Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Individual Tree Basal Area Increment Models for Brazilian Pine (Araucaria angustifolia) Using Artificial Neural Networks
Lorena Oliveira Barbosa, Emanuel Arnoni Costa, Cristine Tagliapietra Schons, et al.
Forests (2022) Vol. 13, Iss. 7, pp. 1108-1108
Open Access | Times Cited: 10

Showing 10 citing articles:

Developing machine learning models with multiple environmental data to predict stand biomass in natural coniferous-broad leaved mixed forests in Jilin Province of China
Xiao He, Xiangdong Lei, Di Liu, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108162-108162
Closed Access | Times Cited: 8
Decision-Tree Application to Predict and Spatialize the Wood Productivity Probabilities of Eucalyptus Plantations
Clayton Alcarde Álvares, Ítalo Ramos Cegatta, Henrique Ferraço Scolforo, et al.
Forests (2023) Vol. 14, Iss. 7, pp. 1334-1334
Open Access | Times Cited: 7
Assessment of the forest seed material quality at the Scots pine (Pinus sylvestris L.) experimental site during adaptive restoration of forest landscapes
Tatyana Novikova
Forestry Engineering Journal (2023) Vol. 13, Iss. 1, pp. 112-128
Open Access | Times Cited: 5
Regional variability and determinants of tree growth in Araucaria angustifolia plantations
Gabriela Morais Olmedo, Leonardo Marques Urruth, Juliano Morales de Oliveira
Forest Ecology and Management (2024) Vol. 558, pp. 121795-121795
Closed Access | Times Cited: 1
Developing the Additive Systems of Stand Basal Area Model for Broad-Leaved Mixed Forests
Xijuan Zeng, Dongzhi Wang, Dongyan Zhang, et al.
Plants (2024) Vol. 13, Iss. 13, pp. 1758-1758
Open Access | Times Cited: 1
Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas
Pablo Casas-Gómez, J. F. Torres, Juan Carlos Linares, et al.
Ecological Informatics (2024), pp. 102951-102951
Open Access | Times Cited: 1
Enhancing Height Predictions of Brazilian Pine for Mixed, Uneven-Aged Forests Using Artificial Neural Networks
Emanuel Arnoni Costa, André Felipe Hess, César Augusto Guimarães Finger, et al.
Forests (2022) Vol. 13, Iss. 8, pp. 1284-1284
Open Access | Times Cited: 6
Estimation of tree height with machine learning techniques in coppice-originated pure sessile oak (Quercus petraea (Matt.) Liebl.) stands
Abbas ŞAHİN, Gafura Aylak Özdemir, Okan Oral, et al.
Scandinavian Journal of Forest Research (2023) Vol. 38, Iss. 1-2, pp. 87-96
Closed Access | Times Cited: 3
Modeling Height—Diameter Relationship Using Artificial Neural Networks for Durango Pine Species in Mexico
Yuduan Ou, Gerónimo Quiñonez-Barraza
(2023)
Open Access | Times Cited: 2
Caracterização morfofisiológica de <i>Araucaria angustifolia</i> (Bertol.) Kuntze para identificação de árvores matrizes
Vitória Campos Monteiro Pires, Cristiane Carvalho Guimarães, Thatiele Pereira Eufrazio de Moraes, et al.
Ciência Florestal (2024) Vol. 34, Iss. 4, pp. e68288-e68288
Open Access
Page 1

Scroll to top