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タイトルAn evaluation of the signature extension approach to large area crop inventories utilizing space image data
本文(外部サイト)http://hdl.handle.net/2060/19780004553
著者(英)Nalepka, R. F.; Cicone, R. C.; Stinson, J. L.; Balon, R. J.
著者所属(英)Environmental Research Inst. of Michigan
発行日1977-11-01
言語eng
内容記述The author has identified the following significant results. Two examples of haze correction algorithms were tested: CROP-A and XSTAR. The CROP-A was tested in a unitemporal mode on data collected in 1973-74 over ten sample segments in Kansas. Because of the uniformly low level of haze present in these segments, no conclusion could be reached about CROP-A's ability to compensate for haze. It was noted, however, that in some cases CROP-A made serious errors which actually degraded classification performance. The haze correction algorithm XSTAR was tested in a multitemporal mode on 1975-76 LACIE sample segment data over 23 blind sites in Kansas and 18 sample segments in North Dakota, providing wide range of haze levels and other conditions for algorithm evaluation. It was found that this algorithm substantially improved signature extension classification accuracy when a sum-of-likelihoods classifier was used with an alien rejection threshold.
NASA分類EARTH RESOURCES AND REMOTE SENSING
レポートNO78N12496
NASA-CR-151552
ERIM-122700-33-F
E78-10016
権利No Copyright


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