Traditional spectral classification of remotely sensed images applied on a pixel-by-pixel
basis ignores the potentially useful spatial information between the values of proximate …

Land cover is a critical variable in epidemiology and can be characterized remotely. A
framework is used to describe both the links between land cover and radiation recorded in a …

In geostatistics, spatial autocorrelation is utilized to estimate optimally local values from data
sampled elsewhere. The powerful synergy between geostatistics and remote sensing went …

Remote Sensing image analysis is mostly done using only spectral information on a pixel by
pixel basis. Information captured in neighbouring cells, or information about patterns …

The aim of this study was to develop an efficient and accurate procedure for classifying
Mediterranean land cover with remotely sensed data. Combinations of artificial neural …

To enable data collection by remote sensing instruments the Earth's continuously varying
surface is regularized into a grid of consistently sized and shaped pixels. Remotely sensed …

Semivariogram functions are compared to co-occurrence matrices for classification of digital
image texture, and accuracy is assessed using test sites. Images acquired over the following …

Geostatistically฀ based฀ methods฀ that฀ utilize฀ textural฀ information฀ are฀
frequently฀ used฀ to฀ analyze฀ remote฀ sensing฀(RS)฀ images.฀ The฀ role฀ of฀ …

La connaissance de la dynamique temporelle et de la répartition spatiale des phénomènes
naturels de suintement dans le Golfe du Mexique est fondamentale dans l'élaboration des …

Single and multiple band images are classified using supervised algorithms. Two programs,
MXTEXT and MXMULT, are presented that use minimum-distance-to-mean or Bayesian …