遥感技术革新农业:迈向新前沿

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-01-06 DOI:10.1016/j.future.2024.107691
Xiaoding Wang , Haitao Zeng , Xu Yang , Jiwu Shu , Qibin Wu , Youxiong Que , Xuechao Yang , Xun Yi , Ibrahim Khalil , Albert Y. Zomaya
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引用次数: 0

摘要

遥感农业是利用遥感技术改善农业生产和作物管理的一种重要方法。在农业部门,RS允许检索与土地、植被和作物有关的大量数据,为农民和决策者提供关键信息,以提高作物种植和管理的精度和效率。RS和人工智能(AI)的结合在农业生产中具有巨大的潜力。随着人工智能的融合,遥感农业得到了扩展,其影响日益突出。预计将对全球农业产生深远影响,促进更高效、可持续、智能的发展。在农业领域,本文简要介绍了遥感技术的原理和应用,探讨了人工智能在促进农业遥感中的作用,总结了遥感与人工智能结合在农业领域的应用,并讨论了其效果。还讨论了人工智能与人工智能在农业领域的融合所带来的机遇和挑战。这一综述旨在加速进入RS赋能的农业新时代。
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Remote sensing revolutionizing agriculture: Toward a new frontier
Remote sensing-empowered agriculture is a significant approach that utilizes remote sensing (RS) to improve agricultural production and crop management. In the agricultural sector, RS allows the retrieval of extensive data related to land, vegetation, and crops, providing crucial information for farmers and decision-makers to enhance precision and efficiency in crop cultivation and management. The combination of RS and artificial intelligence (AI) holds tremendous potential for agricultural production. With the integration of AI, remote sensing-empowered agriculture has expanded, and its impact has become increasingly prominent. It is expected to have far-reaching effects on global agriculture, fostering the more efficient, sustainable, and intelligent development. In the agricultural field, this review presents a concise exploration of the principles and usage of RS. It also examines the role of AI in facilitating agricultural RS, summarizes the application of the combination of RS and AI in the field of agriculture, and discusses its effects. Opportunities and challenges arising from the integration of AI and AI in agriculture are also discussed. This review aims to accelerate the entry into a new era for agriculture empowered by RS.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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