Duyuru:
15 Nisan 2025'ten önce Earth Engine'i kullanmak için kaydedilen tüm ticari olmayan projelerin Earth Engine erişimini sürdürmek için
ticari olmayan uygunluğu doğrulaması gerekir.
ee.Image.arrayFlatten
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
Eşit şekilli çok boyutlu piksellerden oluşan tek bantlı bir görüntüyü, dizinin her öğesi için bir bant içeren skalar piksellerden oluşan bir görüntüye dönüştürür.
Kullanım | İadeler |
---|
Image.arrayFlatten(coordinateLabels, separator) | Resim |
Bağımsız Değişken | Tür | Ayrıntılar |
---|
bu: image | Resim | Düzleştirilecek çok boyutlu piksellerin görüntüsü. |
coordinateLabels | Liste | Her eksen boyunca her konumun adı. Örneğin, eksenleri "gün" ve "renk" anlamına gelen 2x2 dizilerde [['monday', 'tuesday'], ['red', 'green']] gibi etiketler olabilir. Bu durumda, "monday_red", "monday_green", "tuesday_red" ve "tuesday_green" gibi bant adları elde edilir. |
separator | Dize, varsayılan: "_" | Her bant adındaki dizi etiketleri arasındaki ayırıcı. |
Örnekler
Kod Düzenleyici (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 kurulumu
Python API'si ve etkileşimli geliştirme için geemap
kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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())
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[[["\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```"]]