000			nab a22 7a 4500
999			_c62018 _d62010
001			62018
003			MX-TxCIM
005			20200608212939.0
008			200602s2010 ne ||||| |||| 00| 0 eng d
022			_a0034-4257
024	8		_ahttps://doi.org/10.1016/j.rse.2010.03.002
040			_aMX-TxCIM
041			_aeng
100	1		_913753 _aHagolle, O.
245	1	2	_aA multi-temporal method for cloud detection, applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images
260			_aAmsterdam (Netherlands) : _bElsevier, _c2010.
500			_aPeer review
520			_aOver lands, the cloud detection on remote sensing images is not an easy task, because of the frequent difficulty to distinguish clouds from the underlying landscape, even at a high resolution. Up to now, most high resolution images have been distributed without an associated cloud mask. This situation should change in the near future, thanks to two new satellite missions that will provide optical images combining 3 features: high spatial resolution, high revisit frequency and constant viewing angles. The VENµS (French and Israeli cooperation) mission should be launched in 2012 and the European SENTINEL-2 mission in 2013. Fortunately, two existing satellite missions, FORMOSAT-2 and LANDSAT, enable to simulate the future data of these sensors. Multi-temporal imagery at constant viewing angles provides a new way to discriminate clouded and unclouded pixels, using the relative stability of the earth surface reflectances compared to the quick variations of the reflectance of pixels affected by clouds. In this study, we have used time series of images from FORMOSAT-2 and LANDSAT to develop and test a Multi-Temporal Cloud Detection (MTCD) method. This algorithm combines a detection of a sudden increase of reflectance in the blue wavelength on a pixel by pixel basis, and a test of the linear correlation of pixel neighborhoods taken from couples of images acquired successively. MTCD cloud masks are compared with cloud cover assessments obtained from FORMOSAT-2 and LANDSAT data catalogs. The results show that the MTCD method provides a better discrimination of clouded and unclouded pixels than the usual methods based on thresholds applied to reflectances or reflectance ratios. This method will be used within VENµS level 2 processing and will be proposed for SENTINEL-2 level 2 processing.
546			_aText in English
650		7	_2AGROVOC _913754 _aClouds
650		7	_2AGROVOC _913755 _aVisibility
650		7	_2AGROVOC _912657 _aInfrared radiation
650		7	_2AGROVOC _91986 _aRemote sensing
700	1		_913756 _aHuc, M.
700	1		_913757 _aVilla Pascual, D.
700	1		_913758 _aDedieu, G.
773	0		_dAmsterdam (Netherlands) : Elsevier, 2010. _gv. 114, no. 8, p. 1747-1755 _tRemote Sensing of Environment _x0034-4257
942			_2ddc _cJA _n0