用遥感评估水深变化和水养殖的评估
Rubén Simeón1, Constanza Rubio2, Antonio Uris2
1Centro Valenciano de Estudios sobre el Riego (CVER), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
在大米耕作期间使用近红外 (NIR) 波段的遥感可以预测产量. 水深与NIR反射率正相关,有助于灌管理和提高作物产量.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 农作物监测 农作物监测
背景情况:
- 传统上,大米种植涉及到洪水条件,因此需要清楚地了解水深对作物反射率和产量的影响.
- 在大米种植中,有效的水资源管理对于优化产量和资源利用至关重要.
研究的目的:
- 为了分析水深与Sentinel-2反射率数据在两个生长季节之间的相关性.
- 调查遥感的潜力,特别是近红外 (NIR) 频段,用于预测大米产量异常.
- 评估NIR异常作为最终收益率偏差指标的有用性.
主要方法:
- 在西班牙瓦伦西亚的商业大米田进行的实地研究,涉及两个生长季节 (2022年和2023年).
- 分析水深与Sentinel-2光谱带 (可见,NIR,SWIR) 和植被指数 (NDVI,GNDVI,NDRE,NDWI) 在耕地阶段之间的相关性.
- 计算和分析NIR异常,以评估它们与最终产量异常的关系.
主要成果:
- 水深与可见带有正相关性,与NIR和SWIR带有负相关性.
- 尼尔射线频段与水深有显著的相关性 (2022年的R2=0.69,2023年的R2=0.71).
- NIR异常有效地表明了收益率异常,具有与显著收益率偏差相关的特定值.
- 最终产量表现为对平均水位高达9厘米的水位的积极反应.
结论:
- 在大米耕种阶段的NIR频段是监测水深和预测产量的宝贵工具.
- 遥感数据,特别是NIR反射异常,可以显著支持农民优化水灌管理.
- 这种方法为提高用水效率和最大限度地提高大米产量提供了一个有希望的方法.
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