ICLR Workshop Challenge #2: Radiant Earth Computer Vision for Crop Detection from Satellite Imagery
$7,000 USD
Identify crop type using satellite imagery, and win a trip to present your work at ICLR 2020 in Addis Ababa.
3 February–15 March 2020 23:59
274 data scientists enrolled, 39 on the leaderboard
Missing Fields in Train and Test Set
published 10 Feb 2020, 05:47

Hi Everyone,

There are missing fields in both train and test, as someone already mentioned in another discussion. In the Data page, it is said that there are 3,361 field images in Train, and 1436 in Test, but on getting the data, there are 3286 field images in train and 1402 in test. One can still work with the train set manageably but there'd be 34 fields in the submission file that aren't captured (these fields were in the sample submission file).

Can these 34 fields be removed from the submission, if they are not available?

We are looking into this and will share an update soon.

@Alchemi Facing the same issue here.Seems you mangaed to solve the issue since i can already see you on the leaderbard?

We have the correct number for fields in the vector layers of ground reference data, and that’s where we generated the field IDs list from (for both training and test). But some of the fields have a very narrow and long shape (while the area is large) and during rasterization they get no pixels. The width of the fields are less than a pixel of Sentinel-2. This caused the fields to disappear in the data shared with users. So our conclusion was to drop them from the list of train and test as they cannot be mapped to Sentinel-2 grid.

There are now 3,286 fields in the train and 1,402 fields in the test.

Thank you for bringing this to our attention and good luck with the challenge!