Please

Hi Tylere,

time = [datetime.datetime.fromtimestamp(i/1000) for i in (data[0:,iTime].astype(int))]

This is from your example Time Series- Landsat. When I run the code, it seems that an error occurs becasue of astype(int).

The error is "Python int too large to convert to C long".

My environment is a Jupyter notebook Python 3 (windows 64-bit).

I think the solution is to exclude astype(int), just use time = [datetime.datetime.fromtimestamp(i/1000) for i in (data[0:,iTime])]. But I have not went through it.

Hi Tylere,
Can you help me with an issue? I am using Jupyter Notebooks with Python 3.

I want to download images in a watershed (I got from a fusion table).

import ee
ee.Initialize()

get features of watershed

w3031 = ee.FeatureCollection('users/hutx2309/wsd3031')

get ndvi data with only June and July from 2009 to 2017

ndvi = ee.ImageCollection('MODIS/006/MOD13A2').filterDate('2009-01-01','2017-12-31').select('NDVI')
ndvi_mon = ndvi.filter(ee.Filter.calendarRange(2009,2017,'year'))
.filter(ee.Filter.calendarRange(6,7,'month'))

download data using watershed feature as a filter using python API

image = ndvi_mon.first()
task = ee.batch.Export.image.toDrive(image,description='NDVI',region=w3031,scale=1000, crs='EPSG:4326')
task.start()

==========================================================

TypeError: Object of type 'FeatureCollection' is not JSON serializable

I have no idea how to deal with this. Thanks!

Hi @tylere, I'm wondered how should I set up the gdal library to run the 4 - Earth Engine and TensorFlow nb? Here the error when I import gdal, I'm using MacOS...

ImportErrorTraceback (most recent call last)
<ipython-input-1-ecfcf1c998b3> in <module>()
      4 from matplotlib import pyplot
      5 import numpy
----> 6 import gdal
      7 import tempfile
      8 import tensorflow as tf

ImportError: No module named gdal

This is a very helpful set of notebooks! I'm trying to initialize Earth Engine on a Datalab instance and couldn't find the "Earth Engine Datalab Initialization" notebook referenced in the "Earth Engine and TensorFlow" notebook. Is it still available, perhaps with a different name?