最优饲草种植带精准识别

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【科技日报】“AI+遥感”精准量化北方干旱流域饲草种植潜力
Ke Ji Ri Bao· 2025-09-30 01:20
"这项研究的创新之处在于,将饲草种植决策转化为一个多维度的空间优化问题,同时权衡'水资源消 耗、土壤固碳效益和饲草产能产出'。"论文通讯作者、空天院研究员王树东介绍,通过这一技术,系统 能自动生成"一张图",直观展示哪些地块最适合种植饲草、投入产出效益最高,极大方便了管理部门进 行精准决策和资源调配。 王树东表示,该技术体系成本低、可推广性强,不仅适用于黄河中游地区,未来也有望在内蒙古—宁夏 生态过渡带、河西走廊等典型干旱区落地,并对全球其他面临类似生态与农业挑战的地区,具有重要的 参考价值。 记者29日从中国科学院空天信息创新研究院(以下简称"空天院")获悉,该院研究团队成功研发出一套 融合人工智能与遥感技术的新方法,在我国北方干旱半干旱流域,首次实现了公里尺度上的"最优饲草 种植带"精准识别,为黄河流域生态保护与农牧业高质量发展提供了科学依据。相关成果发表于《水研 究》。 我国北方干旱半干旱地区,长期面临水资源短缺与保障粮草安全的双重压力。如何在保护生态的同时, 科学提升土地产能,一直是亟待解决的难题。传统评估方法往往依赖大量地面采样,且多侧重于单一指 标,难以实现精准、高效的区域规划。 为破解这一难题, ...
“AI+遥感”精准量化北方干旱流域饲草种植潜力
Ke Ji Ri Bao· 2025-09-29 05:57
Core Insights - The research team at the Chinese Academy of Sciences' Aerospace Information Innovation Research Institute has developed a new method that integrates artificial intelligence and remote sensing technology to identify optimal grass planting zones in northern China's arid and semi-arid regions, providing scientific support for ecological protection and high-quality agricultural development in the Yellow River basin [1][3] Group 1: Research and Methodology - The new method addresses the dual pressures of water resource scarcity and food security in northern China's arid regions, which have long struggled with ecological protection and land productivity enhancement [1] - Traditional assessment methods relied heavily on extensive ground sampling and focused on single indicators, making precise and efficient regional planning challenging [1] - The research team constructed a cross-data source integration framework that effectively combines satellite remote sensing, ecological hydrological models, and ground measurement data [1] - Advanced artificial intelligence techniques, such as ensemble learning, were employed to accurately reverse key indicators like irrigation water usage, vegetation productivity, and soil organic carbon, achieving a reversal accuracy exceeding 90% and eliminating over 40% of regional bias [1] Group 2: Practical Applications and Future Prospects - The system can automatically generate a visual representation indicating which plots are most suitable for grass planting and yield the highest input-output benefits, facilitating precise decision-making and resource allocation for management departments [3] - The technology is cost-effective and highly adaptable, not only applicable to the Yellow River middle reaches but also expected to be implemented in other typical arid areas such as the Inner Mongolia-Ningxia ecological transition zone and the Hexi Corridor [3] - The method holds significant reference value for other regions globally facing similar ecological and agricultural challenges [3]