如何解决请求有效负载大小超出限制:4194304字节
我收到此错误,是因为我试图导出以驱动分类图像,该图像相当大,因为它包含了澳大利亚新南威尔士州的整个区域。手册说,在这种情况下,它将导出为许多较小的文件,但对我而言并非如此。请看一下我的代码,并帮助我弄清楚如何最终以1张或更多图片的形式导出它。 预先感谢。
//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','B2_mean'],min:500,max:2800},"222");
var classnames = burned.merge(unburned);
var bands = ['B2_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
});
解决方法
这里的建议很简单,您的比例尺目前设置为10 m,这非常小。除非您绝对需要高分辨率,否则我建议至少将其提高到100 m。如果仍然无法导出,请减小几何尺寸或进一步增大比例。
版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 dio@foxmail.com 举报,一经查实,本站将立刻删除。