A Deep Learning Approach to an Enhanced Building Footprint and Road Detection in High-Resolution Satellite Imagery

Autor: Christian Ayala, Rubén Sesma, Carlos Aranda, Mikel Galar

Publikováno v: Remote Sensing, Vol 13, Iss 16, p 3135 (2021)

The detection of building footprints and road networks has many useful applications including the monitoring of urban development, real-time navigation, etc. Taking into account that a great deal of human attention is required by these remote sensing

Externí odkaz: https://doaj.org/article/a48863681d2545759cb12187528626d9

SUPER-RESOLUTION FOR SENTINEL-2 IMAGES

Autor: Mikel Galar, Rubén Sesma, C. Aranda, C. Ayala

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2-W16, Pp 95-102 (2019)
Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname
Academica-e: Repositorio Institucional de la Universidad Pública de Navarra
Universidad Pública de Navarra

Trabajo presentado al PIA19+MRSS19 – Photogrammetric Image Analysis & Munich Remote Sensing Symposium, 2019, Munich Incluye póster Obtaining Sentinel-2 imagery of higher spatial resolution than the native bands while ensuring that output imagery p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::150bcdeeac6e7dff0e141793d592f194
https://doi.org/10.5194/isprs-archives-xlii-2-w16-95-2019

Super-Resolution of Sentinel-2 Images Using Convolutional Neural Networks and Real Ground Truth Data

Autor: Rubén Sesma, Mikel Galar, C. Aranda, C. Ayala, Lourdes Albizua

Publikováno v: Remote Sensing, Vol 12, Iss 2941, p 2941 (2020)
Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname
Academica-e: Repositorio Institucional de la Universidad Pública de Navarra
Universidad Pública de Navarra
Remote Sensing; Volume 12; Issue 18; Pages: 2941

Earth observation data is becoming more accessible and affordable thanks to the Copernicus programme and its Sentinel missions. Every location worldwide can be freely monitored approximately every 5 days using the multi-spectral images provided by Se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::143bdd5073a12faaaf6ead4464db1cfd
https://www.mdpi.com/2072-4292/12/18/2941