Duyuru:
15 Nisan 2025'ten önce Earth Engine'i kullanmak için kaydedilen tüm ticari olmayan projelerin Earth Engine erişimini sürdürmek için
ticari olmayan uygunluğu doğrulaması gerekir.
ee.Filter.lessThanOrEquals
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
Sol işlenen sağ işlenenden büyük olmadığı sürece geçen tekli veya ikili filtre oluşturur.
Kullanım | İadeler |
---|
ee.Filter.lessThanOrEquals(leftField, rightValue, rightField, leftValue) | Filtre |
Bağımsız Değişken | Tür | Ayrıntılar |
---|
leftField | Dize, varsayılan: null | Sol işlenen için seçici. leftValue belirtilmişse belirtilmemelidir. |
rightValue | Nesne, varsayılan: null | Sağ işlenenin değeri. rightField belirtilmişse belirtilmemelidir. |
rightField | Dize, varsayılan: null | Sağ işlenen için bir seçici. rightValue belirtilmişse belirtilmemelidir. |
leftValue | Nesne, varsayılan: null | Sol işlenenin değeri. leftField belirtilmişse belirtilmemelidir. |
Örnekler
Kod Düzenleyici (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'));
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap
kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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'))
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 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```"]]