首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >REFLECTANCE FACTOR RETRIEVAL FROM LANDSAT TM AND SPOT HRV DATA FOR BRIGHT AND DARK TARGETS
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REFLECTANCE FACTOR RETRIEVAL FROM LANDSAT TM AND SPOT HRV DATA FOR BRIGHT AND DARK TARGETS

机译:从LANDSAT TM和SPOT HRV数据反演明暗目标

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In recent years, there have been many land-surface studies based on visible and near-infrared reflectance values retrieved from the Landsat Thematic Mapper (TM) and SPOT High Resolution. Visible (HRV) sensors. Retrieval of reflectance from. satellite sensor digital count requires knowledge of the atmospheric conditions and the sensor absolute calibration. In most cases, atmospheric conditions are simulated with a radiative transfer code and sensor calibration coefficients are obtained from preflight sensor calibrations or in-flight calibrations over bright surfaces (such as White Sands, New Mexico, USA, or La Crau, France). Though these procedures are well accepted, there have been few studies specifically designed to validate the accuracy of such reflectance factor retrievals (RFR) for both bright and dark targets. Data from two experiments conducted in an agricultural region in central Arizona were analyzed to quantify the accuracy of RFR from the Landsat TM and SPOT HRV sensors. These data included measurements made with groundbased and aircraft-based four-band radiometers and the NASA Advanced Solid-State Array Spectrometer (ASAS) aboard a C130 aircraft, and TM and HRV images acquired at nadir and off-nadir viewing angles. Results showed that the off-nadir reflectance factors measured using ground- and aircraft-based instruments, including ASAS, were comparable. The RFR from the satellite-based TM and HRV sensors generally resulted in an overestimation of dark target reflectance (up to 0.05 reflectance in the visible) and an underestimation of bright target reflectance (up to 0.1 reflectance in the near-infrared). Even greater error was possible when RFR was based on outdated sensor calibrations, particularly those conducted prelaunch. There was supporting evidence from studies at three sites (White Sands, New Mexico; Maricopa, Arizona; and Walnut Gulch, Arizona) that the Landsat-5 TM sensor sensitivity may have degraded by as much as 20% from the prelaunch calibration. Regarding the potential error in RFR related to recent changes in the processing of Landsat TM data (Level-0 and Level-1) by EOSAT Corporation, we found that the Level-0 data was slightly greater (similar to 2 digital counts) than the Level-1 data for all bands and all targets in our study. [References: 34]
机译:近年来,基于从Landsat专题制图仪(TM)和SPOT高分辨率获得的可见和近红外反射率值,进行了许多陆地表面研究。可见(HRV)传感器。从中检索反射率。卫星传感器的数字计数需要了解大气条件和传感器的绝对校准。在大多数情况下,使用辐射转移码模拟大气条件,并从飞行前传感器校准或在明亮表面(例如美国新墨西哥州的白沙或法国拉克鲁)的飞行中校准中获得传感器校准系数。尽管这些程序已被广泛接受,但很少有专门设计的研究来验证明亮目标和黑暗目标的反射系数检索(RFR)的准确性。分析了在亚利桑那州中部一个农业地区进行的两次实验的数据,以量化Landsat TM和SPOT HRV传感器对RFR的准确性。这些数据包括使用C130飞机上的地面和基于飞机的四波段辐射计以及NASA先进固态阵列光谱仪(ASAS)进行的测量,以及在天底和天底视角获得的TM和HRV图像。结果表明,使用包括ASAS在内的基于地面和基于飞机的仪器测得的离天底反射因子相当。基于卫星的TM和HRV传感器的RFR通常会导致暗目标反射率的高估(可见光中高达0.05的反射率)和明亮目标反射率的低估(近红外中高达0.1的反射率)。如果RFR基于过时的传感器校准,尤其是在启动前进行的校准,则可能会出现更大的误差。在三个地点(新墨西哥州的White Sands,亚利桑那州的Maricopa和亚利桑那州的Walnut Gulch)进行的研究提供的支持证据表明,Landsat-5 TM传感器的灵敏度可能比启动前的校准降低了20%。关于与EOSAT Corporation处理Landsat TM数据(Level-0和Level-1)的最新变化相关的RFR潜在错误,我们发现,Level-0数据略大于(类似于2个数字计数)研究中所有频段和所有目标的1级数据。 [参考:34]

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