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Nieruchomości, Vol. 20, No. 1, Pp. 135-144. Bydłosz J., Parzych P., 2007, Ocena Możliwości Wykorzystania Danych Rejestru Cen I Wartości Nieruchomości Na Potrzeby Wyceny Nieruchomości (Assessment Of The Possibility To Use The Register Of Real Estate Price And Value Data For Property Valuation Purposes), Geomatics And Environmental Engineering, Vol. 1, No. 4, Pp. 31-40. Bydłosz J., Cichociński P., Parzych P., 2010, Możliwości Wykorzystania Danych Rejestru Cen I Wartości Nieruchomości Na Potrzeby Gospodarki Przestrzennej (Possibilities Of Using Data From The Register Of Real

. 20, No. 1, pp. 135-144. B ydłosz J., P arzych P., 2007, Ocena możliwości wykorzystania danych rejestru cen i wartości nieruchomości na potrzeby wyceny nieruchomości (Assessment of the Possibility to Use the Register of Real Estate Price and Value Data for Property Valuation Purposes) , Geomatics and Environmental Engineering, Vol. 1, No. 4, pp. 31-40. B ydłosz J., C ichociński P., P arzych P., 2010, Możliwości wykorzystania danych rejestru cen i wartości nieruchomości na potrzeby gospodarki przestrzennej (Possibilities of Using Data from the Register of Real

A., Meindl M., Mervart L., Rothacher M., Schaer S., Schmid R. Figurski M. (2007): System monitorowania sieci polskich stacji referencyjnych GPS, Magazyn geoinformacyjny Geodeta, nr 6, 7, 8 (145, 146, 147) Springer T., Steigenberger P., Svehla D., Thaller D., Urschl C., Weber R. (2006): Bernese GPS software version 5.0 Kenyeres.A, Figurski M., Legrand J., Bruyninx C., Kaminski P., Habrich H. Homogeneous Reprocessing of the EUREF Permanent Network: First Experiences and Comparisons, Bulletin of Geodesy and Geomatics, in press. (EUREF Symposium 2008 in Brussels

.03.025. Mikhail E.M., Bethel J., McGlone J.C., 2001. Introduction to modern photogrammetry . Wiley & Sons, Chichester. Nebiker S., Lack N., Deuber M., 2014. Building change detection from historical aerial photographs using dense image matching and object-based image analysis. Remote Sensing 6: 8310–8336. DOI 10.3390/rs6098310. Nex F., Remondino F., 2014. UAV for 3D mapping applications: A review. Applied Geomatics 6: 1–15 DOI 10.1007/s12518-013-0120-x. Osaci-Costache G., 1998. Evolutia orasului Curtea de Arges reflectata in documente cartografice (Evolution of Curtea de


During last years the need of knowing the forest in its various aspects, quantitative and qualitative, has enabled the appearance of a new technique forestry geomatics. Named as “the science of future” this technique integrates multiple technologies such as Remote Sensing, Airborne Photogrammetry, LIDAR, Geographic Information System (GIS), Global Positioning Systems (GPS) or classical geodetic technology for data acquisition, data processing, data analysis and data management. The purpose is to provide specific information regarding the evaluation natural forestry resources. In this paper will be presented the utilization of terrestrial 3D laser scanner and GIS technologies in forestry inventory.

A Bridge Deflection Monitoring with GPS

This paper introduces results of investigation carried on by The Applied Geomatics Section in Military University of Technology. Research includes possibilities of monitoring dynamic behavior of a bridge using high rate GPS data. Whole event was executed with collaboration of The Road and Bridge Management and The Warsaw Geodesy Company. Interdisciplinary approach with this project allows authors to get reliable information about investigating constructions and their respond for true traffic loading detected by GPS receivers. Way of compute data and used software (TRACK) are also shown in this paper.


The paper introduces the Special Section on the Hydrology of the Carpathians in this issue. It is the result of an initiative of the Department of Land and Water Resources Management of the Slovak University of Technology in Bratislava, the Institute of Hydraulic Engineering and Water Resources Management of the TU Vienna and the Institute of Geomatics and Civil Engineering of the University of Sopron to allow young hydrologists in the Carpathian Basin (and from outside) to present their research and re-network on the emerging topics of the hydrology of the Carpathians at the HydroCarpath Conferences since 2012.


Algeria loses more than 20,000 hectares of forest to fire every year. The losses are costly both in terms of life and property damage, which weighs heavily on the environment and the local economy. Geomatics can complement the conventional methods used in fire hazard prevention and management. The objective of our study is to use the geographic information system (GIS) and the Remote Sensing (RS) technology to develop the fire risk assessment map of the forest massif of Zelamta located in Southeast Mascara province (Northwest Algeria). The methodology employed was an empirical model involving three parameters that can control fire behaviour: geomorphology, vegetal cover combustibility, and human activity. The obtained results can help in the decision-making process as well as provide cartographic support for forest fire prevention and management.


The methods applied in Algeria for the prevention and fight against the fires remain fairly traditional and have proved to be ineffective in reducing the disastrous impact of this phenomenon. However, the aim of this work is to analyse a forest ecosystem that is fairly representative of the whole of the forests in Algeria, on plan risk and vulnerability of the environment for a better control of risk. Using modern geomatics techniques to map the degree of risk of fires and analysis the space: like satellite imagery spatial data and Geographic Information Systems (GIS).The Guetarnia forest in western Algeria has been retained; seven thematic maps have been developed and have helped to develop a sensitivity map to depict the fire risk.


. Knowledge of how land cover has changed over time improve assessments of the changes in the future. Wide availability of remote sensed data and relatively low cost of their acquisition make them very attractive data source for Geographical Information Systems (GIS). The main goal of this paper is to prepare, run and evaluate image classification using a block of raw aerial images obtained from Digital Mapping Camera (DMC). Classification was preceded by preparation of raw images. It contained geometric and radiometric correction of every image in block. Initial images processing lead to compensate their brightness differences. It was obtained by calculating two vegetation indices: Normalized Difference Vegetation Index (NDVI) and Green Normalized Vegetation Index (gNDVI). These vegetation indices were the foundation of image classification. PCI Geomatics Geomatica 10.2 and Microimages TNT Mips software platforms were used for this purpose.