High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest

Caleb Robinson; Nebojsa Jojic; Nikolay Malkin

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High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest

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arxiv 2101.01154 v1 pith:BBEQ2IDT submitted 2021-01-04 cs.CV cs.AIcs.LG

Nikolay Malkin , Caleb Robinson , Nebojsa Jojic This is my paper · ORCID

classification cs.CVcs.AIcs.LG

keywords datachangecontestcoverlandbaselinesdfc2021fusion

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We present simple algorithms for land cover change detection in the 2021 IEEE GRSS Data Fusion Contest. The task of the contest is to create high-resolution (1m / pixel) land cover change maps of a study area in Maryland, USA, given multi-resolution imagery and label data. We study several baseline models for this task and discuss directions for further research. See https://dfc2021.blob.core.windows.net/competition-data/dfc2021_index.txt for the data and https://github.com/calebrob6/dfc2021-msd-baseline for an implementation of these baselines.

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