Land-Use Land-Cover(LULC)mapping is an important issue in agriculture *** demand for improved and more accurate LULC mapping has led to a methodology known as object-based image analysis(OBIA).The focus of this thesis...
详细信息
Land-Use Land-Cover(LULC)mapping is an important issue in agriculture *** demand for improved and more accurate LULC mapping has led to a methodology known as object-based image analysis(OBIA).The focus of this thesis is about the design and implementation of new methods for object-based(OB)classification of hyperspectral remote sensing *** earth observation instruments collect these ***,in this thesis we investigate the integration of methods for object-based hyperspectral classification in synergic *** images mapping is a crucial step in environmental monitoring,disaster management,agriculture management and military *** recent researches to improved and accurate hyperspectral mapping have led to key methodology known as object-based classification of remotely sensed *** core intention of the OB images analysis is to group-of-pixels named "objects" through segmentation into a specific ***-oriented image analysis segments the data and constructs hierarchical network of homogeneous ***-based enable the analysis of aggregated sets of pixels,exploit shape-related variation,as well as spectral *** pixel-based classification methods always produce mixed pixel problems due to the independency of neighbor *** problem motivates researchers to combine segmentation,color and many other parameters to illuminate the wrongly classified or mixed pixels into their relevant *** the new methodology solved problems and improved accuracy,but it also raises new challenges such as the loss of accuracy in terms of less abundant,but potentially *** key challenges in hyperspectral images classification techniques are the high dimensionality of data,limited number of training samples,and combination of spatial and spectral *** recent years,availability of new remotely sensed data with high dimensions,spectral and spatial resolution rese
暂无评论