Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-61-2020
S. Anuar, A. A. M. Nasir, S. Azri, U. Ujang, Z. Majid, M. G. Cuétara, G. M. Retortillo
Abstract. In recent years, there has been an increase in development of urbanization in the world. Nowadays, all communities in the world are concerned about current technological developments especially in terms of development and management that can facilitate their daily life. In urbanization, smart city is one of modernization changes that improves the infrastructure management, convenience and efficient for the life of citizens. Moreover, 3D asset management is one of the approach of smart city development. Asset management using the 3D concept has been witnessing a welcoming approach due to its high efficiency in organising multiple assets. 3D geometric extraction offers a perfect aid in recording information of an asset such as buildings. The model is derived from the reality techniques where the exterior surfaces of an object are captured in high resolution through the means of special equipment such as airborne imagery. From here, point clouds are generated where the sets of points based on the external surfaces of an object are present. Pre-processing of point clouds should be done in order to perform the 3D modelling. In dealing with point clouds, segmentations are used to investigate the structure of the object with information regarding to different level of sections. The boon behind this segmentation process is to identify different features that is available for the object. In this research, the aim is to analyse the different methodology and algorithm available to segment the point cloud data. Comparison between the results will be made to identify the advantages and disadvantages of the results for the use of asset management.
{"title":"3D GEOMETRIC EXTRACTION USING SEGMENTATION FOR ASSET MANAGEMENT","authors":"S. Anuar, A. A. M. Nasir, S. Azri, U. Ujang, Z. Majid, M. G. Cuétara, G. M. Retortillo","doi":"10.5194/isprs-archives-xliv-4-w3-2020-61-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-61-2020","url":null,"abstract":"Abstract. In recent years, there has been an increase in development of urbanization in the world. Nowadays, all communities in the world are concerned about current technological developments especially in terms of development and management that can facilitate their daily life. In urbanization, smart city is one of modernization changes that improves the infrastructure management, convenience and efficient for the life of citizens. Moreover, 3D asset management is one of the approach of smart city development. Asset management using the 3D concept has been witnessing a welcoming approach due to its high efficiency in organising multiple assets. 3D geometric extraction offers a perfect aid in recording information of an asset such as buildings. The model is derived from the reality techniques where the exterior surfaces of an object are captured in high resolution through the means of special equipment such as airborne imagery. From here, point clouds are generated where the sets of points based on the external surfaces of an object are present. Pre-processing of point clouds should be done in order to perform the 3D modelling. In dealing with point clouds, segmentations are used to investigate the structure of the object with information regarding to different level of sections. The boon behind this segmentation process is to identify different features that is available for the object. In this research, the aim is to analyse the different methodology and algorithm available to segment the point cloud data. Comparison between the results will be made to identify the advantages and disadvantages of the results for the use of asset management.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"41 1","pages":"61-69"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76958401","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-335-2020
T. M. Özbekler, A. Akgul
Abstract. As current cities are attributed to particular dynamism consists of population density and increased urbanization, urban areas are facing some challenges for city logistics, both in terms of economic, environmental, and social impact. Especially, the debates over last-mile logistics are arising with inefficiencies in delivery cost (half truckload on delivery) and delivery time per parcel (unnecessary waiting-load periods at multiple stops) while inner-urban areas are especially suffered from traffic congestion, emission, and noise pollution. In this regard, smart cities as a concept with the potential to produce sustainable solutions to urban problems bring along with the need for innovative urban logistics systems to make conventional distribution channels of the city up to date. The key objective tackled in this paper can be defined as the identification of the city logistics schemes with highlighting current approaches in smart cities. The study adopts a systemic approach based on the typology of consolidation-distribution schemes in city logistics to define the feasibility of micro logistics initiatives from the scope of the smart city consisting of mobility, sustainability, and liveability. Thanks to a detailed examination of city logistics dynamics, this study can contribute theoretically to smart city logistics literature as well as practically the logistics sector.
{"title":"LAST MILE LOGISTICS IN THE FRAMEWORK OF SMART CITIES: A TYPOLOGY OF CITY LOGISTICS SCHEMES","authors":"T. M. Özbekler, A. Akgul","doi":"10.5194/isprs-archives-xliv-4-w3-2020-335-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-335-2020","url":null,"abstract":"Abstract. As current cities are attributed to particular dynamism consists of population density and increased urbanization, urban areas are facing some challenges for city logistics, both in terms of economic, environmental, and social impact. Especially, the debates over last-mile logistics are arising with inefficiencies in delivery cost (half truckload on delivery) and delivery time per parcel (unnecessary waiting-load periods at multiple stops) while inner-urban areas are especially suffered from traffic congestion, emission, and noise pollution. In this regard, smart cities as a concept with the potential to produce sustainable solutions to urban problems bring along with the need for innovative urban logistics systems to make conventional distribution channels of the city up to date. The key objective tackled in this paper can be defined as the identification of the city logistics schemes with highlighting current approaches in smart cities. The study adopts a systemic approach based on the typology of consolidation-distribution schemes in city logistics to define the feasibility of micro logistics initiatives from the scope of the smart city consisting of mobility, sustainability, and liveability. Thanks to a detailed examination of city logistics dynamics, this study can contribute theoretically to smart city logistics literature as well as practically the logistics sector.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"10 1","pages":"335-337"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78546968","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-241-2020
A. Haddach
Abstract. This paper is based on the analysis of ninety-six articles published over twenty-one years, between 1991 and 2012 concerning integration of sustainable development objectives into supply chain management. Disciplinary and geographical origin of authors shows a growing interest in the integration of sustainable development in supply chain management for scientific world, but maturity of this subject remains limited and the most of these studies still exploratory. A more in-depth study of these works therefore seems relevant. Analysis of these works highlights several economic, environmental and social concepts which concern the diffusion of sustainable development in daily activities of supply chain like financial performance, productivity, environmental management systems and Human rights. This work will look at the main sustainable development issues which characterize global performance (integration of economic, environmental and social performances) of supply chain and impact of sustainable practices on performances of this chain, as they appear in studied articles.
{"title":"SPECIFICATION OF LOGISTIC CHAIN SUSTAINABILITY: ENVIRONMENTAL, SOCIAL AND ECONOMIC ISSUES","authors":"A. Haddach","doi":"10.5194/isprs-archives-xliv-4-w3-2020-241-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-241-2020","url":null,"abstract":"Abstract. This paper is based on the analysis of ninety-six articles published over twenty-one years, between 1991 and 2012 concerning integration of sustainable development objectives into supply chain management. Disciplinary and geographical origin of authors shows a growing interest in the integration of sustainable development in supply chain management for scientific world, but maturity of this subject remains limited and the most of these studies still exploratory. A more in-depth study of these works therefore seems relevant. Analysis of these works highlights several economic, environmental and social concepts which concern the diffusion of sustainable development in daily activities of supply chain like financial performance, productivity, environmental management systems and Human rights. This work will look at the main sustainable development issues which characterize global performance (integration of economic, environmental and social performances) of supply chain and impact of sustainable practices on performances of this chain, as they appear in studied articles.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"46 1 1","pages":"241-248"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79909798","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-81-2020
A. Awad, H. Ali, S. Abujayyab, I. R. Karas, D. Sumunar
Abstract. The massive disasters that arise by nature and humanity are significantly leads to several losses in lives and infrastructures. Disasters such as chemical explosions, flash floods and volcanoes. The high level of preparedness from the governments and administration authorities and ambulance services can significantly reduce the losses in lives. The aim of this paper is to measure the spatial readiness of ambulance facilities for natural disasters using GIS networks analysis. The measurement performed based on three standards, the area covered by the ambulance service, speed of service and the proportion to the population. ArcGIS spatial analysis and network analysis tools employed to develop the coverage maps of the three measured standards. According to the analysis, 94.4% from the study area appeared within the standard distance (20 km) from the ambulance stations, while 91% from the study area appeared within the time response standard (15 minutes) from the ambulance stations. The study area has a deficit of 256,714 people and needs 5 additional ambulances to achieve the demographic standard. The main recommendation of this study is to apply this methodology regularly in the study area to avoid any weakness before the disasters and to increase the level of preparedness.
{"title":"MEASURING THE SPATIAL READINESS OF AMBULANCE FACILITIES FOR NATURAL DISASTERS USING GIS NETWORKS ANALYSIS","authors":"A. Awad, H. Ali, S. Abujayyab, I. R. Karas, D. Sumunar","doi":"10.5194/isprs-archives-xliv-4-w3-2020-81-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-81-2020","url":null,"abstract":"Abstract. The massive disasters that arise by nature and humanity are significantly leads to several losses in lives and infrastructures. Disasters such as chemical explosions, flash floods and volcanoes. The high level of preparedness from the governments and administration authorities and ambulance services can significantly reduce the losses in lives. The aim of this paper is to measure the spatial readiness of ambulance facilities for natural disasters using GIS networks analysis. The measurement performed based on three standards, the area covered by the ambulance service, speed of service and the proportion to the population. ArcGIS spatial analysis and network analysis tools employed to develop the coverage maps of the three measured standards. According to the analysis, 94.4% from the study area appeared within the standard distance (20 km) from the ambulance stations, while 91% from the study area appeared within the time response standard (15 minutes) from the ambulance stations. The study area has a deficit of 256,714 people and needs 5 additional ambulances to achieve the demographic standard. The main recommendation of this study is to apply this methodology regularly in the study area to avoid any weakness before the disasters and to increase the level of preparedness.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"40 1","pages":"81-84"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84820052","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-89-2020
A. C. Aydinoglu, R. Bovkir
Abstract. Successful land information management is an important issue for governments in regards to sustainable development. Reliable and comprehensive data about land and all related factors are essential for effective land policies. Various land related legal applications such as planning, taxation, property management, mortgage, and real estate investments require interoperable, extensive and realistic information about the land and real property. GIS provides greater insight into land by its capability to advance geographic analysis in different aspects. The statistical analysis capabilities of GIS increase the efficiency and accuracy of the evaluations related to land and real estate. Along with the developments of information and communication technologies, modern GIS technologies can handle large and complex data. Web-based and mobile GIS technologies provide the capability of operating and sharing local data and provide geographic analysis tools to users via the web. In this way, various mobile GIS applications can be developed in many different application areas. In this study, a mobile application titled as Smart Real Estate was developed for presenting urban real estate characteristics in different thematic groups by analysing data in different formats coming from different sources.
{"title":"DEVELOPING A MOBILE APPLICATION FOR SMART REAL ESTATE INFORMATION","authors":"A. C. Aydinoglu, R. Bovkir","doi":"10.5194/isprs-archives-xliv-4-w3-2020-89-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-89-2020","url":null,"abstract":"Abstract. Successful land information management is an important issue for governments in regards to sustainable development. Reliable and comprehensive data about land and all related factors are essential for effective land policies. Various land related legal applications such as planning, taxation, property management, mortgage, and real estate investments require interoperable, extensive and realistic information about the land and real property. GIS provides greater insight into land by its capability to advance geographic analysis in different aspects. The statistical analysis capabilities of GIS increase the efficiency and accuracy of the evaluations related to land and real estate. Along with the developments of information and communication technologies, modern GIS technologies can handle large and complex data. Web-based and mobile GIS technologies provide the capability of operating and sharing local data and provide geographic analysis tools to users via the web. In this way, various mobile GIS applications can be developed in many different application areas. In this study, a mobile application titled as Smart Real Estate was developed for presenting urban real estate characteristics in different thematic groups by analysing data in different formats coming from different sources.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"18 1","pages":"89-94"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87609991","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-53-2020
B. Anbaroğlu, I. Coşkun, H. H. Gürler
Abstract. This paper investigates the use of Augmented Reality (AR) in pedestrian wayfinding in two aspects. First, an experiment was conducted to understand whether an AR-based mobile platform improves finding the direction of a query destination compared to a paper map. A total of 54 participants were enrolled to represent each group, in which the task was to show the direction of a query point-of-interest (POI). The experiments were carried out at the Beytepe Campus of Hacettepe University. The results suggest that AR-based platform significantly improves the task completion time compared to a paper map. Second, an online questionnaire was conducted to understand the preference of participants in terms of visualising the distances of POIs on an AR-based platform. Four different methods were utilised which vary the colour and size of a POI depending on its distance to the user. The results suggest that the majority of the participants preferred visualising POIs with the same colour but with different sizes depending on their distance to the user. This finding adds further support to the default visualisation adopted in Mapbox, the technology that was used to develop the AR-based platform.
{"title":"WHICH WAY IS ‘YILDIZ AMFİ’? AUGMENTED REALITY VS. PAPER MAP ON PEDESTRIAN WAYFINDING","authors":"B. Anbaroğlu, I. Coşkun, H. H. Gürler","doi":"10.5194/isprs-archives-xliv-4-w3-2020-53-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-53-2020","url":null,"abstract":"Abstract. This paper investigates the use of Augmented Reality (AR) in pedestrian wayfinding in two aspects. First, an experiment was conducted to understand whether an AR-based mobile platform improves finding the direction of a query destination compared to a paper map. A total of 54 participants were enrolled to represent each group, in which the task was to show the direction of a query point-of-interest (POI). The experiments were carried out at the Beytepe Campus of Hacettepe University. The results suggest that AR-based platform significantly improves the task completion time compared to a paper map. Second, an online questionnaire was conducted to understand the preference of participants in terms of visualising the distances of POIs on an AR-based platform. Four different methods were utilised which vary the colour and size of a POI depending on its distance to the user. The results suggest that the majority of the participants preferred visualising POIs with the same colour but with different sizes depending on their distance to the user. This finding adds further support to the default visualisation adopted in Mapbox, the technology that was used to develop the AR-based platform.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"34 1","pages":"53-60"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83922332","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}
Pub Date : 2020-11-23DOI: 10.5194/ISPRS-ARCHIVES-XLIV-4-W3-2020-323-2020
Zineb Nassr, N. Sael, F. Benabbou
Abstract. Sentiment Analysis concerns the analysis of ideas, emotions, evaluations, values, attitudes and feelings about products, services, companies, individuals, tasks, events, titles and their characteristics. With the increase in applications on the Internet and social networks, Sentiment Analysis has become more crucial in the field of text mining research and has since been used to explore users’ opinions on various products or topics discussed on the Internet. Developments in the fields of Natural Language Processing and Computational Linguistics have contributed positively to Sentiment Analysis studies, especially for sentiments written in non-structured or semi-structured languages. In this paper, we present a literature review on the pre-processing task on the field of sentiment analysis and an analytical and comparative study of different researches conducted in Arabic social networks. This study allowed as concluding that several works have dealt with the generation of stop words dictionary. In this context, two approaches are adopted: first, the manual one, which gives rise to a limited list, and second, the automatic, where the list of stop words is extracted from social networks based on defined rules. For stemming two, algorithms have been proposed to isolate prefixes and suffixes from words in dialects. However, few works have been interested in dialects directly without translation. The Moroccan dialect in particular is considered as the 5th dialect studied among Arabic dialects after Jordanian, Egyptian, Tunisian and Algerian dialects. Despite the significant lack in studies carried out on Arabic dialects, we were able to extract several conclusions about the difficulties and challenges encountered through this comparative study, as well as the possible ways and tracks to study in any dialects sentiment analysis pre-processing solution.
{"title":"PREPROCESSING ARABIC DIALECT FOR SENTIMENT MINING: STATE OF ART","authors":"Zineb Nassr, N. Sael, F. Benabbou","doi":"10.5194/ISPRS-ARCHIVES-XLIV-4-W3-2020-323-2020","DOIUrl":"https://doi.org/10.5194/ISPRS-ARCHIVES-XLIV-4-W3-2020-323-2020","url":null,"abstract":"Abstract. Sentiment Analysis concerns the analysis of ideas, emotions, evaluations, values, attitudes and feelings about products, services, companies, individuals, tasks, events, titles and their characteristics. With the increase in applications on the Internet and social networks, Sentiment Analysis has become more crucial in the field of text mining research and has since been used to explore users’ opinions on various products or topics discussed on the Internet. Developments in the fields of Natural Language Processing and Computational Linguistics have contributed positively to Sentiment Analysis studies, especially for sentiments written in non-structured or semi-structured languages. In this paper, we present a literature review on the pre-processing task on the field of sentiment analysis and an analytical and comparative study of different researches conducted in Arabic social networks. This study allowed as concluding that several works have dealt with the generation of stop words dictionary. In this context, two approaches are adopted: first, the manual one, which gives rise to a limited list, and second, the automatic, where the list of stop words is extracted from social networks based on defined rules. For stemming two, algorithms have been proposed to isolate prefixes and suffixes from words in dialects. However, few works have been interested in dialects directly without translation. The Moroccan dialect in particular is considered as the 5th dialect studied among Arabic dialects after Jordanian, Egyptian, Tunisian and Algerian dialects. Despite the significant lack in studies carried out on Arabic dialects, we were able to extract several conclusions about the difficulties and challenges encountered through this comparative study, as well as the possible ways and tracks to study in any dialects sentiment analysis pre-processing solution.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"1 1","pages":"323-330"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83157290","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-249-2020
A. Htitiou, A. Boudhar, Y. Lebrini, T. Benabdelouahab
Abstract. Remote sensing offers spatially explicit and temporally continuous observational data of various land surface parameters such as vegetation index, land surface temperature, soil moisture, leaf area index, and evapotranspiration, which can be widely leveraged for various applications at different scales and contexts. One of the main applications is agricultural monitoring, where a smart system based on precision agriculture requires a set of satellite images with a high resolution, both in time and space to capture the phenological stages and fine spatial details, especially in landscapes with various spatial heterogeneity and temporal variation. These requirements sometimes cannot be provided by a single sensor due to the trade-off required between spatial and temporal resolutions and/or the influence of cloud cover. The data availability of new generation multispectral sensors of Landsat-8 (L8) and Sentinel-2 (S2) satellites offers unprecedented options for such applications. Given this, the current study aims to display how the synergistic use of these optical sensors can efficiently support such an application. Herein, this study proposes a deep learning spatiotemporal data fusion method to fill the need for predicting a dense time series of vegetation index with fine spatial resolution. The results show that the developed method creates more accurate fused NDVI time-series data that were able to derive phenological stages and characteristics in single-crop fields, while keeps more spatial details in such a heterogeneous landscape.
{"title":"DEEP LEARNING-BASED RECONSTRUCTION OF SPATIOTEMPORALLY FUSED SATELLITE IMAGES FOR SMART AGRICULTURE APPLICATIONS IN A HETEROGENEOUS AGRICULTURAL REGION","authors":"A. Htitiou, A. Boudhar, Y. Lebrini, T. Benabdelouahab","doi":"10.5194/isprs-archives-xliv-4-w3-2020-249-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-249-2020","url":null,"abstract":"Abstract. Remote sensing offers spatially explicit and temporally continuous observational data of various land surface parameters such as vegetation index, land surface temperature, soil moisture, leaf area index, and evapotranspiration, which can be widely leveraged for various applications at different scales and contexts. One of the main applications is agricultural monitoring, where a smart system based on precision agriculture requires a set of satellite images with a high resolution, both in time and space to capture the phenological stages and fine spatial details, especially in landscapes with various spatial heterogeneity and temporal variation. These requirements sometimes cannot be provided by a single sensor due to the trade-off required between spatial and temporal resolutions and/or the influence of cloud cover. The data availability of new generation multispectral sensors of Landsat-8 (L8) and Sentinel-2 (S2) satellites offers unprecedented options for such applications. Given this, the current study aims to display how the synergistic use of these optical sensors can efficiently support such an application. Herein, this study proposes a deep learning spatiotemporal data fusion method to fill the need for predicting a dense time series of vegetation index with fine spatial resolution. The results show that the developed method creates more accurate fused NDVI time-series data that were able to derive phenological stages and characteristics in single-crop fields, while keeps more spatial details in such a heterogeneous landscape.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"1 1","pages":"249-254"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89228369","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-351-2020
A. Rafique, I. R. Karas, S. Abujayyab, Ashfak ahmad Khan, E. Demiral
Abstract. Exploratory Spatial Analysis Techniques (ESDA) have become popular to identify the spatial association of different variables in many fields of natural and social sciences. The application of Global Moran’s I statistics enables us to provide visual insights of spatial data. It helps to detect spatial patterns and hotspots of an activity or process, based on spatial autocorrelation. This study aims to investigate the spatial dependence of domestic and inbound tourist arrivals to 123 cities of all eight provinces of the Aegean Region of Turkey. For analysis, city-level data about domestic and inbound tourist arrivals during 2015–2019 is collected from the Turkish Ministry of Culture and Tourism and is converted to logarithm form to avoid any skewness. The Arc GIS and GeoDa programs are employed for the analysis of spatial autocorrelation and visualization of hotspots of tourist flows in the regions. The results of the study reveal that tourist flows in the region are concentrated in the coastal areas, while inland cities receive an insufficient number of tourists. The hotspots of tourist flow are located mostly in the coastal towns of the provinces of Izmir, Aydin, and Mugla. The study is significant in the provision of useful information regarding resource allocation to the tourism hotspots and the implication of sustainable tourism policy to better utilization of tourism potential.
{"title":"APPLICATION OF EXPLORATORY SPATIAL TECHNIQUES IN THE IDENTIFICATION OF TOURISM HOTSPOTS IN THE AEGEAN REGION OF TURKEY","authors":"A. Rafique, I. R. Karas, S. Abujayyab, Ashfak ahmad Khan, E. Demiral","doi":"10.5194/isprs-archives-xliv-4-w3-2020-351-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-4-w3-2020-351-2020","url":null,"abstract":"Abstract. Exploratory Spatial Analysis Techniques (ESDA) have become popular to identify the spatial association of different variables in many fields of natural and social sciences. The application of Global Moran’s I statistics enables us to provide visual insights of spatial data. It helps to detect spatial patterns and hotspots of an activity or process, based on spatial autocorrelation. This study aims to investigate the spatial dependence of domestic and inbound tourist arrivals to 123 cities of all eight provinces of the Aegean Region of Turkey. For analysis, city-level data about domestic and inbound tourist arrivals during 2015–2019 is collected from the Turkish Ministry of Culture and Tourism and is converted to logarithm form to avoid any skewness. The Arc GIS and GeoDa programs are employed for the analysis of spatial autocorrelation and visualization of hotspots of tourist flows in the regions. The results of the study reveal that tourist flows in the region are concentrated in the coastal areas, while inland cities receive an insufficient number of tourists. The hotspots of tourist flow are located mostly in the coastal towns of the provinces of Izmir, Aydin, and Mugla. The study is significant in the provision of useful information regarding resource allocation to the tourism hotspots and the implication of sustainable tourism policy to better utilization of tourism potential.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"3 1","pages":"351-354"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82634585","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}
Pub Date : 2020-11-23DOI: 10.5194/isprs-archives-xliv-4-w3-2020-215-2020
R. A. Emek, N. Demir
Abstract. SAR images are different from the optical images in terms of image properties with the values of scattering instead of reflectance. This makes SAR images difficult to apply the traditional object detection methodologies. In recent years, deep learning models are frequently used in segmentation and object detection purposes. In this study, we have investigated the potential of U-Net models for building detection from SAR and optical image fusion. The datasets used are Sentinel 1 SAR and Sentinel-2 multispectral images, provided from ‘SpaceNet 6 Multi Sensor All-Weather Mapping’ challenge. These images cover an area of 120 km2 in Rotterdam, the Netherlands. As training datasets 20 pieces of 900 by 900 pixel sized HV polarized and optical image patches have been used together. The calculated loss value is 0.4 and the accuracy is 81%.
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