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使用合成孔径雷达 (SAR) 和连贯性变化检测监测秋季农业活动

Laura Dingle Robertson¹, Heather McNairn¹, Marco van der Kooij²

¹Agriculture and Agri-food Canada, Agri-Environment Division, Ottawa, Ontario, Canada.

|July 13, 2023

概括

卫星雷达成功地跟踪了农业领域的活动,如收获和耕作. 通过将Sentinel-1和RADARSAT星座任务 (RCM) 的数据结合起来,精确地确定了这些农业操作的时间.

科学领域:

农业遥感农业遥感
土壤科学土壤科学
环境监测环境监测环境监测

背景情况:

鼓励农民采用有利的管理实践 (BMP) 以保护环境.
监测BMP的采用,如保护性耕作,对于政策评估至关重要.
合成孔径雷达 (SAR) 提供全天候监测农业实践的能力.

研究的目的:

使用SAR数据调查连贯变化检测 (CCD) 来监测农业现场活动.
确定收获和耕作作业的时间.
评估将Sentinel-1和RADARSAT星座任务 (RCM) 数据用于精确监测农业活动的潜力.

主要方法:

获取了Sentinel-1和RCM图像的时间序列,这些图像位于加拿大伊利湖流域.
应用连贯变化检测 (CCD) 来分析16个图像对.
基于101个字段的现场观测的解释一致性值.
利用m-chi分解和体积/表面 (V/S) 比率进行RCM数据分析.

主要成果:

变化事件 (收获,耕作) 显著降低了连贯性值 (低于0.20).
在变化 (0.18 ± 0.03) 和不变 (0.42 ± 0.15) 字段之间,一致性值有显著差异.
CCD在收获和耕作之间进行区分,甚至在作物类型 (玉米与大豆) 之间进行区分.
综合SAR数据精确地确定了五天窗口内的玉米收获和四天窗口内的耕作.

结论:

连贯变化检测 (CCD) 有效地捕捉了秋季农业活动的变化.
SAR数据可以区分收获和耕作事件.
在虚拟星座中将多个SAR任务的数据结合起来,可以提高监测农业时间的精度.

关键词:

农业农业农业农业一致性变化检测检测收获的时间收获的时间雷达卫星星座任务雷达卫星这就是为什么SAR SAR SAR.哨兵一号 - 哨兵一号地地地地地地

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