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As a greater amount of remotely sensed data becomes available, many of the applications will require the interpretation of images collected over a regular period (perhaps every day or every week) in order to identify changes associated with applications such as land-cover mapping, and environmental modelling and monitoring. Since these applications will require the transmission of significant numbers...
Hyperspectral imagery generally contains enormous amounts of data due to hundreds of spectral bands. Band selection is often adopted firstly to reduce computational cost and accelerate knowledge discovery of subsequent classificationand analysis. Recently, a new clustering algorithm, named "affinity propagation," is proposed. Different from the popular k-centers clustering technique, affinity...
Remotely sensed, high spatial resolution images have great potential in assisting vegetation management in power line corridor. With the wide use of object-based approaches in remote sensing image analysis, individual tree crown delineation becomes a key research focus to improve the accuracy of plant information extraction. Although many algorithms have been investigated for individual tree crown...
Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies...
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