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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: 361

Showing 26-50 of 361 citing articles:

Estimating Forest Structure from UAV-Mounted LiDAR Point Cloud Using Machine Learning
Romain Neuville, Jordan Bates, François Jonard
Remote Sensing (2021) Vol. 13, Iss. 3, pp. 352-352
Open Access | Times Cited: 104
Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series
Ben DeVries, Arun Kumar Pratihast, Jan Verbesselt, et al.
PLoS ONE (2016) Vol. 11, Iss. 3, pp. e0147121-e0147121
Open Access | Times Cited: 99
Monitoring Forest Change in the Amazon Using Multi-Temporal Remote Sensing Data and Machine Learning Classification on Google Earth Engine
Maria Antonia Brovelli, Yaru Sun, Vasil Yordanov
ISPRS International Journal of Geo-Information (2020) Vol. 9, Iss. 10, pp. 580-580
Open Access | Times Cited: 97
A spatial and temporal analysis of forest dynamics using Landsat time-series
Nguyễn Huy Trung, Simon Jones, Mariela Soto‐Berelov, et al.
Remote Sensing of Environment (2018) Vol. 217, pp. 461-475
Closed Access | Times Cited: 96
Assessing Climate Change Impact on Soil Salinity Dynamics between 1987–2017 in Arid Landscape Using Landsat TM, ETM+ and OLI Data
Abderrazak Bannari, Zahra M. Al-Ali
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2794-2794
Open Access | Times Cited: 94
Determining extreme heat vulnerability of Harare Metropolitan City using multispectral remote sensing and socio-economic data
Terence Darlington Mushore, Onisimo Mutanga, John Odindi, et al.
Journal of Spatial Science (2017) Vol. 63, Iss. 1, pp. 173-191
Closed Access | Times Cited: 92
Sentinel-2 Data in an Evaluation of the Impact of the Disturbances on Forest Vegetation
Josef Laštovička, Pavel Švec, Daniel Paluba, et al.
Remote Sensing (2020) Vol. 12, Iss. 12, pp. 1914-1914
Open Access | Times Cited: 90
Post-disturbance recovery of forest cover and tree height differ with management in Central Europe
Cornelius Senf, Jörg Müller, Rupert Seidl
Landscape Ecology (2019) Vol. 34, Iss. 12, pp. 2837-2850
Open Access | Times Cited: 89
Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches
Angela Lausch, Erik Borg, Jan Bumberger, et al.
Remote Sensing (2018) Vol. 10, Iss. 7, pp. 1120-1120
Open Access | Times Cited: 88
Estimating Forest Volume and Biomass and Their Changes Using Random Forests and Remotely Sensed Data
Jéssica Esteban, Ronald E. McRoberts, Alfredo Fernández-Landa, et al.
Remote Sensing (2019) Vol. 11, Iss. 16, pp. 1944-1944
Open Access | Times Cited: 88
Remote sensing techniques to assess post-fire vegetation recovery
Fernando Pérez, Raquel Montorio, Daniel Borini Alves
Current Opinion in Environmental Science & Health (2021) Vol. 21, pp. 100251-100251
Open Access | Times Cited: 80
Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
Andrew J. Lister, Hans Henrik Andersen, Tracey S. Frescino, et al.
Forests (2020) Vol. 11, Iss. 12, pp. 1364-1364
Open Access | Times Cited: 75
A Vision Transformer Model for Convolution-Free Multilabel Classification of Satellite Imagery in Deforestation Monitoring
Maria Kaselimi, Athanasios Voulodimos, Ioannis Daskalopoulos, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 34, Iss. 7, pp. 3299-3307
Open Access | Times Cited: 69
Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics
Angelo Nolè, Angelo Rita, Maria Floriana Spatola, et al.
The Science of The Total Environment (2022) Vol. 823, pp. 153807-153807
Closed Access | Times Cited: 44
Seeing the System from Above: The Use and Potential of Remote Sensing for Studying Ecosystem Dynamics
Cornelius Senf
Ecosystems (2022) Vol. 25, Iss. 8, pp. 1719-1737
Open Access | Times Cited: 42
Testing the Effect of Relative Pollen Productivity on the REVEALS Model: A Validated Reconstruction of Europe-Wide Holocene Vegetation
Maria Antonia Serge, Florence Mazier, Ralph Fyfe, et al.
Land (2023) Vol. 12, Iss. 5, pp. 986-986
Open Access | Times Cited: 26
Deforestation detection using a spatio-temporal deep learning approach with synthetic aperture radar and multispectral images
Jonathan V. Solórzano, Jean‐François Mas, J. Alberto Gallardo-Cruz, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 199, pp. 87-101
Closed Access | Times Cited: 25
Progress and Limitations in Forest Carbon Stock Estimation Using Remote Sensing Technologies: A Comprehensive Review
Weifeng Xu, Yu-Hao Cheng, Mengyuan Luo, et al.
Forests (2025) Vol. 16, Iss. 3, pp. 449-449
Open Access | Times Cited: 1
The application of geospatial techniques in monitoring karst vegetation recovery in southwest China
Chunhua Zhang, Xiangkun Qi, Kelin Wang, et al.
Progress in Physical Geography Earth and Environment (2017) Vol. 41, Iss. 4, pp. 450-477
Closed Access | Times Cited: 83
Boreal Shield forest disturbance and recovery trends using Landsat time series
Ryan J. Frazier, Nicholas C. Coops, Michael A. Wulder
Remote Sensing of Environment (2015) Vol. 170, pp. 317-327
Closed Access | Times Cited: 79
Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review
Manuela Hirschmugl, Heinz Gallaun, Matthias Dees, et al.
Current Forestry Reports (2017) Vol. 3, Iss. 1, pp. 32-45
Open Access | Times Cited: 77
Obtaining rubber plantation age information from very dense Landsat TM & ETM + time series data and pixel-based image compositing
Philip Beckschäfer
Remote Sensing of Environment (2017) Vol. 196, pp. 89-100
Closed Access | Times Cited: 76
Confirmation of post-harvest spectral recovery from Landsat time series using measures of forest cover and height derived from airborne laser scanning data
Joanne C. White, Ninni Saarinen, Ville Kankare, et al.
Remote Sensing of Environment (2018) Vol. 216, pp. 262-275
Open Access | Times Cited: 76
Quantifying the response of potential flooding risk to urban growth in Beijing
Yibing Wang, Xianhong Xie, Shunlin Liang, et al.
The Science of The Total Environment (2019) Vol. 705, pp. 135868-135868
Closed Access | Times Cited: 76
Historic flood events in NE Romania (post-1990)
Gheorghe Romanescu, Cătălin Ioan Cîmpianu, Alin Mihu‐Pintilie, et al.
Journal of Maps (2017) Vol. 13, Iss. 2, pp. 787-798
Open Access | Times Cited: 75

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