1

我正在尝试处理从这里下载的坦桑尼亚形状文件。

    # im -> {Image} ee.Image({...})
    # self.geom_coll -> {FeatureCollection} ee.FeatureCollection({...}). containing 
    # 3000 features.
    # spacereducer() -> ee.Reducer.mean
    # self.scale -> 10 #Changing this value to small number gives error

    feats = im.reduceRegions(self.geom_coll, spacereducer(), self.scale)
    flist = getInfo_werrorcontrol(feats,
                          self.errorcheck)['features']

.

def getInfo_werrorcontrol(featureCollection, errorcontrolon=True):
    """
    Wrapper to add error control to GEE evaluations.

    For large computations GEE sometimes times out and needs to be
    restarted. This does so in a controlled manner with out 
    interrrupting the program flow.
    """
    if errorcontrolon:
        i=0
        while True:
            try:
                with timeout.timeout(10*60):
                    return featureCollection.getInfo() # In this line I am getting exception.
            except NameError:
                exc_type, exc_value, exc_traceback = sys.exc_info()
                lines = traceback.format_exception(exc_type, exc_value, exc_traceback)
                print ''.join('!! ' + line for line in lines)
                i+=1
                print 'attempts: '+str(i)
                if i > 20:
                    raise ValueError('to many attempts') 
                elif i > 10:
                    print 'waiting 2 minutes'
                    time.sleep(60*2)
    else:
        return featureCollection.getInfo()

更改self.scale为 10 会引发以下行错误：

featureCollection.getInfo()

ee.ee_exception.EEException：服务器返回 HTTP 代码：413

更改self.scale为 1000 会引发此错误：

ee.ee_exception.EEException：计算超时

处理较大区域的形状文件的正确方法是什么？

4

1 回答 1

2

请注意，对 Earth Engine API 的请求已经用指数退避包装。因此，您的代码不会对解决问题有太大帮助。这些错误是如何从您发布的代码中产生的并不明显，但无论哪种情况，答案都可能相同：导出结果。例子：

import ee
ee.Initialize()
image = ee.Image('srtm90_v4')
geometry = ee.Geometry.Polygon([[[-113.64, 39.97], [-113.64, 38.13],[-109.42, 38.13],[-109.42, 39.97]]], None, False)
dict = image.reduceRegion(reducer=ee.Reducer.mean(), geometry=geometry, scale=1000)
featureCollection = ee.FeatureCollection([ee.Feature(None, dict)])
task = ee.batch.Export.table.toDrive(collection=featureCollection, description='foo', fileNamePrefix='foo', fileFormat='CSV')
task.start()
print task.status()

导出的输出将在您的 Google Drive 文件夹中实现。要了解有关比例的更多信息，请参阅此文档。

于 2017-07-18T23:28:09.017 回答