A new land-cover match-based change detection for hyperspectral imagery

Land Cover Subpixel Change Detection using Hyperspectral Images Based on Spectral Unmixing and Post-processing

  The earth is continually being influenced by some actions such as flood, tornado and human artificial activities. This process causes the changes in land cover type. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Today’s remote sensing plays key role in geology and environmental monitoring by its high resolution, wide covering and low cost...

A New Dictionary Construction Method in Sparse Representation Techniques for Target Detection in Hyperspectral Imagery

Hyperspectral data in Remote Sensing which have been gathered with efficient spectral resolution (about 10 nanometer) contain a plethora of spectral bands (roughly 200 bands). Since precious information about the spectral features of target materials can be extracted from these data, they have been used exclusively in hyperspectral target detection. One of the problem associated with the detect...

Land Cover Change Detection Using Texture Analysis

Problem statement: It is an important task to detect land cover changes from remotely sensed data for environmental monitoring. Although there are some applications of visual textures to the land use, they are limited to a few land cover categories with the application of one texture measure. Since land cover types are complex and often the integration of various objects, applying one texture m...

Land cover change detection in northern Belarus

Study deals with the land cover dynamics analysis using remote sensing data over urban, suburban area in northern Belarus (Polotsk and Novopolotsk cities and surroundings) over the period 1994 – 2002. SPOT 3 and 5 images are used for the study. Land cover change detection is conducted using image differencing and post-classification comparison methods. Several classification methods are tested ...

Super-resolution land-cover mapping based on the selective endmember spectral mixture model in hyperspectral imagery