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1.

001-es BibID:BIBFORM121657
Első szerző:Abriha Dávid (geográfus)
Cím:Mély konvolúciós neurális hálózat alkalmazása épület detektálásra kisszámú tanító adat felhasználásával / Abriha Dávid, Enyedi Péter, Papp Melitta, Kovács Lilla, Szabó Szilárd
Dátum:2024
Megjegyzések:We investigated the effectiveness of the U-Net architecture for building extraction from remote sensing data using varying numbers of training images. The results showed promising performance with a few training images (94?97% validation accuracy). However, combining different data sources initially yielded poor results, but the inclusion of a small number of target image training samples significantly improved the accuracy (F1 score increased from 0.184 to 0.693).
ISBN:978-963-490-619-3
Tárgyszavak:Természettudományok Földtudományok könyvfejezet
könyvrészlet
Megjelenés:Az elmélet és a gyakorlat találkozása a térinformatikában XV. / (szerk.)Abriha-Molnár Vanda Éva. - p. 7-14. -
További szerzők:Enyedi Péter (1982-) (környezettudós) Papp Melitta Kovács Lilla (Msc hallgató) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:K138079
OTKA
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2.

001-es BibID:BIBFORM123733
Első szerző:Diószegi Gergő
Cím:Testing 'treecbh' in Central European forests: an R package for crown base height detection using high-resolution aerial laser-scanned data / Gyergő Diószegi, Vanda Éva Molnár, Loránd Attila Nagy, Péter Enyedi, Péter Török, Szilárd Szabó
Dátum:2024
ISSN:0015-752X
Megjegyzések:Accurate information regarding tree canopy characteristics is crucial for forest management, but it is often difficult to assess. This study presents an innovative framework designed for crown base height (CBH) detection using high-resolution laser-scanned data, with a specific focus on individual trees within forests. The framework comprises three key steps: (i) segmenting the input tree point cloud to identify the tree trunk and its branches using the treesio software; (ii) applying vertical cross-sectional K-means clustering to cluster the identified tree and to define the elevation threshold for removing low-lying understory vegetation; (iii) employing a novel 2D kernel method for detecting CBH after eliminating low-lying understory vegetation. The 2D kernel method, developed for broadleaf forests using leaf-off airborne laser scanning (ALS) data, underpins the treecbh tool. This tool features a visual CBH adjustment component that shows a 2D profile plot of the tree point cloud, and suggests a CBH value for user approval or adjustment. To evaluate accuracy, in situ measured CBH data from five forest plots in Germany and Hungary with varied species compositions were used. ALS data were collected during leaf-off conditions for the two Hungarian plots and during leaf-on conditions for the three German plots. Leaf-off terrestrial laser-scanned data from individual trees were also used in the accuracy assessment. A sensitivity analysis using random point decimation was conducted on the terrestrial laser-scanned data to assess treecbh's sensitivity to point density. The initial results exhibited matching rates of 45% and 60% for leaf-off ALS plots, which significantly improved to 71% and 77%, respectively, when using the visual CBH adjustment feature of the tool. The leaf-on ALS results demonstrated matching rates between 24% and 33%, whereas the CBHs of individual terrestrial laser-scanned trees could be detected with 93% accuracy in visual mode. It was observed that treecbh operates effectively when the input ALS data have a minimum point density of 20 pts/ ?, with its optimal performance achieved at 110 pts/ ?. These findings indicated treecbh's sensitivity to ALS data quality, scanning season (leaf-on and leaf-off), and point density. This sensitivity can be effectively mitigated in the case of leaf-off ALS data by utilizing the visual CBH adjustment feature of the tool.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Forestry. - [Epub ahead of print] : - (2024), p. 1-15. -
További szerzők:Molnár Vanda Éva (1994-) (környezetkutató) Nagy Loránd Attila (1993-) (geográfus) Enyedi Péter (1982-) (környezettudós) Török Péter (1979-) (biológus-ökológus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:K138079
Egyéb
KKP 144068
Egyéb
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3.

001-es BibID:BIBFORM122075
035-os BibID:(Scopus)85195669359 (WoS)001244602100001
Első szerző:Diószegi Gergő
Cím:A new method for individual treetop detection with low-resolution aerial laser scanned data / Gergő Diószegi, Vanda Éva Molnár, Loránd Attila Nagy, Péter Enyedi, Péter Török, Szilárd Szabó
Dátum:2024
ISSN:2363-6203 2363-6211
Megjegyzések:In the past decade, the use of three-dimensional forest information from airborne Light Detection and Ranging (LiDAR) has become widespread in forest inventories. Accurate Individual Treetop Detection (ITD) and crown boundary delineation using LiDAR data are critical for obtaining precise inventory metrics. To address this need, we introduced a novel growing tree region (GTR)-driven ITD method that utilizes canopy height models (CHM) derived from very low-resolution airborne LiDAR data. The GTR algorithm consists of three key stages: (i) preserving all height layers through incremental cutting and stacking of CHM; (ii) employing a three-layer concept to identify individual treetops; and (iii) refining the detected treetops using a distance-based filter. Our method was tested in five temperate forests across Central Europe and was compared against the widely-used local maxima (LM) search combined with an optimized variable window filtering (VWF) technique. Our results showed that the GTR method outperformed LM with VWF, particularly in forests with high canopy density. The achieved root mean square accuracies were 74% for the matching rate, 19% for commission errors, and 27% for omission errors. In comparison, the LM with the VWF method resulted in a matching rate of 71%, commission errors of 20%, and omission errors of 31%. To facilitate the application of our algorithm, we developed an R package called TREETOPS, which seamlessly integrates with the lidR package, ensuring compatibility with existing treetop-based segmentation methods. By introducing TREETOPS, we provide the most accurate open-source tool for detecting treetops using low-resolution LiDAR-derived CHM.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
CHM-based treetop detection
Growing tree region
Local maxima
Variable window filtering
Low-resolution LiDAR
Central European forest
R
Megjelenés:Modeling Earth Systems and Environment. - [Epub ahead of print] : - (2024), p. -. -
További szerzők:Molnár Vanda Éva (1994-) (környezetkutató) Nagy Loránd Attila (1993-) (geográfus) Enyedi Péter (1982-) (környezettudós) Török Péter (1979-) (biológus-ökológus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:K138079
NKFIH
KKP 144068
NKFIH
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4.

001-es BibID:BIBFORM078730
035-os BibID:(WoS)000476899700005 (Scopus)85050563947
Első szerző:Enyedi Péter (környezettudós)
Cím:Efficiency of local minima and GLM techniques in sinkhole extraction from a LiDAR-based terrain model / Péter Enyedi, Melinda Pap, Zoltán Kovács, László Takács-Szilágyi, Szilárd Szabó
Dátum:2019
ISSN:1753-8947 1753-8955
Megjegyzések:The aim of this paper was to study reliable automated delineation possibilities of karst sinkholes using a LiDAR-based digital terrain model (DTM) with pixel-based classifications. We applied two approaches to extract sinkholes: (1) general linear modeling (GLM) with morphometric indices derived from DTM; (2) and a local minima-based delineation using only LiDAR DTM as the input layer. The outcome of the local minima was significantly different from the reference ones but found all the sinkholes without previous knowledge of the area. The GLM-based outcome did not differ statistically from the reference. Results showed that these approaches were efficient in detecting sinkholes based on LIDAR derivatives, and can be used for risk assessment and hazard preparedness in karst areas: GLM had an overall accuracy of 89.5% and local minima had an accuracy of 92.3%; both methods identified sinkholes but also had commission errors, identifying depressions as sinkholes.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Karst mapping
sinkhole identification
general linear model
statistical evaluation
sinkfill
Megjelenés:International Journal of Digital Earth. - 12 : 9 (2019), p. 1067-1082. -
További szerzők:Pap Melinda (1982-) (informatikus) Kovács Zoltán (1988-) (geográfus) Takács-Szilágyi László Szabó Szilárd (1974-) (geográfus)
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5.

001-es BibID:BIBFORM087257
035-os BibID:(cikkazonosító)2397 (WOS)000567130200001 (Scopus)85089524467
Első szerző:Schlosser Aletta Dóra (geográfus)
Cím:Building Extraction Using Orthophotos and Dense Point Cloud Derived from Visual Band Aerial Imagery Based on Machine Learning and Segmentation / Schlosser Aletta Dóra, Szabó Gergely, Bertalan László, Varga Zsolt, Enyedi Péter, Szabó Szilárd
Dátum:2020
ISSN:2072-4292
Megjegyzések:Urban sprawl related increase of built-in areas requires reliable monitoring methods and remote sensing can be an efficient technique. Aerial surveys, with high spatial resolution, provide detailed data for building monitoring, but archive images usually have only visible bands. We aimed to reveal the efficiency of visible orthophotographs and photogrammetric dense point clouds in building detection with segmentation-based machine learning (with five algorithms) using visible bands, texture information, and spectral and morphometric indices in different variable sets. Usually random forest (RF) had the best (99.8%) and partial least squares the worst overall accuracy (~60%). We found that >95% accuracy can be gained even in class level. Recursive feature elimination (RFE) was an efficient variable selection tool, its result with six variables was like when we applied all the available 31 variables. Morphometric indices had 82% producer's and 85% user's Accuracy (PA and UA, respectively) and combining them with spectral and texture indices, it had the largest contribution in the improvement. However, morphometric indices are not always available but by adding texture and spectral indices to red-green-blue (RGB) bands the PA improved with 12% and the UA with 6%. Building extraction from visual aerial surveys can be accurate, and archive images can be involved in the time series of a monitoring.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
photogrammetry
RGB indices
image texture
morphometric indices
recursive feature elimination
random forest
support vector machine
multiple adatptive regression spline
partial least square
Megjelenés:Remote Sensing. - 12 : 15 (2020), p. 1-28. -
További szerzők:Szabó Gergely (1975-) (geográfus) Bertalan László (1989-) (geográfus) Varga Zsolt (1968-) (építőmérnök) Enyedi Péter (1982-) (környezettudós) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:NKFI KH 130427
Egyéb
ED_18-1-2019-0028 Thematic Excellence Programme of the ministry for Innovation and Technology in Hungary, framework of the Space Sciences thematic programme of the University of Debrecen
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6.

001-es BibID:BIBFORM082762
Első szerző:Szabó Gergely
Cím:Preliminary results on the determination of solar energy potential using LiDAR technology / Szabó Gergely, Enyedi Péter, Szabó György Emőd, Fazekas István, Buday Tamás, Kerényi Attila, Paládi Mónika, Mecser Nikoletta, Szabó Szilárd
Dátum:2015
ISSN:2062-0810 2063-4269
Megjegyzések:According to the challenge of the reduction of greenhouse gases, the structure of energy production should be revised and the increase of the ratio of alternative energy sources can be a possible solution. Redistribution of the energy production to the private houses is an alternative of large power stations at least in a partial manner. Especially, the utilization of solar energy represents a real possibility to exploit the natural resources in a sustainable way. In this study we attempted to survey the roofs of the buildings with an automatic method as the potential surfaces of placing solar panels. A LiDAR survey was carried out with 12 points/ m2 density as the most up-to-date method of surveys and automatic data collection techniques. Our primary goal was to extract the buildings with special regard to the roofs in a 1 km2 study area, in Debrecen. The 3D point cloud generated by the LiDAR was processed with MicroStation TerraScan software, using semi-automatic algorithms. Slopes, aspects and annual solar radiation income of roof planes were determined in ArcGIS10 environment from the digital surface model. Results showed that, generally, the outcome can be regarded as a roof cadaster of the buildings with correct geometry. Calculated solar radiation values revealed those roof planes where the investment for photovoltaic solar panels can be feasible.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény hazai lapban
folyóiratcikk
potential solar radiation
LiDAR
point cloud
roof extraction
Megjelenés:International Review of Applied Sciences and Engineering. - 6 : 1 (2015), p. 11-17. -
További szerzők:Szabó György (1964-) (geográfus, egyetemi tanár) Fazekas István Buday Tamás (1982-) (geográfus) Kerényi Attila (1943-2023) (geográfus) Paládi Mónika (1987-) (geográfus) Mecser Nikoletta (1988-) (geográfus) Szabó Szilárd (1974-) (geográfus) Szabó Gergely (1975-) (geográfus) Enyedi Péter (1982-) (környezettudós) Szabó György (1964-) (geográfus, egyetemi tanár) Fazekas István (1954-) (matematikus, informatikus) Buday Tamás (1982-) (geográfus) Kerényi Attila (1943-2023) (geográfus) Paládi Mónika (1987-) (geográfus) Mecser Nikoletta (1988-) (geográfus) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:TÁMOP 4.2.4. A/2-11-1-2012-0001
TÁMOP
TÁMOP- 4.2.2.A-11/1/KONV-2012-0041
TÁMOP
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7.

001-es BibID:BIBFORM062880
035-os BibID:(WoS)000368207500021 (Scopus)84952815702
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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8.

001-es BibID:BIBFORM056488
Első szerző:Szabó Szilárd (geográfus)
Cím:Lidar based assessment of roofs : Perspectives for solar energy / Szilárd Szabó, Péter Enyedi, György Szabó, István Fazekas, Tamás Buday, Attila Kerényi, Mónika Paládi, Nikoletta Mecser, Gergely Szabó
Dátum:2014
Megjegyzések:According to the Horizon 2020 climate and energy package, legislation has to meet the 20-20-20 target. It means that EU member countries have to reduce the amount of greenhouse gases by 20%, to increase the proportion of renewable energy to 20% and to improve the energy efficiency by 20%. Regarding the energy production issues, locally produced solar energy can be a possible solution installed on the top of the buildings. In this study we made an attempt to register the roofs of the buildings and evaluated the roof planes whether they are appropriate for the installation of photovoltaic solar panels. Main question was the correct roof geometry, but most of our roof models showed high correspondence with real forms. We calculated the annual solar radiation and evaluated with geoinformation techniques and statistical methods.
ISBN:978-963-473-736-0
Tárgyszavak:Természettudományok Földtudományok előadáskivonat
LiDAR
point cloud
roof detection
solar radiation
Megjelenés:Proceedings of Denzero International Conference: Sustainable energy by optmal integration of renewable energy sources / ed. Kalmár Ferenc. - p. 114-122. -
További szerzők:Enyedi Péter (1982-) (környezettudós) Szabó György (1964-) (geográfus, egyetemi tanár) Fazekas István (1973-) (geográfus) Buday Tamás (1982-) (geográfus) Kerényi Attila (1943-2023) (geográfus) Paládi Mónika (1987-) (geográfus) Mecser Nikoletta (1988-) (geográfus) Szabó Gergely (1975-) (geográfus)
Pályázati támogatás:TÁMOP-4.2.2.A-11/1/KONV-2012-0041
Egyéb
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