ee.Filter.greaterThanOrEquals
Zadbaj o dobrą organizację dzięki kolekcji
Zapisuj i kategoryzuj treści zgodnie ze swoimi preferencjami.
Tworzy filtr jednoargumentowy lub dwuargumentowy, który jest spełniony, chyba że lewy argument operacji jest mniejszy niż prawy.
Wykorzystanie | Zwroty |
---|
ee.Filter.greaterThanOrEquals(leftField, rightValue, rightField, leftValue) | Filtr |
Argument | Typ | Szczegóły |
---|
leftField | Ciąg tekstowy, domyślnie: null | Selektor lewego argumentu. Nie należy go określać, jeśli określono wartość leftValue. |
rightValue | Obiekt, domyślnie: null | Wartość prawego argumentu. Nie należy go określać, jeśli określono parametr rightField. |
rightField | Ciąg tekstowy, domyślnie: null | Selektor prawego argumentu. Nie należy go określać, jeśli określono wartość rightValue. |
leftValue | Obiekt, domyślnie: null | Wartość lewego argumentu. Nie należy go określać, jeśli określono parametr leftField. |
Przykłady
Edytor kodu (JavaScript)
// Field site vegetation characteristics from projects in western USA.
var fc = ee.FeatureCollection('BLM/AIM/v1/TerrADat/TerrestrialAIM')
.filter('ProjectName == "Colorado NWDO Kremmling FO 2016"');
// Display field plots on the map.
Map.setCenter(-107.792, 39.871, 7);
Map.addLayer(fc);
// Compare the per-feature values of two properties and filter the collection
// based on the results of various relational expressions. The two properties
// to compare are invasive and non-invasive annual forb cover at each plot.
var leftProperty = 'InvAnnForbCover_AH';
var rightProperty = 'NonInvAnnForbCover_AH';
print('Plots where invasive forb cover is…');
print('…EQUAL to non-invasive cover',
fc.filter(ee.Filter.equals(
{leftField: leftProperty, rightField: rightProperty})));
print('…NOT EQUAL to non-invasive cover',
fc.filter(ee.Filter.notEquals(
{leftField: leftProperty, rightField: rightProperty})));
print('…LESS THAN non-invasive cover',
fc.filter(ee.Filter.lessThan(
{leftField: leftProperty, rightField: rightProperty})));
print('…LESS THAN OR EQUAL to non-invasive cover',
fc.filter(ee.Filter.lessThanOrEquals(
{leftField: leftProperty, rightField: rightProperty})));
print('…GREATER THAN non-invasive cover',
fc.filter(ee.Filter.greaterThan(
{leftField: leftProperty, rightField: rightProperty})));
print('…GREATER THAN OR EQUAL to non-invasive cover',
fc.filter(ee.Filter.greaterThanOrEquals(
{leftField: leftProperty, rightField: rightProperty})));
print('…is not greater than 10 percent different than non-invasive cover',
fc.filter(ee.Filter.maxDifference(
{difference: 10, leftField: leftProperty, rightField: rightProperty})));
// Instead of comparing values of two feature properties using the leftField
// and rightField parameters, you can compare a property value (leftProperty)
// against a constant value (rightValue).
print('Plots where invasive forb cover is greater than 20%',
fc.filter(ee.Filter.greaterThan(
{leftField: leftProperty, rightValue: 20})));
// You can also swap the operands to assign the constant to the left side of
// the relational expression (leftValue) and the feature property on the right
// (rightField). Here, we get the complement of the previous example.
print('Plots where 20% is greater than invasive forb cover.',
fc.filter(ee.Filter.greaterThan(
{leftValue: 20, rightField: leftProperty})));
// Binary filters are useful in joins. For example, group all same-site plots
// together using a saveAll join.
var groupingProp = 'SiteID';
var sitesFc = fc.distinct(groupingProp);
var joinFilter = ee.Filter.equals(
{leftField: groupingProp, rightField: groupingProp});
var groupedPlots = ee.Join.saveAll('site_plots').apply(sitesFc, fc, joinFilter);
print('List of plots in first site', groupedPlots.first().get('site_plots'));
Konfiguracja Pythona
Informacje o interfejsie Python API i używaniu geemap
do interaktywnego programowania znajdziesz na stronie
Środowisko Python.
import ee
import geemap.core as geemap
Colab (Python)
# Field site vegetation characteristics from projects in western USA.
fc = ee.FeatureCollection('BLM/AIM/v1/TerrADat/TerrestrialAIM').filter(
'ProjectName == "Colorado NWDO Kremmling FO 2016"'
)
# Display field plots on the map.
m = geemap.Map()
m.set_center(-107.792, 39.871, 7)
m.add_layer(fc)
display(m)
# Compare the per-feature values of two properties and filter the collection
# based on the results of various relational expressions. The two properties
# to compare are invasive and non-invasive annual forb cover at each plot.
left_property = 'InvAnnForbCover_AH'
right_property = 'NonInvAnnForbCover_AH'
display('Plots where invasive forb cover is…')
display(
'…EQUAL to non-invasive cover',
fc.filter(
ee.Filter.equals(leftField=left_property, rightField=right_property)
),
)
display(
'…NOT EQUAL to non-invasive cover',
fc.filter(
ee.Filter.notEquals(leftField=left_property, rightField=right_property)
),
)
display(
'…LESS THAN non-invasive cover',
fc.filter(
ee.Filter.lessThan(leftField=left_property, rightField=right_property)
),
)
display(
'…LESS THAN OR EQUAL to non-invasive cover',
fc.filter(
ee.Filter.lessThanOrEquals(
leftField=left_property, rightField=right_property
)
),
)
display(
'…GREATER THAN non-invasive cover',
fc.filter(
ee.Filter.greaterThan(
leftField=left_property, rightField=right_property
)
),
)
display(
'…GREATER THAN OR EQUAL to non-invasive cover',
fc.filter(
ee.Filter.greaterThanOrEquals(
leftField=left_property, rightField=right_property
)
),
)
display(
'…is not greater than 10 percent different than non-invasive cover',
fc.filter(
ee.Filter.maxDifference(
difference=10, leftField=left_property, rightField=right_property
)
),
)
# Instead of comparing values of two feature properties using the leftField
# and rightField parameters, you can compare a property value (left_property)
# against a constant value (rightValue).
display(
'Plots where invasive forb cover is greater than 20%',
fc.filter(ee.Filter.greaterThan(leftField=left_property, rightValue=20)),
)
# You can also swap the operands to assign the constant to the left side of
# the relational expression (leftValue) and the feature property on the right
# (rightField). Here, we get the complement of the previous example.
display(
'Plots where 20% is greater than invasive forb cover.',
fc.filter(ee.Filter.greaterThan(leftValue=20, rightField=left_property)),
)
# Binary filters are useful in joins. For example, group all same-site plots
# together using a saveAll join.
grouping_prop = 'SiteID'
sites_fc = fc.distinct(grouping_prop)
join_filter = ee.Filter.equals(
leftField=grouping_prop, rightField=grouping_prop
)
grouped_plots = ee.Join.saveAll('site_plots').apply(sites_fc, fc, join_filter)
display('List of plots in first site', grouped_plots.first().get('site_plots'))
O ile nie stwierdzono inaczej, treść tej strony jest objęta licencją Creative Commons – uznanie autorstwa 4.0, a fragmenty kodu są dostępne na licencji Apache 2.0. Szczegółowe informacje na ten temat zawierają zasady dotyczące witryny Google Developers. Java jest zastrzeżonym znakiem towarowym firmy Oracle i jej podmiotów stowarzyszonych.
Ostatnia aktualizacja: 2025-07-26 UTC.
[null,null,["Ostatnia aktualizacja: 2025-07-26 UTC."],[],["The code filters a `FeatureCollection` based on relational expressions between properties or between a property and a constant value. It uses `ee.Filter` methods like `equals`, `notEquals`, `lessThan`, `greaterThan`, `lessThanOrEquals`, `greaterThanOrEquals`, and `maxDifference`. These filters compare properties (`leftField`, `rightField`) or values (`leftValue`, `rightValue`). Finally, they are applied in joins to group same-site plots.\n"],null,[]]