Overview
Once you have found the imagery data you want to analyze in Earth OnDemand, the next step is to analyze these data in your EarthAI Notebook. To do this, you'll want to copy your query from Earth OnDemand into the EarthAI Notebook environment.
How To Copy your Query to EarthAI Notebook
High Level Approach
- Search for data in Earth OnDemand
- Copy query
- Paste and run query in EarthAI Notebook
1. Search
The first step is to search for the data you want to analyze in Earth OnDemand. The Copy Query tool will copy the most specific version of your search. This means if you have selected and are viewing a specific image on the map, the query that will be copied will return only this image. By contrast, if you have only specified an Area of Interest using the bounding box, all of the imagery over all indexed history for all of the footprints intersecting the bounding box will be returned. In between these two extremes, you can filter by date, cloud cover, and footprint.
2. Copy Query
Once you have a query you'd like to copy, Click on the Export menu (top-right of map) and select Export Query to EarthAI Notebook.
This will open a pop-up dialog (unless you've already done this and disabled the dialog). If you are logged in and have a subscription (or trial subscription) to EarthAI Notebook, the dialog will have a button that opens your notebook. Otherwise, it will direct you to the EarthAI Notebook Webpage where you can start a free trial.
If you don't have a subscription, you will need to start a trial to use this feature.
If you do have a subscription, proceed to the notebook.
3. Paste and run query in EarthAI Notebook
In notebook, you will need to add an include statement to your notebook.
Best practice is to put all of your include statements in the first cell of your notebook.
from earthai import earth_ondemand
Create a new cell. The copy query function uses a JupyterLab magic function. This means it must be in its own cell.
Paste your query from the clip board.
The result set will be returned as a new geopandas dataframe with the result set metadata:
Note: Every time you run this cell, the variable name will increment (eod0, eod1, eod2,...)
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