ee.ImageCollection.fromImages

مجموعه تصاویر حاوی تصاویر داده شده را برمی گرداند.

استفاده	برمی گرداند
ee.ImageCollection.fromImages(images)	ImageCollection

استدلال	تایپ کنید	جزئیات
images	فهرست کنید	تصاویری که باید در مجموعه گنجانده شود.

نمونه ها

ویرایشگر کد (جاوا اسکریپت)

// A series of images.
var img1 = ee.Image(0);
var img2 = ee.Image(1);
var img3 = ee.Image(2);

// Convert the list of images into an image collection.
var col = ee.ImageCollection.fromImages([img1, img2, img3]);
print('Collection from list of images', col);

// The ee.ImageCollection.fromImages function is intended to coerce the image
// list to a collection when the list is an ambiguous, computed object fetched
// from the properties of a server-side object. For instance, a list
// of images retrieved from a ee.Feature property. Here, we set an image
// list as a property of a feature, retrieve it, and convert it to
// a collection. Notice that the ee.ImageCollection constructor fails to coerce
// the image list to a collection, but ee.ImageCollection.fromImages does.
var feature = ee.Feature(null).set('img_list', [img1, img2, img3]);
var ambiguousImgList = feature.get('img_list');
print('Coerced to collection', ee.ImageCollection.fromImages(ambiguousImgList));
print('NOT coerced to collection', ee.ImageCollection(ambiguousImgList));

// A common use case is coercing an image list from a saveAll join to a
// image collection, like in this example of building a collection of mean
// annual NDVI images from a MODIS collection.
var modisCol = ee.ImageCollection('MODIS/006/MOD13A2')
  .filterDate('2017', '2021')
  .select('NDVI')
  .map(function(img) {return img.set('year', img.date().get('year'))});

var distinctYearCol = modisCol.distinct('year');

var joinedCol = ee.Join.saveAll('img_list').apply({
  primary: distinctYearCol,
  secondary: modisCol,
  condition: ee.Filter.equals({'leftField': 'year', 'rightField': 'year'})
});

var annualNdviMean = joinedCol.map(function(img) {
  return ee.ImageCollection.fromImages(img.get('img_list')).mean()
    .copyProperties(img, ['year']);
});
print('Mean annual NDVI collection', annualNdviMean);

راه اندازی پایتون

برای اطلاعات در مورد API پایتون و استفاده از geemap برای توسعه تعاملی به صفحه محیط پایتون مراجعه کنید.

import ee
import geemap.core as geemap

کولب (پایتون)

# A series of images.
img1 = ee.Image(0)
img2 = ee.Image(1)
img3 = ee.Image(2)

# Convert the list of images into an image collection.
col = ee.ImageCollection.fromImages([img1, img2, img3])
print('Collection from list of images:', col.getInfo())

# The ee.ImageCollection.fromImages function is intended to coerce the image
# list to a collection when the list is an ambiguous, computed object fetched
# from the properties of a server-side object. For instance, a list
# of images retrieved from a ee.Feature property. Here, we set an image
# list as a property of a feature, retrieve it, and convert it to
# a collection. Notice that the ee.ImageCollection constructor fails to coerce
# the image list to a collection, but ee.ImageCollection.fromImages does.
feature = ee.Feature(None).set('img_list', [img1, img2, img3])
ambiguous_img_list = feature.get('img_list')
print(
    'Coerced to collection:',
    ee.ImageCollection.fromImages(ambiguous_img_list).getInfo(),
)
print(
    'NOT coerced to collection:',
    ee.ImageCollection(ambiguous_img_list).getInfo(),
)

# A common use case is coercing an image list from a saveAll join to a
# image collection, like in this example of building a collection of mean
# annual NDVI images from a MODIS collection.
modis_col = (
    ee.ImageCollection('MODIS/006/MOD13A2')
    .filterDate('2017', '2021')
    .select('NDVI')
    .map(lambda img: img.set('year', img.date().get('year')))
)

distinct_year_col = modis_col.distinct('year')

joined_col = ee.Join.saveAll('img_list').apply(
    primary=distinct_year_col,
    secondary=modis_col,
    condition=ee.Filter.equals(leftField='year', rightField='year'),
)

annual_ndvi_mean = joined_col.map(
    lambda img: ee.ImageCollection.fromImages(img.get('img_list'))
    .mean()
    .copyProperties(img, ['year'])
)
print('Mean annual NDVI collection:', annual_ndvi_mean.getInfo())

،مجموعه تصاویر حاوی تصاویر داده شده را برمی گرداند.

استفاده	برمی گرداند
ee.ImageCollection.fromImages(images)	ImageCollection

استدلال	تایپ کنید	جزئیات
images	فهرست کنید	تصاویری که باید در مجموعه گنجانده شود.

نمونه ها

ویرایشگر کد (جاوا اسکریپت)

// A series of images.
var img1 = ee.Image(0);
var img2 = ee.Image(1);
var img3 = ee.Image(2);

// Convert the list of images into an image collection.
var col = ee.ImageCollection.fromImages([img1, img2, img3]);
print('Collection from list of images', col);

// The ee.ImageCollection.fromImages function is intended to coerce the image
// list to a collection when the list is an ambiguous, computed object fetched
// from the properties of a server-side object. For instance, a list
// of images retrieved from a ee.Feature property. Here, we set an image
// list as a property of a feature, retrieve it, and convert it to
// a collection. Notice that the ee.ImageCollection constructor fails to coerce
// the image list to a collection, but ee.ImageCollection.fromImages does.
var feature = ee.Feature(null).set('img_list', [img1, img2, img3]);
var ambiguousImgList = feature.get('img_list');
print('Coerced to collection', ee.ImageCollection.fromImages(ambiguousImgList));
print('NOT coerced to collection', ee.ImageCollection(ambiguousImgList));

// A common use case is coercing an image list from a saveAll join to a
// image collection, like in this example of building a collection of mean
// annual NDVI images from a MODIS collection.
var modisCol = ee.ImageCollection('MODIS/006/MOD13A2')
  .filterDate('2017', '2021')
  .select('NDVI')
  .map(function(img) {return img.set('year', img.date().get('year'))});

var distinctYearCol = modisCol.distinct('year');

var joinedCol = ee.Join.saveAll('img_list').apply({
  primary: distinctYearCol,
  secondary: modisCol,
  condition: ee.Filter.equals({'leftField': 'year', 'rightField': 'year'})
});

var annualNdviMean = joinedCol.map(function(img) {
  return ee.ImageCollection.fromImages(img.get('img_list')).mean()
    .copyProperties(img, ['year']);
});
print('Mean annual NDVI collection', annualNdviMean);

راه اندازی پایتون

برای اطلاعات در مورد API پایتون و استفاده از geemap برای توسعه تعاملی به صفحه محیط پایتون مراجعه کنید.

import ee
import geemap.core as geemap

کولب (پایتون)

# A series of images.
img1 = ee.Image(0)
img2 = ee.Image(1)
img3 = ee.Image(2)

# Convert the list of images into an image collection.
col = ee.ImageCollection.fromImages([img1, img2, img3])
print('Collection from list of images:', col.getInfo())

# The ee.ImageCollection.fromImages function is intended to coerce the image
# list to a collection when the list is an ambiguous, computed object fetched
# from the properties of a server-side object. For instance, a list
# of images retrieved from a ee.Feature property. Here, we set an image
# list as a property of a feature, retrieve it, and convert it to
# a collection. Notice that the ee.ImageCollection constructor fails to coerce
# the image list to a collection, but ee.ImageCollection.fromImages does.
feature = ee.Feature(None).set('img_list', [img1, img2, img3])
ambiguous_img_list = feature.get('img_list')
print(
    'Coerced to collection:',
    ee.ImageCollection.fromImages(ambiguous_img_list).getInfo(),
)
print(
    'NOT coerced to collection:',
    ee.ImageCollection(ambiguous_img_list).getInfo(),
)

# A common use case is coercing an image list from a saveAll join to a
# image collection, like in this example of building a collection of mean
# annual NDVI images from a MODIS collection.
modis_col = (
    ee.ImageCollection('MODIS/006/MOD13A2')
    .filterDate('2017', '2021')
    .select('NDVI')
    .map(lambda img: img.set('year', img.date().get('year')))
)

distinct_year_col = modis_col.distinct('year')

joined_col = ee.Join.saveAll('img_list').apply(
    primary=distinct_year_col,
    secondary=modis_col,
    condition=ee.Filter.equals(leftField='year', rightField='year'),
)

annual_ndvi_mean = joined_col.map(
    lambda img: ee.ImageCollection.fromImages(img.get('img_list'))
    .mean()
    .copyProperties(img, ['year'])
)
print('Mean annual NDVI collection:', annual_ndvi_mean.getInfo())