为什么我的组合蒙版通过 GEE 中的 ImageCollection 将不同区域屏蔽到各个蒙版？
Why is my combined Mask masking different areas to the individual Masks over an ImageCollection in GEE?
我正在尝试对 Water 上的 Sentinel-2 卫星图像执行时间序列分析，为此我一直在混淆使用函数对图像集合中的图像执行分析。
我之前使用 .mosaic() 对单个图像进行了进一步的分析，但不能将其用于时间序列。使用 this earlier question and the GEE Guides 我已经能够 运行 测试区域的 NDVI 和 NDWI，根据这些创建单独的掩码，然后 'Add'（Combine/Overlay/Union？）将它们变成一个新的所有区域都被两个蒙版覆盖的图层。
我 运行 遇到的问题是，当我有最终的组合遮罩层时，未遮罩的图像与组合遮罩或单个遮罩都不匹配。我怀疑应用蒙版的图像也与原始图像完全不同，因为大部分剪切图像都包含原始 L1C 图像所没有的新区域中的云。
例如：
原图
组合 NDVI/NDWI 面具（即匹配“1”的水区域，面具上的红色）
与上面的 L1C 蒙版相比，应用于图像的相同组合蒙版（L1C 应用，白灰色）
那么，是什么导致出现不同的蒙版区域呢？我的代码的哪一部分导致了这个错误，对于我必须对图像集合中的每个单独图像应用蒙版的方式，是否有修复或更简单的替代方法？
我已经包含了下面的代码，以及 GEE Link。我已尽力组织和解释每个部分的作用，但由于我对 GEE 和 .js 还很陌生，所以这里和那里可能有明显的错误。我很乐意就任何事情提供更多说明。
// ### IMPORTED GEOMETRY ###
var ShannonGeom =
/* color: #d6cfcf */
/* shown: false */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[-9.061457413652322, 52.9400316020557],
[-9.061457413652322, 52.6131383784731],
[-8.26623608491697, 52.6131383784731],
[-8.26623608491697, 52.9400316020557]]], null, false);
// ### FILTER PARAMETERS ###
//These apply the parameters to stop repetitive data entry and searching for the correct line to enter them.
// CLOUD % format '00' , numbers only without quotes
var MIN_CLOUD_PERCENT = 50;
// START DATE & END DATE format: 'YYYY-MM-DD', include the quotes
var START_DATE = '2022-01-01';
var END_DATE = '2022-04-01';
// BOUNDS can either be a drawn geometry shape within GEE, or an imported SHP file
// See: https://developers.google.com/earth-engine/guides/table_upload#upload-a-shapefile
var BOUNDS = ShannonGeom;
// ZOOM is based on GEE's 1-24 level system. Larger number = Larger Zoom
var ZOOM = 10;
// PARAMETERS END - You don't need to change anything below this line to make the script function
// ### MISC ###
//Prints out the Parameters set
print('Filtering available Sentinel 2 imagery between ' + START_DATE + ' & ' + END_DATE + ' with ' + MIN_CLOUD_PERCENT + '% cloud over the area of interest.');
// Centre based on the Geometry (Region of Interest, Zoom Level)
Map.centerObject(BOUNDS, ZOOM, print('Map centered on Region of Interest'));
// Sets the default Map to Terrain mode (Roadmap overlain with hillsahde)
Map.setOptions("TERRAIN");
// ### EEPALETTES & LAYER VISUALISATION ###
/* Required for most layer visualisations
* See https://github.com/gee-community/ee-palettes for more information
*
* IF IT FAILS TO LOAD the PALETTES, LOAD THIS URL FIRST, THEN REFRESH THE PAGE:
* (https://code.earthengine.google.com/?accept_repo=users/gena/packages)
*/
var palettes = require('users/gena/packages:palettes');
// NDWI palette
var NDWIPalette = palettes.cmocean.Ice[7].reverse();
// NDVI palette
var NDVIPalette = palettes.colorbrewer.RdYlGn[10];
// Truecolour (R-G-B) Visualisation
var rgbVis = {
min: 0,
max: 0.35,
bands: ['B4', 'B3', 'B2'],
};
// NDWI Visualisation
var NDWIVis = {
min: -1,
max: 1,
bands: ['NDWI'],
palette: NDWIPalette
};
// NDVI Visualisation
var NDVIVis = {
min: -1,
max: 1,
bands: ['NDVI'],
palette: NDVIPalette
};
// NDVI Mask Visualisation
var NDVIMaskVis = {
min: 0, // Land Areas
max: 1, // Other Areas
bands: ['NDVI_Mask'],
palette: ['cccccc','088300'],
opacity: 0.65
};
// NDWI Mask Visualisation
var NDWIMaskVis = {
min: 0, // Land and Non-Water Areas
max: 1, // Water Areas
bands: ['NDWI_Mask'],
palette: ['cccccc','0000ff'],
opacity: 0.65
};
// L1C Water/Veg Mask Visualisation
var L1CMaskVis = {
min: 0, // Land and Non-Water Areas
max: 1, // Water Areas
bands: ['L1CMask'],
palette: ['cccccc','f90000'],
opacity: 0.65
};
// ### CLOUD MASKING ###
// Sentinel 2 Cloud Masking Function using the 60m Cloud Mask Band
/* Function to mask clouds using the Sentinel-2 QA band
* @param {ee.Image} image Sentinel-2 image
* @return {ee.Image} cloud masked Sentinel-2 image
*/
function maskS2clouds(image) {
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = 1 << 10;
var cirrusBitMask = 1 << 11;
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and(qa.bitwiseAnd(cirrusBitMask).eq(0));
return image.updateMask(mask).divide(10000);
}
print('Sentinel 2 Cloud Mask Function Complete');
// ### IMAGE COLLECTIONS ###
//Load and Map L1C imagery with the filter parameters applied
/*
* Load Sentinel-2 'Harmonized' Top Of Atomsphere (L1C) data
* Dataset details: https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED
* HARMONIZED makes sure scenes after 25 January 2022 have the same DN ranges as older L1C scenes.
* Harmonised L1C Data is available from Sentinel 2 Launch (2015-06-23) onwards.
*/
var S2_L1C = ee.ImageCollection('COPERNICUS/S2_HARMONIZED')
// Filter by Date Period (YYYY-MM-DD)
.filterDate(START_DATE, END_DATE)
/*
* Pre-filter to get less cloudy granules
* 'Default' is aiming for 10% cloud
* Dependent on availability of cloud-free imagery in the time period set
* Longer periods will take longer to load
*/
.filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', MIN_CLOUD_PERCENT))
// Select only image tiles that fall within the Geometry (Region of Interest) to reduce processing time
.filterBounds(BOUNDS)
// Applies the S2 Cloud Masking Function to each image in the IC
.map(maskS2clouds)
// Clips each image in the IC by the Bounds to reduce processing time further
.map(function(image) {
return image.clip(BOUNDS);
});
print('Time, Date, Bounding, and Cloud Tile Filtering parameters set for Imagery');
// Add the pre-clipped IC's to the map
Map.addLayer(S2_L1C,rgbVis,'L1C');
// ### FUNCTIONS ###
// Add NDWI band to IC
var addNDWI = function(image) {
return image.addBands(image.normalizedDifference(['B3', 'B8']).rename('NDWI'));
};
// Add an NDVI band to IC
var addNDVI = function(image) {
return image.addBands(image.normalizedDifference(['B8', 'B4']).rename('NDVI'));
};
// ### L1C MASK FUNCTIONS ###
// Function to mask out NDWI (L1C)
var WaterMaskL1C = function(image) {
var NDWI = image.select(['NDWI']);
return image.addBands(NDWI.gte(0.1).rename('NDWI_Mask'));
};
// Function to mask out NDVI (L1C)
var VegMaskL1C = function(image) {
var NDVI = image.select(['NDVI']);
return image.addBands(NDVI.lte(0).rename('NDVI_Mask'));
};
// Function to combine both L1C Masks
var CombinedL1CMask = function(image) {
var NDWI_Mask = image.select(['NDWI_Mask']);
var NDVI_Mask = image.select(['NDVI_Mask']);
// Adds the 2 masks together, and then clamps the output to be binary to keep it suitable for masking
return image.addBands(NDWI_Mask.add(NDVI_Mask).clamp(0,1).rename('L1CMask'));
};
// Function to update the clipping of imagery to just the water areas, as defined by the combined Mask
//.rename(['B1_Msk','B2_Msk','B3_Msk','B4_Msk','B5_Msk','B6_Msk','B7_Msk','B8_Msk','B8A_Msk','B9_Msk','B10_Msk','B11_Msk','B12_Msk','QA10_Msk','QA20_Msk','QA60_Msk','NDWI_Msk','NDVI_Msk','NDVI_Mask2','NDWI_Mask2','L1CMask2'])
var L1CMasking = function(image) {
var Mask = image.select(['L1CMask']);
return image.updateMask(Mask.eq(1));
};
// Applies all the functions to respective image collections
var S2_L1C_Func = S2_L1C.map(addNDWI).map(addNDVI).map(VegMaskL1C).map(WaterMaskL1C).map(CombinedL1CMask);
// Add the individual new bands to the Map
// NDVI
Map.addLayer(S2_L1C_Func, NDVIVis, 'L1C NDVI');
// NDWI
Map.addLayer(S2_L1C_Func, NDWIVis, 'L1C NDWI');
// NDVI Mask
Map.addLayer(S2_L1C_Func, NDVIMaskVis, 'L1C NDVIMask');
// NDWI Mask
Map.addLayer(S2_L1C_Func, NDWIMaskVis, 'L1C NDWIMask');
// Combo Mask
Map.addLayer(S2_L1C_Func, L1CMaskVis, 'L1C Mask');
/* Creating a new var to run the mask apply function, because otherwise for some reason it retroactively
* breaks all the earlier separate ND VI/WI masks
*/
var S2_L1C_Masked = S2_L1C_Func.map(L1CMasking);
// Clipped hopefully?!
Map.addLayer(S2_L1C_Masked, rgbVis, 'L1C MaskApplied');
我也尝试过分别将蒙版更新为图像，如下所示，但这只会带来另一个不同且不正确的蒙版图像（很明显，蒙版 L1C 图像中包含云，而蒙版 L1C 图像中没有云） L1C原图，连右下角的Estuary都变潮了！）。
/* Instead of combining the two Masks prior to applying them to the IC, this updates the IC's Mask by the two separate layers
* together. This is only applied to the "image" bands (B1-B12), not the other newly created bands.
*/
var MaskBandsL1C = function(image) {
return image.select(['B1','B2','B3','B4','B5','B6','B7','B8','B9','B10','B11','B12','NDVI_Mask','NDWI_Mask'])
.updateMask(image.select('NDVI_Mask'))
.updateMask(image.select('NDWI_Mask'));
};
// Combo Mask
var ICMaskL2A = S2_L2A_Func.map(MaskBandsL2A);
var ICMaskL1C = S2_L1C_Func.map(MaskBandsL1C);
Map.addLayer(ICMaskL2A, rgbVis, 'L2A Masked');
Map.addLayer(ICMaskL1C, rgbVis, 'L1C Masked');
第二个掩码示例的替代（和不正确）结果
所以蒙版 'working' 因为它提供了适合我的条件的区域，但它至少会显示一天中不同时间的图像（最坏的情况是不同日期的图像）完全） - 是否也可以让蒙版图像按 system:time_start 对齐，因为我将不得不使用它来创建 Time Series chart?
感谢您花时间对正在发生的事情做出任何解释。
回答更新
我之前向姐妹 GIS Stack Exchange 发布了这个类似的问题（我不确定这是否是不礼貌的，我只是想之后在这里问可能会有更好的影响力）和 Olga Danylo was able to explain the issue I was having。如果其他人遇到类似问题，我建议您阅读他们的回答，如果他们也帮助了您，请给他们 +1。
简而言之：
屏蔽是工作，只是当我.map一个没有特定过滤日期或图像的图层时，任何结果都会被拉出并显示，并且它碰巧我的单独蒙版似乎匹配，直到最终组合蒙版层。将 system:time_start 属性 添加到第一个云映射函数，然后将所有 Map.addLayer 过滤到同一日期（即 Map.addLayer(S2_L1C_Func.filterDate('2022-03-30', '2022-04-01') 给出了我想要的地图结果。Olga 给出比我更好的解释，所以我真的建议只阅读他们在上面 link 上的回答。
我正在尝试对 Water 上的 Sentinel-2 卫星图像执行时间序列分析，为此我一直在混淆使用函数对图像集合中的图像执行分析。
我之前使用 .mosaic() 对单个图像进行了进一步的分析，但不能将其用于时间序列。使用 this earlier question and the GEE Guides 我已经能够 运行 测试区域的 NDVI 和 NDWI，根据这些创建单独的掩码，然后 'Add'（Combine/Overlay/Union？）将它们变成一个新的所有区域都被两个蒙版覆盖的图层。
我 运行 遇到的问题是，当我有最终的组合遮罩层时，未遮罩的图像与组合遮罩或单个遮罩都不匹配。我怀疑应用蒙版的图像也与原始图像完全不同，因为大部分剪切图像都包含原始 L1C 图像所没有的新区域中的云。
例如：
原图
那么，是什么导致出现不同的蒙版区域呢？我的代码的哪一部分导致了这个错误，对于我必须对图像集合中的每个单独图像应用蒙版的方式，是否有修复或更简单的替代方法？
我已经包含了下面的代码，以及 GEE Link。我已尽力组织和解释每个部分的作用，但由于我对 GEE 和 .js 还很陌生，所以这里和那里可能有明显的错误。我很乐意就任何事情提供更多说明。
// ### IMPORTED GEOMETRY ###
var ShannonGeom =
/* color: #d6cfcf */
/* shown: false */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[-9.061457413652322, 52.9400316020557],
[-9.061457413652322, 52.6131383784731],
[-8.26623608491697, 52.6131383784731],
[-8.26623608491697, 52.9400316020557]]], null, false);
// ### FILTER PARAMETERS ###
//These apply the parameters to stop repetitive data entry and searching for the correct line to enter them.
// CLOUD % format '00' , numbers only without quotes
var MIN_CLOUD_PERCENT = 50;
// START DATE & END DATE format: 'YYYY-MM-DD', include the quotes
var START_DATE = '2022-01-01';
var END_DATE = '2022-04-01';
// BOUNDS can either be a drawn geometry shape within GEE, or an imported SHP file
// See: https://developers.google.com/earth-engine/guides/table_upload#upload-a-shapefile
var BOUNDS = ShannonGeom;
// ZOOM is based on GEE's 1-24 level system. Larger number = Larger Zoom
var ZOOM = 10;
// PARAMETERS END - You don't need to change anything below this line to make the script function
// ### MISC ###
//Prints out the Parameters set
print('Filtering available Sentinel 2 imagery between ' + START_DATE + ' & ' + END_DATE + ' with ' + MIN_CLOUD_PERCENT + '% cloud over the area of interest.');
// Centre based on the Geometry (Region of Interest, Zoom Level)
Map.centerObject(BOUNDS, ZOOM, print('Map centered on Region of Interest'));
// Sets the default Map to Terrain mode (Roadmap overlain with hillsahde)
Map.setOptions("TERRAIN");
// ### EEPALETTES & LAYER VISUALISATION ###
/* Required for most layer visualisations
* See https://github.com/gee-community/ee-palettes for more information
*
* IF IT FAILS TO LOAD the PALETTES, LOAD THIS URL FIRST, THEN REFRESH THE PAGE:
* (https://code.earthengine.google.com/?accept_repo=users/gena/packages)
*/
var palettes = require('users/gena/packages:palettes');
// NDWI palette
var NDWIPalette = palettes.cmocean.Ice[7].reverse();
// NDVI palette
var NDVIPalette = palettes.colorbrewer.RdYlGn[10];
// Truecolour (R-G-B) Visualisation
var rgbVis = {
min: 0,
max: 0.35,
bands: ['B4', 'B3', 'B2'],
};
// NDWI Visualisation
var NDWIVis = {
min: -1,
max: 1,
bands: ['NDWI'],
palette: NDWIPalette
};
// NDVI Visualisation
var NDVIVis = {
min: -1,
max: 1,
bands: ['NDVI'],
palette: NDVIPalette
};
// NDVI Mask Visualisation
var NDVIMaskVis = {
min: 0, // Land Areas
max: 1, // Other Areas
bands: ['NDVI_Mask'],
palette: ['cccccc','088300'],
opacity: 0.65
};
// NDWI Mask Visualisation
var NDWIMaskVis = {
min: 0, // Land and Non-Water Areas
max: 1, // Water Areas
bands: ['NDWI_Mask'],
palette: ['cccccc','0000ff'],
opacity: 0.65
};
// L1C Water/Veg Mask Visualisation
var L1CMaskVis = {
min: 0, // Land and Non-Water Areas
max: 1, // Water Areas
bands: ['L1CMask'],
palette: ['cccccc','f90000'],
opacity: 0.65
};
// ### CLOUD MASKING ###
// Sentinel 2 Cloud Masking Function using the 60m Cloud Mask Band
/* Function to mask clouds using the Sentinel-2 QA band
* @param {ee.Image} image Sentinel-2 image
* @return {ee.Image} cloud masked Sentinel-2 image
*/
function maskS2clouds(image) {
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = 1 << 10;
var cirrusBitMask = 1 << 11;
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and(qa.bitwiseAnd(cirrusBitMask).eq(0));
return image.updateMask(mask).divide(10000);
}
print('Sentinel 2 Cloud Mask Function Complete');
// ### IMAGE COLLECTIONS ###
//Load and Map L1C imagery with the filter parameters applied
/*
* Load Sentinel-2 'Harmonized' Top Of Atomsphere (L1C) data
* Dataset details: https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED
* HARMONIZED makes sure scenes after 25 January 2022 have the same DN ranges as older L1C scenes.
* Harmonised L1C Data is available from Sentinel 2 Launch (2015-06-23) onwards.
*/
var S2_L1C = ee.ImageCollection('COPERNICUS/S2_HARMONIZED')
// Filter by Date Period (YYYY-MM-DD)
.filterDate(START_DATE, END_DATE)
/*
* Pre-filter to get less cloudy granules
* 'Default' is aiming for 10% cloud
* Dependent on availability of cloud-free imagery in the time period set
* Longer periods will take longer to load
*/
.filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', MIN_CLOUD_PERCENT))
// Select only image tiles that fall within the Geometry (Region of Interest) to reduce processing time
.filterBounds(BOUNDS)
// Applies the S2 Cloud Masking Function to each image in the IC
.map(maskS2clouds)
// Clips each image in the IC by the Bounds to reduce processing time further
.map(function(image) {
return image.clip(BOUNDS);
});
print('Time, Date, Bounding, and Cloud Tile Filtering parameters set for Imagery');
// Add the pre-clipped IC's to the map
Map.addLayer(S2_L1C,rgbVis,'L1C');
// ### FUNCTIONS ###
// Add NDWI band to IC
var addNDWI = function(image) {
return image.addBands(image.normalizedDifference(['B3', 'B8']).rename('NDWI'));
};
// Add an NDVI band to IC
var addNDVI = function(image) {
return image.addBands(image.normalizedDifference(['B8', 'B4']).rename('NDVI'));
};
// ### L1C MASK FUNCTIONS ###
// Function to mask out NDWI (L1C)
var WaterMaskL1C = function(image) {
var NDWI = image.select(['NDWI']);
return image.addBands(NDWI.gte(0.1).rename('NDWI_Mask'));
};
// Function to mask out NDVI (L1C)
var VegMaskL1C = function(image) {
var NDVI = image.select(['NDVI']);
return image.addBands(NDVI.lte(0).rename('NDVI_Mask'));
};
// Function to combine both L1C Masks
var CombinedL1CMask = function(image) {
var NDWI_Mask = image.select(['NDWI_Mask']);
var NDVI_Mask = image.select(['NDVI_Mask']);
// Adds the 2 masks together, and then clamps the output to be binary to keep it suitable for masking
return image.addBands(NDWI_Mask.add(NDVI_Mask).clamp(0,1).rename('L1CMask'));
};
// Function to update the clipping of imagery to just the water areas, as defined by the combined Mask
//.rename(['B1_Msk','B2_Msk','B3_Msk','B4_Msk','B5_Msk','B6_Msk','B7_Msk','B8_Msk','B8A_Msk','B9_Msk','B10_Msk','B11_Msk','B12_Msk','QA10_Msk','QA20_Msk','QA60_Msk','NDWI_Msk','NDVI_Msk','NDVI_Mask2','NDWI_Mask2','L1CMask2'])
var L1CMasking = function(image) {
var Mask = image.select(['L1CMask']);
return image.updateMask(Mask.eq(1));
};
// Applies all the functions to respective image collections
var S2_L1C_Func = S2_L1C.map(addNDWI).map(addNDVI).map(VegMaskL1C).map(WaterMaskL1C).map(CombinedL1CMask);
// Add the individual new bands to the Map
// NDVI
Map.addLayer(S2_L1C_Func, NDVIVis, 'L1C NDVI');
// NDWI
Map.addLayer(S2_L1C_Func, NDWIVis, 'L1C NDWI');
// NDVI Mask
Map.addLayer(S2_L1C_Func, NDVIMaskVis, 'L1C NDVIMask');
// NDWI Mask
Map.addLayer(S2_L1C_Func, NDWIMaskVis, 'L1C NDWIMask');
// Combo Mask
Map.addLayer(S2_L1C_Func, L1CMaskVis, 'L1C Mask');
/* Creating a new var to run the mask apply function, because otherwise for some reason it retroactively
* breaks all the earlier separate ND VI/WI masks
*/
var S2_L1C_Masked = S2_L1C_Func.map(L1CMasking);
// Clipped hopefully?!
Map.addLayer(S2_L1C_Masked, rgbVis, 'L1C MaskApplied');
我也尝试过分别将蒙版更新为图像，如下所示，但这只会带来另一个不同且不正确的蒙版图像（很明显，蒙版 L1C 图像中包含云，而蒙版 L1C 图像中没有云） L1C原图，连右下角的Estuary都变潮了！）。
/* Instead of combining the two Masks prior to applying them to the IC, this updates the IC's Mask by the two separate layers
* together. This is only applied to the "image" bands (B1-B12), not the other newly created bands.
*/
var MaskBandsL1C = function(image) {
return image.select(['B1','B2','B3','B4','B5','B6','B7','B8','B9','B10','B11','B12','NDVI_Mask','NDWI_Mask'])
.updateMask(image.select('NDVI_Mask'))
.updateMask(image.select('NDWI_Mask'));
};
// Combo Mask
var ICMaskL2A = S2_L2A_Func.map(MaskBandsL2A);
var ICMaskL1C = S2_L1C_Func.map(MaskBandsL1C);
Map.addLayer(ICMaskL2A, rgbVis, 'L2A Masked');
Map.addLayer(ICMaskL1C, rgbVis, 'L1C Masked');
第二个掩码示例的替代（和不正确）结果
所以蒙版 'working' 因为它提供了适合我的条件的区域，但它至少会显示一天中不同时间的图像（最坏的情况是不同日期的图像）完全） - 是否也可以让蒙版图像按 system:time_start 对齐，因为我将不得不使用它来创建 Time Series chart?
感谢您花时间对正在发生的事情做出任何解释。
回答更新
我之前向姐妹 GIS Stack Exchange 发布了这个类似的问题（我不确定这是否是不礼貌的，我只是想之后在这里问可能会有更好的影响力）和 Olga Danylo was able to explain the issue I was having。如果其他人遇到类似问题，我建议您阅读他们的回答，如果他们也帮助了您，请给他们 +1。
简而言之：
屏蔽是工作，只是当我.map一个没有特定过滤日期或图像的图层时，任何结果都会被拉出并显示，并且它碰巧我的单独蒙版似乎匹配，直到最终组合蒙版层。将 system:time_start 属性 添加到第一个云映射函数，然后将所有 Map.addLayer 过滤到同一日期（即 Map.addLayer(S2_L1C_Func.filterDate('2022-03-30', '2022-04-01') 给出了我想要的地图结果。Olga 给出比我更好的解释，所以我真的建议只阅读他们在上面 link 上的回答。