Yihang Zhang

Orcid: 0009-0008-9446-5111

Affiliations:
  • Chinese Academy of Sciences, Institute of Geodesy and Geophysics, Wuhan, China


According to our database1, Yihang Zhang authored at least 27 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Unmixing-Based Spatiotemporal Image Fusion Based on the Self-Trained Random Forest Regression and Residual Compensation.
IEEE Trans. Geosci. Remote. Sens., 2023

Deep Feature and Domain Knowledge Fusion Network for Mapping Surface Water Bodies by Fusing Google Earth RGB and Sentinel-2 Images.
IEEE Geosci. Remote. Sens. Lett., 2023

2022
A Cascaded Spectral-Spatial CNN Model for Super-Resolution River Mapping With MODIS Imagery.
IEEE Trans. Geosci. Remote. Sens., 2022

Spatiotemporal Reflectance Fusion Using a Generative Adversarial Network.
IEEE Trans. Geosci. Remote. Sens., 2022

2021
Object-Based Area-to-Point Regression Kriging for Pansharpening.
IEEE Trans. Geosci. Remote. Sens., 2021

Spatiotemporal Continuous Impervious Surface Mapping by Fusion of Landsat Time Series Data and Google Earth Imagery.
Remote. Sens., 2021

2020
Predicting soil organic carbon content in Spain by combining Landsat TM and ALOS PALSAR images.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Spatial-Temporal Super-Resolution Land Cover Mapping With a Local Spatial-Temporal Dependence Model.
IEEE Trans. Geosci. Remote. Sens., 2019

Optimal Endmember-Based Super-Resolution Land Cover Mapping.
IEEE Geosci. Remote. Sens. Lett., 2019

2018
Spatio-Temporal Super-Resolution Land Cover Mapping Based on Fuzzy C-Means Clustering.
Remote. Sens., 2018

2017
Learning-Based Spatial-Temporal Superresolution Mapping of Forest Cover With MODIS Images.
IEEE Trans. Geosci. Remote. Sens., 2017

Fusion of Landsat 8 OLI and Sentinel-2 MSI Data.
IEEE Trans. Geosci. Remote. Sens., 2017

Enhancing Spatio-Temporal Fusion of MODIS and Landsat Data by Incorporating 250 m MODIS Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Spectral-Spatial Adaptive Area-to-Point Regression Kriging for MODIS Image Downscaling.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Impervious Surface Change Mapping with an Uncertainty-Based Spatial-Temporal Consistency Model: A Case Study in Wuhan City Using Landsat Time-Series Datasets from 1987 to 2016.
Remote. Sens., 2017

Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM+ Thermal Infrared Images.
Remote. Sens., 2017

Updating Landsat-based forest cover maps with MODIS images using multiscale spectral-spatial-temporal superresolution mapping.
Int. J. Appl. Earth Obs. Geoinformation, 2017

2016
Learning-Based Superresolution Land Cover Mapping.
IEEE Trans. Geosci. Remote. Sens., 2016

Assessing a Temporal Change Strategy for Sub-Pixel Land Cover Change Mapping from Multi-Scale Remote Sensing Imagery.
Remote. Sens., 2016

Water Bodies' Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band.
Remote. Sens., 2016

2015
Super-Resolution Land Cover Mapping Using Multiscale Self-Similarity Redundancy.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015

Improvement of the Example-Regression-Based Super-Resolution Land Cover Mapping Algorithm.
IEEE Geosci. Remote. Sens. Lett., 2015

Burned-Area Mapping at the Subpixel Scale With MODIS Images.
IEEE Geosci. Remote. Sens. Lett., 2015

2014
Superresolution Land Cover Mapping With Multiscale Information by Fusing Local Smoothness Prior and Downscaled Coarse Fractions.
IEEE Trans. Geosci. Remote. Sens., 2014

Spatially Adaptive Superresolution Land Cover Mapping With Multispectral and Panchromatic Images.
IEEE Trans. Geosci. Remote. Sens., 2014

Example-Based Super-Resolution Land Cover Mapping Using Support Vector Regression.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

Unsupervised Subpixel Mapping of Remotely Sensed Imagery Based on Fuzzy C-Means Clustering Approach.
IEEE Geosci. Remote. Sens. Lett., 2014


  Loading...