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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:

Forest Monitoring Using Landsat Time Series Data: A Review
Asim Banskota, Nilam Kayastha, Michael J. Falkowski, et al.
Canadian Journal of Remote Sensing (2014) Vol. 40, Iss. 5, pp. 362-384
Open Access | Times Cited: 358

Showing 1-25 of 358 citing articles:

Current status of Landsat program, science, and applications
Michael A. Wulder, Thomas R. Loveland, David P. Roy, et al.
Remote Sensing of Environment (2019) Vol. 225, pp. 127-147
Open Access | Times Cited: 853
First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe
Markus Immitzer, Francesco Vuolo, Clement Atzberger
Remote Sensing (2016) Vol. 8, Iss. 3, pp. 166-166
Open Access | Times Cited: 803
Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications
Zhe Zhu
ISPRS Journal of Photogrammetry and Remote Sensing (2017) Vol. 130, pp. 370-384
Open Access | Times Cited: 718
Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery
Jordi Inglada, Marcela Arias, Benjamin Tardy, et al.
Remote Sensing (2015) Vol. 7, Iss. 9, pp. 12356-12379
Open Access | Times Cited: 348
A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series
Joanne C. White, Michael A. Wulder, Txomin Hermosilla, et al.
Remote Sensing of Environment (2017) Vol. 194, pp. 303-321
Open Access | Times Cited: 329
Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics
Txomin Hermosilla, Michael A. Wulder, Joanne C. White, et al.
Remote Sensing of Environment (2015) Vol. 170, pp. 121-132
Closed Access | Times Cited: 281
Forest disturbance across the conterminous United States from 1985–2012: The emerging dominance of forest decline
Warren B. Cohen, Zhiqiang Yang, Stephen V. Stehman, et al.
Forest Ecology and Management (2015) Vol. 360, pp. 242-252
Closed Access | Times Cited: 256
A review of machine learning in processing remote sensing data for mineral exploration
Hojat Shirmard, Ehsan Farahbakhsh, R. Dietmar Müller, et al.
Remote Sensing of Environment (2021) Vol. 268, pp. 112750-112750
Open Access | Times Cited: 236
Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring
Txomin Hermosilla, Michael A. Wulder, Joanne C. White, et al.
International Journal of Digital Earth (2016) Vol. 9, Iss. 11, pp. 1035-1054
Open Access | Times Cited: 231
Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics
Angela Lausch, Stefan Erasmi, Douglas J. King, et al.
Remote Sensing (2016) Vol. 8, Iss. 12, pp. 1029-1029
Open Access | Times Cited: 185
How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?
Warren B. Cohen, Sean P. Healey, Zhiqiang Yang, et al.
Forests (2017) Vol. 8, Iss. 4, pp. 98-98
Open Access | Times Cited: 179
Multi-sensor cloud and cloud shadow segmentation with a convolutional neural network
Marc Wieland, Yu Li, Sandro Martinis
Remote Sensing of Environment (2019) Vol. 230, pp. 111203-111203
Open Access | Times Cited: 178
Remote sensing of forest degradation: a review
Yan Gao, Margaret Skutsch, Jaime Paneque‐Gálvez, et al.
Environmental Research Letters (2020) Vol. 15, Iss. 10, pp. 103001-103001
Open Access | Times Cited: 171
Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types
Benjamin C. Bright, Andrew T. Hudak, Robert E. Kennedy, et al.
Fire Ecology (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 167
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: 153
An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends
Qiang Zhao, Le Yu, Zhenrong Du, et al.
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1863-1863
Open Access | Times Cited: 120
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: 116
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: 100
A First Assessment of Canopy Cover Loss in Germany’s Forests after the 2018–2020 Drought Years
Frank Thonfeld, Ursula Geßner, Stefanie Holzwarth, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 562-562
Open Access | Times Cited: 93
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: 74
Unveiling China’s natural and planted forest spatial–temporal dynamics from 1990 to 2020
Kai Cheng, Haitao Yang, Hongcan Guan, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 209, pp. 37-50
Closed Access | Times Cited: 32
A 2020 forest age map for China with 30 m resolution
Kai Cheng, Yu‐Ling Chen, Tianyu Xiang, et al.
Earth system science data (2024) Vol. 16, Iss. 2, pp. 803-819
Open Access | Times Cited: 18
Forest recovery trends derived from Landsat time series for North American boreal forests
Paul D. Pickell, Txomin Hermosilla, Ryan J. Frazier, et al.
International Journal of Remote Sensing (2015) Vol. 37, Iss. 1, pp. 138-149
Open Access | Times Cited: 148
Influence of Variable Selection and Forest Type on Forest Aboveground Biomass Estimation Using Machine Learning Algorithms
Zhenzhen Liu, Chao Li, Mingyang Li, et al.
Forests (2019) Vol. 10, Iss. 12, pp. 1073-1073
Open Access | Times Cited: 130
Natural disturbances are spatially diverse but temporally synchronized across temperate forest landscapes in Europe
Cornelius Senf, Rupert Seidl
Global Change Biology (2017) Vol. 24, Iss. 3, pp. 1201-1211
Open Access | Times Cited: 128
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