Alkot Reda Mohamed, Zakaria Yehia Abd El Gawad, M. Voda
: The article is analyzing the use of WebGIS for tourism development in historic Cairo which is considered as an open-air museum, designing the touristic map and publishing it on the web as an interactive map. ArcGIS Server and WebGIS were used to create and promote a platform guide for tourists enabling them to find the touristic places and services in an easy and quickly manner. Therefore, by using the WebGIS, the digitization of the cultural heritage will create a large quantity of digital images and maps of the study area, leading to an easy and accurate identification, analysis and interpretation of geographical data and touristic places attributes. The research results will contribute to local authorities better planning and decision-making process, having good impacts on the touristic development of Egypt in general.
{"title":"USING WEB GIS FOR MARKETING HISTORICAL DESTINATION CAIRO, EGYPT","authors":"Alkot Reda Mohamed, Zakaria Yehia Abd El Gawad, M. Voda","doi":"10.21163/gt_2021.162.16","DOIUrl":"https://doi.org/10.21163/gt_2021.162.16","url":null,"abstract":": The article is analyzing the use of WebGIS for tourism development in historic Cairo which is considered as an open-air museum, designing the touristic map and publishing it on the web as an interactive map. ArcGIS Server and WebGIS were used to create and promote a platform guide for tourists enabling them to find the touristic places and services in an easy and quickly manner. Therefore, by using the WebGIS, the digitization of the cultural heritage will create a large quantity of digital images and maps of the study area, leading to an easy and accurate identification, analysis and interpretation of geographical data and touristic places attributes. The research results will contribute to local authorities better planning and decision-making process, having good impacts on the touristic development of Egypt in general.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42026345","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}
: Since a few years or decades, climate change has an impact felt in a very visible way in everyday life. People are increasingly confronted with its negative effects. Naturally, scientific research on the subject is multiplying. The present exploratory study attempts to present a network modelling approach on studying climate change. Networks are increasingly present in different areas of life, but have not played a significant role in climate research. This publication attempts to assess climate changes at five municipalities in Hungary by developing and analyzing three network data models. The developed different data models provide an opportunity to approach climate change from different perspectives, as the change itself is multifaceted. Data analyses are based solely on the structural indicators of the constructed networks, the measured weather characteristics only contributing to the construction of the data model. The obtained results for each location and season are complex, but interpreting them together helps to see the variations and their different nature.
{"title":"BUILDING AND EXPLORING NETWORK DATA MODEL FOR A SEASON LEVEL CLIMATE CHANGE STUDY FOR FIVE LARGE CITIES IN HUNGARY","authors":"Zsolt Magyari-Saska","doi":"10.21163/gt_2021.162.15","DOIUrl":"https://doi.org/10.21163/gt_2021.162.15","url":null,"abstract":": Since a few years or decades, climate change has an impact felt in a very visible way in everyday life. People are increasingly confronted with its negative effects. Naturally, scientific research on the subject is multiplying. The present exploratory study attempts to present a network modelling approach on studying climate change. Networks are increasingly present in different areas of life, but have not played a significant role in climate research. This publication attempts to assess climate changes at five municipalities in Hungary by developing and analyzing three network data models. The developed different data models provide an opportunity to approach climate change from different perspectives, as the change itself is multifaceted. Data analyses are based solely on the structural indicators of the constructed networks, the measured weather characteristics only contributing to the construction of the data model. The obtained results for each location and season are complex, but interpreting them together helps to see the variations and their different nature.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41459302","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}
Marelianda Al Dianty, F. J. Putuhena, D. Mah, R. Bustami, Fachrian Kanafani
: The storm in the early hours on the first day of 2020 had recorded the highest intensity of rainfall since 1996. It deluged Jakarta as the capital city of Indonesia and the surrounding satellite cities which including Tangerang Selatan. An urban housing area in Tangerang Selatan, located adjacent to the Ciputat river is selected as study area. The area was affected by floods since the urban housing was established. The United States Environmental Protection Agency’s Storm Water Management Model version 5.1 was used for finding out the hydrological and hydraulic problems. The model indicated that the flows from the sub-catchments did not contribute to cause flood. It was discovered that backwater effects occurred in the Ciputat river was the main cause of flooding. Thus, the existing drainage channels were overwhelmed by additional flow from the river.
{"title":"FLOOD RECONSTRUCTION OF 1st JANUARY 2020 STORM IN AN URBAN HOUSING AREA OF TANGERANG SELATAN, INDONESIA","authors":"Marelianda Al Dianty, F. J. Putuhena, D. Mah, R. Bustami, Fachrian Kanafani","doi":"10.21163/gt_2021.162.14","DOIUrl":"https://doi.org/10.21163/gt_2021.162.14","url":null,"abstract":": The storm in the early hours on the first day of 2020 had recorded the highest intensity of rainfall since 1996. It deluged Jakarta as the capital city of Indonesia and the surrounding satellite cities which including Tangerang Selatan. An urban housing area in Tangerang Selatan, located adjacent to the Ciputat river is selected as study area. The area was affected by floods since the urban housing was established. The United States Environmental Protection Agency’s Storm Water Management Model version 5.1 was used for finding out the hydrological and hydraulic problems. The model indicated that the flows from the sub-catchments did not contribute to cause flood. It was discovered that backwater effects occurred in the Ciputat river was the main cause of flooding. Thus, the existing drainage channels were overwhelmed by additional flow from the river.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42607379","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}
Z. Zylshal, A. A. Bayanuddin, Ferman Setia Nugroho, S. Munawar
: The topographic effect on satellite imagery has long been acknowledged and several methods have been proposed to address it. These methods mostly employ a digital elevation model to identify topographic conditions. The availability of various digital elevation models (DEMs) with different spatial resolutions prompts a thorough investigation to select suitable data for use when correcting the topographic effect on high-resolution satellite imagery. The release of Digital Elevation Model Nasional (DEMNAS) with its 8-meter spatial resolution provides a similar spatial resolution with SPOT-6/7 multispectral data (6 meters). This study presents our results for topographic correction performed using three different DEMs on orthorectified SPOT-6/7 multispectral data. These DEMs are Shuttle Radar Topography Mission (SRTM) and ALOS World 3D 30 meters (AW3D30), as well as DEMNAS. All three DEMs were resampled to match SPOT-6/7 spatial resolution (6 meters). Atmospheric correction using the MODTRAN-4 algorithm was conducted on the SPOT-6/7 multispectral images. Our study was conducted on two test sites located in the mountainous region over South Sulawesi Province, Indonesia. The Minnaert correction was chosen as the correction algorithm with the k constant calculated for each band over forest land cover. To evaluate the performance of each DEM, visual evaluation and statistical assessment were employed. Pixel values before and after topographic correction were compared over sunlit as well as shaded forest. Coefficient of variation (CV) was used as the statistical assessment tool. Our results show that AW3D30 is able to reduce the topographic effect on SPOT-6/7 multispectral images. The correlation ( r ) between image surface reflectance value and local illumination were reduced from 0.78 to - 0.06 for the best performer on the NIR infrared band. CV was also reduced from 24.46 to 19.02 for the same NIR band. AW3D30 performed the best without the apparent under- and over-correction produced by the two other DEMs. Tweaks and modifications are found to be necessary to resolve the under-correction encountered when using SRTM and the over-correction associated with using DEMNAS on SPOT-6/7 multispectral imagery.
{"title":"CORRECTING THE TOPOGRAPHIC EFFECT ON SPOT-6/ 7 MULTISPECTRAL IMAGERIES: A COMPARISON OF DIFFERENT DIGITAL ELEVATION MODELS","authors":"Z. Zylshal, A. A. Bayanuddin, Ferman Setia Nugroho, S. Munawar","doi":"10.21163/gt_2021.163.13","DOIUrl":"https://doi.org/10.21163/gt_2021.163.13","url":null,"abstract":": The topographic effect on satellite imagery has long been acknowledged and several methods have been proposed to address it. These methods mostly employ a digital elevation model to identify topographic conditions. The availability of various digital elevation models (DEMs) with different spatial resolutions prompts a thorough investigation to select suitable data for use when correcting the topographic effect on high-resolution satellite imagery. The release of Digital Elevation Model Nasional (DEMNAS) with its 8-meter spatial resolution provides a similar spatial resolution with SPOT-6/7 multispectral data (6 meters). This study presents our results for topographic correction performed using three different DEMs on orthorectified SPOT-6/7 multispectral data. These DEMs are Shuttle Radar Topography Mission (SRTM) and ALOS World 3D 30 meters (AW3D30), as well as DEMNAS. All three DEMs were resampled to match SPOT-6/7 spatial resolution (6 meters). Atmospheric correction using the MODTRAN-4 algorithm was conducted on the SPOT-6/7 multispectral images. Our study was conducted on two test sites located in the mountainous region over South Sulawesi Province, Indonesia. The Minnaert correction was chosen as the correction algorithm with the k constant calculated for each band over forest land cover. To evaluate the performance of each DEM, visual evaluation and statistical assessment were employed. Pixel values before and after topographic correction were compared over sunlit as well as shaded forest. Coefficient of variation (CV) was used as the statistical assessment tool. Our results show that AW3D30 is able to reduce the topographic effect on SPOT-6/7 multispectral images. The correlation ( r ) between image surface reflectance value and local illumination were reduced from 0.78 to - 0.06 for the best performer on the NIR infrared band. CV was also reduced from 24.46 to 19.02 for the same NIR band. AW3D30 performed the best without the apparent under- and over-correction produced by the two other DEMs. Tweaks and modifications are found to be necessary to resolve the under-correction encountered when using SRTM and the over-correction associated with using DEMNAS on SPOT-6/7 multispectral imagery.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":"85 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41272252","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}
Ramón Ripoll, Jordi Gomis, Carlos Turón, G. Barbeta, M. Chamorro
: The relationship between traditional farmers with the physical characteristics of the site (material function) has long been analysed, but rarely has farmers’ cultural relationship with their geographical environment (emotional function) been upheld. To demonstrate this duality implies finding farmland created both due to material profitability or family subsistence and due to psychological necessity or personal self-realization. For example, the transformation in the nineteenth century of desolate, stony unproductive landscapes in la Garriga d'Empordà -Catalonia- (of some 8 km²) into farmland, for poorer peasant families meant not only a minuscule means of material progress but above all a major means of social hope and human dignity. To confirm this duality is to corroborate that many functional territories are also emotional landscapes for those who farm them, mainly during the period of major agricultural expansion in Europe due to the growth in population at the onset of the modern era.
传统农民与遗址的物理特征(物质功能)之间的关系一直被分析，但农民与其地理环境的文化关系(情感功能)却很少得到重视。要证明这种两重性，就意味着要找到既因物质利益或家庭生存而创造的农田，又因心理需要或个人自我实现而创造的农田。例如，在19世纪，加泰罗尼亚的la Garriga d' empord(约8平方公里)荒凉、多石、贫瘠的土地被改造成农田，对较贫穷的农民家庭来说，这不仅意味着物质进步的微小手段，而且最重要的是社会希望和人类尊严的主要手段。要确认这种二元性，就需要确认许多功能性领土对于那些耕种这些领土的人来说也是情感景观，主要是在现代开始时人口增长导致欧洲农业大规模扩张的时期。
{"title":"FUNCTIONAL LAND AND EMOTIONAL LANDSCAPE. DRY STONE CONSTRUCTIONS IN LA GARRIGA D'EMPORDÀ IN THE 19TH CENTURY","authors":"Ramón Ripoll, Jordi Gomis, Carlos Turón, G. Barbeta, M. Chamorro","doi":"10.21163/gt_2021.162.13","DOIUrl":"https://doi.org/10.21163/gt_2021.162.13","url":null,"abstract":": The relationship between traditional farmers with the physical characteristics of the site (material function) has long been analysed, but rarely has farmers’ cultural relationship with their geographical environment (emotional function) been upheld. To demonstrate this duality implies finding farmland created both due to material profitability or family subsistence and due to psychological necessity or personal self-realization. For example, the transformation in the nineteenth century of desolate, stony unproductive landscapes in la Garriga d'Empordà -Catalonia- (of some 8 km²) into farmland, for poorer peasant families meant not only a minuscule means of material progress but above all a major means of social hope and human dignity. To confirm this duality is to corroborate that many functional territories are also emotional landscapes for those who farm them, mainly during the period of major agricultural expansion in Europe due to the growth in population at the onset of the modern era.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41498892","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}
: Shrimp production was the high demand for the popular in the global market in Thailand. The change of land use is important for the management and monitoring of land use changed. The objectives of this paper to (1) classification of shrimp farm using artificial neural networks (ANN) technique from the Sentinel-2 imagery. (2) change detection of land use changes map among 2015, 2018, and 2020. The land use classification based on ANN technique and the accuracy assessment by used the confusion matrices and kappa coefficient. The classify of land use classes divide into built-up, forest, water bodies, paddy field, shrimp farm, and field crop. The change detection methods used was the image differencing technique was performed to the land use changes map. The result of land use classification show that the field crop area was 80% cover the most area. The result of land use changed show that built-up, paddy field, and shrimp farm increased throughout between year 2015 to 2020. The shrimp farm between year 2015 to 2020 to increasing trend of related with the shrimp production was the high demand for the popular in the global market. layer. The several ANN models have been applied in land use classification such as Hopfield network, self-organizing competition, radial basis function, multilayer perception,
{"title":"ARTIFICIAL NEURAL NETWORKS FOR THE CLASSIFICATION OF SHRIMP FARM FROM SATELLITE IMAGERY","authors":"Ilada Aroonsri, Satith Sangpradid","doi":"10.21163/gt_2021.162.12","DOIUrl":"https://doi.org/10.21163/gt_2021.162.12","url":null,"abstract":": Shrimp production was the high demand for the popular in the global market in Thailand. The change of land use is important for the management and monitoring of land use changed. The objectives of this paper to (1) classification of shrimp farm using artificial neural networks (ANN) technique from the Sentinel-2 imagery. (2) change detection of land use changes map among 2015, 2018, and 2020. The land use classification based on ANN technique and the accuracy assessment by used the confusion matrices and kappa coefficient. The classify of land use classes divide into built-up, forest, water bodies, paddy field, shrimp farm, and field crop. The change detection methods used was the image differencing technique was performed to the land use changes map. The result of land use classification show that the field crop area was 80% cover the most area. The result of land use changed show that built-up, paddy field, and shrimp farm increased throughout between year 2015 to 2020. The shrimp farm between year 2015 to 2020 to increasing trend of related with the shrimp production was the high demand for the popular in the global market. layer. The several ANN models have been applied in land use classification such as Hopfield network, self-organizing competition, radial basis function, multilayer perception,","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42848107","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}
Muhamad Khairul Rosyidy, M. Dimyati, I. P. A. Shidiq, F. Zulkarnain, Nurul Sri Rahaningtyas, Riza Putera Syamsuddin, Farhan Makarim Zein
Landslide is a natural phenomenon that frequently occurs on the Java Island of Indonesia, causing significant damage and casualties. Due to advances in remote sensing technology, radar imaging can detect and evaluate ground surface deformation. This study examines the ground surface deformation and displacement in each landslide location in terms of spatial and temporal and identifies the different types and characteristics of landslides in the Sukabumi area of West Java, Indonesia. The Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) methodology was used in this study, and the DinSAR method was applied. We combined the LiCSAR data product with the Python coding-based LiCSBAS processing package to derive a surface displacement value at each landslide location. The results show that the DinSAR approach can detect surface deformation by integrating the LiCSAR product with the Python coding-based LiCSBAS processing software. According to quantitative data, the research area experienced surface deformation with a surface displacement velocity of -36,297 mm/year to 58,837 mm/year. The ground surface displacement at each landslide location ranged from -9.79 mm/year to +33.69 mm/year, with most of the landslides occurring on moderate to steep slopes (16-35). These results are suitable to use for support regional development planning in reducing losses and casualties. Key-words: Displacement, Deformation, Landslide, LICSBAS, SBAS-InSAR
{"title":"LANDSLIDE SURFACE DEFORMATION ANALYSIS USING SBAS-INSAR IN THE SOUTHERN PART OF THE SUKABUMI AREA, INDONESIA","authors":"Muhamad Khairul Rosyidy, M. Dimyati, I. P. A. Shidiq, F. Zulkarnain, Nurul Sri Rahaningtyas, Riza Putera Syamsuddin, Farhan Makarim Zein","doi":"10.21163/gt_2021.163.11","DOIUrl":"https://doi.org/10.21163/gt_2021.163.11","url":null,"abstract":"Landslide is a natural phenomenon that frequently occurs on the Java Island of Indonesia, causing significant damage and casualties. Due to advances in remote sensing technology, radar imaging can detect and evaluate ground surface deformation. This study examines the ground surface deformation and displacement in each landslide location in terms of spatial and temporal and identifies the different types and characteristics of landslides in the Sukabumi area of West Java, Indonesia. The Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) methodology was used in this study, and the DinSAR method was applied. We combined the LiCSAR data product with the Python coding-based LiCSBAS processing package to derive a surface displacement value at each landslide location. The results show that the DinSAR approach can detect surface deformation by integrating the LiCSAR product with the Python coding-based LiCSBAS processing software. According to quantitative data, the research area experienced surface deformation with a surface displacement velocity of -36,297 mm/year to 58,837 mm/year. The ground surface displacement at each landslide location ranged from -9.79 mm/year to +33.69 mm/year, with most of the landslides occurring on moderate to steep slopes (16-35). These results are suitable to use for support regional development planning in reducing losses and casualties. Key-words: Displacement, Deformation, Landslide, LICSBAS, SBAS-InSAR","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47162682","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}
V. Baiocchi, F. Vatore, M. Lombardi, F. Monti, R. Onori
: Recent events, including the floods in central Europe in May 2021, have highlighted how climate change is giving rise to scenarios that were neither foreseen nor predictable. One problem this poses is the need to rethink the logic of various environmental constraints that are often based on return times of 20-50 years or 100-200. A single event does not change the statistical expectations for the recurrence of the event itself, but the recurrence of several extraordinary events in a few years is a clear indication of a changing trend. The prevention of the effects of such events is based on the definition of the areas at greater or lesser risk specifically based on the return times of the exceptional events, so it is foreseeable that a series of territorial plans, mostly carried out a few decades ago, will have to be updated or re-executed from scratch. These reworkings will be able to take advantage of the open-source software and open spatial data that have become available in the meantime, facilitating the entire process, and making it more open and shareable. In this paper we tested on a real case (the May 1999 pyroclastic flows in Campania, southern Italy) the actual possibility of implementing a model for forecasting such events using only open-source software and open data. It has been demonstrated that the entire process can be carried out using only open-source resources and it has been verified that the predictions of the hazard and risk model obtained with only input data prior to the event, give an output prediction that is significantly coincident with the events that actually occurred as documented by the authorities.
{"title":"The Contribution of Open-Source GIS Software and Open Spatial Data for the Re-Evaluation of Landslide Risk and Hazard in View of Climate Change","authors":"V. Baiocchi, F. Vatore, M. Lombardi, F. Monti, R. Onori","doi":"10.21163/gt_2021.163.12","DOIUrl":"https://doi.org/10.21163/gt_2021.163.12","url":null,"abstract":": Recent events, including the floods in central Europe in May 2021, have highlighted how climate change is giving rise to scenarios that were neither foreseen nor predictable. One problem this poses is the need to rethink the logic of various environmental constraints that are often based on return times of 20-50 years or 100-200. A single event does not change the statistical expectations for the recurrence of the event itself, but the recurrence of several extraordinary events in a few years is a clear indication of a changing trend. The prevention of the effects of such events is based on the definition of the areas at greater or lesser risk specifically based on the return times of the exceptional events, so it is foreseeable that a series of territorial plans, mostly carried out a few decades ago, will have to be updated or re-executed from scratch. These reworkings will be able to take advantage of the open-source software and open spatial data that have become available in the meantime, facilitating the entire process, and making it more open and shareable. In this paper we tested on a real case (the May 1999 pyroclastic flows in Campania, southern Italy) the actual possibility of implementing a model for forecasting such events using only open-source software and open data. It has been demonstrated that the entire process can be carried out using only open-source resources and it has been verified that the predictions of the hazard and risk model obtained with only input data prior to the event, give an output prediction that is significantly coincident with the events that actually occurred as documented by the authorities.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49140107","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}
N. A. Haris, S. S. Kusuma, S. Arjasakusuma, P. Wicaksono
: The identification of land cover and land use is necessary to support the strategic management of coastal areas. The utilization of remote sensing technology such as synthetic aperture radar (SAR) data has been widely used for mapping the distribution of land cover and land use. This application includes the detection of aquaculture ponds in coastal areas due to SAR’s sensitivity to surface water content. In addition, multitemporal Sentinel-1 data helps to distinguish between ponds and rice fields that possess a visually similar appearance during the flooding stage. This study aims to explore the accuracy of the gray level of co-occurrence model (GCLM) textures of multitemporal Sentinel-1 data for aquaculture pond mapping in Brebes Regency, Central Java Province, Indonesia. In addition, single-date Sentinel-2 optical imagery was used to compare the results from Sentinel-1 data. The Sentinel-2 data has been identified using supervised classifications, e.g., maximum likelihood (ML), minimum distance (MD), random forest (RF), and K-nearest neighbor (KNN) algorithms, and the most accurate algorithm was selected to classify the Sentinel-1 data using GLCM textures. The results indicated that the Sentinel-1 imagery showed the best results using GLCM metrics from VH polarization with an accuracy value of 92.2% using the ML algorithm, while the best results from Sentinel-2 were also produced using ML, with an 88.4% overall accuracy. These results demonstrate that multitemporal Sentinel-1 data have higher accuracy than Sentinel-2 data when used for pond detection. This shows the potential of the combination of both sensors to increase the accuracy of aquaculture pond mapping.
{"title":"COMPARISON OF SENTINEL-2 AND MULTITEMPORAL SENTINEL-1 SAR IMAGERY FOR MAPPING AQUACULTURE POND DISTRIBUTION IN THE COASTAL REGION OF BREBES REGENCY, CENTRAL JAVA, INDONESIA","authors":"N. A. Haris, S. S. Kusuma, S. Arjasakusuma, P. Wicaksono","doi":"10.21163/gt_2021.163.10","DOIUrl":"https://doi.org/10.21163/gt_2021.163.10","url":null,"abstract":": The identification of land cover and land use is necessary to support the strategic management of coastal areas. The utilization of remote sensing technology such as synthetic aperture radar (SAR) data has been widely used for mapping the distribution of land cover and land use. This application includes the detection of aquaculture ponds in coastal areas due to SAR’s sensitivity to surface water content. In addition, multitemporal Sentinel-1 data helps to distinguish between ponds and rice fields that possess a visually similar appearance during the flooding stage. This study aims to explore the accuracy of the gray level of co-occurrence model (GCLM) textures of multitemporal Sentinel-1 data for aquaculture pond mapping in Brebes Regency, Central Java Province, Indonesia. In addition, single-date Sentinel-2 optical imagery was used to compare the results from Sentinel-1 data. The Sentinel-2 data has been identified using supervised classifications, e.g., maximum likelihood (ML), minimum distance (MD), random forest (RF), and K-nearest neighbor (KNN) algorithms, and the most accurate algorithm was selected to classify the Sentinel-1 data using GLCM textures. The results indicated that the Sentinel-1 imagery showed the best results using GLCM metrics from VH polarization with an accuracy value of 92.2% using the ML algorithm, while the best results from Sentinel-2 were also produced using ML, with an 88.4% overall accuracy. These results demonstrate that multitemporal Sentinel-1 data have higher accuracy than Sentinel-2 data when used for pond detection. This shows the potential of the combination of both sensors to increase the accuracy of aquaculture pond mapping.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49498191","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}
Mohamed Aghad, Mohamed Manaouch, M. Sadiki, Mohcine Batchi, J. A. Karkouri
: The rising need for water coupled with an increasing scarcity in many parts across the world especially in the middle east and north african countries (MENA) requires more sustainable solutions for effective water conservation. In Morocco, water ressource is characterized by significant spatio-temporal variability. So, to ensure the availability of water for domestic and agro-industrial uses, it is advised to develop some alternatives that improve the local water resources management throughout the country. Rainwater harvesting (RWH) has been proven to be a very promising alternative to water shortage problem. However, identifying appropriate sites for RWH remains a complex task in the management of rainwater. The present study aims to identify optimal sites for RWH using GIS based Fuzzy Analytical Hierarchy Process (FAHP) method in the Kenitra province, NW Morocco. For preparing thematic layers, several data sources were used including remote sensing data (RS), digital elevation model (DEM), the soil and precipitation data were used to create the necessary database using ArcGIS software. Next, the model of the soil conservation service-curve number (SCS-CN) was adopted to generate the map of the annual potential runoff. Then, five thematic layers including runoff, slope, soil texture, land use/land cover (LULC) and drainage density were assigned apropriate weights for generating the RWH suitability map. The resultant map of runoff depth revealed that it ranges from 137 to 738 mm. Moreover, the RWH suitability map showed that Kenitra province can be classed into five RWH candidate areas: (i) unsuitable (12.7%), (ii) less suitable (10.9%), (iii) suitable (20.3%), (iv) very suitable (36%) and (v) extremely suitable (19.9%). The extremely suitable areas for RWH are distributed in the central and northeastern parts. Based on the area under curve (AUC) of the receiver operating caracteristics (ROC), the success rate for predicting suitable RWH sites was 51%.
{"title":"IDENTIFYING SUITABLE SITES FOR RAINWATER HARVESTING USING RUNOFF MODEL (SCS-CN), REMOTE SENSING AND GIS BASED FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP) IN KENITRA PROVINCE, NW MOROCCO","authors":"Mohamed Aghad, Mohamed Manaouch, M. Sadiki, Mohcine Batchi, J. A. Karkouri","doi":"10.21163/gt_2021.163.09","DOIUrl":"https://doi.org/10.21163/gt_2021.163.09","url":null,"abstract":": The rising need for water coupled with an increasing scarcity in many parts across the world especially in the middle east and north african countries (MENA) requires more sustainable solutions for effective water conservation. In Morocco, water ressource is characterized by significant spatio-temporal variability. So, to ensure the availability of water for domestic and agro-industrial uses, it is advised to develop some alternatives that improve the local water resources management throughout the country. Rainwater harvesting (RWH) has been proven to be a very promising alternative to water shortage problem. However, identifying appropriate sites for RWH remains a complex task in the management of rainwater. The present study aims to identify optimal sites for RWH using GIS based Fuzzy Analytical Hierarchy Process (FAHP) method in the Kenitra province, NW Morocco. For preparing thematic layers, several data sources were used including remote sensing data (RS), digital elevation model (DEM), the soil and precipitation data were used to create the necessary database using ArcGIS software. Next, the model of the soil conservation service-curve number (SCS-CN) was adopted to generate the map of the annual potential runoff. Then, five thematic layers including runoff, slope, soil texture, land use/land cover (LULC) and drainage density were assigned apropriate weights for generating the RWH suitability map. The resultant map of runoff depth revealed that it ranges from 137 to 738 mm. Moreover, the RWH suitability map showed that Kenitra province can be classed into five RWH candidate areas: (i) unsuitable (12.7%), (ii) less suitable (10.9%), (iii) suitable (20.3%), (iv) very suitable (36%) and (v) extremely suitable (19.9%). The extremely suitable areas for RWH are distributed in the central and northeastern parts. Based on the area under curve (AUC) of the receiver operating caracteristics (ROC), the success rate for predicting suitable RWH sites was 51%.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43856435","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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