten the 1D array image into an image with n bands equal to all\n// combinations of rows and columns. Here, we have 3 rows and 0 columns,\n// so the result will be a 3-band image.\nvar imgFrom1Darray = arrayImg1D.arrayFlatten(bandNames1D);\nprint('Image from 1D array', imgFrom1Darray);\n\n// Make a 2D array image by repeating the 1D array on 2-axis.\nvar arrayImg2D = arrayImg1D.arrayRepeat(1, 2);\nprint('2D array image (pixel)', sampArrImg(arrayImg2D));\n// [[0, 0],\n// [1, 1],\n// [2, 2]]\n\n// Define image band names for a 2D array image with 3 rows and 2 columns.\n// Recall that you are labeling all rows and columns using a list of lists;\n// The 1st sub list defines labels for array rows and the 2nd (if applicable)\n// defines labels for array columns.\nvar bandNames2D = [['row0', 'row1', 'row2'], ['col0', 'col1']];\n\n// Flatten the 2D array image into an image with n bands equal to all\n// combinations of rows and columns. Here, we have 3 rows and 2 columns,\n// so the result will be a 6-band image.\nvar imgFrom2Darray = arrayImg2D.arrayFlatten(bandNames2D);\nprint('Image from 2D array', imgFrom2Darray);\n```\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\n# A function to print arrays for a selected pixel in the following examples.\ndef samp_arr_img(arr_img):\n point = ee.Geometry.Point([-121, 42])\n return arr_img.sample(point, 500).first().get('array')\n\n# A 1D array image.\narray_img_1d = ee.Image([0, 1, 2]).toArray()\nprint('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())\n# [0, 1, 2]\n\n# Define image band names for a 1D array image with 3 rows. You are labeling\n# all rows and columns using a list of lists; the 1st sub list defines labels\n# for array rows and the 2nd (if applicable) defines labels for array columns.\nband_names_1d = [['row0', 'row1', 'row2']]\n\n# Flatten the 1D array image into an image with n bands equal to all\n# combinations of rows and columns. Here, we have 3 rows and 0 columns,\n# so the result will be a 3-band image.\nimg_from_1d_array = array_img_1d.arrayFlatten(band_names_1d)\nprint('Image from 1D array:', img_from_1d_array.getInfo())\n\n# Make a 2D array image by repeating the 1D array on 2-axis.\narray_img_2d = array_img_1d.arrayRepeat(1, 2)\nprint('2D array image (pixel):', samp_arr_img(array_img_2d).getInfo())\n# [[0, 0],\n# [1, 1],\n# [2, 2]]\n\n# Define image band names for a 2D array image with 3 rows and 2 columns.\n# Recall that you are labeling all rows and columns using a list of lists;\n# The 1st sub list defines labels for array rows and the 2nd (if applicable)\n# defines labels for array columns.\nband_names_2d = [['row0', 'row1', 'row2'], ['col0', 'col1']]\n\n# Flatten the 2D array image into an image with n bands equal to all\n# combinations of rows and columns. Here, we have 3 rows and 2 columns,\n# so the result will be a 6-band image.\nimg_from_2d_array = array_img_2d.arrayFlatten(band_names_2d)\nprint('Image from 2D array:', img_from_2d_array.getInfo())\n```"]]