TY - CHAP AU - Nagy, Gábor ED - Kulcsár, Attila TI - Nyílt forráskódú eszközök GML állományok kezelésére T2 - GISopen 2023 Konferencia kiadvány PB - Óbudai Egyetem, Alba Regia Műszaki Kar CY - Székesfehérvár SN - 9789634493433 PY - 2023 SP - 22 EP - 24 PG - 3 UR - https://m2.mtmt.hu/api/publication/34541032 ID - 34541032 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Jancsó, Tamás AU - Széll, Károly AU - Vakulya, Gergely AU - Borbély, József AU - Katona, János AU - Nagy, Gábor ED - Petőné Csuka, Ildikó ED - Simon, Gyula TI - Common aspects of 3D modeling and vision solutions in robotics and geoinformatics T2 - AIS 2023 - 18th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634493341 PY - 2023 SP - 99 EP - 104 PG - 6 UR - https://m2.mtmt.hu/api/publication/34379021 ID - 34379021 LA - English DB - MTMT ER - TY - CHAP AU - Verőné Wojtaszek, Malgorzata AU - Molnár, Gábor AU - Balázsik, Valéria AU - Pődör, Andrea AU - Nagy, Gábor AU - Katona, János AU - Noboa, Erick AU - Ádám, Bence AU - Eigner, György AU - Györök, György ED - Petőné Csuka, Ildikó ED - Simon, Gyula TI - Water Resources in Efficient Networks (WREN) project overview and presentation of the research results carried out during the first year T2 - AIS 2023 - 18th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634493341 PY - 2023 SP - 90 EP - 98 PG - 9 UR - https://m2.mtmt.hu/api/publication/34378635 ID - 34378635 LA - English DB - MTMT ER - TY - JOUR AU - Zhou, Xiaocheng AU - Wang, Hongyu AU - Chen, Chongcheng AU - Nagy, Gábor AU - Jancsó, Tamás AU - Huang, Hongyu TI - Detection of Growth Change of Young Forest Based on UAV RGB Images at Single-Tree Level JF - FORESTS J2 - FORESTS VL - 14 PY - 2023 IS - 1 SP - 1 EP - 22 PG - 22 SN - 1999-4907 DO - 10.3390/f14010141 UR - https://m2.mtmt.hu/api/publication/33573928 ID - 33573928 AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Zhou, Xiaocheng AU - Hao, Youzhuang AU - Di, Liping AU - Wang, Xiaoqin AU - Chen, Chongcheng AU - Chen, Yunzhi AU - Nagy, Gábor AU - Jancsó, Tamás TI - 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 JF - REMOTE SENSING J2 - REMOTE SENS-BASEL VL - 15 PY - 2023 IS - 2 SP - 467 PG - 20 SN - 2072-4292 DO - 10.3390/rs15020467 UR - https://m2.mtmt.hu/api/publication/33573924 ID - 33573924 AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Nagy, Gábor AU - Ungvári, Zsuzsanna ED - Petőné Csuka, Ildikó ED - Simon, Gyula TI - Comparative Analysis of several contour line generation methods and softwares T2 - AIS 2022 - 17th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634493020 PY - 2022 SP - 147 EP - 150 PG - 4 UR - https://m2.mtmt.hu/api/publication/33265148 ID - 33265148 LA - English DB - MTMT ER - TY - CONF AU - Jancsó, Tamás AU - Pődör, Andrea AU - E., Nagyne Hajnal AU - Udvardy, Péter AU - Nagy, Gábor AU - Varga, Attila AU - Q., Meng AU - L., Zhang TI - Data Integration with Geographic Information System Tools for Rural Environmental Monitoring T2 - IRC 2022 XVI. International Research Conference Proceedings C1 - Peking PY - 2022 SP - 52 EP - 59 PG - 8 UR - https://m2.mtmt.hu/api/publication/33148225 ID - 33148225 LA - English DB - MTMT ER - TY - CHAP AU - Nagy, Gábor TI - Mi a pontfelhő, mire használható? T2 - Garai Géza Szabadegyetem III. PB - Óbudai Egyetem CY - Budapest SN - 9789634492818 PY - 2021 SP - 57 EP - 66 PG - 10 UR - https://m2.mtmt.hu/api/publication/32539838 ID - 32539838 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Nagy, Gábor ED - Petőné Csuka, Ildikó ED - Simon, Gyula TI - Analysis of a Prime-Representing Constant T2 - AIS 2021-16th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634492634 PY - 2021 SP - 69 EP - 70 PG - 2 UR - https://m2.mtmt.hu/api/publication/32503352 ID - 32503352 LA - English DB - MTMT ER - TY - CHAP AU - Nagy, Gábor ED - Petőné Csuka, Ildikó ED - Simon, Gyula TI - Using Sector Based Linear Regression in Epidemic Data T2 - AIS 2021-16th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634492634 PY - 2021 SP - 16 EP - 18 PG - 3 UR - https://m2.mtmt.hu/api/publication/32498882 ID - 32498882 LA - English DB - MTMT ER -