我得到了这个错误,因为我试图导出以驱动一个分类图像,这是相当大的,因为它包括整个澳大利亚新南威尔士州的区域。手册说,在这种情况下,它将导出为许多较小的文件,但这不是我的情况。请看一下我的代码,并帮助我找出如何最终导出它,无论是一个或更多的图像。提前谢谢。
//SPECIFY AND MODIFY THE AREA OF INTEREST
var S2 = ee.ImageCollection('COPERNICUS/S2_SR')
.filterBounds(geometry);
var S2 = S2.filterMetadata('CLOUD_COVERAGE_ASSESSMENT', 'less_than', 5);
var S2 = S2.filterDate('2019-12-14','2020-01-16');
print(S2.size());
var S2_image = S2.first();
var S2_clipped_collection = S2.map(function (S2_image){
return S2_image.clip(geometry);
});
print(S2_clipped_collection);
var S2_image = S2_image.select('B2');
var S2_clipped_collection = S2_clipped_collection
.reduce(ee.Reducer.mean());
print(S2_clipped_collection);
var S2_clipped_collection = S2_clipped_collection.select( 'B2_mean', 'B3_mean', 'B4_mean', 'B5_mean', 'B6_mean', 'B7_mean', 'B8_mean', 'B11_mean','B12_mean');
Map.addLayer(S2_clipped_collection, {bands:['B4_mean', 'B3_mean', 'B2_mean'], min:500, max:2800}, "222");
var classnames = burned.merge(unburned);
var bands = ['B2_mean', 'B3_mean', 'B4_mean', 'B5_mean', 'B6_mean', 'B7_mean', 'B8_mean', 'B11_mean','B12_mean'];
var training = S2_clipped_collection.select(bands).sampleRegions({
collection: classnames,
properties: ['landcover'],
scale: 10
});
print(training);
var classifier = ee.Classifier.smileRandomForest(100).train({
features: training,
classProperty: 'landcover',
inputProperties: bands
});
//Run the classification
var classified = S2_clipped_collection.select(bands).classify(classifier);
//Display classification
Map.centerObject(classnames, 11);
Map.addLayer(classified,
{min: 0, max: 3, palette: ['red', 'blue', 'green','yellow']},
'classification');
Export.image.toDrive({
image: classified,
description: 'description',
region: geometry,
scale: 10,
crs: 'EPSG:25832',
maxPixels: 1e19
});发布于 2020-11-11 04:29:37
这里有一个简单的建议,你的比例目前设置为10米,这是令人难以置信的小。除非你绝对需要高分辨率,否则我建议你至少把它调到100米。如果仍不能导出,请减小几何体的大小或进一步增加比例。
https://stackoverflow.com/questions/64735787
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