{"title":"A ROBUST UNIFIED MODEL FOR NATIONAL STREET GAZETTEER BASED ON LAND REGISTER AND GIS FOR THE REPUBLIC OF KOSOVO","authors":"Përparim AMETI, Dustin SANCHEZ","doi":"10.21163/gt_2023.182.13","DOIUrl":"https://doi.org/10.21163/gt_2023.182.13","url":null,"abstract":"","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134910610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: This paper presents a method for identifying retention areas in forest stands using publicly available ALS (Aerial Laser Scanning) data. Retention areas/trees are the cause of large inaccuracies in compartmental timber volume calculations when updated with remote sensing data. Tree height was selected as the most explanatory parameter for identification. The calculation of the threshold value for each compartment was based on data from the FMS (Forest Management System) or on the evaluation of the statistical distribution of LiDAR data in the compartment. The calculation was applied directly to the 3D point cloud, where points with the corresponding height were classified and processed into the resulting vector layer. Both methods were tested and validated on a reference dataset. The statistical approach proved to be more reliable (OA 89%) due to frequent errors or outdated data in the FMS (OA 82%). After removing dead retention trees (standing tree torsos) from the validation dataset, the OA of both methods increased (FMS approach 90%, statistical approach 94%).
{"title":"IDENTIFICATION OF RETENTION AREAS USING AIRBORNE LIDAR DATA. A CASE STUDY FROM CENTRAL SWEDEN","authors":"J. Seidl","doi":"10.21163/gt_2023.182.12","DOIUrl":"https://doi.org/10.21163/gt_2023.182.12","url":null,"abstract":": This paper presents a method for identifying retention areas in forest stands using publicly available ALS (Aerial Laser Scanning) data. Retention areas/trees are the cause of large inaccuracies in compartmental timber volume calculations when updated with remote sensing data. Tree height was selected as the most explanatory parameter for identification. The calculation of the threshold value for each compartment was based on data from the FMS (Forest Management System) or on the evaluation of the statistical distribution of LiDAR data in the compartment. The calculation was applied directly to the 3D point cloud, where points with the corresponding height were classified and processed into the resulting vector layer. Both methods were tested and validated on a reference dataset. The statistical approach proved to be more reliable (OA 89%) due to frequent errors or outdated data in the FMS (OA 82%). After removing dead retention trees (standing tree torsos) from the validation dataset, the OA of both methods increased (FMS approach 90%, statistical approach 94%).","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46373687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdelali Gouiss, Youness Taybi, Y. Gharmane, Souad M’rabet
{"title":"CONTRIBUTION OF SPACE REMOTE SENSING AND NEW GIS TOOLS FOR MAPPING GEOLOGICAL STRUCTURES IN THE MEKKAM REGION OF NORTHEAST MOROCCO","authors":"Abdelali Gouiss, Youness Taybi, Y. Gharmane, Souad M’rabet","doi":"10.21163/gt_2023.182.11","DOIUrl":"https://doi.org/10.21163/gt_2023.182.11","url":null,"abstract":"","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":"408 15","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41283940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Purbani, M. I. Marzuki, B. Ontowirjo, Farhan Makarim Zein, D. Tjahjo, S. E. Purnamaningtyas, Rudy Akhwady, A. Syam, Arip Rahman, Y. Sugianti, S. Dody, A. S. Nastiti, A. Warsa, L. P. Astuti, Yosmaniar, T. Kadarini, T. Prihadi, U. J. Wisha
{"title":"TSUNAMI EVACUATION MODEL IN THE PANIMBANG SUBDISTRICT, BANTEN PROVINCE, INDONESIA: GIS- AND AGENT-BASED MODELING","authors":"D. Purbani, M. I. Marzuki, B. Ontowirjo, Farhan Makarim Zein, D. Tjahjo, S. E. Purnamaningtyas, Rudy Akhwady, A. Syam, Arip Rahman, Y. Sugianti, S. Dody, A. S. Nastiti, A. Warsa, L. P. Astuti, Yosmaniar, T. Kadarini, T. Prihadi, U. J. Wisha","doi":"10.21163/gt_2023.182.10","DOIUrl":"https://doi.org/10.21163/gt_2023.182.10","url":null,"abstract":"","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46433282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: One of the main natural disasters that has an impact on the environment and economy of nations throughout the world is drought. It has an impact on the local vegetation's state. The study's main goal was to look for years of severe drought by looking at Thailand's Eastern Economic Corridor (EEC). To determine the vegetation condition in the research area between 2017 and 2021, the Normalized Vegetation Index (NDVI) from Terra/MODIS data was employed. The area with the NDVI difference from the average value of NDVI during the same time period was examined using the Standardized Vegetation Index (SVI). Through the vegetation index, the drought can be reflected in this. According to the study, the highest drought area covered an area of 216.36 km 2 in 2017. This was followed by years 2019 and 2020, which each covered an area of 212.65 km 2 , 211.23 km 2 , 197.09 km 2 , and 178.07 km 2 . Additionally, a statistical analysis of the monthly correlation between the SVI (independent variable) and rainfall (dependent variable) over the course of the five years revealed that the coefficient of determination R 2 was 0.8018 in 2020, 0.6819 in 2021, 0.6262 in 2017, 0.5772 in 2018, and 0.5108 in 2019. The methodology can be obtained and used by other departments to assess and forecast drought in other regions of Thailand and other nations.
{"title":"THAI EASTERN ECONOMIC CORRIDOR DROUGHT MONITORING USING TERRA/MODIS SATELLITE-BASED DATA","authors":"P. Jeefoo","doi":"10.21163/gt_2023.182.09","DOIUrl":"https://doi.org/10.21163/gt_2023.182.09","url":null,"abstract":": One of the main natural disasters that has an impact on the environment and economy of nations throughout the world is drought. It has an impact on the local vegetation's state. The study's main goal was to look for years of severe drought by looking at Thailand's Eastern Economic Corridor (EEC). To determine the vegetation condition in the research area between 2017 and 2021, the Normalized Vegetation Index (NDVI) from Terra/MODIS data was employed. The area with the NDVI difference from the average value of NDVI during the same time period was examined using the Standardized Vegetation Index (SVI). Through the vegetation index, the drought can be reflected in this. According to the study, the highest drought area covered an area of 216.36 km 2 in 2017. This was followed by years 2019 and 2020, which each covered an area of 212.65 km 2 , 211.23 km 2 , 197.09 km 2 , and 178.07 km 2 . Additionally, a statistical analysis of the monthly correlation between the SVI (independent variable) and rainfall (dependent variable) over the course of the five years revealed that the coefficient of determination R 2 was 0.8018 in 2020, 0.6819 in 2021, 0.6262 in 2017, 0.5772 in 2018, and 0.5108 in 2019. The methodology can be obtained and used by other departments to assess and forecast drought in other regions of Thailand and other nations.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42693805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giovanni Mataloni, Donato Palumbo, M. Pepe, C. Varagnoli
: The aim of this research is the identification of geomatics techniques and methods capable of representing historic centres in a rapid, detailed and accurate manner. Indeed, historic centres are a cultural heritage asset to be preserved, protected and conserved for future generations, taking into account the history of a community. The paper describes a geomatics methodology applied to the case study of Capitignano (Italy), one of the municipalities that was affected by the 2009 earthquake that involved numerous historic centres causing extensive damage, not only in terms of human lives but also to the cultural heritage. The integration of geomatics techniques made it possible to obtain a georeferenced point cloud that is particularly useful for the description of buildings in historic centres, both at the urban scale and at the scale of individual artefacts. In addition, it was also possible to produce orthophotos with a high geometric resolution that made it possible to identify lesions in structures quickly and accurately.
{"title":"A MULTISCALE GEOMATIC APPROACH FOR THE SURVEY OF HISTORIC CENTRES MAIN STREETS: THE CASE STUDY OF CAPITIGNANO, ITALY","authors":"Giovanni Mataloni, Donato Palumbo, M. Pepe, C. Varagnoli","doi":"10.21163/gt_2023.182.08","DOIUrl":"https://doi.org/10.21163/gt_2023.182.08","url":null,"abstract":": The aim of this research is the identification of geomatics techniques and methods capable of representing historic centres in a rapid, detailed and accurate manner. Indeed, historic centres are a cultural heritage asset to be preserved, protected and conserved for future generations, taking into account the history of a community. The paper describes a geomatics methodology applied to the case study of Capitignano (Italy), one of the municipalities that was affected by the 2009 earthquake that involved numerous historic centres causing extensive damage, not only in terms of human lives but also to the cultural heritage. The integration of geomatics techniques made it possible to obtain a georeferenced point cloud that is particularly useful for the description of buildings in historic centres, both at the urban scale and at the scale of individual artefacts. In addition, it was also possible to produce orthophotos with a high geometric resolution that made it possible to identify lesions in structures quickly and accurately.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43136150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ASSESSMENT OF INUNDATION SUSCEPTIBILITY IN THE CONTEXT OF CLIMATE CHANGE, BASED ON MACHINE LEARNING AND REMOTE SENSING: CASE STUDY IN VINH PHUC PROVINCE OF VIETNAM","authors":"Phan Manh Hung, H. Nguyen, C. P. Van","doi":"10.21163/gt_2023.182.07","DOIUrl":"https://doi.org/10.21163/gt_2023.182.07","url":null,"abstract":"","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49211047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: GNSS reflectometry (GNSS-R) is a method to derive sea level using Signal to Noise Ratio (SNR) from the Global Navigation Satellite Systems (GNSS). SNR data consist of the direct signal from the satellite (multipath) and of the signals reflected by the sea surface, and hence separating the multipath is necessary to extract the signal from the sea surface. The process of separating multipath may affect the number of data and may eventually affect the quality of the derived sea level values. There are two multipath separation techniques that are mostly used: polynomial fitting and wavelet decomposition. This study investigates the performance of both techniques by applying them to analyze three months of the L1 SNR data of Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) as observed from two stations, Barus (CBRS) at North Sumatera from January 1 to March 31, 2022, and Morotai (CMOR) at North Maluku, Indonesia using data from February 1 to May 1, 2022. Comparison with sea level from tide gauge observations shows a high correlation for both techniques, with correlation coefficients of approximately 0.90 and 0.97 for CBRS and CMOR, respectively. The Root Mean Square Error (RMSE) of polynomial fitting for CBRS and CMOR have the same value, 11.5 cm, whereas those of wavelet are 11.4 cm and 11.5 cm. Since polynomial fitting and wavelet decomposition show similar performance, we conclude that both techniques give comparable accuracy of multipath SNR data for GNSS-R in Indonesia with appropriate quality control parameters.
{"title":"COMPARISON OF TWO SEPARATION MULTIPATH TECHNIQUES IN GNSS REFLECTOMETRY FOR SEA LEVEL DETERMINATION IN INDONESIA","authors":"Lisa A. Cahyaningtyas, D. Wijaya, Nabila Putri","doi":"10.21163/gt_2023.182.06","DOIUrl":"https://doi.org/10.21163/gt_2023.182.06","url":null,"abstract":": GNSS reflectometry (GNSS-R) is a method to derive sea level using Signal to Noise Ratio (SNR) from the Global Navigation Satellite Systems (GNSS). SNR data consist of the direct signal from the satellite (multipath) and of the signals reflected by the sea surface, and hence separating the multipath is necessary to extract the signal from the sea surface. The process of separating multipath may affect the number of data and may eventually affect the quality of the derived sea level values. There are two multipath separation techniques that are mostly used: polynomial fitting and wavelet decomposition. This study investigates the performance of both techniques by applying them to analyze three months of the L1 SNR data of Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) as observed from two stations, Barus (CBRS) at North Sumatera from January 1 to March 31, 2022, and Morotai (CMOR) at North Maluku, Indonesia using data from February 1 to May 1, 2022. Comparison with sea level from tide gauge observations shows a high correlation for both techniques, with correlation coefficients of approximately 0.90 and 0.97 for CBRS and CMOR, respectively. The Root Mean Square Error (RMSE) of polynomial fitting for CBRS and CMOR have the same value, 11.5 cm, whereas those of wavelet are 11.4 cm and 11.5 cm. Since polynomial fitting and wavelet decomposition show similar performance, we conclude that both techniques give comparable accuracy of multipath SNR data for GNSS-R in Indonesia with appropriate quality control parameters.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46932208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SPATIAL MODEL OF RUNOFF FLOWING INTO THE NEWLY FORMED LAKE AT SINABUNG VOLCANO","authors":"Sandy Budi WIBOWO, Polin Mouna TOGATOROP, Tsamara HANINDHIYA, Barandi Sapta WIDARTONO, R. Ibnu ROSYADI","doi":"10.21163/gt_2023.182.05","DOIUrl":"https://doi.org/10.21163/gt_2023.182.05","url":null,"abstract":"","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135691879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danardono, A. A. Wibowo, Dewi Novita, K. Priyono, Ecky Safira, Maharani Dewi
: The Kukup Coastal Area is located in the southern part of Java's coastal area, which has an active megathrust subduction zone. The dynamics of tectonic activities in this zone trigger earthquakes with various intensities. Some of these earthquakes can trigger a tsunami threatening human activities in this area. Therefore, a detailed study of tsunami hazards by integrating physical and socio-economic aspects needs to be done to estimate disaster risk and determine spatial planning in coastal areas. The objectives of this study are (1) to identify the coastal system and (2) to create a tsunami hazard map in the Kukup Coastal Area. Coastal systems can be identified by analyzing the physical and socio-economic conditions. Physical conditions such as morphological and coastal typology can be extracted from Digital Elevation Model (DEM) from aerial photo processing. Socio-economic conditions such as land use analysis and tourism activities can be extracted from orthophoto, which is extracted from aerial photo processing using drones. The tsunami hazard can be analyzed using three modelling stages: earthquake source modelling, tsunami wave propagation modelling, and tsunami inundation modelling using Geographic Information System (GIS). The results show that the morphological conditions in the study area were dominated by the formation of conical hills with a firm lineament pattern causing the formation of elongated basins such as labyrinths. This basin is a place for developing socio-economic activities, especially tourism, which can be seen from a large amount of built-up land area. The presence of these basins causes the tsunami inundation pattern to extend perpendicular to the shoreline, causing the tsunami inundation in the study area to extend as far as 2 km from the shoreline.
{"title":"TSUNAMI HAZARD MAPPING BASED ON COASTAL SYSTEM ANALYSIS USING HIGH-RESOLUTION UNMANNED AERIAL VEHICLE (UAV) IMAGERY (Case Study in Kukup Coastal Area, Gunungkidul Regency, Indonesia)","authors":"Danardono, A. A. Wibowo, Dewi Novita, K. Priyono, Ecky Safira, Maharani Dewi","doi":"10.21163/gt_2023.182.04","DOIUrl":"https://doi.org/10.21163/gt_2023.182.04","url":null,"abstract":": The Kukup Coastal Area is located in the southern part of Java's coastal area, which has an active megathrust subduction zone. The dynamics of tectonic activities in this zone trigger earthquakes with various intensities. Some of these earthquakes can trigger a tsunami threatening human activities in this area. Therefore, a detailed study of tsunami hazards by integrating physical and socio-economic aspects needs to be done to estimate disaster risk and determine spatial planning in coastal areas. The objectives of this study are (1) to identify the coastal system and (2) to create a tsunami hazard map in the Kukup Coastal Area. Coastal systems can be identified by analyzing the physical and socio-economic conditions. Physical conditions such as morphological and coastal typology can be extracted from Digital Elevation Model (DEM) from aerial photo processing. Socio-economic conditions such as land use analysis and tourism activities can be extracted from orthophoto, which is extracted from aerial photo processing using drones. The tsunami hazard can be analyzed using three modelling stages: earthquake source modelling, tsunami wave propagation modelling, and tsunami inundation modelling using Geographic Information System (GIS). The results show that the morphological conditions in the study area were dominated by the formation of conical hills with a firm lineament pattern causing the formation of elongated basins such as labyrinths. This basin is a place for developing socio-economic activities, especially tourism, which can be seen from a large amount of built-up land area. The presence of these basins causes the tsunami inundation pattern to extend perpendicular to the shoreline, causing the tsunami inundation in the study area to extend as far as 2 km from the shoreline.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42352065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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