Remote sensing for pasture biomass quantity and quality assessment: Challenges and future prospects

IF 6.3 Q1 AGRICULTURAL ENGINEERING
Nicola Furnitto , Juan Miguel Ramírez-Cuesta , Diego S. Intrigliolo , Giuseppe Todde , Sabina Failla
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引用次数: 0

Abstract

Optimizing pasture use through careful management is critical to ensure the economic and environmental sustainability of pasture-based agriculture. Maximizing grass utilization and accurately measuring grass quantity and quality by adopting precision agriculture technologies, including estimates from satellite or unmanned aerial vehicles (UAVs), are key aspects to improve production efficiency and reducing environmental impact. With these goals, the review explores the crucial role of biomass quality and assessment estimation in pasture-based agricultural practices, with a focus on the potential offered by remote sensing technologies. This review examined recent advances in biomass and grassland quality assessment, highlighting the most widely used methodologies, remaining challenges and future prospects. The analysis focused particularly on applications of UAV and satellite platforms, discussing the advantages and limitations of the different techniques. Their and applications including machine learning (ML) technologies. A deep analysis of the main indices, electromagnetic regions and ML approaches utilized was also addressed, distinguishing among those intended to biomass quantity and quality assessment. Through the integration of innovative technologies and improved measurement protocols, the full potential of more sustainable and productive pasture-based agriculture can be realised, ensuring improved animal productivity and economic viability for farmers. These advances will pave the way for more effective management practices and contribute significantly to the global effort toward more sustainable agricultural systems.
牧草生物量数量与质量遥感评价:挑战与未来展望
通过精心管理优化牧场利用对于确保以牧场为基础的农业的经济和环境可持续性至关重要。通过采用精准农业技术(包括卫星或无人机估算),最大限度地提高草地利用率,准确测量草地的数量和质量,是提高生产效率和减少环境影响的关键方面。基于这些目标,本综述探讨了生物质质量和评估估算在基于牧场的农业实践中的关键作用,重点是遥感技术提供的潜力。本文审查了生物量和草地质量评估的最新进展,强调了最广泛使用的方法、仍然存在的挑战和未来前景。分析特别集中在无人机和卫星平台的应用上,讨论了不同技术的优点和局限性。它们的应用包括机器学习(ML)技术。深入分析了主要指标、电磁区域和使用的ML方法,并区分了用于生物量数量和质量评估的方法。通过整合创新技术和改进的测量方案,可以充分发挥更具可持续性和生产力的牧场农业的潜力,确保提高动物生产力和农民的经济生存能力。这些进展将为更有效的管理实践铺平道路,并为建立更可持续的农业系统的全球努力作出重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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