Landsat Super-Resolution Enhancement Using Convolution Neural Networks and Sentinel-2 for Training

Author： Pouliot Darren   Latifovic Rasim   Pasher Jon   Duffe Jason  

Publisher： MDPI

E-ISSN： 2072-4292|10|3|394-394

ISSN： 2072-4292

Source： Remote Sensing, Vol.10, Iss.3, 2018-03, pp. : 394-394

Access to resources Favorite

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Improved Urban Flooding Mapping from Remote Sensing Images Using Generalized Regression Neural Network-Based Super-Resolution Algorithm

By Li Linyi   Xu Tingbao   Chen Yun  

Remote Sensing, Vol. 8, Iss. 8, 2016-07 ,pp. : 625-625

MDPI

Access to resources Recommend Favorite

Glacier Remote Sensing Using Sentinel-2. Part II: Mapping Glacier Extents and Surface Facies, and Comparison to Landsat 8

By Paul Frank   Winsvold Solveig H.   Kääb Andreas   Nagler Thomas   Schwaizer Gabriele  

Remote Sensing, Vol. 8, Iss. 7, 2016-07 ,pp. : 575-575

MDPI

Access to resources Recommend Favorite

Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

By Hughes M. Joseph   Hayes Daniel J.  

Remote Sensing, Vol. 6, Iss. 6, 2014-05 ,pp. : 4907-4926

MDPI

Access to resources Recommend Favorite

Preliminary Comparison of Sentinel-2 and Landsat 8 Imagery for a Combined Use

By Mandanici Emanuele   Bitelli Gabriele  

Remote Sensing, Vol. 8, Iss. 12, 2016-12 ,pp. : 1014-1014

MDPI

Access to resources Recommend Favorite

Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images

By Yokoya Naoto   Chan Jonathan Cheung-Wai   Segl Karl  

Remote Sensing, Vol. 8, Iss. 3, 2016-02 ,pp. : 172-172

MDPI

Access to resources Recommend Favorite