@inproceedings{MTMT:34541032, title = {Nyílt forráskódú eszközök GML állományok kezelésére}, url = {https://m2.mtmt.hu/api/publication/34541032}, author = {Nagy, Gábor}, booktitle = {GISopen 2023 Konferencia kiadvány}, unique-id = {34541032}, year = {2023}, pages = {22-24}, orcid-numbers = {Nagy, Gábor/0000-0001-9453-2291} } @inproceedings{MTMT:34379021, title = {Common aspects of 3D modeling and vision solutions in robotics and geoinformatics}, url = {https://m2.mtmt.hu/api/publication/34379021}, author = {Jancsó, Tamás and Széll, Károly and Vakulya, Gergely and Borbély, József and Katona, János and Nagy, Gábor}, booktitle = {AIS 2023 - 18th International Symposium on Applied Informatics and Related Areas - Proceedings}, unique-id = {34379021}, year = {2023}, pages = {99-104}, orcid-numbers = {Jancsó, Tamás/0000-0003-4954-7202; Széll, Károly/0000-0001-7499-5643; Vakulya, Gergely/0000-0002-4289-5469; Katona, János/0000-0002-0948-7017; Nagy, Gábor/0000-0001-9453-2291} } @inproceedings{MTMT:34378635, title = {Water Resources in Efficient Networks (WREN) project overview and presentation of the research results carried out during the first year}, url = {https://m2.mtmt.hu/api/publication/34378635}, author = {Verőné Wojtaszek, Malgorzata and Molnár, Gábor and Balázsik, Valéria and Pődör, Andrea and Nagy, Gábor and Katona, János and Noboa, Erick and Ádám, Bence and Eigner, György and Györök, György}, booktitle = {AIS 2023 - 18th International Symposium on Applied Informatics and Related Areas - Proceedings}, unique-id = {34378635}, year = {2023}, pages = {90-98}, orcid-numbers = {Molnár, Gábor/0000-0001-9309-3418; Pődör, Andrea/0000-0002-8534-9361; Nagy, Gábor/0000-0001-9453-2291; Katona, János/0000-0002-0948-7017; Györök, György/0000-0003-3668-7855} } @article{MTMT:33573928, title = {Detection of Growth Change of Young Forest Based on UAV RGB Images at Single-Tree Level}, url = {https://m2.mtmt.hu/api/publication/33573928}, author = {Zhou, Xiaocheng and Wang, Hongyu and Chen, Chongcheng and Nagy, Gábor and Jancsó, Tamás and Huang, Hongyu}, doi = {10.3390/f14010141}, journal-iso = {FORESTS}, journal = {FORESTS}, volume = {14}, unique-id = {33573928}, issn = {1999-4907}, abstract = {With the rapid development of Unmanned Aerial Vehicle (UAV) technology, more and more UAVs have been used in forest survey. UAV (RGB) images are the most widely used UAV data source in forest resource management. However, there is some uncertainty as to the reliability of these data when monitoring height and growth changes of low-growing saplings in an afforestation plot via UAV RGB images. This study focuses on an artificial Chinese fir (Cunninghamia lancelota, named as Chinese Fir) young forest plot in Fujian, China. Divide-and-conquer (DAC) and the local maximum (LM) method for extracting seedling height are described in the paper, and the possibility of monitoring young forest growth based on low-cost UAV remote sensing images was explored. Two key algorithms were adopted and compared to extract the tree height and how it affects the young forest at single-tree level from multi-temporal UAV RGB images from 2019 to 2021. Compared to field survey data, the R2 of single saplings’ height extracted from digital orthophoto map (DOM) images of tree pits and original DSM information using a divide-and-conquer method reached 0.8577 in 2020 and 0.9968 in 2021, respectively. The RMSE reached 0.2141 in 2020 and 0.1609 in 2021. The R2 of tree height extracted from the canopy height model (CHM) via the LM method was 0.9462. The RMSE was 0.3354 in 2021. The results demonstrated that the survival rates of the young forest in the second year and the third year were 99.9% and 85.6%, respectively. This study shows that UAV RGB images can obtain the height of low sapling trees through a computer algorithm based on using 3D point cloud data derived from high-precision UAV images and can monitor the growth of individual trees combined with multi-stage UAV RGB images after afforestation. This research provides a fully automated method for evaluating the afforestation results provided by UAV RGB images. In the future, the universality of the method should be evaluated in more afforestation plots featuring different tree species and terrain.}, year = {2023}, eissn = {1999-4907}, orcid-numbers = {Zhou, Xiaocheng/0000-0003-4553-2978; Nagy, Gábor/0000-0001-9453-2291; Jancsó, Tamás/0000-0003-4954-7202; Huang, Hongyu/0000-0001-5683-6497} } @article{MTMT:33573924, title = {Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China}, url = {https://m2.mtmt.hu/api/publication/33573924}, author = {Zhou, Xiaocheng and Hao, Youzhuang and Di, Liping and Wang, Xiaoqin and Chen, Chongcheng and Chen, Yunzhi and Nagy, Gábor and Jancsó, Tamás}, doi = {10.3390/rs15020467}, journal-iso = {REMOTE SENS-BASEL}, journal = {REMOTE SENSING}, volume = {15}, unique-id = {33573924}, abstract = {Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With the technological development of satellite-based LiDAR, it is possible to determine forest canopy height over a large area. However, the forest canopy height that is acquired by this technology is influenced by topography and climate, and the canopy height that is acquired in complex subtropical mountainous regions has large errors. In this paper, we propose a method for estimating forest canopy height by combining long-time series Landsat images with GEDI satellite-based LiDAR data, with Fujian, China, as the study area. This approach optimizes the quality of GEDI canopy height data in topographically complex areas by combining stand age and tree height, while retaining the advantage of fast and effective forest canopy height measurements with satellite-based LiDAR. In this study, the growth curves of the main forest types in Fujian were first obtained by using a large amount of forest survey data, and the LandTrendr algorithm was used to obtain the forest age distribution in 2020. The obtained forest age was then combined with the growth curves of each forest type in order to determine the tree height distribution. Finally, the obtained average tree heights were merged with the GEDI_V27 canopy height product in order to create a modified forest canopy height model (MGEDI_V27) with a 30 m spatial resolution. The results showed that the estimated forest canopy height had a mean of 15.04 m, with a standard deviation of 4.98 m. In addition, we evaluated the accuracy of the GEDI_V27 and the MGEDI_V27 using the sample dataset. The MGEDI_V27 had a higher accuracy (R2 = 0.67, RMSE = 2.24 m, MAE = 1.85 m) than the GEDI_V27 (R2 = 0.39, RMSE = 3.35 m, MAE = 2.41 m). R2, RMSE, and MAE were improved by 71.79%, 33.13%, and 22.53%, respectively. We also produced a forest age distribution map of Fujian for the year 2020 and a forest disturbance map of Fujian for the past 32 years. The research results can provide decision support for forest ecological protection and management and for carbon sink analysis in Fujian.}, year = {2023}, eissn = {2072-4292}, pages = {467-487}, orcid-numbers = {Zhou, Xiaocheng/0000-0003-4553-2978; Di, Liping/0000-0002-3953-9965; Nagy, Gábor/0000-0001-9453-2291; Jancsó, Tamás/0000-0003-4954-7202} } @inproceedings{MTMT:33265148, title = {Comparative Analysis of several contour line generation methods and softwares}, url = {https://m2.mtmt.hu/api/publication/33265148}, author = {Nagy, Gábor and Ungvári, Zsuzsanna}, booktitle = {AIS 2022 - 17th International Symposium on Applied Informatics and Related Areas - Proceedings}, unique-id = {33265148}, year = {2022}, pages = {147-150}, orcid-numbers = {Nagy, Gábor/0000-0001-9453-2291; Ungvári, Zsuzsanna/0000-0001-6084-2195} } @CONFERENCE{MTMT:33148225, title = {Data Integration with Geographic Information System Tools for Rural Environmental Monitoring}, url = {https://m2.mtmt.hu/api/publication/33148225}, author = {Jancsó, Tamás and Pődör, Andrea and E., Nagyne Hajnal and Udvardy, Péter and Nagy, Gábor and Varga, Attila and Q., Meng and L., Zhang}, booktitle = {IRC 2022 XVI. International Research Conference Proceedings}, unique-id = {33148225}, year = {2022}, pages = {52-59}, orcid-numbers = {Jancsó, Tamás/0000-0003-4954-7202; Pődör, Andrea/0000-0002-8534-9361; Udvardy, Péter/0000-0002-8897-9326; Nagy, Gábor/0000-0001-9453-2291} } @inbook{MTMT:32539838, title = {Mi a pontfelhő, mire használható?}, url = {https://m2.mtmt.hu/api/publication/32539838}, author = {Nagy, Gábor}, booktitle = {Garai Géza Szabadegyetem III.}, unique-id = {32539838}, year = {2021}, pages = {57-66}, orcid-numbers = {Nagy, Gábor/0000-0001-9453-2291} } @inproceedings{MTMT:32503352, title = {Analysis of a Prime-Representing Constant}, url = {https://m2.mtmt.hu/api/publication/32503352}, author = {Nagy, Gábor}, booktitle = {AIS 2021-16th International Symposium on Applied Informatics and Related Areas - Proceedings}, unique-id = {32503352}, year = {2021}, pages = {69-70}, orcid-numbers = {Nagy, Gábor/0000-0001-9453-2291} } @inproceedings{MTMT:32498882, title = {Using Sector Based Linear Regression in Epidemic Data}, url = {https://m2.mtmt.hu/api/publication/32498882}, author = {Nagy, Gábor}, booktitle = {AIS 2021-16th International Symposium on Applied Informatics and Related Areas - Proceedings}, unique-id = {32498882}, year = {2021}, pages = {16-18}, orcid-numbers = {Nagy, Gábor/0000-0001-9453-2291} }