Google Earth Engine（GEE）——Sentinel-2影像在同一区域同一时间段有多个不同的ID影像，如何进行筛选其中单景影像

Sentinel-2 以条带方式拍摄地球图像，这些条带根据​​军事网格参考系统​​​或“MGRS”切片方案划分为瓷砖分布。对于您所在的地区，有两个具有广泛重叠的磁贴（36TYM、37TBG）。您可以在​​此处​​探索网格系统。它们是来自相同条带的数据，但对于 SR 产品，两者对于“相同像素”的值可能略有不同，因为 SR 数据是在分块级别处理的，并且两个不同 UTM 区域（36TYM）的重采样存在差异是 EPSG:32636 而 37TBG 是 EPSG:32637) 并且大气校正等参数的差异会传播到结果。

为避免“重复”数据，您可以通过要保留的 MGRS_TILE 属性值列表过滤集合，例如仅保留 36TYM 和 36TYN 磁贴数据：

函数：

ee.Filter.inList(leftField, rightValue, rightField, leftValue)

Filter on metadata contained in a list.

Returns the constructed filter.

Arguments:

leftField (String, optional):

A selector for the left operand. Should not be specified if leftValue is specified.

rightValue (List<Object>|Object, optional):

The value of the right operand. Should not be specified if rightField is specified.

rightField (String, optional):

A selector for the right operand. Should not be specified if rightValue is specified.

leftValue (List<Object>|Object, optional):

The value of the left operand. Should not be specified if leftField is specified.

Returns: Filter

var tileList = ['36TYM', '36TYN']
var SrFiltered = Sr.filter(ee.Filter.inList('MGRS_TILE', tileList))

代码：

var geometry=ee.Geometry.Polygon([[35.602367261137886,41.62480227265362],
[36.563670972075386,41.62480227265362],
[36.563670972075386,42.54611702000942],
[35.602367261137886,42.54611702000942],
[35.602367261137886,41.62480227265362]])
Map.centerObject(geometry)
var Sr = ee.ImageCollection('COPERNICUS/S2_SR')
                      .filterBounds(geometry)
                      .filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', 5))
                      .filterDate('2021-01-01','2021-12-30')


print('Sr size', Sr.size())
print('Sr sample', Sr.limit(20))
var list=Sr.toList(20)
Map.addLayer(ee.Image(list.get(0)),{'bands':['B4','B3','B2'], 'min':0, 'max':2000})
Map.addLayer(ee.Image(list.get(1)),{'bands':['B4','B3','B2'], 'min':0, 'max':2000})



var tileList = ['36TYM', '36TYN']
var SrFiltered = Sr.filter(ee.Filter.inList('MGRS_TILE', tileList))
print('SrFiltered size', SrFiltered.size())
print('SrFiltered sample', SrFiltered.limit(20))