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 essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America
Бин Чэн, Ying Tu, Yimeng Song, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 178, pp. 203-218
Open Access | Times Cited: 75

Showing 26-50 of 75 citing articles:

Mapping Urban Functional Areas Using Multisource Remote Sensing Images and Open Big Data
Yifan Chen, Chaokang He, Wei Guo, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 16, pp. 7919-7931
Open Access | Times Cited: 12

Mapping the Future of Sustainable Development Through Cloud-Based Solutions
Munir Ahmad, Asmat Ali
Advances in environmental engineering and green technologies book series (2023), pp. 153-176
Closed Access | Times Cited: 12

Enhancing Urban Land Use Identification Using Urban Morphology
Chuan Lin, Guang Li, Zegen Zhou, et al.
Land (2024) Vol. 13, Iss. 6, pp. 761-761
Open Access | Times Cited: 4

Enhancing Remote Sensing Semantic Segmentation Accuracy and Efficiency Through Transformer and Knowledge Distillation
Kang Zheng, Yu Chen, Jingrong Wang, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025) Vol. 18, pp. 4074-4092
Open Access

Urban functional zone mapping by coupling domain knowledge graphs and high‐resolution satellite images
Yixiang Chen, Dang Xu, Daoyou Zhu, et al.
Transactions in GIS (2024) Vol. 28, Iss. 6, pp. 1510-1535
Closed Access | Times Cited: 3

Assessing Spatiotemporal Changes of SDG Indicators at the Neighborhood Level in Guilin, China: A Geospatial Big Data Approach
Liying Han, Linlin Lu, Junyu Lu, et al.
Remote Sensing (2022) Vol. 14, Iss. 19, pp. 4985-4985
Open Access | Times Cited: 14

A 30 m annual cropland dataset of China from 1986 to 2021
Ying Tu, Shengbiao Wu, Bin Chen, et al.
(2023)
Open Access | Times Cited: 8

Using POI Data and Baidu Migration Big Data to Modify Nighttime Light Data to Identify Urban and Rural Area
Yaping Chen, Akot Deng
IEEE Access (2022) Vol. 10, pp. 93513-93524
Open Access | Times Cited: 13

Developing a mapping procedure for urban forests using online map services and Sentinel-2A images
Jinsuk Jeong, Chan‐Ryul Park
Urban forestry & urban greening (2023) Vol. 89, pp. 128095-128095
Open Access | Times Cited: 7

Land-use classification based on high-resolution remote sensing imagery and deep learning models
Mengmeng Hao, Xiaohan Dong, Dong Jiang, et al.
PLoS ONE (2024) Vol. 19, Iss. 4, pp. e0300473-e0300473
Open Access | Times Cited: 2

Time-series China urban land use mapping (2016–2022): An approach for achieving spatial-consistency and semantic-transition rationality in temporal domain
Shuping Xiong, Xiuyuan Zhang, Yichen Lei, et al.
Remote Sensing of Environment (2024) Vol. 312, pp. 114344-114344
Closed Access | Times Cited: 2

Assessment of ensemble learning for object-based land cover mapping using multi-temporal Sentinel-1/2 images
Suchen Xu, Wu Xiao, Linlin Ruan, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 6

Evidence of Multi-Source Data Fusion on the Relationship between the Specific Urban Built Environment and Urban Vitality in Shenzhen
Pei Zhang, Tao Zhang, Hiroatsu Fukuda, et al.
Sustainability (2023) Vol. 15, Iss. 8, pp. 6869-6869
Open Access | Times Cited: 6

Uncovering the Nature of Urban Land Use Composition Using Multi-Source Open Big Data with Ensemble Learning
Ying Tu, Бин Чэн, Wei Lang, et al.
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4241-4241
Open Access | Times Cited: 14

A Cloud-Based Mapping Approach Using Deep Learning and Very-High Spatial Resolution Earth Observation Data to Facilitate the SDG 11.7.1 Indicator Computation
Natalia Verde, Πέτρος Πατιάς, Giorgos Mallinis
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 1011-1011
Open Access | Times Cited: 9

IoT-Based Smart Air Conditioner as a Preventive in the Post-COVID-19 Era: A Review
Dhanar Intan Surya Saputra, I Putu Dody Suarnatha, Fajar Mahardika, et al.
Journal of Robotics and Control (JRC) (2023) Vol. 4, Iss. 1, pp. 60-70
Open Access | Times Cited: 5

Consistent metropolitan boundaries for the remote sensing of urban land
Michiel Daams, Alexandre Banquet, Paul Delbouve, et al.
Remote Sensing of Environment (2023) Vol. 297, pp. 113789-113789
Open Access | Times Cited: 5

Fine-resolution mapping and assessment of artificial surfaces in the northern hemisphere permafrost environments
Chong Liu, Huabing Huang, Qi Zhang, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 1

Analysis and Quantification of the Distribution of Marabou (Dichrostachys cinerea (L.) Wight & Arn.) in Valle de los Ingenios, Cuba: A Remote Sensing Approach
E. Moreno, Encarnación González, Reinaldo Alvarez, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 752-752
Open Access | Times Cited: 1

Analyzing the extent and use of impervious land in rural landscapes
Andreas Möser, Jasper van Vliet, Ulrike Wissen Hayek, et al.
Geography and sustainability (2024) Vol. 5, Iss. 4, pp. 625-636
Open Access | Times Cited: 1

Disparities in Low-Carbon Concrete GWP at the metropolitan level in the United States
Jonathan M. Broyles, Juan Pablo Gevaudan
Research Square (Research Square) (2024)
Closed Access | Times Cited: 1

Quantitative Identification of Mixed Urban Functions: A Probabilistic Approach Based on Physical and Social Sensing Data
Yan Zhang, Mei‐Po Kwan, B. X. Yu, et al.
Transactions in GIS (2024)
Closed Access | Times Cited: 1

Automated School Location Mapping at Scale from Satellite Imagery Based on Deep Learning
Iyke Maduako, Zhuang‐Fang Yi, Naroa Zurutuza, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 897-897
Open Access | Times Cited: 7

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