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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:

Assessing spring phenology of a temperate woodland: A multiscale comparison of ground, unmanned aerial vehicle and Landsat satellite observations
Elias Fernando Berra, Rachel Gaulton, Stuart Barr
Remote Sensing of Environment (2019) Vol. 223, pp. 229-242
Closed Access | Times Cited: 119

Showing 1-25 of 119 citing articles:

A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing
Sha Huang, Lina Tang, Joseph P. Hupy, et al.
Journal of Forestry Research (2020) Vol. 32, Iss. 1, pp. 1-6
Open Access | Times Cited: 1016
A review of vegetation phenological metrics extraction using time-series, multispectral satellite data
Linglin Zeng, Brian D. Wardlow, Daxiang Xiang, et al.
Remote Sensing of Environment (2019) Vol. 237, pp. 111511-111511
Closed Access | Times Cited: 600
Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities
Zheng Gong, Wenyan Ge, Jiaqi Guo, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 217, pp. 149-164
Closed Access | Times Cited: 28
Data and resolution requirements in mapping vegetation in spatially heterogeneous landscapes
Aleksi Räsänen, Tarmo Virtanen
Remote Sensing of Environment (2019) Vol. 230, pp. 111207-111207
Closed Access | Times Cited: 117
Remote sensing of temperate and boreal forest phenology: A review of progress, challenges and opportunities in the intercomparison of in-situ and satellite phenological metrics
Elias Fernando Berra, Rachel Gaulton
Forest Ecology and Management (2020) Vol. 480, pp. 118663-118663
Open Access | Times Cited: 99
Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework
Riccardo Dainelli, Piero Toscano, Salvatore Filippo Di Gennaro, et al.
Forests (2021) Vol. 12, Iss. 3, pp. 327-327
Open Access | Times Cited: 84
Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications
Riccardo Dainelli, Piero Toscano, Salvatore Filippo Di Gennaro, et al.
Forests (2021) Vol. 12, Iss. 4, pp. 397-397
Open Access | Times Cited: 84
Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions
Dominic Fawcett, Cinzia Panigada, Giulia Tagliabue, et al.
Remote Sensing (2020) Vol. 12, Iss. 3, pp. 514-514
Open Access | Times Cited: 80
DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection
Santiago Belda, Luca Pipia, Pablo Morcillo-Pallarés, et al.
Environmental Modelling & Software (2020) Vol. 127, pp. 104666-104666
Open Access | Times Cited: 80
Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations
Shengbiao Wu, Jing Wang, Zhengbing Yan, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 171, pp. 36-48
Open Access | Times Cited: 79
Low-cost UAV applications in dynamic tropical volcanic landforms
Sebastián Granados-Bolaños, Adolfo Quesada‐Román, Guillermo E. Alvarado
Journal of Volcanology and Geothermal Research (2020) Vol. 410, pp. 107143-107143
Closed Access | Times Cited: 77
UAVs as remote sensing platforms in plant ecology: review of applications and challenges
Zhongyu Sun, Xiaonian Wang, Zhihui Wang, et al.
Journal of Plant Ecology (2021) Vol. 14, Iss. 6, pp. 1003-1023
Closed Access | Times Cited: 74
Integrating spectral and textural information for identifying the tasseling date of summer maize using UAV based RGB images
Yahui Guo, Yongshuo H. Fu, Shouzhi Chen, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102435-102435
Open Access | Times Cited: 71
A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
Rabia Munsaf Khan, Bahram Salehi, Masoud Mahdianpari, et al.
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4347-4347
Open Access | Times Cited: 62
Validating GEDI tree canopy cover product across forest types using co-registered aerial LiDAR data
Xiao Li, Linyuan Li, Wenjian Ni, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 207, pp. 326-337
Closed Access | Times Cited: 12
Assessing urban vegetation inequalities: Methodological insights and evidence
Alicia González‐Marín, Marco Garrido‐Cumbrera
Ecological Informatics (2025), pp. 102987-102987
Open Access | Times Cited: 1
Multi-scale integration of satellite remote sensing improves characterization of dry-season green-up in an Amazon tropical evergreen forest
Jing Wang, Dedi Yang, Matteo Detto, et al.
Remote Sensing of Environment (2020) Vol. 246, pp. 111865-111865
Open Access | Times Cited: 69
Monitoring spring phenology of individual tree crowns using drone‐acquired NDVI data
Dominic Fawcett, Jonathan Bennie, Karen Anderson
Remote Sensing in Ecology and Conservation (2020) Vol. 7, Iss. 2, pp. 227-244
Open Access | Times Cited: 68
High‐throughput drone‐based remote sensing reliably tracks phenology in thousands of conifer seedlings
Petra D’Odorico, Ariana Besik, Christopher Y. S. Wong, et al.
New Phytologist (2020) Vol. 226, Iss. 6, pp. 1667-1681
Open Access | Times Cited: 62
Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites
Jakob J. Assmann, Isla H. Myers‐Smith, Jeffrey T. Kerby, et al.
Environmental Research Letters (2020) Vol. 15, Iss. 12, pp. 125002-125002
Open Access | Times Cited: 61
Assessing Forest Phenology: A Multi-Scale Comparison of Near-Surface (UAV, Spectral Reflectance Sensor, PhenoCam) and Satellite (MODIS, Sentinel-2) Remote Sensing
Shangharsha Thapa, Virginia García Millán, Lars Eklundh
Remote Sensing (2021) Vol. 13, Iss. 8, pp. 1597-1597
Open Access | Times Cited: 55
Monitoring Forest Phenology in a Changing World
Ross Gray, Robert M. Ewers
Forests (2021) Vol. 12, Iss. 3, pp. 297-297
Open Access | Times Cited: 49
Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach
Linyuan Li, Xihan Mu, Francesco Chianucci, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 107, pp. 102686-102686
Open Access | Times Cited: 35
How can UAV contribute in satellite-based Phragmites australis aboveground biomass estimating?
Lu Lirong, Juhua Luo, Yihao Xin, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 114, pp. 103024-103024
Open Access | Times Cited: 33
Evaluating fine-scale phenology from PlanetScope satellites with ground observations across temperate forests in eastern North America
Yingyi Zhao, Calvin K. F. Lee, Zhihui Wang, et al.
Remote Sensing of Environment (2022) Vol. 283, pp. 113310-113310
Closed Access | Times Cited: 31
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