ee.ImageCollection.aggregate_max
با مجموعهها، منظم بمانید
ذخیره و طبقهبندی محتوا براساس اولویتهای شما.
بر روی یک ویژگی معین از اشیاء در یک مجموعه جمع می شود و حداکثر مقادیر ویژگی انتخاب شده را محاسبه می کند.
استفاده | برمی گرداند | ImageCollection. aggregate_max (property) | |
استدلال | تایپ کنید | جزئیات | این: collection | مجموعه ویژگی ها | مجموعه برای جمع آوری بیش از. |
property | رشته | ویژگی مورد استفاده از هر عنصر مجموعه. |
نمونه ها
ویرایشگر کد (جاوا اسکریپت)
// A Lansat 8 TOA image collection for a specific year and location.
var col = ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA")
.filterBounds(ee.Geometry.Point([-122.073, 37.188]))
.filterDate('2018', '2019');
// An image property of interest, percent cloud cover in this case.
var prop = 'CLOUD_COVER';
// Use ee.ImageCollection.aggregate_* functions to fetch information about
// values of a selected property across all images in the collection. For
// example, produce a list of all values, get counts, and calculate statistics.
print('List of property values', col.aggregate_array(prop));
print('Count of property values', col.aggregate_count(prop));
print('Count of distinct property values', col.aggregate_count_distinct(prop));
print('First collection element property value', col.aggregate_first(prop));
print('Histogram of property values', col.aggregate_histogram(prop));
print('Min of property values', col.aggregate_min(prop));
print('Max of property values', col.aggregate_max(prop));
// The following methods are applicable to numerical properties only.
print('Mean of property values', col.aggregate_mean(prop));
print('Sum of property values', col.aggregate_sum(prop));
print('Product of property values', col.aggregate_product(prop));
print('Std dev (sample) of property values', col.aggregate_sample_sd(prop));
print('Variance (sample) of property values', col.aggregate_sample_var(prop));
print('Std dev (total) of property values', col.aggregate_total_sd(prop));
print('Variance (total) of property values', col.aggregate_total_var(prop));
print('Summary stats of property values', col.aggregate_stats(prop));
// Note that if the property is formatted as a string, min and max will
// respectively return the first and last values according to alphanumeric
// order of the property values.
var propString = 'LANDSAT_SCENE_ID';
print('List of property values (string)', col.aggregate_array(propString));
print('Min of property values (string)', col.aggregate_min(propString));
print('Max of property values (string)', col.aggregate_max(propString));
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)
from pprint import pprint
# A Lansat 8 TOA image collection for a specific year and location.
col = ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA").filterBounds(
ee.Geometry.Point([-122.073, 37.188])).filterDate('2018', '2019')
# An image property of interest, percent cloud cover in this case.
prop = 'CLOUD_COVER'
# Use ee.ImageCollection.aggregate_* functions to fetch information about
# values of a selected property across all images in the collection. For
# example, produce a list of all values, get counts, and calculate statistics.
print('List of property values:', col.aggregate_array(prop).getInfo())
print('Count of property values:', col.aggregate_count(prop).getInfo())
print('Count of distinct property values:',
col.aggregate_count_distinct(prop).getInfo())
print('First collection element property value:',
col.aggregate_first(prop).getInfo())
print('Histogram of property values:')
pprint(col.aggregate_histogram(prop).getInfo())
print('Min of property values:', col.aggregate_min(prop).getInfo())
print('Max of property values:', col.aggregate_max(prop).getInfo())
# The following methods are applicable to numerical properties only.
print('Mean of property values:', col.aggregate_mean(prop).getInfo())
print('Sum of property values:', col.aggregate_sum(prop).getInfo())
print('Product of property values:', col.aggregate_product(prop).getInfo())
print('Std dev (sample) of property values:',
col.aggregate_sample_sd(prop).getInfo())
print('Variance (sample) of property values:',
col.aggregate_sample_var(prop).getInfo())
print('Std dev (total) of property values:',
col.aggregate_total_sd(prop).getInfo())
print('Variance (total) of property values:',
col.aggregate_total_var(prop).getInfo())
print('Summary stats of property values:')
pprint(col.aggregate_stats(prop).getInfo())
# Note that if the property is formatted as a string, min and max will
# respectively return the first and last values according to alphanumeric
# order of the property values.
prop_string = 'LANDSAT_SCENE_ID'
print('List of property values (string):',
col.aggregate_array(prop_string).getInfo())
print('Min of property values (string):',
col.aggregate_min(prop_string).getInfo())
print('Max of property values (string):',
col.aggregate_max(prop_string).getInfo())
جز در مواردی که غیر از این ذکر شده باشد،محتوای این صفحه تحت مجوز Creative Commons Attribution 4.0 License است. نمونه کدها نیز دارای مجوز Apache 2.0 License است. برای اطلاع از جزئیات، به خطمشیهای سایت Google Developers مراجعه کنید. جاوا علامت تجاری ثبتشده Oracle و/یا شرکتهای وابسته به آن است.
تاریخ آخرین بهروزرسانی 2025-07-24 بهوقت ساعت هماهنگ جهانی.
[null,null,["تاریخ آخرین بهروزرسانی 2025-07-24 بهوقت ساعت هماهنگ جهانی."],[[["\u003cp\u003e\u003ccode\u003eaggregate_max\u003c/code\u003e calculates the maximum value of a specified property across all images in an ImageCollection.\u003c/p\u003e\n"],["\u003cp\u003eIt's used to determine the highest value for a given property, such as maximum cloud cover within a collection of satellite images.\u003c/p\u003e\n"],["\u003cp\u003eFor string properties, \u003ccode\u003eaggregate_max\u003c/code\u003e returns the last value based on alphanumeric order.\u003c/p\u003e\n"],["\u003cp\u003eThe function is part of the Earth Engine API and is accessible in both JavaScript and Python environments.\u003c/p\u003e\n"]]],[],null,["# ee.ImageCollection.aggregate_max\n\nAggregates over a given property of the objects in a collection, calculating the maximum of the values of the selected property.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-------------------------------------------|---------|\n| ImageCollection.aggregate_max`(property)` | |\n\n| Argument | Type | Details |\n|--------------------|-------------------|----------------------------------------------------------|\n| this: `collection` | FeatureCollection | The collection to aggregate over. |\n| `property` | String | The property to use from each element of the collection. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// A Lansat 8 TOA image collection for a specific year and location.\nvar col = ee.ImageCollection(\"LANDSAT/LC08/C02/T1_TOA\")\n .filterBounds(ee.Geometry.Point([-122.073, 37.188]))\n .filterDate('2018', '2019');\n\n// An image property of interest, percent cloud cover in this case.\nvar prop = 'CLOUD_COVER';\n\n// Use ee.ImageCollection.aggregate_* functions to fetch information about\n// values of a selected property across all images in the collection. For\n// example, produce a list of all values, get counts, and calculate statistics.\nprint('List of property values', col.aggregate_array(prop));\nprint('Count of property values', col.aggregate_count(prop));\nprint('Count of distinct property values', col.aggregate_count_distinct(prop));\nprint('First collection element property value', col.aggregate_first(prop));\nprint('Histogram of property values', col.aggregate_histogram(prop));\nprint('Min of property values', col.aggregate_min(prop));\nprint('Max of property values', col.aggregate_max(prop));\n\n// The following methods are applicable to numerical properties only.\nprint('Mean of property values', col.aggregate_mean(prop));\nprint('Sum of property values', col.aggregate_sum(prop));\nprint('Product of property values', col.aggregate_product(prop));\nprint('Std dev (sample) of property values', col.aggregate_sample_sd(prop));\nprint('Variance (sample) of property values', col.aggregate_sample_var(prop));\nprint('Std dev (total) of property values', col.aggregate_total_sd(prop));\nprint('Variance (total) of property values', col.aggregate_total_var(prop));\nprint('Summary stats of property values', col.aggregate_stats(prop));\n\n// Note that if the property is formatted as a string, min and max will\n// respectively return the first and last values according to alphanumeric\n// order of the property values.\nvar propString = 'LANDSAT_SCENE_ID';\nprint('List of property values (string)', col.aggregate_array(propString));\nprint('Min of property values (string)', col.aggregate_min(propString));\nprint('Max of property values (string)', col.aggregate_max(propString));\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\nfrom pprint import pprint\n\n# A Lansat 8 TOA image collection for a specific year and location.\ncol = ee.ImageCollection(\"LANDSAT/LC08/C02/T1_TOA\").filterBounds(\n ee.Geometry.Point([-122.073, 37.188])).filterDate('2018', '2019')\n\n# An image property of interest, percent cloud cover in this case.\nprop = 'CLOUD_COVER'\n\n# Use ee.ImageCollection.aggregate_* functions to fetch information about\n# values of a selected property across all images in the collection. For\n# example, produce a list of all values, get counts, and calculate statistics.\nprint('List of property values:', col.aggregate_array(prop).getInfo())\nprint('Count of property values:', col.aggregate_count(prop).getInfo())\nprint('Count of distinct property values:',\n col.aggregate_count_distinct(prop).getInfo())\nprint('First collection element property value:',\n col.aggregate_first(prop).getInfo())\nprint('Histogram of property values:')\npprint(col.aggregate_histogram(prop).getInfo())\nprint('Min of property values:', col.aggregate_min(prop).getInfo())\nprint('Max of property values:', col.aggregate_max(prop).getInfo())\n\n# The following methods are applicable to numerical properties only.\nprint('Mean of property values:', col.aggregate_mean(prop).getInfo())\nprint('Sum of property values:', col.aggregate_sum(prop).getInfo())\nprint('Product of property values:', col.aggregate_product(prop).getInfo())\nprint('Std dev (sample) of property values:',\n col.aggregate_sample_sd(prop).getInfo())\nprint('Variance (sample) of property values:',\n col.aggregate_sample_var(prop).getInfo())\nprint('Std dev (total) of property values:',\n col.aggregate_total_sd(prop).getInfo())\nprint('Variance (total) of property values:',\n col.aggregate_total_var(prop).getInfo())\nprint('Summary stats of property values:')\npprint(col.aggregate_stats(prop).getInfo())\n\n# Note that if the property is formatted as a string, min and max will\n# respectively return the first and last values according to alphanumeric\n# order of the property values.\nprop_string = 'LANDSAT_SCENE_ID'\nprint('List of property values (string):',\n col.aggregate_array(prop_string).getInfo())\nprint('Min of property values (string):',\n col.aggregate_min(prop_string).getInfo())\nprint('Max of property values (string):',\n col.aggregate_max(prop_string).getInfo())\n```"]]