There is abundant evidence that thematic map accuracy may vary across a landscape in a manner that is only partially related to land cover type. Spatial variation in accuracy may be attributable to factors such as terrain, landscape complexity, and land use patterns. There may be serious consequences in the construction and application of thematic maps when the pattern and degree of spatial var...

In this paper, a new multispectral image wavelet representation is introduced, based on multiscale fundamental forms. This representation describes gradient information of multispectral images in a multiresolution framework. The representation is in particular extremely suited for the fusion and merging of multispectral images. For fusion as well as for merging, a strategy is described. Experim...

Semivariogram functions are compared to cooccurrence matrices for classification of digital image texture, and accuracy is assessed using test sites. Images acquired over the following six different spectral bands are used: 1) SPOT HRV, near infrared; 2) Landsat thematic mapper (TM), visible red; 3) India Remote Sensing (IRS) LISS-II, visible green; 4) Magellan, Venus, S-band microwave; 5) shut...

Statistical learning algorithms for identifying contrasting tillage practices with Landsat Thematic Mapper data Pijush Samui a , Prasanna H. Gowda b , Thomas Oommen c , Terry A. Howell b , Thomas H. Marek d & Dana O. Porter e a Centre for Disaster Mitigation and Management, VIT University, Vellore, Tamil Nadu, 632014, India b Conservation and Production Research Laboratory, USDA-ARS, Bushland, ...

This study promotes the use of a multiclassifier system (MCS) fed with high-resolution remote sensing data coupled with contextual and textural data in the domain of land cover and land use classification. The gain of this approach is shown by a favorable comparison of our BAGFS classifier (a mixture of bagging and feature subset classifier) over two single classifier techniques (5-NN and C4.5 ...

This paper presents the applicability of combined Landsat Thematic Mapper and European Remote Sensing 2 synthetic aperture radar (SAR) data to turbidity, Secchi disk depth, and suspended sediment concentration retrievals in the Gulf of Finland. The results show that the estimated accuracy of these water quality variables using a neural network is much higher than the accuracy using simple and m...

The objectives of this study were (a) to evaluate the suitability of SAR imagery for discriminating savanna physiognomies, (b) to combine SAR and optical imagery for achieving improved accuracy, and (c) to develop a hybrid approach based on pixels and objects to characterize gradients of vegetation density. We used imagery from the Phased Array L-band Synthetic Aperture Radar (PALSAR), as well ...

In this letter, a technique for mapping the thermal infrared radiation variation within land cover using both a classification map and a thermal infrared image is proposed. Furthermore, a technique to effectively calculate the average thermal radiance for each land cover from Thematic Mapper (TM)-type sensors, which aquire high resolution of visible and near-infrared images and low resolution o...

In this paper, a new multispectral image wavelet representation is introduced, based on multiscale fundamental forms. This representation describes gradient information of multispectral images in a multiresolution framework. The representation is in particular extremely suited for the fusion and merging of multispectral images. For fusion as well as for merging, a strategy is described. Experim...