APP网站开发私人订制百度的营销方式有哪些

问题：

我有两个具有相同 ID 的特征集，我想从第二个特征集中减去第一个特征集的表格单元格。

我使用了这个函数，但它计算的是表 1 中第一个元素与表 2 中其他元素的减法。

我想逐个单元格计算减法。第一个表格中 id 为 1 的单元格减去第二个表格中 id 为 1 的单元格，2x2、3x3...

有人能帮我完成这项任务吗？
 

var result = falsealarms.map(function(falsealarms){var idb = falsealarms.get('id');var valuea = omission.filter(ee.Filter.eq('id', idb)).first().get('count');var resultvalue = ee.Number(falsealarms.get('count')).subtract(valuea);return omission.set('result', resultvalue)
});

使用它们旨在从两个集合中查找匹配的元素。

函数

ee.Join.saveFirst(matchKey, ordering, ascending, measureKey, outer)

Returns a join that pairs each element from the first collection with a matching element from the second collection. The first match is added to the result as an additional property.

Arguments:

matchKey (String):

The property name used to save the match.

ordering (String, default: null):

The property on which to sort the matches before selecting the first.

ascending (Boolean, default: true):

Whether the ordering is ascending.

measureKey (String, default: null):

An optional property name used to save the measure of the join condition on the match.

outer (Boolean, default: false):

If true, primary rows without matches will be included in the result.

Returns: Join

apply(primary, secondary, condition)

Joins two collections.

Arguments:

this:join (Join):

The join to apply; determines how the the results are constructed.

primary (FeatureCollection):

The primary collection.

secondary (FeatureCollection):

The secondary collection.

condition (Filter):

The join condition used to select the matches from the two collections.

Returns: FeatureCollection

原始代码：

//define the study area 
var roi = roi.filter(ee.Filter.inList('Nomencl', ['SH-21-X-D']));Map.centerObject(roi, 10) Deforestation Mapbiomas///Select the t mapbiomas land use classification
var mabiomas_t = ee.Image('projects/mapbiomas-workspace/public/collection8/mapbiomas_collection80_integration_v1').clip(roi) .select('classification_2000'); // create a list of land use classes from the classification
var fromList = [3, 4, 5, 6, 49, 11, 12, 50, 32, 29, 13, 15, 18, 19, 39, 20, 40, 62, 41, 36, 46, 47, 35, 48, 9, 21, 23, 24, 30, 25, 33, 31, 27];// A corresponding list of replacement values 
var toList =  [1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2];// performs the reclassification
var t_remap = mabiomas_t.remap({from: fromList,to: toList,defaultValue: 0,bandName: 'classification_2000'
}).reproject('EPSG:4326', null, 30);
//Map.addLayer(t_remap)//Select the vegetation land use class
var veg_class_t = t_remap.eq(1) 
//Map.addLayer(veg_class_t, null, 'veg_class_mapbiomas')//Select the t + 1 mapbiomas land use classification
var mapbiomas_t1 = ee.Image('projects/mapbiomas-workspace/public/collection8/mapbiomas_collection80_integration_v1').clip(roi) .select('classification_2020'); var fromList = [3, 4, 5, 6, 49, 11, 12, 50, 32, 29, 13, 15, 18, 19, 39, 20, 40, 62, 41, 36, 46, 47, 35, 48, 9, 21, 23, 24, 30, 25, 33, 31, 27];// A corresponding list of replacement values 
var toList =  [10, 10, 10, 10, 10, 10, 10, 10, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 2