Why can't I successfully export my sample points based on the gee platform？

[quentin98-1]

I selected the sample points for the classification of cultivated land in Uzbekistan, but I could not get the sample points. Why? I've set the maximum pixels! This is my code.

// region
var uzbekistan = countries.filter(ee.Filter.eq('ADM0_NAME', 'Uzbekistan'));
//remove clouds
var roi = uzbekistan;
Map.addLayer(roi,{'color':'grey'},'roi');
// Map.centerObject(roi,5);
// Applies scaling factors.
function applyScaleFactors(image) {
  var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
  // var thermalBands = image.select('ST_B.*').multiply(0.00341802).add(149.0);
  return image.addBands(opticalBands, null, true)
              // .addBands(thermalBands, null, true);
}

// reomove cloud for Landsat-8
function cloudRemoval(image) { 
  // 
  var cloudShadowBitMask = (1 << 4); 
  var cloudsBitMask = (1 << 3); 
  var qa = image.select('QA_PIXEL'); 
  var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0) 
                 .and(qa.bitwiseAnd(cloudsBitMask).eq(0)); 
  var mask2 = image.select("blue").gt(0.2);                 
  return image.updateMask(mask).updateMask(mask2.not()).toDouble()
              .copyProperties(image)
              .copyProperties(image, ["system:time_start"]);
} 

// 计算 NDVI
function calculateNDVI(image) {
  var ndvi = image.normalizedDifference(["nir", "red"]).rename("NDVI");
  return image.addBands(ndvi);
}

// Assign a common name to the sensor-specific bands.
var LC9_BANDS = ['SR_B2','SR_B3','SR_B4','SR_B5','SR_B6','SR_B7','QA_PIXEL']; //Landsat 9
var LC8_BANDS = ['SR_B2','SR_B3','SR_B4','SR_B5','SR_B6','SR_B7','QA_PIXEL']; //Landsat 8
var LC7_BANDS = ['SR_B1','SR_B2','SR_B3', 'SR_B4','SR_B5','SR_B7','QA_PIXEL']; //Landsat 7
var LC5_BANDS = ['SR_B1','SR_B2','SR_B3', 'SR_B4','SR_B5','SR_B7','QA_PIXEL']; //Llandsat 5
var S2_BANDS  = ['B2','B3','B4','B8','B11','B12']; // Sentinel-2
var STD_NAMES = ['blue', 'green', 'red', 'nir', 'swir1', 'swir2','QA_PIXEL'];

var year = 2022;
var month_start = 1;
var month_end = 12;

var L9Col = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')
                .filterBounds(roi)
                .filter(ee.Filter.calendarRange(year,year,'year'))
                .filter(ee.Filter.calendarRange(month_start,month_end,'month'))
                .map(applyScaleFactors)
                .select(LC9_BANDS,STD_NAMES)
                .map(cloudRemoval)
                .map(calculateNDVI);
var L8Col = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
                .filter(ee.Filter.calendarRange(year,year,'year'))
                .filter(ee.Filter.calendarRange(month_start,month_end,'month'))
                .map(applyScaleFactors)
                .select(LC8_BANDS,STD_NAMES)
                .map(cloudRemoval)
                .map(calculateNDVI);
var L7Col = ee.ImageCollection('LANDSAT/LE07/C02/T1_L2')
                .filterBounds(roi)
                .filter(ee.Filter.calendarRange(year,year,'year'))
                .filter(ee.Filter.calendarRange(month_start,month_end,'month'))
                .map(applyScaleFactors)
                .select(LC7_BANDS,STD_NAMES)
                .map(cloudRemoval)
                .map(calculateNDVI);
var L5Col = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2')
                .filterBounds(roi)
                .filter(ee.Filter.calendarRange(year,year,'year'))
                .filter(ee.Filter.calendarRange(month_start,month_end,'month'))
                .map(applyScaleFactors)
                .select(LC5_BANDS,STD_NAMES)
                .map(cloudRemoval)
                .map(calculateNDVI);
                
//l8Col.merge(l7Col).merge(S2Col)
var LandsatCol = ee.ImageCollection(L9Col.merge(L8Col).merge(L7Col).merge(L5Col))
                .sort("system:time_start")
                // .map(addIndex);
print("LandsatCol",LandsatCol.limit(5));

var visParam = {
  bands:["swir1","nir","red"],
  min: 0.0,
  max: 0.3,
  maxPixels:1e10
};
Map.addLayer(LandsatCol.min().clip(roi), visParam, 'LandsatCol');

// 创建 NDVI 时间序列图表
var ndviTimeSeries = ui.Chart.image.series({
  imageCollection: LandsatCol.select("NDVI"),
  region: roi,
  reducer: ee.Reducer.mean(),
  scale: 30,
  xProperty: 'system:time_start'
}).setOptions({
  title: 'NDVI 时间序列图表',
  vAxis: {title: 'NDVI'},
  hAxis: {title: '日期'},
});
print(ndviTimeSeries);

// 注册地图点击事件
Map.onClick(function(coords){
  var lon = coords.lon;
  var lat = coords.lat;
  print("点击点坐标: ", lon, lat);
  
  var point = ee.Geometry.Point(lon, lat);
  
  var ndviTimeSeriesPoint = ui.Chart.image.seriesByRegion({
    imageCollection: LandsatCol.select("NDVI"),
    regions: point,
    reducer: ee.Reducer.mean(),
    scale: 30,
    xProperty: 'system:time_start',
    seriesProperty: 'NDVI'
  }).setChartType('ScatterChart').setOptions({
    title: 'NDVI 时间序列散点图',
    vAxis: {title: 'NDVI'},
    hAxis: {title: '日期'},
  });
  print(ndviTimeSeriesPoint);
});

// Merge points together
var sampleCollection =LandsatCol.merge(Cotton).merge(Mazie).merge(Rice).merge(WheatandOther).merge(Alfalfa).merge(Other).merge(Wheat);
print(sampleCollection , 'Sample Collection ')

//Export
Export.table.toDrive({
collection: sampleCollection,
description: 'Sample Feature Collection',
maxPixels:1e10
}); 

[giswqs]

This is not a geemap question.
Check the documentation on how to export vector data using JavaScript
https://developers.google.com/earth-engine/guides/exporting_tables

[quentin98-1]

thanks for your answer! I will check this documentation now.