ee.Filter.greaterThan

Tạo một bộ lọc một ngôi hoặc bộ lọc nhị phân sẽ truyền nếu toán hạng bên trái lớn hơn toán hạng bên phải.

Cách sử dụng	Giá trị trả về
ee.Filter.greaterThan(leftField, rightValue, rightField, leftValue)	Lọc

Đối số	Loại	Thông tin chi tiết
leftField	Chuỗi, mặc định: rỗng	Bộ chọn cho toán hạng bên trái. Không được chỉ định nếu leftValue được chỉ định.
rightValue	Đối tượng, mặc định: rỗng	Giá trị của toán hạng bên phải. Không được chỉ định nếu bạn chỉ định rightField.
rightField	Chuỗi, mặc định: rỗng	Bộ chọn cho toán hạng bên phải. Không được chỉ định nếu rightValue được chỉ định.
leftValue	Đối tượng, mặc định: rỗng	Giá trị của toán hạng bên trái. Không được chỉ định nếu leftField được chỉ định.

Ví dụ

Trình soạn thảo mã (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'));

Thiết lập Python

Hãy xem trang Môi trường Python để biết thông tin về API Python và cách sử dụng geemap để phát triển tương tác.

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'))