Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery

D He, Q Shi, X Liu, Y Zhong, G Xia… - GIScience & Remote …, 2022 - Taylor & Francis
High resolution of global land cover dynamic is indicative for understanding the influence of
anthropogenic activity on environmental change. However, most of the land cover products …

Spatial validation of spectral unmixing results: A systematic review

RM Cavalli - Remote Sensing, 2023 - mdpi.com
The pixels of remote images often contain more than one distinct material (mixed pixels),
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …

New generation hyperspectral data from DESIS compared to high spatial resolution PlanetScope data for crop type classification

I Aneece, D Foley, P Thenkabail… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Thoroughly investigating the characteristics of new generation hyperspectral and high
spatial resolution spaceborne sensors will advance the study of agricultural crops …

Attention-driven dual feature guidance for hyperspectral super resolution

M Zhao, J Ning, J Hu, T Li - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Benefiting from the high spectral resolution, hyperspectral image (HSI) owns the property of
discriminating material. However, the spatial resolution of HSIs is limited by the hardware …

Adaptively dictionary construction for hyperspectral target detection

C Li, W Zhang, Y Zhang, Z Chen… - IEEE Geoscience and …, 2023 - ieeexplore.ieee.org
The task of hyperspectral images (HSIs) target detection is to identify whether the target
spectral sequences present in the HSI. Recently, the topic of representation models has …

Deep Spatial Feedback Refined Network with Multi-Level Feature Fusion for Hyperspectral Image Sub-pixel Mapping

J Zhong, K Wu, Y Xu - IEEE Transactions on Geoscience and …, 2024 - ieeexplore.ieee.org
The issue of mixed pixels is a prevalent challenge in hyperspectral images (HSIs), largely
due to imaging modalities and hardware limitations. Subpixel mapping (SPM) can address …

Unsupervised Bayesian subpixel mapping autoencoder network for hyperspectral images

Y Fang, Y Wang, L Xu, Y Chen, A Wong… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unsupervised subpixel mapping (SPM) of hyperspectral image (HSI) is a challenging task
due to the difficulties to integrate different prior information and model constraints into a …

Super-Resolution Mapping With a Fraction Error Eliminating CNN Model

Z Yin, Y Wu, P Wu, Z Hao, F Ling - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Super-resolution mapping (SRM) is an effective way to alleviate the mixed pixel problem of
remotely sensed imagery by transforming the coarse-resolution fraction image originating …

Nonlinear Spectral Unmixing of Hyperspectral Imagery Based on Hapke Model and Relevance Vector Regression Algorithm

C Sun, F Xing, D Liu, J Han… - Journal of Physics …, 2022 - iopscience.iop.org
This paper put forward a nonlinear hyperspectral imagery unmixing method based on
Hapke nonlinear spectral mixture model and the relevance vector regression. This paper …