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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Mapping landslides through a temporal lens: an insight toward multi-temporal landslide mapping using the u-net deep learning model
Kushanav Bhuyan, Sansar Raj Meena, Lorenzo Nava, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 14

Showing 14 citing articles:

Landslide mapping based on a hybrid CNN-transformer network and deep transfer learning using remote sensing images with topographic and spectral features
Lei Wu, Rui Liu, Nengpan Ju, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 126, pp. 103612-103612
Open Access | Times Cited: 22
Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation
Nicola Nocentini, Camilla Medici, Francesco Barbadori, et al.
Landslides (2023) Vol. 21, Iss. 3, pp. 557-571
Open Access | Times Cited: 13
On the estimation of landslide intensity, hazard and density via data-driven models
Mariano Di Napoli, Hakan Tanyaş, Daniela Castro‐Camilo, et al.
Natural Hazards (2023) Vol. 119, Iss. 3, pp. 1513-1530
Open Access | Times Cited: 10
A Multi-Input Channel U-Net Landslide Detection Method Fusing SAR Multisource Remote Sensing Data
Hesheng Chen, Yi He, Lifeng Zhang, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 17, pp. 1215-1232
Open Access | Times Cited: 10
Pan‐European Landslide Risk Assessment: From Theory to Practice
Francesco Caleca, Luigi Lombardo, Stefan Steger, et al.
Reviews of Geophysics (2025) Vol. 63, Iss. 1
Open Access
Failure process and three-dimensional motions of mining-induced Jianshanying landslide in China observed by optical, LiDAR and SAR datasets
Chaoying Zhao, Liquan Chen, Yueping Yin, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 9
Unsupervised Landslide Detection from Multi-Temporal High-Resolution Images based on Progressive Label Upgradation and Cross-Temporal Style Adaption
Penglei Li, Yi Wang, Guanting Liu, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-15
Closed Access | Times Cited: 2
An updated landslide susceptibility model and a log-Gaussian Cox process extension for Scotland
Erin Bryce, Daniela Castro‐Camilo, Claire Dashwood, et al.
Landslides (2024)
Open Access | Times Cited: 2
Automatic Identification for the Boundaries of InSAR Anomalous Deformation Areas Based on Semantic Segmentation Model
Yiwen Liang, Yi Zhang, Yuanxi Li, et al.
Remote Sensing (2023) Vol. 15, Iss. 21, pp. 5262-5262
Open Access | Times Cited: 1
An updated landslide susceptibility model and a log-Gaussian Cox process extension for Scotland
Erin Bryce, Daniela Castro‐Camilo, Claire Dashwood, et al.
EarthArXiv (California Digital Library) (2024)
Open Access
Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction
Zheng Zhao, Weihong Wang, Jianhua Chen, et al.
GIScience & Remote Sensing (2024) Vol. 61, Iss. 1
Open Access
Automatic detection of landslide impact areas using Google Earth Engine
Yu-En Yang, Teng-To Yu, Chun-Yuan Chen
Terrestrial Atmospheric and Oceanic Sciences (2024) Vol. 35, Iss. 1
Open Access
Remote Sensing Identification of Picea schrenkiana var. tianschanica in GF-1 Images Based on a Multiple Mixed Attention U-Net Model
Jian Zheng, Donghua Chen, Hanchi Zhang, et al.
Forests (2024) Vol. 15, Iss. 11, pp. 2039-2039
Open Access
Long-term prediction of Arctic sea ice concentrations using deep learning: Effects of surface temperature, radiation, and wind conditions
Young Jun Kim, Hyun‐Cheol Kim, Daehyeon Han, et al.
Remote Sensing of Environment (2024) Vol. 318, pp. 114568-114568
Closed Access
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