Advances in Cartography and GIScience of the ICA最新文献

{"title":"A Comparative Study of Semantic Segmentation using Deep Neural Networks in a GNSS-denied Underground Parking Lot","authors":"Kristie Hu, Jing Du, Xinghan Gong, Lingfei Ma, Jonathan Li","doi":"10.5194/ica-adv-4-18-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-18-2023","url":null,"abstract":"Abstract. Deep neural networks (DNNs) in intelligent point cloud processing have achieved remarkable progress in recent years. Most existing methods and models were adopted on either outdoor or indoor scenes while very few previous studies were conducted in GNSS-denied environments. In this paper, we carried out a comparative study in semantic segmentation outputs using different DNNs in an underground parking lot dataset. Manually labeled indoor point cloud data were trained and tested using 7 different DNNs (e.g. PointNet, KPConv, FPConv, BAAF-Net, etc.). Our experiments demonstrated how well different DNNs perform in GNSS-denied environments with performance assessments in mIoU, Mean Accuracy (mAcc), Overall Accuracy (OA), as well as visualization outputs. The main contribution of this comparative study is to compare state-of-the-art DNN algorithms’ performance in semantic segmentation directly on the raw indoor mobile laser scanning (iMLS) data from a GNSS-denied underground parking lot and evaluate the effectiveness and potentials of different DNNs in underground 3D taskings. Draw upon that, which current algorithms are optimal and how future work in GNSS-denied environments can be inspired and implemented would be discussed.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130187551","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":"Automatic Labels in Leaflet","authors":"M. Gede","doi":"10.5194/ica-adv-4-8-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-8-2023","url":null,"abstract":"Abstract. Automatic labelling is a lacking feature in the popular client-side web mapping library, Leaflet. Although there exist various workarounds and substitutes, most of these do not fulfil the basic cartographic rules, e.g. avoiding text overlaps.This paper discusses the various workarounds addressing this problem, and introduces the author’s solution, which extends Leaflet’s GeoJSON class with automatic labelling functionality. The new class displays labels for point, line or polygon features. Labels can be placed either on right or left side of points or automatically for better fitting. Markers for points are only displayed if their labels can be drawn without overlaps. Label text is specified either by property field name or a user-specified function. It is also possible to specify priority order of features (higher priority labels are drawn first) and to customize label styles.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123722847","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":"Geosite database of the High Gerecse Hills (Hungary): with cartographic and GIS-based methodologies","authors":"Edina Hajdú, Krisztina Irás, Márton Pál","doi":"10.5194/ica-adv-4-10-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-10-2023","url":null,"abstract":"Abstract. Geotourism is a branch of tourism that primarily presents the inanimate and spectacular objects of nature that sustainably have scientific and tourism significance. Although in Hungary, activities connected to it are not widely spread yet, the sector is dynamically developing. Dissemination of geotourism values is primarily concentrated in geoparks. The main goal of these institutions is to preserve and popularize geoscientific (geological, geomorphological, soil, landscape) values. We consider all inanimate geoscientific, social, cultural, or religious values as geosites, which carry scientific content in an easily interpretable and spectacular way for visitors. Geosites are the most important objects of these organizations. When founding a new geopark, the first step is to identify geosites by using cartographic and database materials and with some additional fieldwork. In our research, we conducted a survey of this kind in a geotouristically undiscovered, midmountain area in Hungary. After analogue and digital data collection, we identified all the geologically valuable objects in 16-day-long fieldwork. A digital Leaflet-based database has also been prepared encompassing the results of the field survey, which can be a basis for further research and infrastructural development.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123275132","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":"A Data Structure for the Interactive Exploration of Public Transportation Networks","authors":"A. Bonerath, Yu Dong, J. Haunert","doi":"10.5194/ica-adv-4-1-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-1-2023","url":null,"abstract":"Abstract. To understand the quality of a public transportation network, map-based visualizations are the first choice. Since the network quality depends on the transportation schedule, the visualization interface should also incorporate time. In this work, we provide such an interface where users can filter the data for time windows. When a user queries for a certain time window, we display all network segments that are traversed by at least θ means of public transportation, e.g., buses in the time window on the map.Since such transportation networks can contain a high number of network segments, testing each network segment at the moment when the user specifies the time-window query is not fast enough. We investigate an approach to provide the query result in real time. Our contribution is a data structure that answers such arbitrary time-window queries from the user interface. The data structure is based on a tree structure which is augmented with further information. To evaluate our data structure, we perform experiments on real-world data. With our data structure, we answer time-window queries in at most 25 milliseconds whereas testing each network segment on-demand takes at least 60 milliseconds for the data set that has 102599 road segments.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125137333","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":"A spatio-temporal fusion method based on Landsat and MODIS normalized vegetation index data","authors":"Xianghong Che, Jiping Liu, Yong Wang, Qing Sun","doi":"10.5194/ica-adv-4-2-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-2-2023","url":null,"abstract":"Abstract. Normalized difference vegetation index (NDVI) can simply and effectively reflect the growth status of plants, and has a linear relationship with vegetation coverage, thus it is an important indicator to identify vegetation growth status and coverage. However, the commonly used MODIS NDVI or Landsat NDVI cannot simultaneously achieve the high temporal and spatial resolution. To this end, we proposed a generic and automatic method to fuse MODIS and Landsat satellite vegetation index (NDVI) into daily high-resolution products which takes time series NDVI data from MODIS/Landsat as input, filters noise pixels, and generates high-resolution and high-frequency products through a fusion process of temporal-linearly interpolation to increase the temporal resolution and spatial filtering to alleviate the blocky artifacts from MODIS pixel border. The fused NDVI maps are visually compared to evaluate the performance of this method, and more quantitative assessment will be continued in the next step. This study can provide important support for large-scale long-term surface vegetation monitoring.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131581492","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":"Assessing completeness of global airport data in OSM","authors":"Yijun Chen, Zheng Wei, Qi Zhou","doi":"10.5194/ica-adv-4-3-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-3-2023","url":null,"abstract":"Abstract. Airports are not only important infrastructure for both civil and military use but also have significant impacts on socio-economic development and the built-up environment. OpenStreetMap (OSM) can be an essential data source for acquiring various airport elements, but few studies have investigated data quality. To fill this gap, this study aims to assess the quality (especially completeness) of airport data in OSM by comparing it with locations of airports acquired from the OurAirports platform. More precisely, the three different types (large, medium, and small) and the four different elements (runway, taxiway, apron, and terminal) of airports are assessed for over 40,000 airports worldwide. Results show that completeness varies depending on types, elements, and geographical regions. Specifically, 1) almost all large airports are complete; most medium airports are also complete; but most small airports are not complete. 2) The runway element is much more complete than the terminal element. 3) In most cases, completeness is relatively high in India, China, and Northern Africa but relatively low in Canada, the United States, Russia, and Australia, where the total number of airports is much larger. We conclude that most large and medium airports in OSM have been mapped well. The reasons for incomplete airport data in OSM and potential applications of OSM airport data are also discussed.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127606324","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":"Parametrization of the Hungarian Stereographic Map Sheets","authors":"Krisztián Kerkovits, M. Gede","doi":"10.5194/ica-adv-4-13-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-13-2023","url":null,"abstract":"Abstract. A topographic map series of Northern Transylvania was drawn in the 1940s. Georeferencing them needs information about their coordinate systems. These maps used two reference systems known as the Budapest and the Marosvásárhely Stereographic projections. The datum transformation parameters of the former had already been determined in previous studies, but they had to be adjusted slightly to use a common Ferro–Greenwich difference for both systems. Parameters of the Marosvásárhely system were only available as a Molodenskiy transformation determined with insufficient accuracy. In this study, we recalculate the Molodenskiy parameters with higher accuracy and determine six parameters from the usual 7-parameter Helmert (aka. Burša–Wolf) transformation. The ideas given in this paper can be useful in other similar cases when the information about base point coordinates on the old system is very limited: We had access only to the ellipsoidal coordinates of the origin and the projected coordinates of one single point. The accuracy of the resulting transformation was evaluated by aligning the old map sheets with recent base maps.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132822751","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":"Integrating spatial analytics in power system planning techniques for the green energy transition","authors":"Keagen Liebenberg, Sanjian Malapermal","doi":"10.5194/ica-adv-4-14-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-14-2023","url":null,"abstract":"Abstract. Fossil fuel energy generation contributes significantly to greenhouse gas emissions globally. Energy transition towards sustainable, low-carbon energy needs to occur. South Africa has pledged to achieve a net-zero carbon economy by 2050 and in-line with this energy transition. The country has implemented the Renewable Energy Independent Power Procurement Programme (REIPPPP) to promote private investment within the energy sector. As new capacity is constructed, it requires the national grid to move from a vertically integrated passive power model to a deregulated active power flow due to the distributed sources of energy. In this paper, a method for connecting distributed power producers is introduced by providing candidate locations for Network Planners to develop insights for optimal placement of collector stations that connect multiple power producers in an orderly manner onto the electrical grid. This method uses buffer distances and Voronoi polygons from the stations on the national grid in order for the power producers to be aggregated and assigned connection to a collector station. Furthermore, this paper proposes a model for potential power producers that allows Network Planners to adequately plan for future grid access applications.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116319250","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":"A lightweight ontology for landmarks to assist rescue in mountainous areas","authors":"Ana-Maria Olteanu-Raimond, Mattia Bunel, Catherine Dominguès, C. Duchêne, L. Jolivet, S. Mustière, Marie-Dominique Van Damme, Olivier Favre, Véronique Gendner","doi":"10.5194/ica-adv-4-15-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-15-2023","url":null,"abstract":"Abstract. When people are injured or lost in mountains during outdoor activities and when web-based locations are not available, they locate themselves by describing their environment, routes and activities. The description of their location is done using landmarks and spatial locations (e.g., “I am located in front of Punay Lake”, “I am near a protected area”). Landmarks used can be named (e.g., “Punay Lake”) or unnamed if the landmark has no name or if the victim does not know it (e.g., \"area lake\"). Landmarks are represented in geographic databases by name (if possible), type and geometry. To reduce the heterogeneity of landmark types present in oral language and geographic databases representing landmarks, and thus improve locating victims, our goal is to define a controlled vocabulary for landmarks. In this research, we present a lightweight ontology (i.e. ontology having generally less complexity and does not express formal constraints) of landmarks, named Landmark Ontology (OOR), describing landmark types. It is an application ontology, i.e. it is designed to support mountain rescue operations. The ontology construction is adapted from the SAMOD methodology for engineering ontology development and involves researchers and experts from mountain rescue teams. The construction of OOR is composed of four main phases: knowledge acquisition, conceptual formalisation, implementation, and testing. The implementation phase is carried out by an iterative and collaborative approach and using four formalised sources of knowledge (a landmark and a landform ontologies, and two other domain vocabularies), an un-formalised taxonomy of outdoor activities, and five authoritative and volunteered geographic information sources representing geographic data. The landmarks ontology contains 543 classes associated with 1739 labels: 1086 prefLabel (preferential label) in French and English, 321 altLabel (alternative label) in French, and 332 altLabel in English. The depth of the ontology varies from four for land cover, hydrological and land subdivision landmark types), to six for landform types, and eight for building types. Although the use of ontology is broader, in this paper we illustrate and test its use through three applications in the context of mountain rescue operations: semantic mapping, data instantiation and data matching.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"1498 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123369930","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":"Investigating spatiotemporal trends of large wildfires in\u0000California (1950–2020)","authors":"Sarah A. Ostertag, Matthew Rice, J. Qu","doi":"10.5194/ica-adv-4-16-2023","DOIUrl":"https://doi.org/10.5194/ica-adv-4-16-2023","url":null,"abstract":"Abstract. A database capturing large wildfire perimeters (> 1,000 acres / 405 hectares; n=2,857) in the state of California in the United States was used to document trends in fire occurrence (as frequency of large wildfires per year) and fire severity (using total burned area as a proxy) per ecoregion for the study period 1950–2020. Approximately 20.67% of the total area of California has been burned by large wildfires during the study period; of this, approximately 8.01% of the total area of California has been burned repeatedly. Large wildfires are becoming more severe in the state of California, burning an average of 5,068 additional acres (2,051 additional hectares) of land each year, however large wildfires are not occurring more frequently across the entire state as originally postulated. Rather, certain ecoregions, particularly mountainous regions with coniferous forests, exhibit statistically significant increasing trends in both large wildfire severity and occurrence compared to other regions of the state, likely contributing to the sentiment that wildfires are becoming worse in the state overall. As conditions relating to climate change, extreme weather events, invasive species, population distribution, and fire management decisions continue to change, the impacts of larger, more frequent fires will likely be felt more broadly across the state of California.\u0000","PeriodicalId":324347,"journal":{"name":"Advances in Cartography and GIScience of the ICA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129397923","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}