Crop Mapping Using the Historical Crop Data Layer and Deep Neural Networks: A Case Study in Jilin Province, China

Machine learning combined with satellite image time series can quickly, and reliably be implemented to map crop distribution and growth monitoring necessary for food security. However, obtaining a large number of field survey samples for classifier training is often time-consuming and costly, which...

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Detalles Bibliográficos
Autores principales: Jiang, Deyang, Chen, Shengbo, Useya, Juliana, Cao, Lisai, Lu, Tianqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371029/
https://www.ncbi.nlm.nih.gov/pubmed/35957410
http://dx.doi.org/10.3390/s22155853

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371029/
https://www.ncbi.nlm.nih.gov/pubmed/35957410
http://dx.doi.org/10.3390/s22155853

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