nowadays, remote sensing comes under the title of management method for precision farming. for provision of the land cover and therefore land use map use must be made of satellite images. for an assessment of the type of agricultural crops it is required to have satellite images of high resolution. from specifications of the satellite images one is to produce maps with varied scales. in this re...

forest classification on the basis of satellite images is a promising technique both for primary map production and for map updating and forest monitoring. for accurate for-est classification into three classes, using mapping by canopy cover density “high spatial resolution satellite images have to be used in order to obtain the required spatial detail” [schneider, 1999]. at the same time, the ...

Automatic identification and localization of cartographic objects in aerial and satellite images have gained increasing attention in recent years in digital photogrammetry and remote sensing. Although the automatic extraction of man made objects in essence is still an unresolved issue, the man made objects can be extracted from aerial photos and satellite images. Recently, the high-resolution s...

This paper presents an unsupervised method to segment multispectral images, involving a correlated non-Gaussian noise. The efficiency of the Markovian quadtree-based method we propose will be illustrated on a satellite image segmentation task with multispectral observations, in order to update nautical charts. The proposed method relies on a hierarchical Markovian modeling and includes the esti...

Multispectral images such as multispectral chemical images or multispectral satellite images provide detailed data with information in both the spatial and spectral domains. Many segmentation methods for multispectral images are based on a per-pixel classification, which uses only spectral information and ignores spatial information. A clustering algorithm based on both spectral and spatial inf...

On board of Quickbird satellite two types of sensors are present: panchromatic and multispectral. The first acquires earth images within spectral range 0.405 μm – 1.053 μm; the second acquires simultaneously four images of the same scene, each of them within shorter range of spectrum (Blue, Green, Red, Near-Infrared). Panchromatic images present geometric resolution 0.60 m while multispectral o...

We investigated the Classification of satellite images and multispectral remote sensing data .we focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area and green area. We carried out classification in three modules namely (a) Preprocess...