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:

Investigating the impact of classification features and classifiers on crop mapping performance in heterogeneous agricultural landscapes
Huanxue Zhang, Yuji Wang, Jiali Shang, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102388-102388
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Support Vector Machine in Precision Agriculture: A review
Zhi Hong Kok, Abdul Rashid Mohamed Shariff, Meftah Salem M. Alfatni, et al.
Computers and Electronics in Agriculture (2021) Vol. 191, pp. 106546-106546
Closed Access | Times Cited: 140

Exploring the potential of multi-source unsupervised domain adaptation in crop mapping using Sentinel-2 images
Yumiao Wang, Luwei Feng, Weiwei Sun, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 2247-2265
Closed Access | Times Cited: 41

Exploring the effects of training samples on the accuracy of crop mapping with machine learning algorithm
Yangyang Fu, Ruoque Shen, Chaoqing Song, et al.
Science of Remote Sensing (2023) Vol. 7, pp. 100081-100081
Open Access | Times Cited: 17

Crop mapping through a hybrid machine learning and deep learning method
Bahar Asadi, Ali Shamsoddini
Remote Sensing Applications Society and Environment (2023) Vol. 33, pp. 101090-101090
Closed Access | Times Cited: 17

Review of synthetic aperture radar with deep learning in agricultural applications
Mahya G.Z. Hashemi, Ehsan Jalilvand, Hamed Alemohammad, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 218, pp. 20-49
Closed Access | Times Cited: 7

Irrigation Detection Using Sentinel-1 and Sentinel-2 Time Series on Fruit Tree Orchards
Amal Chakhar, David Hernández‐López, Rocío Ballesteros, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 458-458
Open Access | Times Cited: 5

Utilizing convolutional neural networks (CNN) and U-Net architecture for precise crop and weed segmentation in agricultural imagery: A deep learning approach
Mughair Aslam Bhatti, Syam M.S., Huafeng Chen, et al.
Big Data Research (2024) Vol. 36, pp. 100465-100465
Closed Access | Times Cited: 5

Comparison of common classification strategies for large-scale vegetation mapping over the Google Earth Engine platform
Tomás Marín Del Valle, Ping Jiang
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 115, pp. 103092-103092
Open Access | Times Cited: 21

Investigating the Potential of Crop Discrimination in Early Growing Stage of Change Analysis in Remote Sensing Crop Profiles
Mengfan Wei, Hongyan Wang, Yuan Zhang, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 853-853
Open Access | Times Cited: 11

Ensemble machine learning models for monitoring riparian vegetation dynamics using historical aerial orthophotos
Hamid Afzali, Miloš Rusnák
Remote Sensing Applications Society and Environment (2025), pp. 101545-101545
Closed Access

Extraction of Broad-Leaved Tree Crown Based on UAV Visible Images and OBIA-RF Model: A Case Study for Chinese Olive Trees
Kaile Yang, Houxi Zhang, Fan Wang, et al.
Remote Sensing (2022) Vol. 14, Iss. 10, pp. 2469-2469
Open Access | Times Cited: 16

Cropland Mapping in Tropical Smallholder Systems with Seasonally Stratified Sentinel-1 and Sentinel-2 Spectral and Textural Features
Manushi B. Trivedi, Michael Marshall, Lyndon Estes, et al.
Remote Sensing (2023) Vol. 15, Iss. 12, pp. 3014-3014
Open Access | Times Cited: 9

Investigating the Potential of Sentinel-2 MSI in Early Crop Identification in Northeast China
Mengfan Wei, Hongyan Wang, Yuan Zhang, et al.
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1928-1928
Open Access | Times Cited: 11

Improving classification accuracy for separation of area under crops based on feature selection from multi-temporal images and machine learning algorithms
Mostafa Kabolizadeh, Kazem Rangzan, Khalil Habashi
Advances in Space Research (2023) Vol. 72, Iss. 11, pp. 4809-4824
Closed Access | Times Cited: 5

Bi-stage feature selection for crop mapping using grey wolf metaheuristic optimization
Marwa S. Moustafa, Amira S. Mahmoud, Eslam Farg, et al.
Advances in Space Research (2024) Vol. 73, Iss. 10, pp. 5005-5016
Closed Access | Times Cited: 1

Exploring optimal features and image analysis methods for crop type classification from the perspective of crop landscape heterogeneity
Chen Chen, Taifeng Dong, Zhaohai Wang, et al.
Remote Sensing Applications Society and Environment (2024) Vol. 36, pp. 101308-101308
Closed Access | Times Cited: 1

Land use/land cover mapping using deep neural network and sentinel image dataset based on google earth engine in a heavily urbanized area, China
Shudan Chen, Fan Lei, Shengguang Dong, et al.
Geocarto International (2022) Vol. 37, Iss. 27, pp. 16951-16972
Closed Access | Times Cited: 4

In-Season Wall-to-Wall Crop-Type Mapping Using Ensemble of Image Segmentation Models
Sheir Afgen Zaheer, Youngryel Ryu, Junghee Lee, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-11
Closed Access | Times Cited: 2

Deep Learning Performance Comparison Using Multispectral Images and Vegetation Index for Farmland Classification
Semo Kim, Seoung-Hun Bae, Min-Kwan Kim, et al.
International Journal of Aeronautical and Space Sciences (2023) Vol. 24, Iss. 5, pp. 1533-1545
Closed Access | Times Cited: 1

An improved zoning crop mapping approach in complex agricultural landscapes considering crop heterogeneity
Guanru Fang, Wenyao Song, Wang Chen, et al.
(2023), pp. 1-5
Closed Access | Times Cited: 1

A Functional Zoning Method in Rural Landscape Based on High-Resolution Satellite Imagery
Yuying Zheng, Yuanyong Dian, Zhiqiang Guo, et al.
Remote Sensing (2023) Vol. 15, Iss. 20, pp. 4920-4920
Open Access | Times Cited: 1

Garlic Crops’ Mapping and Change Analysis in the Erhai Lake Basin Based on Google Earth Engine
Wenfeng Li, Jiao Pan, Wenyi Peng, et al.
Agronomy (2024) Vol. 14, Iss. 4, pp. 755-755
Open Access

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