Spatial high-resolution modelling and uncertainty assessment of forest growing stock volume based on remote sensing and environmental covariates-Reference-Cited by-同舟云学术

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Spatial high-resolution modelling and uncertainty assessment of forest growing stock volume based on remote sensing and environmental covariates

Published:2024-02 Issue: Volume:554 Page:121676
ISSN:0378-1127
Container-title:Forest Ecology and Management
language:en
Short-container-title:Forest Ecology and Management

Author:

Suleymanov Azamat,Bogdan Ekaterina,Gaysin Ildar,Volkov Alexander,Tuktarova Iren,Belan Larisa,Shagaliev Ruslan

Funder

Ministry of Education and Science of the Russian Federation

Publisher

Elsevier BV

Reference66 articles.

1. Ecosystem services of the cryogenic environments: identification, evaluation and monetisation - a review;Abakumov;J. Water Land Dev.,2022

2. Anuchin, N.P., 1982. Forest Taxation; Forestry Industry. Moscow. (In Russian).

3. Assessing and mapping changes in forest growing stock volume over time in bashkiriya Nature Reserve, Russia;Belan;Forests 13,2023

4. Modelling for forest growing stock assessment using satellite data — a case study;Benchalli;J. Indian Soc. Remote Sens,1998

5. The state of mountain forest ecosystems in the Bashkir Nature Reserve (Southern Urals);Biembetov;BIO Web Conf.,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forest growing stock volume mapping with accompanying uncertainty in heterogeneous landscapes using remote sensing data;Earth Science Informatics;2024-08-26

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