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For a clustering algorithm, the number of clusters is a key parameter since it is directly related to the number of homogenous regions in the given image. Although ISODATA clustering algorithm can det...
Over the last couple of years more and more analogue airborne cameras were replaced by digital cameras. Digitally recorded image data show significant advantages to film based data. Digital aerial pho...
In the field of aerial/satellite remote sensing, the quality of data generated by remote sensing platforms is increasing at a significant rate and researches in image compression focus in two aspects:...
This paper reports on research analysing the potential of Support Vector Machines (SVMs) for mapping vegetation from high spatial resolution Ikonos imagery. The work investigated the utility of SVMs f...
Sub-pixel based digital image classification outputs from coarse spatial resolution remote sensing images can be closer to ground information as compared to hard classification outputs. This hasbeen p...
Wetlands are considered an integral part of the global ecosystem, the development of the remote sensing technology makes us obtain very abundant information of wetlands, especially with the appearance...
Classification is an open, old and basic problem in many domains. Recently, a lot of new methods come forth, such as Bayesian Networks. Bayesian Networks, one of probabilistic networks, are a powerful...
Compared with the traditional remote sensing image processing system based on pixel, there are some unique characters in the object-based classification: various operations on objects; variety of obje...
Information extraction from Hyperspectral imagery is highly affected by difficulties in accounting for flux density variation and Bidirectional reflectance effects. Calculation of flux density require...
Thee rapid advances in hyperspectral sensing technology have made it possible to collect remote sensing data in hundreds of bands. However, the data analysis methods which have been successfully appli...
The high-dimensional feature vectors of hyper spectral data often impose a high computational cost as well as the risk of "over fitting" when classification is performed. Therefore it is necessary to ...
In the paper, a novel method for high spatial remote sensing data classification was put forward. The method was based on fuzzy set theory combined with NDVI. The classification experiments were carri...
The most significant breakthrough in remote sensing has been the development of hyperspectral sensors. Due to the spectral resolution limitations of conventional multispectral remote sensing, hyperspe...
This study focus on the characterization of hydrocarbon microseepages in the northern Tucano Basin (Bahia State, Brazil), using geostatistical analysis of regional hydrocarbon geochemical data yielded...
The Mount Cameroon forests risk being disappeared. This threat results from aspects such as lava destruction, the creation of vast plantations, farms and extension of settlements. Being 4095m high fac...

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