OpenAlex Citation Counts

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:

Neutrons on Rails: Transregional Monitoring of Soil Moisture and Snow Water Equivalent
Martin Schrön, Sascha E. Oswald, Steffen Zacharias, et al.
Geophysical Research Letters (2021) Vol. 48, Iss. 24
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

COSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensors
Heye Bogena, Martin Schrön, Jannis Jakobi, et al.
Earth system science data (2022) Vol. 14, Iss. 3, pp. 1125-1151
Open Access | Times Cited: 82

Toward Large‐Scale Soil Moisture Monitoring Using Rail‐Based Cosmic Ray Neutron Sensing
Daniel Altdorff, Sascha E. Oswald, Steffen Zacharias, et al.
Water Resources Research (2023) Vol. 59, Iss. 3
Open Access | Times Cited: 22

Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture
Till Francke, Maik Heistermann, Markus Köhli, et al.
Geoscientific instrumentation, methods and data systems (2022) Vol. 11, Iss. 1, pp. 75-92
Open Access | Times Cited: 22

Comprehensive quality assessment of satellite- and model-based soil moisture products against the COSMOS network in Germany
Toni Schmidt, Martin Schrön, Zhan Li, et al.
Remote Sensing of Environment (2023) Vol. 301, pp. 113930-113930
Open Access | Times Cited: 14

Incoming Neutron Flux Corrections for Cosmic‐Ray Soil and Snow Sensors Using the Global Neutron Monitor Network
David McJannet, D. Desilets
Water Resources Research (2023) Vol. 59, Iss. 4
Open Access | Times Cited: 12

Technical Note: Revisiting the general calibration of cosmic-ray neutron sensors to estimate soil water content
Maik Heistermann, Till Francke, Martin Schrön, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 4, pp. 989-1000
Open Access | Times Cited: 4

Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach
Maik Heistermann, Heye Bogena, Till Francke, et al.
Earth system science data (2022) Vol. 14, Iss. 5, pp. 2501-2519
Open Access | Times Cited: 20

URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Markus Köhli, Martin Schrön, Steffen Zacharias, et al.
Geoscientific model development (2023) Vol. 16, Iss. 2, pp. 449-477
Open Access | Times Cited: 11

Probabilistic prediction by means of the propagation of response variable uncertainty through a Monte Carlo approach in regression random forest: Application to soil moisture regionalization
Ségolène Dega, Peter Dietrich, Martin Schrön, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 11

Signal contribution of distant areas to cosmic-ray neutron sensors – implications for footprint and sensitivity
Martin Schrön, Markus Köhli, Steffen Zacharias
Hydrology and earth system sciences (2023) Vol. 27, Iss. 3, pp. 723-738
Open Access | Times Cited: 9

Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany
Maik Heistermann, Till Francke, Lena Scheiffele, et al.
Earth system science data (2023) Vol. 15, Iss. 7, pp. 3243-3262
Open Access | Times Cited: 5

Following the cosmic-ray-neutron-sensing-based soil moisture under grassland and forest: Exploring the potential of optical and SAR remote sensing
Veronika Döpper, Thomas Jagdhuber, Ann-Kathrin Holtgrave, et al.
Science of Remote Sensing (2022) Vol. 5, pp. 100056-100056
Open Access | Times Cited: 9

First implementation of a new cross-disciplinary observation strategy for heavy precipitation events from formation to flooding
Andreas Wieser, Andreas Güntner, Peter Dietrich, et al.
Environmental Earth Sciences (2023) Vol. 82, Iss. 17
Open Access | Times Cited: 3

Solar Modulation Corrections for Cosmic-ray Soil and Snow Sensors Using the Global Neutron Monitor Network
David McJannet, Darin Desilets
(2022)
Open Access | Times Cited: 4

Water Leakage Pre-Localization in Drinking Water Networks via the Cosmic-Ray Neutron Sensing Technique
Luca Morselli, Federica Lorenzi, Andrea Basso, et al.
(2024) Vol. 4, pp. 157-157
Open Access

Depth extrapolation of field-scale soil moisture time series derived with cosmic-ray neutron sensing (CRNS) using the soil moisture analytical relationship (SMAR) model
Daniel Rasche, Theresa Blume, Andreas Güntner
SOIL (2024) Vol. 10, Iss. 2, pp. 655-677
Open Access

Mesoscale soil moisture measurements along the rover route using the mobile cosmic-ray neutron sensing in the eastern Tibetan Plateau
Yongyong Zhang, Shaoxiong Wu, Wenzhi Zhao, et al.
Geoderma (2024) Vol. 450, pp. 117046-117046
Open Access

Score filtering for contextualized noise suppression of Poisson‐distributed geophysical signals
Daniel Altdorff, Martin Schrön
Near Surface Geophysics (2024) Vol. 22, Iss. 6, pp. 599-616
Open Access

Hydrology on Solid Grounds? Integration Is Key to Closing Knowledge Gaps Concerning Landscape Subsurface Water Storage Dynamics
Sascha E. Oswald, Lisa Angermann, Heye Bogena, et al.
Hydrological Processes (2024) Vol. 38, Iss. 11
Open Access

On the combined use of static and mobile cosmic-ray neutron sensors for monitoring spatio-temporal variability of soil water content in cropped fields
Luca Morselli, Stefano Gianessi, R. Mazzoleni, et al.
(2023), pp. 243-247
Closed Access | Times Cited: 1

URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Markus Köhli, Martin Schrön, Steffen Zacharias, et al.
(2022)
Open Access | Times Cited: 1

Empirical analysis of machine learning-based moisture sensing platforms for agricultural applications: A statistical perspective
Neema Ukani, Saurabh S. Chakole
Journal of Physics Conference Series (2022) Vol. 2327, Iss. 1, pp. 012026-012026
Open Access | Times Cited: 1

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Requested Article:

Showing 1-25 of 59 citing articles:

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