Agriculture is shifting to precision farming methodologies, allowing to use less water and chemicals and reducing its environmental impact. Technology has been a key factor in this shift: access to new high-resolution and high-frequency satellite data is revolutionising the way information about fields and crops are gathered, managed, and used to make informed, data-driven decisions.
The first step in gathering information about a specific crop is to identify the field from satellite imagery. This is the focus of this challenge.
The first prize winner receives a cash prize of $150 USD!
The second prize winner receives a cash prize of $75 USD!
The third prize winner receives a cash prize of $50 USD!
Sept. 23, 2019 Competition Start
Nov. 11, 2019 Competition End
Nov. 14, 2019 Results Announcement
Detect the contour boundary of the cultivated fields. The solution should take the satellite image as input and give a monochromatic output of the same resolution containing only the contour outlines and the geographic metadata. Use the best spectral band(s), pre-processing and contour boundary detection strategy to accomplish the task. The solution should work both on the provided sample data and new data.
Out of 675 fields in test dataset, how many crop id labels you get correct will you give you scoring on leaderboard
For more information, there is a document in the Dataset known as (Competition Data Information.docx)
Outputs should follow the format:
For additional information and context, see here:
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During your participation in this competition, we ask that you abide by the Non-Disclosure Agreement, which acceptance of is a mandatory step in participating in this competition.
Where a winning result is matching with another users in accuracy, the earliest submission will be judged as the winner, with submission time taking precedence in a linear fashion. Example: 97.7% submission at 10:01 UTC winning over 97.7% submission at 10:07 UTC.
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