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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:

Parcel-Based Crop Classification Using Multi-Temporal TerraSAR-X Dual Polarimetric Data
Rei Sonobe
Remote Sensing (2019) Vol. 11, Iss. 10, pp. 1148-1148
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Machine Learning in Agriculture: A Comprehensive Updated Review
Lefteris Benos, Aristotelis C. Tagarakis, Georgios Dolias, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3758-3758
Open Access | Times Cited: 526
Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine
Jarrett Adrian, Vasit Sagan, Maitiniyazi Maimaitijiang
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 175, pp. 215-235
Open Access | Times Cited: 176
Mapping crop types in complex farming areas using SAR imagery with dynamic time warping
Getachew Workineh Gella, W. Bijker, Mariana Belgiu
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 175, pp. 171-183
Open Access | Times Cited: 80
Comparative Assessment of Machine Learning Methods for Urban Vegetation Mapping Using Multitemporal Sentinel-1 Imagery
Mateo Gašparović, Dino Dobrinić
Remote Sensing (2020) Vol. 12, Iss. 12, pp. 1952-1952
Open Access | Times Cited: 77
Estimation of Leaf Chlorophyll a, b and Carotenoid Contents and Their Ratios Using Hyperspectral Reflectance
Rei Sonobe, Hiroto Yamashita, Harumi Mihara, et al.
Remote Sensing (2020) Vol. 12, Iss. 19, pp. 3265-3265
Open Access | Times Cited: 67
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
Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms
Rei Sonobe, Yuhei Hirono, Ayako Oi
Plants (2020) Vol. 9, Iss. 3, pp. 368-368
Open Access | Times Cited: 48
Enhanced crop classification through integrated optical and SAR data: a deep learning approach for multi-source image fusion
Niantang Liu, Qunshan Zhao, Richard Williams, et al.
International Journal of Remote Sensing (2023) Vol. 45, Iss. 19-20, pp. 7605-7633
Open Access | Times Cited: 14
Feature Dimension Reduction Using Stacked Sparse Auto-Encoders for Crop Classification with Multi-Temporal, Quad-Pol SAR Data
Jiao Guo, Hongping Li, Jifeng Ning, et al.
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 321-321
Open Access | Times Cited: 28
Early-Season Crop Mapping on an Agricultural Area in Italy Using X-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks
Giacomo Fontanelli, Alessandro Lapini, Leonardo Santurri, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022) Vol. 15, pp. 6789-6803
Open Access | Times Cited: 18
Spatial variability in paddy intensity and pattern of groundwater trend in part of Lower Gangetic Plain
Piyasa Gayen, Dipanwita Dutta
Environmental Monitoring and Assessment (2025) Vol. 197, Iss. 3
Closed Access
Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
Mario Busquier, Juan M. López‐Sánchez, Alejandro Mestre-Quereda, et al.
Remote Sensing (2020) Vol. 12, Iss. 11, pp. 1774-1774
Open Access | Times Cited: 25
Quantifying chlorophyll-a and b content in tea leaves using hyperspectral reflectance and deep learning
Rei Sonobe, Yuhei Hirono, Ayako Oi
Remote Sensing Letters (2020) Vol. 11, Iss. 10, pp. 933-942
Closed Access | Times Cited: 21
Generating pre-harvest crop maps by applying convolutional neural network on multi-temporal Sentinel-1 data
Subir Paul, Mamta Kumari, C. S. Murthy, et al.
International Journal of Remote Sensing (2022) Vol. 43, Iss. 15-16, pp. 6078-6101
Closed Access | Times Cited: 13
Combining ASNARO-2 XSAR HH and Sentinel-1 C-SAR VH/VV Polarization Data for Improved Crop Mapping
Rei Sonobe
Remote Sensing (2019) Vol. 11, Iss. 16, pp. 1920-1920
Open Access | Times Cited: 21
Effective SAR image segmentation and classification of crop areas using MRG and CDNN techniques
N. V. S. Natteshan, N. Suresh Kumar
European Journal of Remote Sensing (2020) Vol. 53, Iss. sup1, pp. 126-140
Open Access | Times Cited: 19
Parcel level staple crop type identification based on newly defined red-edge vegetation indices and ORNN
Lu Xu, Dongping Ming, Liang Zhang, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108012-108012
Closed Access | Times Cited: 6
Using SAR-based products to calculate potato carbon uptake in a tropical Andean region
Gustavo Alfonso Araujo-Carrillo, Julio M. Duarte‐Carvajalino, Diego Fernando Sánchez-Vívas, et al.
European Journal of Remote Sensing (2024) Vol. 57, Iss. 1
Open Access | Times Cited: 2
Parcel-Based Sugarcane Mapping Using Smoothed Sentinel-1 Time Series Data
Hongzhong Li, Zhengxin Wang, Luyi Sun, et al.
Remote Sensing (2024) Vol. 16, Iss. 15, pp. 2785-2785
Open Access | Times Cited: 2
Combination of Time Series of L-, C-, and X-Band SAR Images for Land Cover and Crop Classification
Mario Busquier, Juan M. López‐Sánchez, Francesca Ticconi, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022) Vol. 15, pp. 8266-8286
Open Access | Times Cited: 10
Field Geometry and the Spatial and Temporal Generalization of Crop Classification Algorithms—A Randomized Approach to Compare Pixel Based and Convolution Based Methods
Mario Gilcher, Thomas Udelhoven
Remote Sensing (2021) Vol. 13, Iss. 4, pp. 775-775
Open Access | Times Cited: 12
Crop Mapping Using Sentinel Full-Year Dual-Polarized SAR Data and a CPU-Optimized Convolutional Neural Network With Two Sampling Strategies
Shengjie Liu, Zhize Zhou, Huaxiang Ding, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021) Vol. 14, pp. 7017-7031
Open Access | Times Cited: 12
Crop Health Assessment Using Sentinel-1 SAR Time Series Data in a Part of Central India
Sandeep Kaushik, Varun Narayan Mishra, Milap Punia, et al.
Remote Sensing in Earth Systems Sciences (2021) Vol. 4, Iss. 4, pp. 217-234
Closed Access | Times Cited: 12
Accurate Segmentation for Low Resolution Satellite images by Discriminative Generative Adversarial Network for Identifying Agriculture Fields
S. Iwin Thanakumar Joseph
Journal of Innovative Image Processing (2021) Vol. 3, Iss. 4, pp. 298-310
Open Access | Times Cited: 11
Crop Type Classification using Sentinel 2A-Derived Normalized Difference Red Edge Index (NDRE) and Machine Learning Approach
Bere Benjamin Bantchına, Kemal Sulhi Gündoğdu
Uludağ Üniversitesi Ziraat Fakültesi dergisi/Bursa uludağ üniversitesi ziraat fakültesi dergisi (2024) Vol. 38, Iss. 1, pp. 89-105
Open Access | Times Cited: 1
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