satellite imagery was used as a rapid and spatially explicit method to delineate crop residue cover and to estimate the use and intensity of conservation tillage. the potential of multispectral high-spatial resolution of worldview-2 local data was evaluated using 11 satellite spectral indices and linear spectral unmixing analysis (lsua). experimental plots were examined; residue cover was measu...

This paper shows the potential of LIDAR for extracting buildings and other objects from medium resolution satellite imagery. To that end, the study integrated multispectral and LIDAR elevation data in a single imagery file and then classified it using the Support Vector Machine. To determine the method’s potential, the study used a SPOT5 satellite from an area situated southeast of Madrid, Spai...

An attempt has been made in this paper to classify multispectral images using customized particle swam optimization. To reduce the time consumption due to increase in dimensionality of multispectral imagery a preprocessing is done using feature extraction based on decision boundary. The customized particle swam optimization then works on the reduced multispectral imagery to find globally optima...

Digital imagery from satellites or multispectral and hyperspectral scanners is well accepted. Tremendous challenges are inherent in the development of a digital sensor to acquire imagery suitable for both high precision photogrammetric mapping and image processing for interpretative purposes. The performance of the film aerial camera is almost impossible to reach with current digital technology...

Giant Salvinia (Salvinia molesta) is one of the world’s most invasive aquatic weeds. We evaluated the accuracy of airborne multispectral digital video imagery for separating giant salvinia from other aquatic and terrestrial features at a study site located in northeast, Texas. The five-band multispectral digital video imagery was subjected to an unsupervised computer analysis to derive a themat...

We have developed an automated feature detection/classification system, called GENetic Imagery Exploitation (GENIE), which has been designed to generate image processing pipelines for a variety of feature detection/classification tasks. GENIE is a hybrid evolutionary algorithm that addresses the general problem of finding features of interest in multispectral remotely-sensed images. We describe...

Multispectral and hyperspectral imagery is used in a wide variety of remote sensing applications such as global environmental monitoring, mapping, charting and land use planning (Vaughn et al. 1995). The evolution of sensor technology has dramatically improved the quality of multispectral imagery through increase in spectral, spatial and radiometric resolutions of earth observations. This is ac...

Airborne pushbroom systems for the direct acquisition of digital imagery enable the simultaneous capture of high quality 3D and multispectral information of a scene. The combination of geometric and radiometric information should improve tasks like DTM generation – usually solely based on stereo imagery – and landuse classification, which is traditionally restricted to the interpretation of spe...

For the years 1997 to 2000 it is expected that a number of new satellites will be launched into orbit by private companies which are specified to deliver panchromatic imagery of the earth surface with a spatial resolution as fine as 1m. In contrast to the panchromatic band, the spectrally resolved bands will have a four times coarser ground resolution. Therefore, image fusion algorithms will be...

Multispectral images usually present complimentary information such as visual-band imagery and infrared imagery (near infrared or long wave infrared). There are strong evidences that the fused multispectral imagery (in gray scales) increases the reliability of interpretation (Rogers & Wood, 1990; Essock et al., 2001) and thus good for machine analysis (computer vision); whereas the colorized mu...