Xiaoding Wang , Haitao Zeng , Xu Yang , Jiwu Shu , Qibin Wu , Youxiong Que , Xuechao Yang , Xun Yi , Ibrahim Khalil , Albert Y. Zomaya
{"title":"遥感技术革新农业:迈向新前沿","authors":"Xiaoding Wang , Haitao Zeng , Xu Yang , Jiwu Shu , Qibin Wu , Youxiong Que , Xuechao Yang , Xun Yi , Ibrahim Khalil , Albert Y. Zomaya","doi":"10.1016/j.future.2024.107691","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"166 ","pages":"Article 107691"},"PeriodicalIF":6.2000,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Remote sensing revolutionizing agriculture: Toward a new frontier\",\"authors\":\"Xiaoding Wang , Haitao Zeng , Xu Yang , Jiwu Shu , Qibin Wu , Youxiong Que , Xuechao Yang , Xun Yi , Ibrahim Khalil , Albert Y. Zomaya\",\"doi\":\"10.1016/j.future.2024.107691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":55132,\"journal\":{\"name\":\"Future Generation Computer Systems-The International Journal of Escience\",\"volume\":\"166 \",\"pages\":\"Article 107691\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-01-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Generation Computer Systems-The International Journal of Escience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167739X24006551\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X24006551","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
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.
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.