Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

Earth observation (EO) sensors deliver data at daily or weekly intervals. Most land use and land cover classification (LULC) approaches, however, are designed for cloud-free and mono-temporal observations. The increasing temporal capabilities of today’s sensors enable the use of temporal, along with...

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Bibliographic Details
Main Authors: Marc Rußwurm, Marco Körner
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:ISPRS International Journal of Geo-Information
Subjects:
deep learning
multi-temporal classification
land use and land cover classification
recurrent networks
sequence encoder
crop classification
sequence-to-sequence
Sentinel 2
Online Access:http://www.mdpi.com/2220-9964/7/4/129

Internet

http://www.mdpi.com/2220-9964/7/4/129

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