Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Soil organic carbon and texture retrieving and mapping using proximal, airborne and Sentinel-2 spectral imaging
Asa Gholizadeh, Daniel Žížala, Mohammadmehdi Saberioon, et al.
Remote Sensing of Environment (2018) Vol. 218, pp. 89-103
Open Access | Times Cited: 368

Showing 1-25 of 368 citing articles:

Sentinel-2 Data for Land Cover/Use Mapping: A Review
Darius Phiri, Matamyo Simwanda, Serajis Salekin, et al.
Remote Sensing (2020) Vol. 12, Iss. 14, pp. 2291-2291
Open Access | Times Cited: 588
Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications
Joel Segarra, Ma. Luisa Buchaillot, J. L. Araus, et al.
Agronomy (2020) Vol. 10, Iss. 5, pp. 641-641
Open Access | Times Cited: 355
Digital mapping of GlobalSoilMap soil properties at a broad scale: A review
Songchao Chen, Dominique Arrouays, Vera Leatitia Mulder, et al.
Geoderma (2021) Vol. 409, pp. 115567-115567
Open Access | Times Cited: 333
Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review
Theodora Angelopoulou, Nikolaos Tziolas, Athanasios Τ. Balafoutis, et al.
Remote Sensing (2019) Vol. 11, Iss. 6, pp. 676-676
Open Access | Times Cited: 293
Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands
Fabio Castaldi, Andreas Hueni, Sabine Chabrillat, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2018) Vol. 147, pp. 267-282
Open Access | Times Cited: 243
Machine learning-based detection of soil salinity in an arid desert region, Northwest China: A comparison between Landsat-8 OLI and Sentinel-2 MSI
Jingzhe Wang, Jianli Ding, Danlin Yu, et al.
The Science of The Total Environment (2019) Vol. 707, pp. 136092-136092
Closed Access | Times Cited: 208
High-resolution digital mapping of soil organic carbon and soil total nitrogen using DEM derivatives, Sentinel-1 and Sentinel-2 data based on machine learning algorithms
Tao Zhou, Yajun Geng, Jie Chen, et al.
The Science of The Total Environment (2020) Vol. 729, pp. 138244-138244
Closed Access | Times Cited: 199
Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space
Ruhollah Taghizadeh–Mehrjardi, Karsten Schmidt, Alireza Amirian‐Chakan, et al.
Remote Sensing (2020) Vol. 12, Iss. 7, pp. 1095-1095
Open Access | Times Cited: 170
Improving the spatial prediction of soil organic carbon using environmental covariates selection: A comparison of a group of environmental covariates
Mojtaba Zeraatpisheh, Younes Garosi, Hamidreza Owliaie, et al.
CATENA (2021) Vol. 208, pp. 105723-105723
Closed Access | Times Cited: 150
Mapping soil organic carbon stock by hyperspectral and time-series multispectral remote sensing images in low-relief agricultural areas
Long Guo, Xiaoru Sun, Peng Fu, et al.
Geoderma (2021) Vol. 398, pp. 115118-115118
Closed Access | Times Cited: 123
Integrating Active and Passive Remote Sensing Data for Mapping Soil Salinity Using Machine Learning and Feature Selection Approaches in Arid Regions
Sayed A. Mohamed, Mohamed M. Metwaly, Mohamed R. Metwalli, et al.
Remote Sensing (2023) Vol. 15, Iss. 7, pp. 1751-1751
Open Access | Times Cited: 49
Digital exploration of selected heavy metals using Random Forest and a set of environmental covariates at the watershed scale
Shohreh Moradpour, Mojgan Entezari, Shamsollah Ayoubi, et al.
Journal of Hazardous Materials (2023) Vol. 455, pp. 131609-131609
Closed Access | Times Cited: 49
LiDAR GEDI derived tree canopy height heterogeneity reveals patterns of biodiversity in forest ecosystems
Michele Torresani, Duccio Rocchini, Alessandro Alberti, et al.
Ecological Informatics (2023) Vol. 76, pp. 102082-102082
Open Access | Times Cited: 46
Improving model parsimony and accuracy by modified greedy feature selection in digital soil mapping
Xianglin Zhang, Songchao Chen, Jie Xue, et al.
Geoderma (2023) Vol. 432, pp. 116383-116383
Open Access | Times Cited: 45
Can environmental variables, high sampling density and machine learning deliver detailed maps of soil organic carbon and carbon stock in tropical regions?
Fernanda Almeida Bócoli, Diego Ribeiro, Marcelo Mancini, et al.
CATENA (2025) Vol. 249, pp. 108718-108718
Closed Access | Times Cited: 2
Prediction of soil organic carbon and the C:N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and Landsat-8 images
Tao Zhou, Yajun Geng, Cheng Ji, et al.
The Science of The Total Environment (2020) Vol. 755, pp. 142661-142661
Closed Access | Times Cited: 138
Improved digital soil mapping with multitemporal remotely sensed satellite data fusion: A case study in Iran
Solmaz Fathololoumi, Ali Reza Vaezi, Seyed Kazem Alavipanah, et al.
The Science of The Total Environment (2020) Vol. 721, pp. 137703-137703
Closed Access | Times Cited: 128
Soil Science Challenges in a New Era: A Transdisciplinary Overview of Relevant Topics
Jesús Rodrigo‐Comino, Manuel López‐Vicente, Vinod Kumar, et al.
Air Soil and Water Research (2020) Vol. 13
Open Access | Times Cited: 117
Soil Organic Carbon Mapping Using LUCAS Topsoil Database and Sentinel-2 Data: An Approach to Reduce Soil Moisture and Crop Residue Effects
Fabio Castaldi, Sabine Chabrillat, Axel Don, et al.
Remote Sensing (2019) Vol. 11, Iss. 18, pp. 2121-2121
Open Access | Times Cited: 112
Satellite data integration for soil clay content modelling at a national scale
Thomas Loiseau, Songchao Chen, Vera Leatitia Mulder, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 82, pp. 101905-101905
Closed Access | Times Cited: 105
Soil Organic Carbon Mapping Using Multispectral Remote Sensing Data: Prediction Ability of Data with Different Spatial and Spectral Resolutions
Daniel Žížala, Robert Minařík, Tereza Zádorová
Remote Sensing (2019) Vol. 11, Iss. 24, pp. 2947-2947
Open Access | Times Cited: 103
Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest models with different predictors
Yue Zhang, Biao Sui, Haiou Shen, et al.
Computers and Electronics in Agriculture (2019) Vol. 160, pp. 23-30
Closed Access | Times Cited: 99
Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran
Ruhollah Taghizadeh–Mehrjardi, Masoud Mahdianpari, Fariba Mohammadimanesh, et al.
Geoderma (2020) Vol. 376, pp. 114552-114552
Closed Access | Times Cited: 99
A novel intelligence approach based active and ensemble learning for agricultural soil organic carbon prediction using multispectral and SAR data fusion
Thu Thủy Nguyễn, Tien Dat Pham, Chi Trung Nguyen, et al.
The Science of The Total Environment (2021) Vol. 804, pp. 150187-150187
Closed Access | Times Cited: 97
Exploring the potential of airborne hyperspectral image for estimating topsoil organic carbon: Effects of fractional-order derivative and optimal band combination algorithm
Yongsheng Hong, Long Guo, Songchao Chen, et al.
Geoderma (2020) Vol. 365, pp. 114228-114228
Closed Access | Times Cited: 95
Page 1 - Next Page

Scroll to top