Original paper

Crop mapping from image time series: Deep learning with multi-scale label hierarchies

Volume: 264, Pages: 112603 - 112603
Published: Oct 1, 2021
Abstract
The aim of this paper is to map agricultural crops by classifying satellite image time series. Domain experts in agriculture work with crop type labels that are organised in a hierarchical tree structure, where coarse classes (like orchards) are subdivided into finer ones (like apples, pears, vines, etc.). We develop a crop classification method that exploits this expert knowledge and significantly improves the mapping of rare crop types. The...
Paper Details
Title
Crop mapping from image time series: Deep learning with multi-scale label hierarchies
Published Date
Oct 1, 2021
Volume
264
Pages
112603 - 112603
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.