ee.Filter.lessThan

左のオペランドが右のオペランドより小さい場合にパスする単項または二項フィルタを作成します。

用途	戻り値
ee.Filter.lessThan(leftField, rightValue, rightField, leftValue)	フィルタ

引数	タイプ	詳細
leftField	文字列、デフォルト: null	左オペランドのセレクタ。leftValue が指定されている場合は指定しないでください。
rightValue	オブジェクト、デフォルト: null	右オペランドの値。rightField が指定されている場合は指定しないでください。
rightField	文字列、デフォルト: null	右オペランドのセレクタ。rightValue が指定されている場合は指定しないでください。
leftValue	オブジェクト、デフォルト: null	左オペランドの値。leftField が指定されている場合は指定しないでください。

例

コードエディタ（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 の設定

Python API とインタラクティブな開発での geemap の使用については、 Python 環境のページをご覧ください。

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'))