ee.Filter.lessThanOrEquals
Restez organisé à l'aide des collections
Enregistrez et classez les contenus selon vos préférences.
Crée un filtre unaire ou binaire qui est transmis, sauf si l'opérande de gauche est supérieur à l'opérande de droite.
Utilisation | Renvoie |
---|
ee.Filter.lessThanOrEquals(leftField, rightValue, rightField, leftValue) | Filtre |
Argument | Type | Détails |
---|
leftField | Chaîne, valeur par défaut : null | Sélecteur pour l'opérande de gauche. Ne doit pas être spécifié si leftValue est spécifié. |
rightValue | Objet, valeur par défaut : null | Valeur de l'opérande de droite. Ne doit pas être spécifié si rightField est spécifié. |
rightField | Chaîne, valeur par défaut : null | Sélecteur pour l'opérande de droite. Ne doit pas être spécifié si rightValue est spécifié. |
leftValue | Objet, valeur par défaut : null | Valeur de l'opérande de gauche. Ne doit pas être spécifié si leftField est spécifié. |
Exemples
Éditeur de code (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'));
Configuration de Python
Consultez la page
Environnement Python pour en savoir plus sur l'API Python et sur l'utilisation de geemap
pour le développement interactif.
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'))
Sauf indication contraire, le contenu de cette page est régi par une licence Creative Commons Attribution 4.0, et les échantillons de code sont régis par une licence Apache 2.0. Pour en savoir plus, consultez les Règles du site Google Developers. Java est une marque déposée d'Oracle et/ou de ses sociétés affiliées.
Dernière mise à jour le 2025/07/26 (UTC).
[null,null,["Dernière mise à jour le 2025/07/26 (UTC)."],[[["\u003cp\u003eCreates a filter that passes features unless the left operand is greater than the right operand.\u003c/p\u003e\n"],["\u003cp\u003eThe filter can be unary or binary, comparing a property to a constant or two properties.\u003c/p\u003e\n"],["\u003cp\u003eOperands are specified using \u003ccode\u003eleftField\u003c/code\u003e, \u003ccode\u003erightValue\u003c/code\u003e, \u003ccode\u003erightField\u003c/code\u003e, and \u003ccode\u003eleftValue\u003c/code\u003e parameters.\u003c/p\u003e\n"],["\u003cp\u003eUseful for filtering FeatureCollections based on property comparisons.\u003c/p\u003e\n"],["\u003cp\u003eCan be used in joins to group features based on shared properties.\u003c/p\u003e\n"]]],["The content describes creating filters using `ee.Filter` for comparing data. This involves using methods like `equals`, `notEquals`, `lessThan`, `lessThanOrEquals`, `greaterThan`, `greaterThanOrEquals`, and `maxDifference` to filter a FeatureCollection based on property comparisons. These comparisons can be between two fields (e.g., `leftField`, `rightField`) or a field and a constant value (e.g., `leftField`, `rightValue`). These filters are used to filter collections and are also used in joins.\n"],null,["# ee.Filter.lessThanOrEquals\n\nCreates a unary or binary filter that passes unless the left operand is greater than the right operand.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-----------------------------------------------------------------------------------------------|---------|\n| `ee.Filter.lessThanOrEquals(`*leftField* `, `*rightValue* `, `*rightField* `, `*leftValue*`)` | Filter |\n\n| Argument | Type | Details |\n|--------------|-----------------------|---------------------------------------------------------------------------------------|\n| `leftField` | String, default: null | A selector for the left operand. Should not be specified if leftValue is specified. |\n| `rightValue` | Object, default: null | The value of the right operand. Should not be specified if rightField is specified. |\n| `rightField` | String, default: null | A selector for the right operand. Should not be specified if rightValue is specified. |\n| `leftValue` | Object, default: null | The value of the left operand. Should not be specified if leftField is specified. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// Field site vegetation characteristics from projects in western USA.\nvar fc = ee.FeatureCollection('BLM/AIM/v1/TerrADat/TerrestrialAIM')\n .filter('ProjectName == \"Colorado NWDO Kremmling FO 2016\"');\n\n// Display field plots on the map.\nMap.setCenter(-107.792, 39.871, 7);\nMap.addLayer(fc);\n\n// Compare the per-feature values of two properties and filter the collection\n// based on the results of various relational expressions. The two properties\n// to compare are invasive and non-invasive annual forb cover at each plot.\nvar leftProperty = 'InvAnnForbCover_AH';\nvar rightProperty = 'NonInvAnnForbCover_AH';\n\nprint('Plots where invasive forb cover is...');\n\nprint('...EQUAL to non-invasive cover',\n fc.filter(ee.Filter.equals(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...NOT EQUAL to non-invasive cover',\n fc.filter(ee.Filter.notEquals(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...LESS THAN non-invasive cover',\n fc.filter(ee.Filter.lessThan(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...LESS THAN OR EQUAL to non-invasive cover',\n fc.filter(ee.Filter.lessThanOrEquals(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...GREATER THAN non-invasive cover',\n fc.filter(ee.Filter.greaterThan(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...GREATER THAN OR EQUAL to non-invasive cover',\n fc.filter(ee.Filter.greaterThanOrEquals(\n {leftField: leftProperty, rightField: rightProperty})));\n\nprint('...is not greater than 10 percent different than non-invasive cover',\n fc.filter(ee.Filter.maxDifference(\n {difference: 10, leftField: leftProperty, rightField: rightProperty})));\n\n// Instead of comparing values of two feature properties using the leftField\n// and rightField parameters, you can compare a property value (leftProperty)\n// against a constant value (rightValue).\nprint('Plots where invasive forb cover is greater than 20%',\n fc.filter(ee.Filter.greaterThan(\n {leftField: leftProperty, rightValue: 20})));\n\n// You can also swap the operands to assign the constant to the left side of\n// the relational expression (leftValue) and the feature property on the right\n// (rightField). Here, we get the complement of the previous example.\nprint('Plots where 20% is greater than invasive forb cover.',\n fc.filter(ee.Filter.greaterThan(\n {leftValue: 20, rightField: leftProperty})));\n\n// Binary filters are useful in joins. For example, group all same-site plots\n// together using a saveAll join.\nvar groupingProp = 'SiteID';\nvar sitesFc = fc.distinct(groupingProp);\n\nvar joinFilter = ee.Filter.equals(\n {leftField: groupingProp, rightField: groupingProp});\n\nvar groupedPlots = ee.Join.saveAll('site_plots').apply(sitesFc, fc, joinFilter);\nprint('List of plots in first site', groupedPlots.first().get('site_plots'));\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# Field site vegetation characteristics from projects in western USA.\nfc = ee.FeatureCollection('BLM/AIM/v1/TerrADat/TerrestrialAIM').filter(\n 'ProjectName == \"Colorado NWDO Kremmling FO 2016\"'\n)\n\n# Display field plots on the map.\nm = geemap.Map()\nm.set_center(-107.792, 39.871, 7)\nm.add_layer(fc)\ndisplay(m)\n\n# Compare the per-feature values of two properties and filter the collection\n# based on the results of various relational expressions. The two properties\n# to compare are invasive and non-invasive annual forb cover at each plot.\nleft_property = 'InvAnnForbCover_AH'\nright_property = 'NonInvAnnForbCover_AH'\n\ndisplay('Plots where invasive forb cover is...')\n\ndisplay(\n '...EQUAL to non-invasive cover',\n fc.filter(\n ee.Filter.equals(leftField=left_property, rightField=right_property)\n ),\n)\n\ndisplay(\n '...NOT EQUAL to non-invasive cover',\n fc.filter(\n ee.Filter.notEquals(leftField=left_property, rightField=right_property)\n ),\n)\n\ndisplay(\n '...LESS THAN non-invasive cover',\n fc.filter(\n ee.Filter.lessThan(leftField=left_property, rightField=right_property)\n ),\n)\n\ndisplay(\n '...LESS THAN OR EQUAL to non-invasive cover',\n fc.filter(\n ee.Filter.lessThanOrEquals(\n leftField=left_property, rightField=right_property\n )\n ),\n)\n\ndisplay(\n '...GREATER THAN non-invasive cover',\n fc.filter(\n ee.Filter.greaterThan(\n leftField=left_property, rightField=right_property\n )\n ),\n)\n\ndisplay(\n '...GREATER THAN OR EQUAL to non-invasive cover',\n fc.filter(\n ee.Filter.greaterThanOrEquals(\n leftField=left_property, rightField=right_property\n )\n ),\n)\n\ndisplay(\n '...is not greater than 10 percent different than non-invasive cover',\n fc.filter(\n ee.Filter.maxDifference(\n difference=10, leftField=left_property, rightField=right_property\n )\n ),\n)\n\n# Instead of comparing values of two feature properties using the leftField\n# and rightField parameters, you can compare a property value (left_property)\n# against a constant value (rightValue).\ndisplay(\n 'Plots where invasive forb cover is greater than 20%',\n fc.filter(ee.Filter.greaterThan(leftField=left_property, rightValue=20)),\n)\n\n# You can also swap the operands to assign the constant to the left side of\n# the relational expression (leftValue) and the feature property on the right\n# (rightField). Here, we get the complement of the previous example.\ndisplay(\n 'Plots where 20% is greater than invasive forb cover.',\n fc.filter(ee.Filter.greaterThan(leftValue=20, rightField=left_property)),\n)\n\n# Binary filters are useful in joins. For example, group all same-site plots\n# together using a saveAll join.\ngrouping_prop = 'SiteID'\nsites_fc = fc.distinct(grouping_prop)\n\njoin_filter = ee.Filter.equals(\n leftField=grouping_prop, rightField=grouping_prop\n)\n\ngrouped_plots = ee.Join.saveAll('site_plots').apply(sites_fc, fc, join_filter)\ndisplay('List of plots in first site', grouped_plots.first().get('site_plots'))\n```"]]