A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Hyperspectral remote sensing provides an efficient tool for ground classifications for large geographical areas. The advantages of this technology for municipal area classification are obvious due to the difficulty of access requirement associated with conventional surveying methods. Hyperspectal information has distinctive characteristics which requires proper procedures to be followed in order to achieve high accuracy and efficiency. This paper uses an example with municipal land cover classification to illustrate the procedures of analyzing hyperspectral remote sensing data. It also compares the performance of different pattern recognitions algorithm that is required for increasing the efficiency of hyperspectral information analyses.
Hyperspectral remote sensing provides an efficient tool for ground classifications for large geographical areas. The advantages of this technology for municipal area classification are obvious due to the difficulty of access requirement associated with conventional surveying methods. Hyperspectal information has distinctive characteristics which requires proper procedures to be followed in order to achieve high accuracy and efficiency. This paper uses an example with municipal land cover classification to illustrate the procedures of analyzing hyperspectral remote sensing data. It also compares the performance of different pattern recognitions algorithm that is required for increasing the efficiency of hyperspectral information analyses.
Hyperspectral Remote Sensing for Municipal Land Cover Classification
Yu, Xiong (author)
GeoCongress 2008 ; 2008 ; New Orleans, Louisiana, United States
GeoCongress 2008 ; 276-283
2008-03-07
Conference paper
Electronic Resource
English
Hyperspectral Remote Sensing for Municipal Land Cover Classification
| British Library Conference Proceedings | 2008
Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing
| Online Contents | 2009
Hyperspectral - Classification of Hyperspectral Remote Sensing Images With Support Vector Machines
| Online Contents | 2004
Sparse Graph Regularization for Hyperspectral Remote Sensing Image Classification
| Online Contents | 2017