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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:

Improved mapping of forest type using spectral-temporal Landsat features
Valerie J. Pasquarella, Christopher E. Holden, Curtis E. Woodcock
Remote Sensing of Environment (2018) Vol. 210, pp. 193-207
Closed Access | Times Cited: 141

Showing 1-25 of 141 citing articles:

Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4–8 and Sentinel-2 imagery
Shi Qiu, Zhe Zhu, Binbin He
Remote Sensing of Environment (2019) Vol. 231, pp. 111205-111205
Closed Access | Times Cited: 397
Forest Stand Species Mapping Using the Sentinel-2 Time Series
Ewa Grabska‐Szwagrzyk, Patrick Hostert, Dirk Pflugmacher, et al.
Remote Sensing (2019) Vol. 11, Iss. 10, pp. 1197-1197
Open Access | Times Cited: 239
Optimal Input Features for Tree Species Classification in Central Europe Based on Multi-Temporal Sentinel-2 Data
Markus Immitzer, Martin Neuwirth, Sebastian Böck, et al.
Remote Sensing (2019) Vol. 11, Iss. 22, pp. 2599-2599
Open Access | Times Cited: 192
Extensive land cover change across Arctic–Boreal Northwestern North America from disturbance and climate forcing
Jonathan Wang, Damien Sulla‐Menashe, Curtis E. Woodcock, et al.
Global Change Biology (2019) Vol. 26, Iss. 2, pp. 807-822
Closed Access | Times Cited: 178
Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians
Ewa Grabska‐Szwagrzyk, David Frantz, Katarzyna Ostapowicz
Remote Sensing of Environment (2020) Vol. 251, pp. 112103-112103
Closed Access | Times Cited: 171
Mapping Forest Type and Tree Species on a Regional Scale Using Multi-Temporal Sentinel-2 Data
Agata Hościło, Aneta Lewandowska
Remote Sensing (2019) Vol. 11, Iss. 8, pp. 929-929
Open Access | Times Cited: 158
Mapping temperate forest tree species using dense Sentinel-2 time series
Jan Hemmerling, Dirk Pflugmacher, Patrick Hostert
Remote Sensing of Environment (2021) Vol. 267, pp. 112743-112743
Closed Access | Times Cited: 141
Remote sensing of land change: A multifaceted perspective
Zhe Zhu, Shi Qiu, Su Ye
Remote Sensing of Environment (2022) Vol. 282, pp. 113266-113266
Open Access | Times Cited: 119
Demystifying LandTrendr and CCDC temporal segmentation
Valerie J. Pasquarella, Paulo Arévalo, Kelsee H. Bratley, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 110, pp. 102806-102806
Open Access | Times Cited: 104
Mapping crop type in Northeast China during 2013–2021 using automatic sampling and tile-based image classification
Xuan Fu, Yi Dong, Jiayu Li, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 117, pp. 103178-103178
Open Access | Times Cited: 81
Mapping the presence and distribution of tree species in Canada's forested ecosystems
Txomin Hermosilla, Alex Bastyr, Nicholas C. Coops, et al.
Remote Sensing of Environment (2022) Vol. 282, pp. 113276-113276
Open Access | Times Cited: 77
Mapping China’s planted forests using high resolution imagery and massive amounts of crowdsourced samples
Kai Cheng, Yanjun Su, Hongcan Guan, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 196, pp. 356-371
Closed Access | Times Cited: 58
Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine cloud computing
Leandro Parente, Vinícius Vieira Mesquita, Fausto Miziara, et al.
Remote Sensing of Environment (2019) Vol. 232, pp. 111301-111301
Closed Access | Times Cited: 130
A Suite of Tools for Continuous Land Change Monitoring in Google Earth Engine
Paulo Arévalo, Eric L. Bullock, Curtis E. Woodcock, et al.
Frontiers in Climate (2020) Vol. 2
Open Access | Times Cited: 109
Improved change monitoring using an ensemble of time series algorithms
Eric L. Bullock, Curtis E. Woodcock, Christopher E. Holden
Remote Sensing of Environment (2019) Vol. 238, pp. 111165-111165
Open Access | Times Cited: 90
Exploring the potential of land surface phenology and seasonal cloud free composites of one year of Sentinel-2 imagery for tree species mapping in a mountainous region
Andreas Kollert, Magnus Bremer, Markus Löw, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 94, pp. 102208-102208
Open Access | Times Cited: 81
Mapping causal agents of disturbance in boreal and arctic ecosystems of North America using time series of Landsat data
Yingtong Zhang, Curtis E. Woodcock, Shijuan Chen, et al.
Remote Sensing of Environment (2022) Vol. 272, pp. 112935-112935
Open Access | Times Cited: 41
Mapping understory plant communities in deciduous forests from Sentinel-2 time series
Xiucheng Yang, Shi Qiu, Zhe Zhu, et al.
Remote Sensing of Environment (2023) Vol. 293, pp. 113601-113601
Open Access | Times Cited: 37
The Effects of Spatial Resolution and Resampling on the Classification Accuracy of Wetland Vegetation Species and Ground Objects: A Study Based on High Spatial Resolution UAV Images
Jianjun Chen, Zizhen Chen, Renjie Huang, et al.
Drones (2023) Vol. 7, Iss. 1, pp. 61-61
Open Access | Times Cited: 34
TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing
Steve Ahlswede, Christian Schulz, Christiano Gava, et al.
Earth system science data (2023) Vol. 15, Iss. 2, pp. 681-695
Open Access | Times Cited: 29
Evaluating the Potential of Sentinel-2 Time Series Imagery and Machine Learning for Tree Species Classification in a Mountainous Forest
Pan Liu, Chunying Ren, Zongming Wang, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 293-293
Open Access | Times Cited: 12
Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning
Peng Dou, Huanfeng Shen, Chunlin Huang, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 129, pp. 103866-103866
Open Access | Times Cited: 10
Mapping Cropping Practices on a National Scale Using Intra-Annual Landsat Time Series Binning
Philippe Rufin, David Frantz, Stefan Ernst, et al.
Remote Sensing (2019) Vol. 11, Iss. 3, pp. 232-232
Open Access | Times Cited: 66
Black bears alter movements in response to anthropogenic features with time of day and season
Katherine A. Zeller, David W. Wattles, Laura Conlee, et al.
Movement Ecology (2019) Vol. 7, Iss. 1
Open Access | Times Cited: 61
Comparison of Random Forest, Support Vector Machines, and Neural Networks for Post-Disaster Forest Species Mapping of the Krkonoše/Karkonosze Transboundary Biosphere Reserve
Bogdan Zagajewski, Marcin Kluczek, Edwin Raczko, et al.
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2581-2581
Open Access | Times Cited: 56
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