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Comparison of ERS-2 SAR and landsat TM imagery for monitoring agricultural crop and soil conditions

机译:ERS-2 SAR和Landat TM影像用于监测农作物和土壤状况的比较

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Studies over the past 25 years have shown that measurements of surface reflectance and temperature (termed optical remote sensing) are useful for monitoring crop and soil conditions. Far less attention has been given to the use of radar imagery, even though synthetic aperture radar (SAR) systems have the advantages of cloud penetration, all-weather coverage, high spatial resolution, dayight acquisitions, and signal independence of the solar illumination angle. In this study, we obtained coincident optical and SAR images of an agricultural area to investigate the use of SAR imagery for farm management. The optical and SAR data were normalized to indices ranging front 0 to 1 based on the meteorological conditions and sun/sensor geometry for each date to allow temporal analysis. Using optical images to interpret the response of SAR backscaner (σ{sup}0) to soil and plant conditions, we found that SAR σ{sup}0 was sensitive to variations in field tillage, surface soil moisture, vegetation density, and plant litter. In an investigation of the relation between SAR σ{sup}0 and soil surface roughness, the optical data were used for two purposes: (1) to filter the SAR images to eliminate fields with substantial vegetation cover and/or high surface soil moisture conditions, and (2) to evaluate the results of the investigation. For dry, bare soil fields, there was a significant correlation (r{sup}2 = .67) between normalized SAR σ{sup}0 and near-infrared (NIR) reflectance, due to the sensitivity of both measurements to surface roughness. Recognizing the limitations of optical remote sensing data due to cloud interference and atmospheric attenuation, the findings of this study encourage further studies of SAR imagery for crop and soil assessment.
机译:过去25年的研究表明,表面反射率和温度的测量(称为光学遥感)可用于监测作物和土壤状况。尽管合成孔径雷达(SAR)系统具有云穿透,全天候覆盖,高空间分辨率,昼/夜采集和太阳照度信号独立性的优点,但对雷达图像的使用却很少受到关注。角度。在这项研究中,我们获得了农业地区的光学和SAR图像,以调查SAR图像在农场管理中的应用。根据气象条件和每个日期的太阳/传感器几何形状,将光学和SAR数据归一化为0到1范围内的索引,以便进行时间分析。使用光学图像解释SAR反向扫描器(σ{sup} 0)对土壤和植物条件的响应,我们发现SARσ{sup} 0对田间耕作,地表土壤水分,植被密度和植物凋落物的变化敏感。 。在研究SARσ{sup} 0与土壤表面粗糙度之间的关系时,光学数据用于两个目的:(1)过滤SAR图像以消除具有大量植被覆盖和/或高土壤水分条件的田野,以及(2)评估调查结果。对于干燥,裸露的土壤田地,归因于两次测量对表面粗糙度的敏感性,归一化SARσ{sup} 0和近红外(NIR)反射率之间存在显着相关性(r {sup} 2 = .67)。认识到由于云干扰和大气衰减造成的光学遥感数据的局限性,这项研究的结果鼓励对用于作物和土壤评估的SAR图像进行进一步研究。

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