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Dr. Paweł Netzel

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Guest Editor

Faculty of Forestry, University of Agriculture in Krakow, Krakow, Poland
Interests: GIS; big data; computer programming; mathematical modeling; artificial intelligence; spatial modelling; forestry

Special Issue Information

Dear Colleagues,

Sustainable forest development is a challenge in terms of both environmental protection and the economy. The forest’s ability to produce oxygen, collect carbon and provide ecosystems for many species is vital for global and local environmental protection. On the other hand, wood is still one of the essential resources of the economy. Maintaining the balance between forest protection and forest production is crucial to preserving forests.

Nowadays, foresters and researchers can apply many different technologies and solutions to model forest ecosystems and forest productivity. Geographic Information Systems (GIS) are one of these tools.

This Special Issue will contain original scientific papers focusing on the application of GIS in sustainable forest development. The submissions will cover topics including but not limited to:

Spatial modelling in forestry;
Web services and portals for forestry;
Spatial databases for forest modelling;
Data-mining methods in forest development;
AI models in GIS applied for forest modelling.

Dr. Paweł Netzel
Guest Editor

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Keywords

geographical information systems
forest development
forest protection
spatial databases
data-mining methods
adaptative systems
big data in forestry

Published Papers (1 paper)

Research

20 pages, 8725 KiB

Open AccessArticle

A Novel Method for Estimating Biomass and Carbon Sequestration in Tropical Rainforest Areas Based on Remote Sensing Imagery: A Case Study in the Kon Ha Nung Plateau, Vietnam

by Hoi Nguyen Dang, Duy Dinh Ba, Dung Ngo Trung and Hieu Nguyen Huu Viet

Sustainability 2022, 14(24), 16857; https://0-doi-org.brum.beds.ac.uk/10.3390/su142416857 - 15 Dec 2022

Cited by 3 | Viewed by 2028

Abstract

Forest ecosystems play a key role in sustaining life on this planet, given their functions in carbon storage, oxygen production, and the water cycle. To date, calculations of the biomass and carbon absorption capacity of forest ecosystems—especially tropical rainforests—have been quite limited, especially in Vietnam. By applying remote sensing materials, geographic information systems (GIS) facilitate the synchronized estimation of both biomass and ability of forest ecosystems to absorb carbon over large spatial ranges. In this study, we calculated the biomass of tropical rainforest vegetation in the Kon Ha Nung Plateau, Vietnam, according to four regression models based on Sentinel-2 satellite image data, forest reserve maps, and forest survey standard cell data (including 19 standard cells for 2016 and 44 standard cells for 2021). The results of the data comparison for the four biomass computing models (log-log, log-lin, lin-log, and lin-lin) demonstrated that the models with the highest accuracy were the lin-log model for 2016 (with a correlation coefficient of R² = 0.76) and the lin-log model for 2021 (with a correlation coefficient of R² = 0.765). Based on the analytical results and the selection of biomass estimation models, biomass maps were developed for the Kon Ha Nung Plateau area, Vietnam, in 2016 and 2021, with a predominant biomass value of 80–180 tons/ha (Mg/ha); furthermore, biomass fluctuations were analyzed for the period 2016–2021. Accordingly, the ability to absorb carbon and CO₂ equivalents in this research area for 2016 and 2021 was calculated based on the estimated biomass values. In summary, we present a method for estimating biomass via four basic linear regression models for tropical rainforest areas based on satellite image data. This method can serve as a basis for managers to calculate and synchronize the payment of carbon services, which contributes to promoting the livelihoods of local people. Full article

(This article belongs to the Special Issue Geographic Information System for Sustainable Forest Management)

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