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我有一个 SHP（名为“vect”的表），我想从 S2 图像集合（按多云百分比、日期和云量过滤）中提取通用索引的值（每个点）。

当我运行它时，我有这个错误：

“地图中的FeatureCollection（错误）错误（ID = 10）：Image.reduceRegions：无法找到crs。”

这是代码：

var mainFunction = function(startDate,endDate,cloud_perc,cloud_prob,B1, B2,timeStep,window,summarize,vect,scale,folder){


Map.addLayer(vect);
Map.centerObject(vect,4);

//import S2 collection and filter by date and cloud coverage
var sen2=ee.ImageCollection("COPERNICUS/S2")
.filterDate(ee.Date(startDate), ee.Date(endDate))//to filter by date
.filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",cloud_perc))//to filter by a propriety of the collection

//load S2_CLOUD_PROBABILITY dataset
var cloud_probability=ee.ImageCollection("COPERNICUS/S2_CLOUD_PROBABILITY")

//join the 2 collection
var s2cloudmask=ee.Join.saveFirst("cloud_mask").apply({
  primary:sen2,
  secondary:cloud_probability,
  condition:ee.Filter.equals({leftField:"system:index",rightField:"system:index"})
})

//convert the list to an immage collection
s2cloudmask=ee.ImageCollection(s2cloudmask)

//define a function to mask out cloudy pixel in the s2 collection
var maskcloud= function(img){
  var clouds=ee.Image(img.get("cloud_mask")).select("probability");
  var noclouds=clouds.lt(cloud_prob);
  return img.mask(noclouds);
}

//apply the function to all the images in the collection
var s2_masked= s2cloudmask.map(maskcloud)

///////INDEX///////
//function to create index
function addIndex(img) {
var Index=img.normalizedDifference([B1, B2]).rename("Index")
return img.addBands(Index)
}
//calculate index for all the collection
var s2_masked_index= s2_masked.map(addIndex)
var Index=s2_masked_index.select('Index')

Map.addLayer(Index.median(), {bands: 'Index', min: -1, max: 1,palette:["brown","yellow","green"]},"Median composite index");



Map.addLayer(composites.median(), {bands: 'Index', min: -1, max: 1,palette:["brown","yellow","green"]},"Moving median composite Index");
scale=ee.Number(scale)
//make the time series chart
var chart=ui.Chart.image.series({
  imageCollection:composites.select("Index"),
  region:vect,
  reducer:ee.Reducer.median(),
  scale:scale
}).setOptions({
lineWidth:1,
pointSize: 3,
title:"Index time series",
interpolateNulls:true,
vAxis:{title:"Index"},
hAxis:{title:'',format:'YYYY-MMM'}})

print(chart,"time series")
//make the doy time series chart
//var series1 = ui.Chart.image.doySeriesByYear(composites,"Index",geometry,ee.Reducer.median(),scale);
//print(series1,"time series-doy")

//extract index values from aoi
var reduced = composites.map(function(image){
  return image.reduceRegions({
    collection:vect , 
    reducer:ee.Reducer.median(), 
    scale: scale
  });
});
//turn collection of collection into table
var table = reduced.flatten();
print(table)
//export the table
Export.table.toDrive({collection:table,
description:"Index_time_series",
folder: folder,
fileFormat:"CSV"})

}
exports.mainFunction = mainFunction;
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