ee.Image.arrayCat

各バンドの指定された軸に沿って各配列ピクセルを連結することで、配列画像を作成します。

用途	戻り値
Image.arrayCat(image2, axis)	画像

引数	タイプ	詳細
これ: image1	画像	連結する最初の配列画像。
image2	画像	連結する 2 つ目の配列イメージ。
axis	Integer	連結する軸。

例

コードエディタ（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');
}

// Create two 1D array images.
var arrayImg1Da = ee.Image([0, 1, 2]).toArray();
print('1D array image (A) (pixel)', sampArrImg(arrayImg1Da));
// [0, 1, 2]
var arrayImg1Db = ee.Image([3, 4, 5]).toArray();
print('1D array image (B) (pixel)', sampArrImg(arrayImg1Db));
// [3, 4, 5]

// Concatenate 1D array image B to 1D array image A on 0-axis (rows).
var arrayImg1DcatAx0 = arrayImg1Da.arrayCat(arrayImg1Db, 0);
print('Concatenate 1D array images on 0-axis', sampArrImg(arrayImg1DcatAx0));
// [0, 1, 2, 3, 4, 5]

// Concatenate 1D array image B to 1D array image A on 1-axis (columns).
var arrayImg1DcatAx1 = arrayImg1Da.arrayCat(arrayImg1Db, 1);
print('Concatenate 1D array images on 1-axis', sampArrImg(arrayImg1DcatAx1));
// [[0, 3],
//  [1, 4]
//  [2, 5]]

// Create two 2D array images (expand the dimensions of 1D arrays).
var arrayImg2Da = arrayImg1Da.toArray(1);
print('2D array image (A) (pixel)', sampArrImg(arrayImg2Da));
// [[0],
//  [1],
//  [2]]
var arrayImg2Db = arrayImg1Db.toArray(1);
print('2D array image (B) (pixel)', sampArrImg(arrayImg2Db));
// [[3],
//  [4],
//  [5]]

// Concatenate 2D array image B to 2D array image A on 0-axis (rows).
var arrayImg2DcatAx0 = arrayImg2Da.arrayCat(arrayImg2Db, 0);
print('Concatenate 2D array images on 0-axis', sampArrImg(arrayImg2DcatAx0));
// [[0],
//  [1],
//  [2],
//  [3],
//  [4],
//  [5]]

// Concatenate 2D array image B to 2D array image A on 1-axis (columns).
var arrayImg2DcatAx1 = arrayImg2Da.arrayCat(arrayImg2Db, 1);
print('Concatenate 2D array images on 1-axis', sampArrImg(arrayImg2DcatAx1));
// [[0, 3],
//  [1, 4],
//  [2, 5]]

Python の設定

Python API とインタラクティブな開発での geemap の使用については、 Python 環境のページをご覧ください。

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')

# Create two 1D array images.
array_img_1d_a = ee.Image([0, 1, 2]).toArray()
print('1D array image (A) (pixel):', samp_arr_img(array_img_1d_a).getInfo())
# [0, 1, 2]
array_img_1d_b = ee.Image([3, 4, 5]).toArray()
print('1D array image (B) (pixel):', samp_arr_img(array_img_1d_b).getInfo())
# [3, 4, 5]

# Concatenate 1D array image B to 1D array image A on 0-axis (rows).
array_img_1d_cat_ax0 = array_img_1d_a.arrayCat(array_img_1d_b, 0)
print(
    'Concatenate 1D array images on 0-axis:',
    samp_arr_img(array_img_1d_cat_ax0).getInfo()
)
# [0, 1, 2, 3, 4, 5]

# Concatenate 1D array image B to 1D array image A on 1-axis (columns).
array_img_1d_cat_ax1 = array_img_1d_a.arrayCat(array_img_1d_b, 1)
print(
    'Concatenate 1D array images on 1-axis:',
    samp_arr_img(array_img_1d_cat_ax1).getInfo()
)
# [[0, 3],
#  [1, 4]
#  [2, 5]]

# Create two 2D array images (expand the dimensions of 1D arrays).
array_img_2d_a = array_img_1d_a.toArray(1)
print('2D array image (A) (pixel):', samp_arr_img(array_img_2d_a).getInfo())
# [[0],
#  [1],
#  [2]]
array_img_2d_b = array_img_1d_b.toArray(1)
print('2D array image (B) (pixel):', samp_arr_img(array_img_2d_b).getInfo())
# [[3],
#  [4],
#  [5]]

# Concatenate 2D array image B to 2D array image A on 0-axis (rows).
array_img_2d_cat_ax0 = array_img_2d_a.arrayCat(array_img_2d_b, 0)
print(
    'Concatenate 2D array images on 0-axis:',
    samp_arr_img(array_img_2d_cat_ax0).getInfo()
)
# [[0],
#  [1],
#  [2],
#  [3],
#  [4],
#  [5]]

# Concatenate 2D array image B to 2D array image A on 1-axis (columns).
array_img_2d_cat_ax1 = array_img_2d_a.arrayCat(array_img_2d_b, 1)
print(
    'Concatenate 2D array images on 1-axis:',
    samp_arr_img(array_img_2d_cat_ax1).getInfo()
)
# [[0, 3],
#  [1, 4],
#  [2, 5]]