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使用遥感和农业技术转移决策支持系统对作物现象学的评估

Naz Ul Amin¹, Fakhrul Islam^2,3,4, Muhammad Umar¹

¹Department of Meteorology, COMSATS University Islamabad (CUI), Park Road, Tarlai Kalan, Islamabad, 45550, Pakistan.

Scientific reports

|April 4, 2025

概括

这项研究将农业技术转让决策支持系统 (DSSAT) 与卫星遥感 (RS) 数据相结合,用于准确的作物监测. 综合方法有效估计叶面积指数 (LAI) 和生物质,帮助可持续农业.

科学领域:

农业科学农业科学
遥感遥感遥感遥感
作物建模作物建模

背景情况:

农业技术转让决策支持系统 (DSSAT) 是一个模拟作物生长和产量的全球平台.
将卫星遥感 (RS) 与作物模型集成,可以提高树冠状态变量的估计.
准确估计叶面积指数 (LAI) 和生物质对于农业管理和政策至关重要.

研究的目的:

将DSSAT与卫星RS数据集成,以更好地估计作物LAI和生物质.
为了校准和验证综合模型使用现场数据从Sheikhupura地区.
评估可持续农业的综合DSSAT-RS方法的性能和持久性.

主要方法:

使用中等分辨率成像光谱辐射仪 (MODIS) 产品 (LAI的MCD15A3H,生物质的MOD17A2/MOD17A3).
集成的DSSAT作物模型与卫星RS数据.
校准和验证模型使用现场数据从NARC谢赫胡普拉区 (2012-2014).

主要成果:

对于LAI (R2:0.82-0.90) 和生物质 (R2:0.92-0.99) 的DSSAT和RS衍生的估计值之间存在强烈一致.
高达成一致指数 (D指数:0.79-0.96) 证实了模型在不同农场和季节的耐用性.
来自RS数据的生物质估计显示由于光学RS和导致低估;CRM和nRMSE指标支持了这一方法.

结论:

通过将DSSAT与卫星RS数据集成,提供了一种可靠的方法来估计作物LAI和生物质.
该方法证明了耐用性和准确性,为农业决策提供了宝贵的见解.
通过这种综合方法增强的地理空间技术可以对可持续的农业实践作出重大贡献.

关键词:

农业技术农业技术农业技术这就是DSSAT.在GEEEE中,GEEEE是指GEEEE.巴基斯坦巴基斯坦巴基斯坦.谢赫胡普拉 (Sheikhupura) 是一个

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