ee.Image.toArray

將每個波段的像素串連成每個像素的單一陣列。如果任何輸入頻帶遭到遮蓋，結果也會遭到遮蓋。

用量	傳回
Image.toArray(axis)	圖片

引數	類型	詳細資料
這個：image	圖片	要轉換成每個像素陣列的波段圖片。頻帶必須具有純量像素，或具有相同維度的陣列像素。
axis	整數，預設值為 0	要沿著串連的軸；必須至少為 0，且最多為輸入內容的維度。如果軸等於輸入的維度，結果的維度會比輸入多 1 個。

範例

程式碼編輯器 (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 3-band image of constants.
var img = ee.Image([0, 1, 2]);
print('3-band image', img);

// Convert the 3-band image to an array image. The resulting array image has a
// single band named "array". The "array" band stores the per-pixel band values
// from the input ee.Image as a 1D array.
var arrayImg1D = img.toArray();
print('1D array image', arrayImg1D);

// Sample a single pixel to see its 1D array using the `sampArrImg` function
// defined above. Similar arrays are present for all pixels in a given array
// image; looking at just one helps conceptualize the structure.
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2]

// Array images can be displayed to the Code Editor map and queried with the
// inspector tool. Per-pixel, the first element in the array is shown.
// Single-band grayscale is used to represent the data. Style parameters `min`
// and `max` are valid. Styling the layer with the Code Editor's layer
// visualization tool is invalid.
Map.addLayer(arrayImg1D, {min: 0, max: 2}, 'Image array');

// Create a 2D array image by concatenating the values in a 1D array image
// along the 1-axis using `toArray(1)`. For a 3D array, apply `toArray(2)` to
// the result.
var arrayImg2D = arrayImg1D.toArray(1);
print('2D array image (pixel)', sampArrImg(arrayImg2D));
// [[0],
//  [1],
//  [2]]

Python 設定

請參閱 Python 環境頁面，瞭解 Python API 和如何使用 geemap 進行互動式開發。

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 3-band image of constants.
img = ee.Image([0, 1, 2])
display('3-band image', img)

# Convert the 3-band image to an array image. The resulting array image has a
# single band named "array". The "array" band stores the per-pixel band values
# from the input ee.Image as a 1D array.
array_img_1_d = img.toArray()
display('1D array image', array_img_1_d)

# Sample a single pixel to see its 1D array using the `samp_arr_img` function
# defined above. Similar arrays are present for all pixels in a given array
# image looking at just one helps conceptualize the structure.
display('1D array image (pixel)', samp_arr_img(array_img_1_d))
# [0, 1, 2]

# Array images can be displayed to the Code Editor map and queried with the
# inspector tool. Per-pixel, the first element in the array is shown.
# Single-band grayscale is used to represent the data. Style parameters `min`
# and `max` are valid. Styling the layer with the Code Editor's layer
# visualization tool is invalid.
m = geemap.Map()
m.add_layer(array_img_1_d, {'min': 0, 'max': 2}, 'Image array')
display(m)

# Create a 2D array image by concatenating the values in a 1D array image
# along the 1-axis using `toArray(1)`. For a 3D array, apply `toArray(2)` to
# the result.
array_img_2_d = array_img_1_d.toArray(1)
display('2D array image (pixel)', samp_arr_img(array_img_2_d))
# [[0],
#  [1],
#  [2]]