期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：2
页码：15727-15730
DOI：10.18535/ijecs/v5i2.11
出版社：IJECS
摘要：Extraction of linear features from Remote Sensing Image (RSI) has found many applications as in urban planning, disastermitigation and environmental monitoring. There were many previous studies in this field appreciating the significance ofstatistical operators to extract linear features. But in RSI domain, it has a different significance as it involve handling a large dataset of multiband data involving complexities in terms of spectral, spatial and temporal domain. Most of the objects in nature werenot easily discernable and extracted as they were often contaminated or mixed with other objects and might influence the spectralcharacter of the object. This may be less in urban environment as they exhibit more or less uniform spectral behavior where as innatural setting it may exhibit complex spectral behavior. Present study demonstrates such complexities in extracting linearfeatures in different setting – urban and coastal area – using first order derivative gradient filters
关键词：RSI; spectral; spatial; temporal; linear future
