Articolele autorului Herbei Mihai Valentin
Link la profilul stiintific al lui Herbei Mihai Valentin


Many applications in GIS are characterized by data network representing and analysis. Network analysis is based on linear structures. The fields where these types of analysis are used are different, such as: roads network, electric networks, hydrographic network and so on. For example, a hydrographic network is characterized by a one way direction (the water will flow in the same direction) with no return. Instead a road network can be crossed in

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Flood risk assessment in Timis River basin - the Caransebes -Lugoj sector- using GIS technique. Over time freshets, thus floods constituted and constitute a particularly important issue that requires attention. In many cases, flood damages are extensive to the environment, to the economy and also socially. The purpose of this paper is to identify flood-prone areas between Caransebes and Lugoj, land that is part of the Timis river basin. This paper

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Sisteme Informatice Geografice Aplicatii
Sisteme Informatice Geografice Fundamente teoretice si aplicatii
Using Mathematical Algorithms for Classification of LANDSAT 8 Satellite Images

Satellite and aerial images are objective photographical representations of the reality from the field, related to spatial – temporal frames. The purpose of the present study is to create a comparative analysis of a LANDSAT 8 satellite image by supervised and unsupervised classification methods. The algorithms used in this research were maximum likelihood algorithm for supervised classification and ISODATA algorithm for unsupervised classification.

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Relation of normalized difference vegetation index with some spectral bands of satellite images

The satellite image is the current graphic document, containing the real data of the terrestrial surface when it was acquired, based on which the soil and the vegetation cover can be evaluated. The NDVI index is used for a large number of the vegetation properties. In this research we analyzed the variation of NDVI index depending on R, G, B and NIR spectral bands, based on the LANDSAT 8 images. The relation between NDVI index with the respective

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