My CNN model input requires around 30,000 square-shaped satellite images, the corner coordinates(lat-long) of which I have already compiled. However, I am not able to figure out how to collectively obtain the images for these specific co-ordinates using the Google Earth Engine.
Hi Arka,
If you have the coordinates of the area which you need, you may use the following code to extract the images combined together for long/short time periods.
https://code.earthengine.google.com/?scriptPath=users%2FNikul%2FLEARNING%3ABatchExportLayers
However, you have to make sure about the size of the image/ area as sometimes, it may give error from the server-side in GEE, if there are a huge number of images in one go. In that case, you may try to take it in small sets.
Hope this helps you.
Cheers
Hi Arka,
If you have the coordinates of the area which you need, you may use the following code to extract the images combined together for long/short time periods.
https://code.earthengine.google.com/?scriptPath=users%2FNikul%2FLEARNING%3ABatchExportLayers
However, you have to make sure about the size of the image/ area as sometimes, it may give error from the server-side in GEE, if there are a huge number of images in one go. In that case, you may try to take it in small sets.
Hope this helps you.
Cheers
You may also use "rgee" package to programmatically download tiles that are associated with any spatial object you have loaded into R.
Have a look at https://www.frontiersin.org/articles/10.3389/feart.2017.00017/full
and https://aws.amazon.com/machine-learning/amis/?nc2=h_ql_prod_ml_amis&trk=ps_a131L0000083KrrQAE&trkCampaign=2020_HowMLisDone_PDP_DeepLearning&sc_channel=ps&sc_campaign=DeepLearning_AD_Google_WP_PreconfiguredEnvironments_PNB&sc_outcome=AIML_Digital_Marketing&sc_geo=mult&sc_country=mult&sc_publisher=Google&sc_detail=%2Bgoogle%20%2Bdeep%20%2Blearning&ef_id=EAIaIQobChMIkoiK-s-B6wIVmzUrCh2I9QHaEAAYASAAEgJO4fD_BwE:G:s&s_kwcid=AL!4422!3!410089056644!b!!
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