Abstract
CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada, USA (38.504°N, 115.692°W). The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CAR’s land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol effects in the EO derived reflectances.
Highlights
Since the 1970s, EO (Earth-Observation) polar orbiter satellites for climate monitoring have increased in number and capabilities leading to a continuous improvement in terms of the accuracy and quality of measurements [1]
Even though MOD09 and MIAIC are based on the same input data (ToA reflectance of Terra/MODIS), MAIAC is more conservative in terms of cloud masking and quality assessment, which has resulted in fewer samples being compared to those of MOD09
The results presented in the previous section clearly show that the satellite-derived surface reflectance of MODIS, MISR, MERIS, and Landsat-7 are generally in agreement with the CAR data
Summary
Since the 1970s, EO (Earth-Observation) polar orbiter satellites for climate monitoring have increased in number and capabilities leading to a continuous improvement in terms of the accuracy and quality of measurements [1]. As satellite data cover much wider areas compared to Remote Sens. 2017, 9, 562 ground data, climate models of different ranges (short, medium) and areal coverage (global, land, ocean, atmosphere) are more and more dependent on EO satellite data [2]. These datasets have greatly increased in size and complexity. EO satellite data constitute the main input for most climate models [2].
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