Effects on Carbon Sources and Sinks from Conversion of Over-Mature Forest to Major Secondary Forests and Korean Pine Plantation in Northeast China

Wu, Bin; Mu, Changcheng; Zhao, Jiaqi; Zhou, Xuejiao; Zhang, Junhui

doi:10.3390/su11154232

Cited by 9 publications

(2 citation statements)

References 90 publications

(120 reference statements)

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“…All the fire experiments were conducted in the same location. In order to ensure the applicability of the proposed model in different scenarios, we collected a variety of combustibles representative of Northeast China, such as conifer, camphor pine, and poplar leaves [44], for experiments. Moreover, we arranged different laying factors, such as the combustible load and bed depth, to simulate diverse environmental variables present during the actual forest fire spread [45].…”

Section: Small-scale Ground Fire Experimentsmentioning

confidence: 99%

Predicting the Continuous Spatiotemporal State of Ground Fire Based on the Expended LSTM Model with Self-Attention Mechanisms

Wang

Zhang

et al. 2023

Fire

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Fire spread prediction is a crucial technology for fighting forest fires. Most existing fire spread models focus on making predictions after a specific time, and their predicted performance decreases rapidly in continuous prediction due to error accumulation when using the recursive method. Given that fire spread is a dynamic spatiotemporal process, this study proposes an expanded neural network of long short-term memory based on self-attention (SA-EX-LSTM) to address this issue. The proposed model predicted the combustion image sequence based on wind characteristics. It had two detailed feature transfer paths, temporal memory flow and spatiotemporal memory flow, which assisted the model in learning complete historical fire features as well as possible. Furthermore, self-attention mechanisms were integrated into the model’s forgetting gates, enabling the model to select the important features associated with the increase in fire spread from massive historical fire features. Datasets for model training and testing were derived from nine experimental ground fires. Compared with the state-of-the-art spatiotemporal prediction models, SA-EX-LSTM consistently exhibited the highest predicted performance and stability throughout the continuous prediction process. The experimental results in this paper have the potential to positively impact the application of spatiotemporal prediction models and UAV-based methods in the field of fire spread prediction.

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Section: Small-scale Ground Fire Experimentsmentioning

confidence: 99%

Predicting the Continuous Spatiotemporal State of Ground Fire Based on the Expended LSTM Model with Self-Attention Mechanisms

Wang

Zhang

et al. 2023

Fire

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show abstract

“…If this occurs, the impact on the global climate is predicted to be catastrophic (Wang & Song, 2020). Therefore, it is crucial to increase and manage the carbon (C) sink capacity of terrestrial ecosystems, which could effectively help to mitigate the increased CO 2 concentration in the atmosphere (Pragasan, 2022; Wu et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

Carbon neutrality of an island with 100% renewable energy production and forest as carbon sinks: El Hierro (Canary Islands) a pilot for Europe

Cruz‐Pérez,

Grūbe,

Ruiz‐Peinado

et al. 2024

Soil Use and Management

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The island of El Hierro is the smallest and youngest island in the Canary archipelago. It has been recognized as a UNESCO Biosphere Reserve since 2000, and it has a population of approximately 10,000 inhabitants. The aim of this study was to determine the amount of CO2 emissions absorbed by the forest stands of the island of El Hierro and compare it to the emissions generated by the population. It is noteworthy that there is a hydro‐wind energy production project on the island that has significantly minimized the emissions linked to energy production. In short, El Hierro's forest stands are capable of capturing 46,785 tons of CO2 annually, while emissions associated with electricity production and emissions linked to road mobility are below the island's carbon sequestration capacity since the Gorona del Viento renewable energy project was built. By working on investment in renewable energies to produce energy and changing mobility with the use of electric vehicles, a small island like El Hierro can adapt to ecological transition by the year 2040. This is a goal set by the government to drastically reduce emissions in the Canary Islands.

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Carbon Dioxide Fluxes of an Urban Forest in Moscow

et al. 2021

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Effects on Carbon Sources and Sinks from Conversion of Over-Mature Forest to Major Secondary Forests and Korean Pine Plantation in Northeast China

Cited by 9 publications

References 90 publications

Predicting the Continuous Spatiotemporal State of Ground Fire Based on the Expended LSTM Model with Self-Attention Mechanisms

Predicting the Continuous Spatiotemporal State of Ground Fire Based on the Expended LSTM Model with Self-Attention Mechanisms

Carbon neutrality of an island with 100% renewable energy production and forest as carbon sinks: El Hierro (Canary Islands) a pilot for Europe

Carbon Dioxide Fluxes of an Urban Forest in Moscow

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