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1.

001-es BibID:BIBFORM053193
Első szerző:Kovács Zoltán (geográfus)
Cím:Tetőtípusok azonosítása hiperspektrális felvételek alapján / Kovács Zoltán, Szabó Szilárd, Burai Péter, Szabó Gergely
Dátum:2014
Megjegyzések:Based on a high ground and spectral resolution imagery, our goal was to identify different rooftypes applying an MS Excel add-in (Hyperspectral Data Analyst) developed by the Department of Physical Geography and Geoinformatics, University of Debrecen. Roofs were detected by using multi-resolution segmentation algorithm on a combinied a normalized Digital Surface Model and NDVI image. In this study case Hyperspectral Data Analyst add-in pointed out some wavelength pairs, where the largest difference can be observed between certain roof type categories.
ISBN:978-963-318-434-9
Tárgyszavak:Természettudományok Földtudományok előadáskivonat
Hiperspektrális adatok
MS Excel
Megjelenés:Az elmélet és gyakorlat találkozása a térinformatikában V. : Térinformatikai konferencia és szakkiállítás 2014 / szerk. Balázs Boglárka. - p. 181-187. -
További szerzők:Szabó Szilárd (1974-) (geográfus) Burai Péter (1977-) (agrármérnök) Szabó Gergely (1975-) (geográfus)
Pályázati támogatás:TÁMOP-4.2.2.A-11/1/KONV-2012-0041
TÁMOP
TÁMOP 4.2.4.A/2-11-1-2012-0001
TÁMOP
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
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2.

001-es BibID:BIBFORM071307
Első szerző:Szabó Gergely (geográfus)
Cím:Zooming on Aerial Survey / Gergely Szabó, László Bertalan, Norbert Barkóczi, Zoltán Kovács, Péter Burai, Csaba Lénárt
Dátum:2018
Megjegyzések:The aim of this chapter is to provide a general overview about the main components of a developed UAS mapping system, the survey, and processing procedure. At frst (4.1), a brief introduction is given about basic operational elements and accessories of UAS. Then, recent camera/sensor technologies allowing various survey solutions are going to be discussed. Once these hardware components are presented, the detailed work?ow of a basic UAV-based mapping procedure is described (4.2). A further discussion focuses not only on the analytical or planning phases but also on providing useful information on the operational and processing parts as well (4.3). Then, there comes image acquisition and project planning (4.4). The photogrammetry-based image processing requires detailed expertise and attention; Sect. 4.5 maybe helpful to avoid potential mistakes. The last section (4.6) summarizes some aspects of the use of LiDAR technologies in UAV-based survey
ISBN:978-3-319-66576-4
Tárgyszavak:Természettudományok Földtudományok könyvfejezet
aerial survey
drone
UAV
Photogrammetry
Megjelenés:Small Flying Drones: Applications for Geographic Observation / ed. Gianluca Casagrande, András Sik, Gergely Szabó. - p. 91-126. -
További szerzők:Bertalan László (1989-) (geográfus) Barkóczi Norbert (1990-) (geográfus) Kovács Zoltán (1988-) (geográfus) Burai Péter (1977-) (agrármérnök) Lénárt Csaba (1969-) (agrármérnök)
Internet cím:DOI
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3.

001-es BibID:BIBFORM062880
Első szerző:Szabó Szilárd (geográfus)
Cím:Automated registration of potential locations for solar energy production with Light Detection And Ranging (LiDAR) and small format photogrammetry / Szilárd Szabó, Péter Enyedi, Miklós Horváth, Zoltán Kovács, Péter Burai, Tamás Csoknyai, Gergely Szabó
Dátum:2016
ISSN:0959-6526
Megjegyzések:Energy production and consumption is a key element in future development which is influenced both bythe technical possibilities available and by decision makers. Sustainability issues are closely linked inwith energy policy, given the desire to increase the proportion of renewable energy. According to theHorizon 2020 climate and energy package, European Union (EU) member countries have to reduce theamount of greenhouse gases they emit by 20%, to increase the proportion of renewable energy to 20%and to improve energy efficiency by 20% by 2020. In this study we aim to assess the opportunitiesavailable to exploit solar radiation on roofs with Light Detection And Ranging (LiDAR) and photogrammetrytechniques. The surveyed areawas in Debrecen, the second largest city in Hungary. An aerial LiDARsurvey was conducted with a density of 12 points/m2, over a 7 1.8 km wide band. We extracted thebuilding and roof models of the buildings from the point cloud. Furthermore, we applied a low-costdrone (DJI Phantom with a GoPro camera) in a smaller area of the LiDAR survey and also created a 3Dmodel: buildings and roof planes were identified with multiresolution segmentation of the digital surfacemodels (DSM) and orthophoto coverages. Building heights and building geometry were alsoextracted and validated in field surveys. 50 buildings were chosen for the geodetic survey and the resultsof the accuracy assessment were extrapolated to other buildings; in addition to this, 100 building heightswere measured. We focused primarily on the roofs, as these surfaces offer possible locations for thermaland photovoltaic equipment. We determined the slope and aspect of roof planes and calculated theincoming solar energy according to roof planes before comparing the results of the point cloud processingof LiDAR data and the segmentation of DSMs. Extracted roof geometries showed varying degreesof accuracy: the research proved that LiDAR-based roof-modelling is the best choice in residential areas,but the results of the drone survey did not differ significantly. Generally, both approaches can be applied,because the solar radiation values calculated were similar. The aerial techniques combined with themultiresolution processing demonstrated can provide a valuable tool to estimate potential solar energy.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
roof plane
solar irradiation
point cloud
multiresolution segmentation
drone
Megjelenés:Journal Of Cleaner Production. - 112 : 5 (2016), p. 3820-3829. -
További szerzők:Enyedi Péter (1982-) (környezettudós) Horváth Miklós Kovács Zoltán (1988-) (geográfus) Burai Péter (1977-) (agrármérnök) Csoknyai Tamás (1975-) (épületgépész mérnök) Szabó Gergely (1975-) (geográfus)
Pályázati támogatás:TAMOP-4.2.2.A-11/1/KONV-2012-0041
TAMOP
SROP-4.2.2.B-15/1/KONV-2015-0001
SROP
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DOI
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4.

001-es BibID:BIBFORM060259
Első szerző:Szabó Szilárd (geográfus)
Cím:Testing of algorithms for the identification of asbestos roofing based on hyperspectral data / Szabó Szilárd, Burai Péter, Kovács Zoltán, Szabó György, Kerényi Attila, Fazekas István, Paládi Mónika, Buday Tamás, Szabó Gergely
Dátum:2014
Megjegyzések:There are several environmental issues in urban areas that are caused by the unintentional consequences of past activities. One of these issues is the wide application of asbestos cement in roofing materials in the 2nd half of the 1900s. In this study, our goal was to identify different roof types and to determine those with asbestos components using high-ground (1 m) and spectral (126 bands) resolution airborne hyperspectral imagery (AISA Eagle II) and several classification approaches. In addition, we aimed to identify those wavelengths that play a significant role in distinguishing the different roof types. In the image analysis, the SAM,MLC and SVM classification methods were used to evaluate the different types of roofs. These methods resulted in accurate maps of the roof types, and asbestos cement roofs were identified with over 85% accuracy.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Aisa EAGLE
asbestos-cement
hyperspectral remote sensing
image classification
roofs
Megjelenés:Environmental Engineering and Management Journal. - 143 : 11 (2014), p. 2875-2880. -
További szerzők:Burai Péter (1977-) (agrármérnök) Kovács Zoltán (1988-) (geográfus) Szabó György (1964-) (geográfus, egyetemi tanár) Kerényi Attila (1943-2023) (geográfus) Fazekas István (1973-) (geográfus) Paládi Mónika (1987-) (geográfus) Buday Tamás (1982-) (geográfus) Szabó Gergely (1975-) (geográfus)
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5.

001-es BibID:BIBFORM091945
035-os BibID:(cikkazonosító)857 (WOS)000628506100001 (Scopus)85102203063
Első szerző:Varga Orsolya Gyöngyi (geográfus)
Cím:Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning / Orsolya Gyöngyi Varga, Zoltán Kovács, László Bekő, Péter Burai, Zsuzsanna Csatáriné Szabó, Imre Holb, Sarawut Ninsawat, Szilárd Szabó
Dátum:2021
ISSN:2072-4292
Megjegyzések:We analyzed the Corine Land Cover 2018 (CLC2018) dataset to reveal the correspondence between land cover categories of the CLC and the spectral information of Landsat-8, Sentinel-2 and PlanetScope images. Level 1 categories of the CLC2018 were analyzed in a 25 km ? 25 km study area in Hungary. Spectral data were summarized by land cover polygons, and the dataset was evaluated with statistical tests. We then performed Linear Discriminant Analysis (LDA) and Random Forest classifications to reveal if CLC L1 level categories were confirmed by spectral values. Wetlands and water bodies were the most likely to be confused with other categories. The least mixture was observed when we applied the median to quantify the pixel variance of CLC polygons. RF outperformed the LDA's accuracy, and PlanetScope's data were the most accurate. Analysis of class level accuracies showed that agricultural areas and wetlands had the most issues with misclassification. We proved the representativeness of the results with a repeated randomized test, and only PlanetScope seemed to be ungeneralizable. Results showed that CLC polygons, as basic units of land cover, can ensure 71.1?78.5% OAs for the three satellite sensors; higher geometric resolution resulted in better accuracy. These results justified CLC polygons, in spite of visual interpretation, can hold relevant information about land cover considering the surface reflectance values of satellites. However, using CLC as ground truth data for land cover classifications can be questionable, at least in the L1 nomenclature.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
landsat
sentinel
planet
CLC2018
Recursive Feature Elimination
validation
representativeness
Random Forest
Linear Discriminant Analysis
Megjelenés:Remote Sensing. - 13 : 5 (2021), p. 1-24. -
További szerzők:Kovács Zoltán (1988-) (geográfus) Bekő László (1986-) (okleveles vidékfejlesztési agrármérnök) Burai Péter (1977-) (agrármérnök) Szabó Zsuzsanna (1985-) (környezetgazdálkodási és vidékfejlesztési agrármérnök) Holb Imre (1973-) (agrármérnök) Ninsawat, Sarawut Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:TNN 123457
Egyéb
ÚNKP-19-3-III-DE-94
Egyéb
TKP2020-NKA-04
Egyéb
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DOI
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