Pub Date : 2020-01-01DOI: 10.15292/geodetski-vestnik.2020.03.361-375
M. Aleknavičius, A. Aleknavičius, K. Kurowska
cross-border integration, gravity model, market sharing čezmejno povezovanje, gravitacijski model, skupni trg UDK: 339.92/.94 Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 19. 6. 2020 Sprejeto: 5. 9. 2020 DOI: 10.15292/geodetski-vestnik.2020.03.361-375 SCIENTIFIC ARTICLE Received: 19. 6. 2020 Accepted: 5. 9. 2020 Marius Aleknavičius, Audrius Aleknavičius, Krystyna Kurowska ANALIZA TURISTIČNIH INTERAKCIJ V PROSTORU V ČEZMEJNI REGIJI LITVE IN POLJSKE NA PODLAGI GRAVITACIJSKEGA MODELA ANALYSIS OF SPATIAL INTERACTIONS OF TOURISM IN LITHUANIAN-POLISH CROSSBORDER REGION USING GRAVITY MODELS
跨境一体化，引力模型，市场共享跨境一体化，重力模型，共同市场UDK:339.92/.94根据COISS.SI:1.01的贡献分类到达时间：19。2020年6月通过：5。92020 DOI:10.15292/geodetski-vestnik.20203.361-375科学文章收到时间：19。2020年6月接受日期：5。92020 Marius Aleknavičius，Audrius Aleknovičus，Krystyna Kurowska使用重力模型分析立陶宛-波兰跨境地区旅游的空间相互作用
{"title":"Analysis of spatial interactions of tourism in Lithuanian-Polish cross-border region using gravity models","authors":"M. Aleknavičius, A. Aleknavičius, K. Kurowska","doi":"10.15292/geodetski-vestnik.2020.03.361-375","DOIUrl":"https://doi.org/10.15292/geodetski-vestnik.2020.03.361-375","url":null,"abstract":"cross-border integration, gravity model, market sharing čezmejno povezovanje, gravitacijski model, skupni trg UDK: 339.92/.94 Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 19. 6. 2020 Sprejeto: 5. 9. 2020 DOI: 10.15292/geodetski-vestnik.2020.03.361-375 SCIENTIFIC ARTICLE Received: 19. 6. 2020 Accepted: 5. 9. 2020 Marius Aleknavičius, Audrius Aleknavičius, Krystyna Kurowska ANALIZA TURISTIČNIH INTERAKCIJ V PROSTORU V ČEZMEJNI REGIJI LITVE IN POLJSKE NA PODLAGI GRAVITACIJSKEGA MODELA ANALYSIS OF SPATIAL INTERACTIONS OF TOURISM IN LITHUANIAN-POLISH CROSSBORDER REGION USING GRAVITY MODELS","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"64 1","pages":"361-375"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66959707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.15292/GEODETSKI-VESTNIK.2020.04.508-544
M. Čeh, Helena Žužel, Simon Mansutti
Marjan Čeh, Helena Žužel, Simon Mansutti | RAZDELITEV NEPREMIČNIN AGRARNIH SKUPNOSTI: MNOŽIČNA KATASTRSKA PREUREDITEV V UPRAVLJANJU ZEMLJIŠČ V SLOVENIJI | SUBDIVISION OF JOINT TENURE IN AGRICULTURAL COMMUNITIES: CUSTOMARY LAND RIGHTS MANAGEMENT IN SLOVENIA | 508-544| UDK: UDK : 332.21:528.44(497.4) Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 29. 1. 2020 Sprejeto: 15. 11. 2020 DOI: 10.15292/geodetski-vestnik.2020.04.508-544 SCIENTIFIC ARTICLE Received: 29. 1. 2020 Accepted: 15. 11. 2020 Marjan Čeh, Helena Žužel, Simon Mansutti RAZDElITEV NEPREMIČNIN AGRARNIH SKUPNOSTI: MNOžIČNA KATASTRSKA PREUREDITEV V UPRAVlJANJU ZEMlJIŠČ V SlOVENIJI SUBDIVISION OF JOINT TENURE IN AGRICUlTURAl COMMUNITIES: CUSTOMARy lAND RIGHTS MANAGEMENT IN SlOVENIA
{"title":"Subdivision of joint tenure in agricultural communities: customary land rights management in Slovenia","authors":"M. Čeh, Helena Žužel, Simon Mansutti","doi":"10.15292/GEODETSKI-VESTNIK.2020.04.508-544","DOIUrl":"https://doi.org/10.15292/GEODETSKI-VESTNIK.2020.04.508-544","url":null,"abstract":"Marjan Čeh, Helena Žužel, Simon Mansutti | RAZDELITEV NEPREMIČNIN AGRARNIH SKUPNOSTI: MNOŽIČNA KATASTRSKA PREUREDITEV V UPRAVLJANJU ZEMLJIŠČ V SLOVENIJI | SUBDIVISION OF JOINT TENURE IN AGRICULTURAL COMMUNITIES: CUSTOMARY LAND RIGHTS MANAGEMENT IN SLOVENIA | 508-544| UDK: UDK : 332.21:528.44(497.4) Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 29. 1. 2020 Sprejeto: 15. 11. 2020 DOI: 10.15292/geodetski-vestnik.2020.04.508-544 SCIENTIFIC ARTICLE Received: 29. 1. 2020 Accepted: 15. 11. 2020 Marjan Čeh, Helena Žužel, Simon Mansutti RAZDElITEV NEPREMIČNIN AGRARNIH SKUPNOSTI: MNOžIČNA KATASTRSKA PREUREDITEV V UPRAVlJANJU ZEMlJIŠČ V SlOVENIJI SUBDIVISION OF JOINT TENURE IN AGRICUlTURAl COMMUNITIES: CUSTOMARy lAND RIGHTS MANAGEMENT IN SlOVENIA","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"64 1","pages":"508-544"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66960577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.15292/GEODETSKI-VESTNIK.2020.04.545-561
Zoran Kokeza, M. Vujasinovic, M. Govedarica, Brankica Milojević, Gordana Jakovljevic
Up-to-date cadastral maps are crucial for urban planning. Creating those maps with the classical geodetic methods is expensive and time-consuming. Emerge of Unmanned Aerial Vehicles (UAV) made a possibility for quick acquisition of data with much more details than it was possible before. The topic of the research refers to the challenges of automatic extraction of building footprints on high-resolution orthophotos. The objectives of this study were as follows: (1) to test the possibility of using different publicly available datasets (Tanzania, AIRS and Inria) for neural network training and then test the generalisation capability of the model on the Area Of Interest (AOI); (2) to evaluate the effect of the normalised digital surface model (nDSM) on the results of neural network training and implementation. Evaluation of the results shown that the models trained on the Tanzania (IoU 36.4%), AIRS (IoU 64.4%) and Inria (IoU 7.4%) datasets doesn't satisfy the requested accuracy to update cadastral maps in study area. Much better results are achieved in the second part of the study, where the training of the neural network was done on tiles (256x256) of the orthophoto of AOI created from data acquired using UAV. A combination of RGB orthophoto with nDSM resulted in a 2% increase of IoU, achieving the final IoU of over 90%.
{"title":"Automatic building footprint extraction from UAV images using neural networks","authors":"Zoran Kokeza, M. Vujasinovic, M. Govedarica, Brankica Milojević, Gordana Jakovljevic","doi":"10.15292/GEODETSKI-VESTNIK.2020.04.545-561","DOIUrl":"https://doi.org/10.15292/GEODETSKI-VESTNIK.2020.04.545-561","url":null,"abstract":"Up-to-date cadastral maps are crucial for urban planning. Creating those maps with the classical geodetic methods is expensive and time-consuming. Emerge of Unmanned Aerial Vehicles (UAV) made a possibility for quick acquisition of data with much more details than it was possible before. The topic of the research refers to the challenges of automatic extraction of building footprints on high-resolution orthophotos. The objectives of this study were as follows: (1) to test the possibility of using different publicly available datasets (Tanzania, AIRS and Inria) for neural network training and then test the generalisation capability of the model on the Area Of Interest (AOI); (2) to evaluate the effect of the normalised digital surface model (nDSM) on the results of neural network training and implementation. Evaluation of the results shown that the models trained on the Tanzania (IoU 36.4%), AIRS (IoU 64.4%) and Inria (IoU 7.4%) datasets doesn't satisfy the requested accuracy to update cadastral maps in study area. Much better results are achieved in the second part of the study, where the training of the neural network was done on tiles (256x256) of the orthophoto of AOI created from data acquired using UAV. A combination of RGB orthophoto with nDSM resulted in a 2% increase of IoU, achieving the final IoU of over 90%.","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"64 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66960592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/geodetski-vestnik.2019.01.27-40
Božo Koler, B. Stopar, Oskar Sterle, T. Urbancic, K. Medved
{"title":"New Slovenian height system SVS2010","authors":"Božo Koler, B. Stopar, Oskar Sterle, T. Urbancic, K. Medved","doi":"10.15292/geodetski-vestnik.2019.01.27-40","DOIUrl":"https://doi.org/10.15292/geodetski-vestnik.2019.01.27-40","url":null,"abstract":"","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/GEODETSKI-VESTNIK.2019.02.234-249
Julius Ernst, R. Mansberger, G. Muggenhuber, G. Navratil, Stefan Ozlberger, Christoph Twaroch
{"title":"The legal boundary cadastre in Austria: A success story?","authors":"Julius Ernst, R. Mansberger, G. Muggenhuber, G. Navratil, Stefan Ozlberger, Christoph Twaroch","doi":"10.15292/GEODETSKI-VESTNIK.2019.02.234-249","DOIUrl":"https://doi.org/10.15292/GEODETSKI-VESTNIK.2019.02.234-249","url":null,"abstract":"","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/GEODETSKI-VESTNIK.2019.02.163-178
T. Ambrožič, Admir Mulahusić, Nedim Tuno, Jusuf Topoljak, Amir Hajdar, D. Kogoj
Tomaž Ambrožič, Admir Mulahusić, Nedim Tuno, Jusuf Topoljak, Amir Hajdar, Dušan Kogoj | DEFORMACIJSKA ANALIZA V GEODETSKIH MREŽAH Z ROBUSTNIMI METODAMI | DEFORMATION ANALYSIS WITH ROBUST METHODS IN GEODETIC NETS | 163-178 | deformation analysis, robust methods, numerical example This article describes the deformation analysis approach with robust methods in geodetic networks. The characteristic of this approach is the iterative weighted similarity transformation in which the displacement vector d is transformed into a datum determined by points with a smaller coordinate difference between two epochs. The article first gives a theoretical background of the approach, and then the approach is applied to the case of simulated measurements in two epochs. The calculated results of the deformation analysis approach with the robust methods in the present case do not differ significantly from the results obtained by conventional deformation analysis approaches.
tomajov Ambrožič， Admir mulahusiki, Nedim Tuno, Jusuf Topoljak, Amir Hajdar, Dušan Kogoj | DEFORMACIJSKA ANALIZA V GEODETSKIH MREŽAH Z ROBUSTNIMI METODAMI |形变分析与鲁棒方法在大地网| 163-178 |形变分析，鲁棒方法，数值实例本文描述了大地网中采用鲁棒方法的形变分析方法。该方法的特点是采用迭代加权相似变换，将位移向量d变换为由两个历元间坐标差较小的点确定的基准。本文首先给出了该方法的理论背景，然后将该方法应用于两个时期的模拟测量实例。本例中采用鲁棒方法的变形分析方法的计算结果与传统变形分析方法的计算结果没有显著差异。
{"title":"Deformation analysis with robust methods in geodetic nets","authors":"T. Ambrožič, Admir Mulahusić, Nedim Tuno, Jusuf Topoljak, Amir Hajdar, D. Kogoj","doi":"10.15292/GEODETSKI-VESTNIK.2019.02.163-178","DOIUrl":"https://doi.org/10.15292/GEODETSKI-VESTNIK.2019.02.163-178","url":null,"abstract":"Tomaž Ambrožič, Admir Mulahusić, Nedim Tuno, Jusuf Topoljak, Amir Hajdar, Dušan Kogoj | DEFORMACIJSKA ANALIZA V GEODETSKIH MREŽAH Z ROBUSTNIMI METODAMI | DEFORMATION ANALYSIS WITH ROBUST METHODS IN GEODETIC NETS | 163-178 | deformation analysis, robust methods, numerical example This article describes the deformation analysis approach with robust methods in geodetic networks. The characteristic of this approach is the iterative weighted similarity transformation in which the displacement vector d is transformed into a datum determined by points with a smaller coordinate difference between two epochs. The article first gives a theoretical background of the approach, and then the approach is applied to the case of simulated measurements in two epochs. The calculated results of the deformation analysis approach with the robust methods in the present case do not differ significantly from the results obtained by conventional deformation analysis approaches.","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/geodetski-vestnik.2019.04.525-540
Sanja Tucikešić, D. Blagojević
1, and describe stationary stochastic process. Then we processed time-series data of two GNSS station coordinates during 5 earthquakes that occurred near SRVJ and BEOG stations and estimated spectral indices of power-law noise from postfit residuals after removing linear, annual and semi-annual variation in the MODELLING THE OF GNSS COORDINATES AND THEIR INTERACTION WITH AVERAGE MAGNITUDE (27.71 mm/year). Estimated horizontal components have smaller deviations than the vertical part. The Weighted Root Mean Square (WRMS) error estimation of a function for one year for coordinates and deformations is 2.31 mm for the horizontal component and 5.36 mm for the height component. This study shows that there are seasonal and semi-annual signals in all three coordinate components. It can be seen that the periodic components are different for the analyzed BEOG station. Also, the annual period is dominant. Annual variation is with typical amplitudes about 1 mm for horizontal and over 2 mm for vertical.
{"title":"Modelling of the time-series of GNSS coordinates and their interaction with average magnitude earthquakes","authors":"Sanja Tucikešić, D. Blagojević","doi":"10.15292/geodetski-vestnik.2019.04.525-540","DOIUrl":"https://doi.org/10.15292/geodetski-vestnik.2019.04.525-540","url":null,"abstract":" 1, and describe stationary stochastic process. Then we processed time-series data of two GNSS station coordinates during 5 earthquakes that occurred near SRVJ and BEOG stations and estimated spectral indices of power-law noise from postfit residuals after removing linear, annual and semi-annual variation in the MODELLING THE OF GNSS COORDINATES AND THEIR INTERACTION WITH AVERAGE MAGNITUDE (27.71 mm/year). Estimated horizontal components have smaller deviations than the vertical part. The Weighted Root Mean Square (WRMS) error estimation of a function for one year for coordinates and deformations is 2.31 mm for the horizontal component and 5.36 mm for the height component. This study shows that there are seasonal and semi-annual signals in all three coordinate components. It can be seen that the periodic components are different for the analyzed BEOG station. Also, the annual period is dominant. Annual variation is with typical amplitudes about 1 mm for horizontal and over 2 mm for vertical.","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/geodetski-vestnik.2019.04.541-553
L. Çakir, B. Konakoglu
The coordinate transformation has always been a hot topic in the field of geodesy. The artificial neural network (ANN) has been used as an alternative tool to determine the relationship between any two coordinate systems. Construction of an effective neural network depends on the network architecture, learning parameters and normalization technique used. Finding the best data normalization technique is an important step when designing a neural network. This study investigated the performances of eight normalization techniques on two-dimensional (2D) coordinate transformation using a generalized regression neural network (GRNN). The methods examined included the maximize, min-max, median, median-median absolute deviation (median-MAD), mean-mean absolute deviation (mean-MAD), statistical column, tanh, and z-score. Comparisons revealed that the min-max,
{"title":"The impact of data normalization on 2D coordinate transformation using GRNN","authors":"L. Çakir, B. Konakoglu","doi":"10.15292/geodetski-vestnik.2019.04.541-553","DOIUrl":"https://doi.org/10.15292/geodetski-vestnik.2019.04.541-553","url":null,"abstract":"The coordinate transformation has always been a hot topic in the field of geodesy. The artificial neural network (ANN) has been used as an alternative tool to determine the relationship between any two coordinate systems. Construction of an effective neural network depends on the network architecture, learning parameters and normalization technique used. Finding the best data normalization technique is an important step when designing a neural network. This study investigated the performances of eight normalization techniques on two-dimensional (2D) coordinate transformation using a generalized regression neural network (GRNN). The methods examined included the maximize, min-max, median, median-median absolute deviation (median-MAD), mean-mean absolute deviation (mean-MAD), statistical column, tanh, and z-score. Comparisons revealed that the min-max,","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.15292/geodetski-vestnik.2019.03.395-414
B. Suleymanoglu, M. Soycan
lidar, airborne lidar, filtering algorithm, digital elevation model, point cloud lidar, aerolasersko skeniranje, algoritmi za filtriranje, digitalni model reliefa, oblak točk UDK: 528.8.044.6:528.2:(560.11) Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 17. 12. 2018 Sprejeto: 23 6. 2019 DOI: 10.15292/geodetski-vestnik.2019.03.395-414 SCIENTIFIC ARTICLE Received: 17. 12. 2018 Accepted: 23. 6. 2019 Baris Suleymanoglu, Metin Soycan PRIMERJAVA ALGORITMOV ZA FILTRIRANJE ZA IZDELAVO DMR IZ LIDARSKIH PODATKOV: ŠTUDIJSKI PRIMER BERGAMA, TURČIJA COMPARISON OF FILTERING ALGORITHMS USED FOR DTM PRODUCTION FROM AIRBORNE LIDAR DATA: A CASE STUDY IN BERGAMA, TURKEY
激光雷达，机载激光雷达，滤波算法，数字高程模型，点云激光雷达，aerolasersko skaniranje，algorimi za filtiranje。2018年12月通过日期：23 6。2019 DOI:10.15292/geodetski-vestnik.2019.03.395-414科学文章收到时间：17。2018年12月接受日期：23。6.2019 Baris Suleymanoglu，Metin Soycan从机载激光雷达数据中产生DTM的滤波算法比较：土耳其BERGAMA的案例研究
{"title":"Comparison of filtering algorithms used for DTM production from airborne lidar data: a case study in Bergama, Turkey","authors":"B. Suleymanoglu, M. Soycan","doi":"10.15292/geodetski-vestnik.2019.03.395-414","DOIUrl":"https://doi.org/10.15292/geodetski-vestnik.2019.03.395-414","url":null,"abstract":"lidar, airborne lidar, filtering algorithm, digital elevation model, point cloud lidar, aerolasersko skeniranje, algoritmi za filtriranje, digitalni model reliefa, oblak točk UDK: 528.8.044.6:528.2:(560.11) Klasifikacija prispevka po COBISS.SI: 1.01 Prispelo: 17. 12. 2018 Sprejeto: 23 6. 2019 DOI: 10.15292/geodetski-vestnik.2019.03.395-414 SCIENTIFIC ARTICLE Received: 17. 12. 2018 Accepted: 23. 6. 2019 Baris Suleymanoglu, Metin Soycan PRIMERJAVA ALGORITMOV ZA FILTRIRANJE ZA IZDELAVO DMR IZ LIDARSKIH PODATKOV: ŠTUDIJSKI PRIMER BERGAMA, TURČIJA COMPARISON OF FILTERING ALGORITHMS USED FOR DTM PRODUCTION FROM AIRBORNE LIDAR DATA: A CASE STUDY IN BERGAMA, TURKEY","PeriodicalId":44295,"journal":{"name":"Geodetski Vestnik","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66958834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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