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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:

Biomass estimation of mixed forest landscape using a Fourier transform texture-based approach on very-high-resolution optical satellite imagery
Minerva Singh, Yadvinder Malhi, Shonil A. Bhagwat
International Journal of Remote Sensing (2014) Vol. 35, Iss. 9, pp. 3331-3349
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects
Lei Tian, Xiaocan Wu, Tao Yu, et al.
Forests (2023) Vol. 14, Iss. 6, pp. 1086-1086
Open Access | Times Cited: 78
A review of remote sensing applications for oil palm studies
Khai Loong Chong, Kasturi Devi Kanniah, Christine Pohl, et al.
Geo-spatial Information Science (2017) Vol. 20, Iss. 2, pp. 184-200
Open Access | Times Cited: 166
Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas
Timothy Dube, Onisimo Mutanga
ISPRS Journal of Photogrammetry and Remote Sensing (2015) Vol. 108, pp. 12-32
Closed Access | Times Cited: 146
Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them
Maxime Réjou‐Méchain, Nicolas Barbier, Pierre Couteron, et al.
Surveys in Geophysics (2019) Vol. 40, Iss. 4, pp. 881-911
Closed Access | Times Cited: 102
Potential of high-resolution ALOS–PALSAR mosaic texture for aboveground forest carbon tracking in tropical region
Rajesh Bahadur Thapa, Manabu Watanabe, Takeshi Motohka, et al.
Remote Sensing of Environment (2015) Vol. 160, pp. 122-133
Closed Access | Times Cited: 74
Toward a general tropical forest biomass prediction model from very high resolution optical satellite images
Pierre Ploton, Nicolas Barbier, Pierre Couteron, et al.
Remote Sensing of Environment (2017) Vol. 200, pp. 140-153
Open Access | Times Cited: 63
UAV-based canopy textures assess changes in forest structure from long-term degradation
Clément Bourgoin, Julie Betbeder, Pierre Couteron, et al.
Ecological Indicators (2020) Vol. 115, pp. 106386-106386
Open Access | Times Cited: 40
Forest Aboveground Biomass Estimation and Mapping through High-Resolution Optical Satellite Imagery—A Literature Review
Adeel Ahmad, Hammad Gilani, Sajid Rashid Ahmad
Forests (2021) Vol. 12, Iss. 7, pp. 914-914
Open Access | Times Cited: 39
Expert systems in oil palm precision agriculture: A decade systematic review
Xiao Jian Tan, Wai Loon Cheor, Kwok Shien Yeo, et al.
Journal of King Saud University - Computer and Information Sciences (2022) Vol. 34, Iss. 4, pp. 1569-1594
Open Access | Times Cited: 27
Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth
Minerva Singh, Damian Evans, Daniel A. Friess, et al.
Remote Sensing (2015) Vol. 7, Iss. 5, pp. 5057-5076
Open Access | Times Cited: 43
Mapping Aboveground Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China
Shili Meng, Yong Pang, Zhongjun Zhang, et al.
Remote Sensing (2016) Vol. 8, Iss. 3, pp. 230-230
Open Access | Times Cited: 42
Combining Kriging Interpolation to Improve the Accuracy of Forest Aboveground Biomass Estimation Using Remote Sensing Data
Zhenzhen Liu, Mingyang Li, Zhenzhen Liu, et al.
IEEE Access (2020) Vol. 8, pp. 128124-128139
Open Access | Times Cited: 36
A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing
Yali Zhang, Ni Wang, Yuliang Wang, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 12
Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests
Mui‐How Phua, Shazrul Azwan Johari, Ong Cieh Wong, et al.
Forest Ecology and Management (2017) Vol. 406, pp. 163-171
Open Access | Times Cited: 36
High-resolution mapping of forest parameters in tropical rainforests through AutoML integration of GEDI with Sentinel-1/2, Landsat 8 and ALOS-2 data
Bo Zhang, Li Zhang, Min Yan, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025) Vol. 18, pp. 9084-9118
Open Access
Inverting Aboveground Biomass–Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery
Sourabh Pargal, Rakesh Fararoda, G. Rajashekar, et al.
Remote Sensing (2017) Vol. 9, Iss. 3, pp. 228-228
Open Access | Times Cited: 24
Attenuating the bidirectional texture variation of satellite images of tropical forest canopies
Nicolas Barbier, Pierre Couteron
Remote Sensing of Environment (2015) Vol. 171, pp. 245-260
Closed Access | Times Cited: 20
Contrasting the potential of Fourier transformed ordination and gray level co-occurrence matrix textures to model a tropical swamp forest’s structural and diversity attributes
Jonathan V. Solórzano
Journal of Applied Remote Sensing (2018) Vol. 12, Iss. 03, pp. 1-1
Closed Access | Times Cited: 19
Improving estimation of forest aboveground biomass using Landsat 8 imagery by incorporating forest crown density as a dummy variable
Chao Li, Mingyang Li, Zhenzhen Liu
Canadian Journal of Forest Research (2019) Vol. 50, Iss. 4, pp. 390-398
Closed Access | Times Cited: 17
Estimation of Above Ground Biomass Using Texture Metrics Derived from IRS Cartosat-1 Panchromatic Data in Evergreen Forests of Western Ghats, India
R. Suraj Reddy, G. Rajashekar, C. S. Jha, et al.
Journal of the Indian Society of Remote Sensing (2016) Vol. 45, Iss. 4, pp. 657-665
Closed Access | Times Cited: 12
Estimation of Individual Tree Stem Biomass in an Uneven-Aged Structured Coniferous Forest Using Multispectral LiDAR Data
Nikos Georgopoulos, Ioannis Z. Gitas, Alexandra Stefanidou, et al.
Remote Sensing (2021) Vol. 13, Iss. 23, pp. 4827-4827
Open Access | Times Cited: 10
Mapping Spatiotemporal Changes in Forest Type and Aboveground Biomass from Landsat Long-Term Time-Series Analysis—A Case Study from Yaoluoping National Nature Reserve, Anhui Province of Eastern China
Boxiang Yang, Yali Zhang, Xupeng Mao, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2786-2786
Open Access | Times Cited: 7
Assessing Landscape Fragmentation Dynamics with Fourier Transforms
Ehsan Rahimi, Pinliang Dong
Journal of Landscape Ecology (2024) Vol. 17, Iss. 3, pp. 97-112
Open Access | Times Cited: 1
Linear vs non-linear learning methods A comparative study for forest above ground biomass, estimation from texture analysis of satellite images
Hippolyte Tapamo, Adamou Mfopou, Blaise Ngonmang, et al.
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées (2014) Vol. Volume 18, 2014
Open Access | Times Cited: 9
Comparative Analysis of Seasonal Landsat 8 Images for Forest Aboveground Biomass Estimation in a Subtropical Forest
Chao Li, Mingyang Li, Jie Liu, et al.
Forests (2019) Vol. 11, Iss. 1, pp. 45-45
Open Access | Times Cited: 8
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