scholarly journals Multi-Temporal Land-Cover Classification of Agricultural Areas in Two European Regions with High Resolution Spotlight TerraSAR-X Data

2011 ◽  
Vol 3 (5) ◽  
pp. 859-877 ◽  
Author(s):  
Damian Bargiel ◽  
Sylvia Herrmann
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Cover Classification ◽  
European Regions ◽  
Multi Temporal ◽  
Agricultural Areas

scholarly journals A Comparison of Two Morphological Techniques in the Classification of Urban Land Cover

2020 ◽  
Vol 12 (7) ◽  
pp. 1089
Author(s):  
Lesiba Thomas Tsoeleng ◽  
John Odindi ◽  
Paidamwoyo Mhangara
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Land Cover ◽  
Urban Areas ◽  
Land Cover Classification ◽  
Urban Land ◽  
Analysis Techniques ◽  
Urban Land Cover ◽  
Image Analysis Techniques

Understanding the often-heterogeneous land cover in urban areas is critical for, among other things, environmental monitoring, spatial planning, and enforcement. Recently, several earth observation satellites were developed with an enhanced spatial resolution that provides for precise and detailed representations of image objects. Morphological image analysis techniques provide useful tools for extracting spatial features from high-resolution, remotely sensed images. This study investigated the efficacy of mathematical morphological (MM) techniques in the land cover classification of a heterogeneous urban landscape using very high-resolution pan-sharpened Pleiades imagery. Specifically, the study evaluated two morphological profiles (MP) techniques (i.e., concatenation of morphological profiles (CMPs) and multi-morphological profiles (MMPs)) in the classification of a heterogeneous urban land cover. The overall accuracies for CMP were 83.14% and 83.19% over the two study areas. Similarly, the MMP overall accuracies were 84.42% and 84.08% for the two study sites. The study concluded that CMP and MMP can greatly improve the classification of heterogeneous landscapes that typify urban areas by effectively representing the structural landscape information necessary for discriminating related land cover classes. In general, similar and visually acceptable results were produced for land cover classification using either CMP or MMP image analysis techniques

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