Articles

• Comparative analysis of Landsat TM, ETM+, OLI and EO-1 ALI satellite images at the Tisza-tó area, Hungary

  53-62

  Loránd Szabó

  Márton Deák

  Szilárd Szabó

  Views:

  336

  Satellite images are important information sources of land cover analysis or land cover change monitoring. We used the sensors of four different spacecraft: TM, ETM+, OLI and ALI. We classified the study area using the Maximum Likelihood algorithm and used segmentation techniques for training area selection. We validated the results of all sensors to reveal which one produced the most accurate data. According to our study Landsat 8’s OLI performed the best (96.9%) followed by TM on Landsat 5 (96.2%) and ALI on EO-1 (94.8%) while Landsat 7’s ETM+ had the worst accuracy (86.3%).

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  61

• Correction of Atmospheric Haze of IRS-1C LISS-III Multispectral Satellite Imagery: An Empirical and Semi-Empirical Based Approach

  63-74

  Sheikh Mustak

  Naresh Baghmar

  Sudhir Singh

  Views:

  273

  The atmospheric effect greatly affects the quality of satellite data and mostly found in the polluted urban area in the great extent. In this paper, the atmospheric correction has been carried out on IRS-1C LISS-III multispectral satellite image for efficient results for the Raipur city, India. The atmospheric conditions during satellite data acquisition was very clear hence very clear relative scattering model of improved dark object subtraction method for the correction of atmospheric effects in the data has been carried out to produce the realistic results. The haze values (HV) for green band (band 2), red band (band 3), NIR band (band 4) and SWIR (band 5) are 79, 53, 54 and 124, respectively; were used for the corrections of haze effects using simple dark object subtraction method (SDOS). But the final predicted haze value (FPHV) for these bands are 79, 49.85, 21.31 and 0.13 that were used for the corrections of haze effects applying improved dark object subtraction method (IDOS). We found that IDOS method produces very realistic results when compared with SDOS method for urban land use mapping and change detection analysis. Consequently, ATCOR2 model provides better results when compared with SDOS and IDOS in the study.

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  0

• Boundless settlements – tendencies and future of urban sprawl in the agglomeration of Budapest

  75-88

  Zsuzsanna Illyés

  Éva Pádárné Török

  László Nádasy

  Zsófia Földi

  Vilja Vaszócsik

  Eszter Kató

  Views:

  212

  The Budapest agglomeration is a rapidly changing environment. Urban sprawl has been a prominent process in municipalities around the Hungarian capital, and its pace has significantly increased since the change of regimes. In our paper, we analyse the tendencies of urban development, the role of territorial protection and the types of land use mostly threatened by urban sprawl in two study areas within the Budapest agglomeration. A significant part of the Northern study area – located on Szentendre Island – is under territorial protection, while the Southern study area – located on Csepel Island – has a considerably lower amount of protected areas. We found that the settlements of the Northern study area have been expanding at a much slower pace than their Southern counterparts, where in the absence of effective restrictions, extensive areas – mostly former agricultural fields – have been converted into built-up areas. In addition, the Spatial Plan of the agglomeration allows the same tendencies to continue in both areas in the future as well.

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  39

• Analysis of multitemporal aerial images for fenyőfő Forest change detection

  89-100

  Shukhrat Shokirov

  Géza Király

  Views:

  237

  This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.

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