MultiEarth 2023 Deforestation Challenge -- Team FOREVER
Seunghan Park Dongoo Lee Yeonju Choi SungTae Moon
It is important problem to accurately estimate deforestation of satellite
imagery since this approach can analyse extensive area without direct human
access. However, it is not simple problem because of difficulty in observing
the clear ground surface due to extensive cloud cover during long rainy season.
In this paper, we present a multi-view learning strategy to predict
deforestation status in the Amazon rainforest area with latest deep neural
network models. Multi-modal dataset consists of three types of different
satellites imagery, Sentinel-1, Sentinel-2 and Landsat 8 is utilized to train
and predict deforestation status. MMsegmentation framework is selected to apply
comprehensive data augmentation and diverse networks. The proposed method
effectively and accurately predicts the deforestation status of new queries.