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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:

Random forest in remote sensing: A review of applications and future directions
Mariana Belgiu, Lucian Drăguţ
ISPRS Journal of Photogrammetry and Remote Sensing (2016) Vol. 114, pp. 24-31
Closed Access | Times Cited: 5185

Showing 1-25 of 5185 citing articles:

The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019
Jie Yang, Xin Huang
Earth system science data (2021) Vol. 13, Iss. 8, pp. 3907-3925
Open Access | Times Cited: 1877
Deep learning in remote sensing applications: A meta-analysis and review
Lei Ma, Yü Liu, Xueliang Zhang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2019) Vol. 152, pp. 166-177
Open Access | Times Cited: 1760
Implementation of machine-learning classification in remote sensing: an applied review
Aaron E. Maxwell, Timothy A. Warner, Fang Fang
International Journal of Remote Sensing (2018) Vol. 39, Iss. 9, pp. 2784-2817
Open Access | Times Cited: 1535
Hyperparameters and tuning strategies for random forest
Philipp Probst, Marvin N. Wright, Anne‐Laure Boulesteix
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2019) Vol. 9, Iss. 3
Open Access | Times Cited: 1448
Remote sensing for agricultural applications: A meta-review
Marie Weiss, Frédéric Jacob, Grégory Duveiller
Remote Sensing of Environment (2019) Vol. 236, pp. 111402-111402
Open Access | Times Cited: 1289
Optical remotely sensed time series data for land cover classification: A review
Cristina Gómez, Joanne C. White, Michael A. Wulder
ISPRS Journal of Photogrammetry and Remote Sensing (2016) Vol. 116, pp. 55-72
Open Access | Times Cited: 1055
Google Earth Engine for geo-big data applications: A meta-analysis and systematic review
Haifa Tamiminia, Bahram Salehi, Masoud Mahdianpari, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 164, pp. 152-170
Closed Access | Times Cited: 965
Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis
Mariana Belgiu, Ovidiu Csillik
Remote Sensing of Environment (2017) Vol. 204, pp. 509-523
Open Access | Times Cited: 786
Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review
Mohammadreza Sheykhmousa, Masoud Mahdianpari, Hamid Ghanbari, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 13, pp. 6308-6325
Open Access | Times Cited: 739
Soybean yield prediction from UAV using multimodal data fusion and deep learning
Maitiniyazi Maimaitijiang, Vasit Sagan, Paheding Sidike, et al.
Remote Sensing of Environment (2019) Vol. 237, pp. 111599-111599
Open Access | Times Cited: 702
GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery
Xiao Zhang, Liangyun Liu, Xidong Chen, et al.
Earth system science data (2021) Vol. 13, Iss. 6, pp. 2753-2776
Open Access | Times Cited: 693
Machine learning algorithms for wireless sensor networks: A survey
D. Praveen Kumar, Tarachand Amgoth, Chandra Sekhara Rao Annavarapu
Information Fusion (2018) Vol. 49, pp. 1-25
Closed Access | Times Cited: 614
A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis
Water (2019) Vol. 11, Iss. 5, pp. 910-910
Open Access | Times Cited: 571
Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas
Charlotte Pelletier, Silvia Valero, Jordi Inglada, et al.
Remote Sensing of Environment (2016) Vol. 187, pp. 156-168
Closed Access | Times Cited: 530
Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Jie Dou, Ali P. Yunus, Dieu Tien Bui, et al.
The Science of The Total Environment (2019) Vol. 662, pp. 332-346
Closed Access | Times Cited: 509
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
Charlotte Pelletier, Geoffrey I. Webb, François Petitjean
Remote Sensing (2019) Vol. 11, Iss. 5, pp. 523-523
Open Access | Times Cited: 464
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
Pardhasaradhi Teluguntla, Prasad S. Thenkabail, Adam Oliphant, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2018) Vol. 144, pp. 325-340
Open Access | Times Cited: 462
Data driven prediction models of energy use of appliances in a low-energy house
Luis M. Candanedo, Véronique Feldheim, Dominique Deramaix
Energy and Buildings (2017) Vol. 140, pp. 81-97
Closed Access | Times Cited: 454
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
Renlong Hang, Qingshan Liu, Danfeng Hong, et al.
IEEE Transactions on Geoscience and Remote Sensing (2019) Vol. 57, Iss. 8, pp. 5384-5394
Open Access | Times Cited: 453
Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data
Kangyang Chen, Hexia Chen, Chuanlong Zhou, et al.
Water Research (2019) Vol. 171, pp. 115454-115454
Closed Access | Times Cited: 436
Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods
Jochem Verrelst, Zbyněk Malenovský, Christiaan van der Tol, et al.
Surveys in Geophysics (2018) Vol. 40, Iss. 3, pp. 589-629
Open Access | Times Cited: 396
A 30 m global map of elevation with forests and buildings removed
Laurence Hawker, Peter Uhe, Luntadila Paulo, et al.
Environmental Research Letters (2022) Vol. 17, Iss. 2, pp. 024016-024016
Open Access | Times Cited: 389
Land cover 2.0
Michael A. Wulder, Nicholas C. Coops, David P. Roy, et al.
International Journal of Remote Sensing (2018) Vol. 39, Iss. 12, pp. 4254-4284
Open Access | Times Cited: 348
Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea
Sunmin Lee, Jeong-Cheol Kim, Hyung-Sup Jung, et al.
Geomatics Natural Hazards and Risk (2017) Vol. 8, Iss. 2, pp. 1185-1203
Open Access | Times Cited: 337
Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities
Lefei Zhang, Liangpei Zhang
IEEE Geoscience and Remote Sensing Magazine (2022) Vol. 10, Iss. 2, pp. 270-294
Closed Access | Times Cited: 321
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