The Role of Artificial Intelligence and Remote Sensing Technologies in Forest Ecosystems and Their Importance in Determining Carbon Capture Potential

Sümeyye Güler
{"title":"The Role of Artificial Intelligence and Remote Sensing Technologies in Forest Ecosystems and Their Importance in Determining Carbon Capture Potential","authors":"Sümeyye Güler","doi":"10.61326/silvaworld.v3i1.248","DOIUrl":null,"url":null,"abstract":"Climate change and global warming are among the most pressing environmental issues requiring urgent and adequate global action to protect future generations worldwide. One of the key approaches used to reduce CO2 emissions and mitigate the worst effects of climate change is carbon capture technologies. Carbon capture technologies have the potential to capture carbon from the atmosphere and convert it into fuels that can be used in environmentally friendly energy production. Innovative technologies can enhance carbon capture potential, which can play a significant role in combating climate change. Better understanding of mechanisms for capturing, storing, and releasing carbon from the atmosphere allows for more accurate assessments of carbon capture potentials. Scientists, industries, and policymakers are making significant efforts to explore new technologies to reduce greenhouse gas emissions and achieve net-zero emission goals. Development of new technologies involves complex processes and requires a digital system to optimize big data forecasting and reduce production time. Mathematical and statistical approaches play a crucial role in solving research problems, providing fast results and cost-effective tools for predicting large datasets. Effective policies for carbon capture and international cooperation can enhance carbon capture potential. New policies and collaboration models can incentivize investment in carbon capture projects, thereby increasing their potential. These new approaches can be used to better understand carbon capture potential and develop effective solutions to combat climate change. However, research in this field is still ongoing, and further research and development will be needed in the future.","PeriodicalId":485195,"journal":{"name":"SilvaWorld","volume":"56 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SilvaWorld","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.61326/silvaworld.v3i1.248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Climate change and global warming are among the most pressing environmental issues requiring urgent and adequate global action to protect future generations worldwide. One of the key approaches used to reduce CO2 emissions and mitigate the worst effects of climate change is carbon capture technologies. Carbon capture technologies have the potential to capture carbon from the atmosphere and convert it into fuels that can be used in environmentally friendly energy production. Innovative technologies can enhance carbon capture potential, which can play a significant role in combating climate change. Better understanding of mechanisms for capturing, storing, and releasing carbon from the atmosphere allows for more accurate assessments of carbon capture potentials. Scientists, industries, and policymakers are making significant efforts to explore new technologies to reduce greenhouse gas emissions and achieve net-zero emission goals. Development of new technologies involves complex processes and requires a digital system to optimize big data forecasting and reduce production time. Mathematical and statistical approaches play a crucial role in solving research problems, providing fast results and cost-effective tools for predicting large datasets. Effective policies for carbon capture and international cooperation can enhance carbon capture potential. New policies and collaboration models can incentivize investment in carbon capture projects, thereby increasing their potential. These new approaches can be used to better understand carbon capture potential and develop effective solutions to combat climate change. However, research in this field is still ongoing, and further research and development will be needed in the future.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
人工智能和遥感技术在森林生态系统中的作用及其对确定碳捕获潜力的重要性
气候变化和全球变暖是最紧迫的环境问题之一,需要采取紧急和充分的全球行动来保护全世界的子孙后代。碳捕集技术是减少二氧化碳排放和减轻气候变化最坏影响的关键方法之一。碳捕捉技术具有从大气中捕捉碳并将其转化为可用于环保能源生产的燃料的潜力。创新技术可以提高碳捕获潜力,从而在应对气候变化方面发挥重要作用。更好地了解从大气中捕获、储存和释放碳的机制,可以更准确地评估碳捕获潜力。科学家、工业界和政策制定者正在大力探索新技术,以减少温室气体排放,实现净零排放目标。新技术的开发涉及复杂的过程,需要一个数字化系统来优化大数据预测并缩短生产时间。数学和统计方法在解决研究问题方面发挥着至关重要的作用,可为预测大型数据集提供快速结果和具有成本效益的工具。有效的碳捕集政策和国际合作可提高碳捕集潜力。新的政策和合作模式可以激励对碳捕集项目的投资,从而提高其潜力。这些新方法可用于更好地了解碳捕集潜力,并制定应对气候变化的有效解决方案。不过,这一领域的研究仍在进行之中,未来还需要进一步的研究和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ecosystemic Alienation from the Perspective of Paraecology Assessment of Root-Shoot Ratio, Biomass, and Carbon Sequestration of Chestnut-leaved Oak Seedling (Quercus castaneifolia C. A. Mey) Stand Analysis and Distribution Areas of European Aspen (Populus tremula L.) Forests in Türkiye Criticism of the Effect of Green Cover Change on Air Quality with i-Tree Canopy (Bursa-Osmangazi Region Sample) The Role of Artificial Intelligence and Remote Sensing Technologies in Forest Ecosystems and Their Importance in Determining Carbon Capture Potential
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1