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數學運算
透過集合功能整理內容
你可以依據偏好儲存及分類內容。
您可以使用 add() 和 subtract() 等運算子執行圖像運算，但如果要執行包含多個項的複雜運算，expression() 函式會是較佳的替代方案。如要進一步瞭解運算子和運算式，請參閱下列章節。
運算子
數學運算子可在圖像頻帶上執行基本算術運算。這類函式會接受兩個輸入內容：兩張圖片或一張圖片和常數，這會解讀為沒有遮罩像素的單一頻帶常數圖片。每個頻帶的每個像素都會執行作業。
舉例來說，假設您要使用 VIIRS 影像計算常態化差異植被指數 (NDVI)，這裡使用 add()、subtract() 和 divide() 運算子：
程式碼編輯器 (JavaScript)
// Load a VIIRS 8-day surface reflectance composite for May 2024.
var viirs202405 = ee.ImageCollection('NASA/VIIRS/002/VNP09H1').filter(
ee.Filter.date('2024-05-01', '2024-05-16')).first();
// Compute NDVI.
var ndvi202405 = viirs202405.select('SurfReflect_I2')
.subtract(viirs202405.select('SurfReflect_I1'))
.divide(viirs202405.select('SurfReflect_I2')
.add(viirs202405.select('SurfReflect_I1')));
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)
# Load a VIIRS 8-day surface reflectance composite for May 2024.
viirs202405 = (
ee.ImageCollection('NASA/VIIRS/002/VNP09H1')
.filter(ee.Filter.date('2024-05-01', '2024-05-16'))
.first()
)
# Compute NDVI.
ndvi202405 = (
viirs202405.select('SurfReflect_I2')
.subtract(viirs202405.select('SurfReflect_I1'))
.divide(
viirs202405.select('SurfReflect_I2').add(
viirs202405.select('SurfReflect_I1')
)
)
)
系統只會考量兩個輸入內容之間未遮罩的像素交集，並以未遮罩的形式傳回，所有其他像素都會遭到遮罩。一般來說，如果任一輸入內容只有一個頻帶，則會用於比較其他輸入內容的所有頻帶。如果輸入內容的頻帶數量相同，但名稱不同，則會以自然順序成對使用。輸出頻帶的名稱會以兩個輸入內容中較長的輸入內容命名，如果兩者長度相同，則會以第一個輸入內容的順序命名。輸出像素的類型是輸入類型的聯集。
以下是多頻帶圖像減法範例，說明如何自動比對頻帶，進而為每個同時出現的頻帶產生「變更向量」。
程式碼編輯器 (JavaScript)
// Load a VIIRS 8-day surface reflectance composite for September 2024.
var viirs202409 = ee.ImageCollection('NASA/VIIRS/002/VNP09H1').filter(
ee.Filter.date('2024-09-01', '2024-09-16')).first();
// Compute multi-band difference between the September composite and the
// previously loaded May composite.
var diff = viirs202409.subtract(ndvi202405);
Map.addLayer(diff, {
bands: ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],
min: -1,
max: 1
}, 'difference');
// Compute the squared difference in each band.
var squaredDifference = diff.pow(2);
Map.addLayer(squaredDifference, {
bands: ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],
min: 0,
max: 0.7
}, 'squared diff.');
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)
# Load a VIIRS 8-day surface reflectance composite for September 2024.
viirs202409 = (
ee.ImageCollection('NASA/VIIRS/002/VNP09H1')
.filter(ee.Filter.date('2024-09-01', '2024-09-16'))
.first()
)
# Compute multi-band difference between the September composite and the
# previously loaded May composite.
diff = viirs202409.subtract(ndvi202405)
m = geemap.Map()
m.add_layer(
diff,
{
'bands': ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],
'min': -1,
'max': 1,
},
'difference',
)
# Compute the squared difference in each band.
squared_difference = diff.pow(2)
m.add_layer(
squared_difference,
{
'bands': ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],
'min': 0,
'max': 0.7,
},
'squared diff.',
)
display(m)
在本範例的第二部分中，我們使用 image.pow(2) 計算平方差。如需完整的數學運算子清單，瞭解如何處理基本算術、三角學、指數、捨入、轉型、位元運算等，請參閱 API 說明文件。
運算式
如要導入更複雜的數學運算式，建議您使用 image.expression()，這個函式會剖析數學運算的文字表示法。以下範例使用 expression() 計算增強植被指數 (EVI)：
程式碼編輯器 (JavaScript)
// Load a Landsat 8 image.
var image = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318');
// Compute the EVI using an expression.
var evi = image.expression(
'2.5 * ((NIR - RED) / (NIR + 6 * RED - 7.5 * BLUE + 1))', {
'NIR': image.select('B5'),
'RED': image.select('B4'),
'BLUE': image.select('B2')
});
Map.centerObject(image, 9);
Map.addLayer(evi, {min: -1, max: 1, palette: ['a6611a', 'f5f5f5', '4dac26']});
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)
# Load a Landsat 8 image.
image = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318')
# Compute the EVI using an expression.
evi = image.expression(
'2.5 * ((NIR - RED) / (NIR + 6 * RED - 7.5 * BLUE + 1))',
{
'NIR': image.select('B5'),
'RED': image.select('B4'),
'BLUE': image.select('B2'),
},
)
# Define a map centered on San Francisco Bay.
map_evi = geemap.Map(center=[37.4675, -122.1363], zoom=9)
# Add the image layer to the map and display it.
map_evi.add_layer(
evi, {'min': -1, 'max': 1, 'palette': ['a6611a', 'f5f5f5', '4dac26']}, 'evi'
)
display(map_evi)
請注意，expression() 的第一個引數是數學運算的文字表示法，第二個引數是字典，其中索引鍵是運算式中使用的變數名稱，值則是應將變數對應至的圖像頻帶。圖片中的頻帶可稱為 b("band name") 或 b(index)，例如 b(0)，而非提供字典。使用頻帶對應字典時，可以從輸入圖像以外的圖像定義頻帶。請注意，expression() 會使用「整除法」，在兩個整數相除時，會捨去餘數並傳回整數。例如 10 / 20 = 0。如要變更這項行為，請將其中一個運算元項乘以 1.0：10 * 1.0 / 20 = 0.5。評估多個來源圖片的頻帶時，系統只會考量未遮罩像素的交集，並將其視為未遮罩的像素傳回。下表列出支援的運算式運算子。
expression() 的運算子
| 類型 |
符號 |
名稱 |
| 算術運算 |
+ - * / % ** |
加、減、乘、除、取餘數、指數 |
| 關聯 |
== != < > <= >= |
等於、不等於、小於、大於等。 |
| Logical |
&& || ! ^。 |
And、Or、Not、Xor |
| 三元組 |
? ： |
If then else |
除非另有註明，否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權，程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間：2025-07-25 (世界標準時間)。
[null,null,["上次更新時間：2025-07-25 (世界標準時間)。"],[[["\u003cp\u003eEarth Engine provides tools for performing image math, including operators for basic arithmetic and the \u003ccode\u003eexpression()\u003c/code\u003e function for complex computations.\u003c/p\u003e\n"],["\u003cp\u003eOperators like \u003ccode\u003eadd()\u003c/code\u003e, \u003ccode\u003esubtract()\u003c/code\u003e, and \u003ccode\u003edivide()\u003c/code\u003e enable pixel-wise calculations between images or an image and a constant.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eexpression()\u003c/code\u003e function allows implementing custom formulas by parsing text representations of mathematical operations and mapping variables to image bands.\u003c/p\u003e\n"],["\u003cp\u003eWhen using \u003ccode\u003eexpression()\u003c/code\u003e, ensure to handle integer division appropriately by multiplying one operand by \u003ccode\u003e1.0\u003c/code\u003e to preserve decimal values if needed.\u003c/p\u003e\n"],["\u003cp\u003eBoth operators and expressions automatically handle band matching and masking, considering only unmasked pixels in the calculations.\u003c/p\u003e\n"]]],[],null,["# Mathematical Operations\n\n|---------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------|\n| [Run in Google Colab](https://colab.research.google.com/github/google/earthengine-community/blob/master/guides/linked/generated/image_math.ipynb) | [View source on GitHub](https://github.com/google/earthengine-community/blob/master/guides/linked/generated/image_math.ipynb) |\n\nImage math can be performed using operators like `add()` and\n`subtract()`, but for complex computations with more than a couple of terms, the\n`expression()` function provides a good alternative. See the following sections\nfor more information on [operators](#operators) and\n[expressions](#expressions).\n\nOperators\n---------\n\nMath operators perform basic arithmetic operations on image bands. They take two inputs:\neither two images or one image and a constant term, which\nis interpreted as a single-band constant image with no masked pixels. Operations are performed\nper pixel for each band.\n\nAs a basic example, consider the task of calculating the Normalized Difference Vegetation\nIndex (NDVI) using VIIRS imagery, where `add()`, `subtract()`,\nand `divide()` operators are used:\n\n### Code Editor (JavaScript)\n\n```javascript\n// Load a VIIRS 8-day surface reflectance composite for May 2024.\nvar viirs202405 = ee.ImageCollection('NASA/VIIRS/002/VNP09H1').filter(\n ee.Filter.date('2024-05-01', '2024-05-16')).first();\n\n// Compute NDVI.\nvar ndvi202405 = viirs202405.select('SurfReflect_I2')\n .subtract(viirs202405.select('SurfReflect_I1'))\n .divide(viirs202405.select('SurfReflect_I2')\n .add(viirs202405.select('SurfReflect_I1')));\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# Load a VIIRS 8-day surface reflectance composite for May 2024.\nviirs202405 = (\n ee.ImageCollection('NASA/VIIRS/002/VNP09H1')\n .filter(ee.Filter.date('2024-05-01', '2024-05-16'))\n .first()\n)\n\n# Compute NDVI.\nndvi202405 = (\n viirs202405.select('SurfReflect_I2')\n .subtract(viirs202405.select('SurfReflect_I1'))\n .divide(\n viirs202405.select('SurfReflect_I2').add(\n viirs202405.select('SurfReflect_I1')\n )\n )\n)\n```\n| **Note:** the normalized difference operation is available as a shortcut method: [`normalizedDifference()`](/earth-engine/apidocs/ee-image-normalizeddifference).\n\nOnly the intersection of unmasked pixels between the two inputs are\nconsidered and returned as unmasked, all else are masked. In general, if either input has only\none band, then it is used against all the bands in the other input. If the inputs have the same\nnumber of bands, but not the same names, they're used pairwise in the natural order. The\noutput bands are named for the longer of the two inputs, or if they're equal in length, in the\nfirst input's order. The type of the output pixels is the union of the input types.\n\nThe following example of multi-band image subtraction demonstrates how bands are matched\nautomatically, resulting in a \"change vector\" for each pixel for each co-occurring band.\n\n### Code Editor (JavaScript)\n\n```javascript\n// Load a VIIRS 8-day surface reflectance composite for September 2024.\nvar viirs202409 = ee.ImageCollection('NASA/VIIRS/002/VNP09H1').filter(\n ee.Filter.date('2024-09-01', '2024-09-16')).first();\n\n// Compute multi-band difference between the September composite and the\n// previously loaded May composite.\nvar diff = viirs202409.subtract(ndvi202405);\nMap.addLayer(diff, {\n bands: ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],\n min: -1,\n max: 1\n}, 'difference');\n\n// Compute the squared difference in each band.\nvar squaredDifference = diff.pow(2);\nMap.addLayer(squaredDifference, {\n bands: ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],\n min: 0,\n max: 0.7\n}, 'squared diff.');\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# Load a VIIRS 8-day surface reflectance composite for September 2024.\nviirs202409 = (\n ee.ImageCollection('NASA/VIIRS/002/VNP09H1')\n .filter(ee.Filter.date('2024-09-01', '2024-09-16'))\n .first()\n)\n\n# Compute multi-band difference between the September composite and the\n# previously loaded May composite.\ndiff = viirs202409.subtract(ndvi202405)\n\nm = geemap.Map()\nm.add_layer(\n diff,\n {\n 'bands': ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],\n 'min': -1,\n 'max': 1,\n },\n 'difference',\n)\n\n# Compute the squared difference in each band.\nsquared_difference = diff.pow(2)\n\nm.add_layer(\n squared_difference,\n {\n 'bands': ['SurfReflect_I1', 'SurfReflect_I2', 'SurfReflect_I3'],\n 'min': 0,\n 'max': 0.7,\n },\n 'squared diff.',\n)\ndisplay(m)\n```\n\nIn the second part of this example, the squared difference is computed using\n`image.pow(2)`. For the complete list of mathematical operators handling\nbasic arithmetic, trigonometry, exponentiation, rounding, casting, bitwise operations\nand more, see the [API documentation](/earth-engine/apidocs).\n\nExpressions\n-----------\n\nTo implement more complex mathematical expressions, consider using\n`image.expression()`, which parses a text representation of a math operation.\nThe following example uses `expression()` to compute the Enhanced\nVegetation Index (EVI):\n\n### Code Editor (JavaScript)\n\n```javascript\n// Load a Landsat 8 image.\nvar image = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318');\n\n// Compute the EVI using an expression.\nvar evi = image.expression(\n '2.5 * ((NIR - RED) / (NIR + 6 * RED - 7.5 * BLUE + 1))', {\n 'NIR': image.select('B5'),\n 'RED': image.select('B4'),\n 'BLUE': image.select('B2')\n});\n\nMap.centerObject(image, 9);\nMap.addLayer(evi, {min: -1, max: 1, palette: ['a6611a', 'f5f5f5', '4dac26']});\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# Load a Landsat 8 image.\nimage = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318')\n\n# Compute the EVI using an expression.\nevi = image.expression(\n '2.5 * ((NIR - RED) / (NIR + 6 * RED - 7.5 * BLUE + 1))',\n {\n 'NIR': image.select('B5'),\n 'RED': image.select('B4'),\n 'BLUE': image.select('B2'),\n },\n)\n\n# Define a map centered on San Francisco Bay.\nmap_evi = geemap.Map(center=[37.4675, -122.1363], zoom=9)\n\n# Add the image layer to the map and display it.\nmap_evi.add_layer(\n evi, {'min': -1, 'max': 1, 'palette': ['a6611a', 'f5f5f5', '4dac26']}, 'evi'\n)\ndisplay(map_evi)\n```\n\nObserve that the first argument to `expression()` is the textual representation of\nthe math operation, the second argument is a dictionary where the keys are variable names used\nin the expression and the values are the image bands to which the variables should be\nmapped. Bands in the image may be referred to as `b(\"band name\")` or\n`b(index)`, for example `b(0)`, instead\nof providing the dictionary. Bands can be defined from images other than the input when using\nthe band map dictionary. Note that `expression()` uses \"floor division\", which\ndiscards the remainder and returns an integer when two integers are divided. For example\n`10 / 20 = 0`. To change this behavior, multiply one of the operands by\n`1.0`: `10 * 1.0 / 20 = 0.5`. Only the intersection of unmasked pixels\nare considered and returned as unmasked when bands from more than one source image are\nevaluated. Supported expression operators are listed in the following table.\n\n| Type | Symbol | Name |\n|----------------|---------------------|----------------------------------------------------|\n| **Arithmetic** | + - \\* / % \\*\\* | Add, Subtract, Multiply, Divide, Modulus, Exponent |\n| **Relational** | == != \\\u003c \\\u003e \\\u003c= \\\u003e= | Equal, Not Equal, Less Than, Greater than, etc. |\n| **Logical** | \\&\\& \\|\\| ! \\^ | And, Or, Not, Xor |\n| **Ternary** | ? : | If then else |\n[Operators for `expression()`]"]]
在 Google Colab 中執行
前往 GitHub 查看來源