Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy....

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Tao, Li, Zhaofu, Pan, Jianjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856114/
https://www.ncbi.nlm.nih.gov/pubmed/29382073
http://dx.doi.org/10.3390/s18020373

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856114/
https://www.ncbi.nlm.nih.gov/pubmed/29382073
http://dx.doi.org/10.3390/s18020373

Ejemplares similares