Results 61 to 70 of about 1,803 (195)

Refined Modeling of Arctic Circumpolar Building Stock Increases Estimated Mid‐Century Permafrost Degradation Damages

Earth's Future, Volume 14, Issue 7, July 2026.
Abstract Near‐surface permafrost degradation has the potential to damage infrastructure needed to sustain Arctic communities, but risk assessments remain highly uncertain due to a limited representation of the Arctic circumpolar building stock. With deep learning building footprint detection and building occupancy classification models, we expand the ...
E. Manos, D. A. Streletskiy, C. Witharana, E. Haggerty, A. K. Liljedahl   +4 more
wiley   +1 more source

Deep Learning Hyperspectral Pansharpening on Large-Scale PRISMA Dataset

Remote Sensing
Hyperspectral pansharpening is crucial for the improvement of the usability of images in various applications. However, it remains underexplored due to a scarcity of data.
Simone Zini, Mirko Paolo Barbato, Flavio Piccoli, Paolo Napoletano   +3 more
doaj   +1 more source

Image Restoration for the MRA-Based Pansharpening Method

IEEE Access, 2020
By merging high-resolution panchromatic (PAN) images with low-resolution multispectral (MS) images, high-resolution MS images with complementary information can be obtained, i.e., pansharpening.
Jiao Jiao, Lingda Wu
doaj   +1 more source

Simultaneous Generation of Topographic Models and Manning Roughness Coefficient Maps From Tri‐Stereoscopic Satellite Images: Application to the Huarmey River, Peru

The Photogrammetric Record, Volume 41, Issue 195, July‐September 2026.
Tri‐stereoscopic PeruSat‐1 imagery enables the simultaneous generation of 0.70 m‐resolution topography and spatially distributed Manning roughness maps, achieving 0.434 m vertical accuracy. Integrated into HEC‐RAS, these products provide consistent, high‐resolution inputs that improve hydraulic modelling and flood risk assessment in data‐scarce river ...
Jorge L. Miranda‐Pita, Pedro A. Plaza‐Álvarez, Jorge Lopez‐Rebollo, Diego González‐Aguilera   +3 more
wiley   +1 more source

Variable Subpixel Convolution Based Arbitrary-Resolution Hyperspectral Pansharpening

, 2022
International audienceStandard hyperspectral (HS) pansharpening relies on fusion to enhance low-resolution HS (LRHS) images to the resolution of their matching panchromatic (PAN) images, whose practical implementation is normally under a stipulation of ...
Li, Jun, Xie, Jinhua, He, Lin, Chanussot, Jocelyn, Plaza, Antonio, Zhu, Jiawei, Jocelyn Chanussot, Jun Li, Jiawei Zhu, Lin He, Antonio Plaza, Jinhua Xie   +11 more
core   +1 more source

Mechanisms of Surface Meltwater Ponding and Drainage on the Greenland Ice Sheet Revealed Using SkySat Imagery and Deep Learning

AGU Advances, Volume 7, Issue 2, April 2026.
Abstract Surface meltwater impacts Greenland Ice Sheet mass balance indirectly by reducing albedo and promoting hydrofracture. However, fully understanding both processes requires accurate mapping of small‐scale features such as ponds, channels, and moulins that govern meltwater formation and drainage. Here we investigate surface water dynamics at high
J. C. Ryan, R. T. Datta, S. W. Cooley
wiley   +1 more source

Adaptive Feedback‐Driven Gram‐Schmidt Pansharpening: An Iterative Quality Enhancement Framework

IET Image Processing, Volume 20, Issue 1, January/December 2026.
We propose an adaptive feedback‐driven pansharpening (AFDP) framework that enhances the classical Gram‐Schmidt (GS) method by iteratively refining the fusion process using low‐pass‐filtered updates and a QNR‐based stopping criterion. Unlike traditional GS sharpening, which injects panchromatic details in a single step, the AFDP approach gradually ...
Mohamed Ghadjati, Elhadi Mehallel, Ammar Bouchemel, Abdelkrim Moussaoui, Mawloud Guermoui, Abdelaziz Rabehi, Takele Ferede Agajie   +6 more
wiley   +1 more source

Joint multichannel pansharpening for multispectral imagery [PDF]

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
Pan-sharpening is a common post-processing operation for captured multispectral satellite imagery, where the spatial resolution of images gathered in various spectral bands is enhanced by fusing them with a panchromatic image captured at a higher resolution.
Hussein A. Aly 0002, Gaurav Sharma 0001
openaire   +1 more source

Learning an Efficient Convolution Neural Network for Pansharpening

, 2019
Pansharpening is a domain-specific task of satellite imagery processing, which aims at fusing a multispectral image with a corresponding panchromatic one to enhance the spatial resolution of multispectral image.
Fei Ye, Hao Gong, Yecai Guo
core   +1 more source

A cross-band transformer on wavelets for pansharpening of satellite imagery

European Journal of Remote Sensing
Pansharpening is the task of fusing panchromatic and low-resolution multi-spectral data to obtain a high-resolution equivalent. In our study, we develop a cross-band transformer (CBT) method for pansharpening, incorporating and adapting successful ...
Nikolaos Ntantis, Jasper S. Wijnands, Jan Fokke Meirink, Domenica Dibenedetto   +3 more
doaj   +1 more source