{"title":"Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images","authors":"Hongyuan Yao, Yi Zhang","doi":"10.22434/ifamr1048","DOIUrl":null,"url":null,"abstract":"\nWith the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.","PeriodicalId":49187,"journal":{"name":"International Food and Agribusiness Management Review","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Food and Agribusiness Management Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.22434/ifamr1048","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 0
Abstract
With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.
随着农业生产现代化和城市化进程的加快,农业景观规划和生态平衡控制已成为促进可持续发展的重要问题。传统的农业生产方式存在资源浪费、环境污染、生态破坏等问题。本文旨在实现农业景观的科学规划与管理,促进农业生产效率的提高、资源的合理利用和生态环境的保护,从而推动农业的可持续发展。本研究首先关注农业遥感数据图像的去噪和特征提取,利用遥感技术获取农业景观信息。之后,采用人工智能技术实现农业景观的智能规划,目的是维护生态平衡,促进高效、生态友好和可持续的农业生产。本研究以某城市的景观为例,测试遥感图像的处理效果,结果证明效果良好。我们测试了基于遥感图像的智能农业景观规划和生态平衡控制系统的性能。根据实验结果可以得出结论:利用遥感图像技术的智能农业景观规划系统监测到的农田 A 的资源利用效率为 82%,而传统的仅为 60%。这表明遥感影像技术的采集效果远远优于传统技术。本文通过遥感图像技术对农田进行全面、及时的监测和评估,包括作物生长状况、土壤墒情、营养状况等。该系统可根据这些信息为农民提供精准的种植和管理建议,帮助他们优化农田布局、作物选择和灌溉管理,从而提高农田生产效率和作物产量。
期刊介绍:
The IFAMR is an internationally recognized catalyst for discussion and inquiry on issues related to the global food and agribusiness system. The journal provides an intellectual meeting place for industry executives, managers, scholars and practitioners interested in the effective management of agribusiness firms and organizations.
IFAMR publishes high quality, peer reviewed, scholarly articles on topics related to the practice of management in the food and agribusiness industry. The Journal provides managers, researchers and teachers a forum where they can publish and acquire research results, new ideas, applications of new knowledge, and discussions of issues important to the worldwide food and agribusiness system. The Review is published electronically on this website.
The core values of the Review are as follows: excellent academic contributions; fast, thorough, and detailed peer reviews; building human capital through the development of good writing skills in scholars and students; broad international representation among authors, editors, and reviewers; a showcase for IFAMA’s unique industry-scholar relationship, and a facilitator of international debate, networking, and research in agribusiness.
The Review welcomes scholarly articles on business, public policy, law and education pertaining to the global food system. Articles may be applied or theoretical, but must relevant to managers or management scholars studies, industry interviews, and book reviews are also welcome.