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의견 보내기
ee.ImageCollection.aggregate_sample_var
컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
컬렉션에 있는 객체의 지정된 속성을 집계하여 선택한 속성 값의 표본 분산을 계산합니다.
사용 반환 값 ImageCollection. aggregate_sample_var (property)
숫자
인수 유형 세부정보 다음과 같은 경우: collection
FeatureCollection 집계할 컬렉션입니다. property
문자열 컬렉션의 각 요소에서 사용할 속성입니다.
예
코드 편집기 (JavaScript)
// 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 ));
Python 설정
Python API 및 geemap
를 사용한 대화형 개발에 관한 자세한 내용은
Python 환경 페이지를 참고하세요.
import ee
import geemap.core as geemap
Colab (Python)
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 ())
의견 보내기
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스 에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스 에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책 을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2025-07-26(UTC)
의견을 전달하고 싶나요?
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["필요한 정보가 없음","missingTheInformationINeed","thumb-down"],["너무 복잡함/단계 수가 너무 많음","tooComplicatedTooManySteps","thumb-down"],["오래됨","outOfDate","thumb-down"],["번역 문제","translationIssue","thumb-down"],["샘플/코드 문제","samplesCodeIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-07-26(UTC)"],[],["The provided code demonstrates how to use `aggregate_*` functions on an `ImageCollection` to derive information about a specified property. Actions include listing all property values, getting counts, finding the first element's property value, creating histograms, and calculating statistical measures like min, max, mean, sum, product, standard deviation, and variance. These methods work on numeric properties, while string property methods are restricted to min and max (alphanumeric order).\n"]]