Geodatabase of Publicly Available Information about Czech Municipalities’ Local Administration

In this data description, we introduce a unique (geo)dataset with publicly available information about the municipalities focused on (geo)participatory aspects of local administration. The dataset comprises 6258 Czech municipalities linked with their respective administrative boundaries. In total, 55 attributes were prepared for each municipality. We also describe the process of data collection, processing, verification, and publication as open data. The uniqueness of the dataset is that such a complex dataset regarding geographical coverage with a high level of detail (municipalities) has never been collected in Czechia before. Besides, it could be applied in various research agendas in public participation and local administration and used thematically using selected indicators from various participation domains. The dataset is available freely in the Esri geodatabase, geospatial services using API (REST, GeoJSON), and other common non-spatial formats (MS Excel and CSV).

A HIGH-CURRENCY GEO-SPATIAL SERVICE GATEWAY FOR NATIONAL GEO-INFORMATION SERVICE PLATFORM

Today, more and more geospatial services are provided by the governments and enterprises to share various geographic information data and functions, and services-based application integration has become a trend. However, many problems existed in the geo-platform for Geographic information sharing while providing services in the form of API, such as the coexistence of different versions of the same service, similar service routes of different APIs, cluttered service protocols, and complex authority management, that makes the integration among different geographic information services difficult and reduces the development efficiency. There are already some API gateway technologies to solve the problem, but the characteristics of geospatial services are not considered in the existing product. To address these problems, this paper proposed a high-currency geospatial service gateway system for National Geo-Information Service Platform based on the opensource framework of Kong for realizing the unified management and authorized open. The system provides the whole lifecycle management and fine-grained control for the service, and the functions such as unified geospatial service access, protocol conversion, service management, authorization verification, rate limiting, and security protection are also equipped. The system has been released and integrated in the National Geo-Information Service Platform, supporting hundreds of millions of service invocation every day. The result proves it simplifies geospatial services management, deployment, and application, and benefits the exchanging and sharing of geographic information.

CREATING A GEOSERVICE FOR AN OBJECT ON THE TERRITORY OF THE NOVOSIBIRSK REGION ON THE EXAMPLE OF THE SANATORIUM AND TOURIST COMPLEX "LAKE KARACHI"

An important task for the development of modern society is the organization of operational access to spatial data. In modern conditions, geoportal technologies are successfully used to implement this task. Spatial information plays an important role in tourism activities, as the visual representation of travel routes, main attractions and tourist infrastructure has a great impact on the promotion of ser-vices. The main goal of the work is to develop a tourist geo-service for the Lake Karachi sanatorium and tourist Park. This article considers the process of creating a geoservice using the "MapInfo" soft-ware. The developed methodology contains recommendations for preparing cartographic information for publication on interactive geospatial services. Web maps are equipped with additional tools that allow you to perform various types of search, create and edit objects in vector layers, use analytical services and other useful tools. There is a tool for embedding interactive maps from geoservice in oth-er sites, while retaining most of the features and tools. There was conducted a study to determine the role of information and geoinformation technologies in the tourism industry. The article proves the relevance of developing a tourist web map of the sanatorium and tourist complex "Lake Karachi" for the geoservice of the same name. The work presents the content and structure of the created tourist web map, and develops an algorithm for creating thematic web maps. It also gives the developed sys-tem of symbols, as well as the results of the study. As a result, there was created the geoservice for the development of tourist recreation in the Novosibirsk region on the territory of the sanatorium and tour-ist complex "Lake Karachi".

ELiT, Multifunctional Web-Software for Feature Extraction from 3D LiDAR Point Clouds

Our research presents a complete R&D cycle—from the urban terrain generation and feature extraction by raw LiDAR data processing, through visualizing a huge number of urban features, and till applied thematic use cases based on these features extracted and modeled. Firstly, the paper focuses on the original contribution to algorithmic solutions concerning the fully automated extraction of building models with the urban terrain generation. Topography modeling and extraction of buildings, as two key constituents of the robust algorithmic pipeline, have been examined. The architectural scheme of the multifunctional software family—EOS LIDAR Tool (ELiT) has been presented with characteristics of its key functionalities and examples of a user interface. Both desktop, and web server software, as well as a cloud-based application, ELiT Geoportal (EGP), as an entity for online geospatial services, have been elaborated on the base of the approach presented. Further emphasis on the web-visualization with Cesium 3D Tiles has demonstrated the original algorithm for efficient feature visualizing though the EGP locations. Summarizing presentation of two thematic use-cases has finalized this research, demonstrating those applied tasks, which can be efficiently resolved with the workflow presented. A necessity of a conclusive workflow elaboration for use cases, which would be based on the actual semantics, has been emphasized.

CGI GeoData360: a cloud-based scalable production platform for big data-driven solutions of Earth Observation and Geospatial services.

<p>Our ability to observe the Earth is transforming, with substantially more satellite imagery and geospatial data fuelling big data-driven opportunities to better monitor and manage the Earth and its systems. CGI’s GeoData360 solves common technical challenges for those aiming to exploit these new opportunities.</p><p>Reliable monitoring solutions that run efficiently at scale require substantial ICT resources and more sophisticated data processing capabilities that can be complex and costly. Cloud-based resources enable new approaches using large, multi-tenant infrastructures, enabling solutions to benefit from massive infrastructural resources, otherwise unattainable for the individual user. GeoData360 makes these opportunities accessible to a wide user base.</p><p>GeoData360 is CGI’s cloud-hosted production platform for Earth Observation (EO) and Geospatial services. GeoData360 is designed for long running, large scale production pipelines as a Platform-as-a-Service. It supports deep customisation and extension, enabling production workflows that consume large volumes of EO and Geospatial data to run cost efficiently at scale.</p><p>GeoData360 is fully scalable, works dynamically and optimises the use of infrastructure resources available from commercial cloud providers, whilst also reducing elapsed processing times. It has the advantage of being portable and securely deployable within public or private cloud environments. Its operational design provides the reliable, consistent performance needed for commercially viable services. The platform is aimed at big data, with production capabilities applicable to services based on EO imagery and other Geospatial data (climate data, meteorological data, points, lines, polygons etc.). GeoData360 has been designed to support cost effective production, with applications using only the resources that are required.</p><p>CGI has already used GeoData360 as enabling technology on EO and non-EO initiatives, benefitting from: (1) granularity, with containerisation at the level of the individual processing step, allowing increased flexibility, efficient testing and implementation, and improved optimisation potential for dynamic scaling; (2) standardisation, with a centralised repository of standardised processing steps enabling efficient re-use for rapid prototyping; (3) orchestration and automation, by linking process steps into complete processing workflows, enabling the granular approach and reducing operational costs; (4) dynamic scaling, for processing resources and for storage; (5) inbuilt monitoring with graphical feedback providing transparency on system performance, allowing to maintain system control for highly automated workflows; (6) data access, with efficient access to online archives; (7) security, with access control and protection for third Party Intellectual Property. Example initiatives that benefit from GeoData360 include PASSES (Peatland Assessment in SE Asia via Satellite) and HiVaCroM (High Value Crop Monitoring). Both initiatives have used GeoData360 to enable data intensive production workflows to be deployed and run at national to regional scales.</p><p>GeoData360 solves the challenges of providing production-ready offerings: reliability, repeatability, traceability and monitoring. Our solution solves the scaling issues inherent in batch processing large volumes of bulky data and decoupling the algorithms from the underlying infrastructure. GeoData360 provides a trusted component in the development, deployment and successful commercialisation of big data-driven solutions.</p>

Empowering Density-based Micro-clusters In Dynamic Data Stream Clustering

Data stream is a continuous sequence of data generated from various sources and continuously transferred from source to target. Streaming data needs to be processed without having access to all of the data. Some of the sources generating data streams are social networks, geospatial services, weather monitoring, e-commerce purchases, etc. Data stream mining is the process of acquiring knowledge structures from the continuously arriving data. Clustering is an unsupervised machine learning technique that can be used to extract knowledge patterns from the data stream. The mining of streaming data is challenging because the data is in huge amounts and arriving continuously. So the traditional algorithms are not suitable for mining data streams. Data stream mining requires fast processing algorithms using a single scan and a limited amount of memory. The micro clustering has a good role in this. In itself, density based micro clustering has its own unique place in data stream mining. This paper presents a survey on different data clustering algorithms, realizes and empowers the use of density-based micro clusters.

Rescaling smart destinations: The growing importance of smart geospatial services during and after COVID-19 pandemic

The COVID-19 pandemic has imposed numerous, lasting adverse effects on the global tourism industry. At the same time, it exposed the competitive advantages that existing smart tourism infrastructure could provide for addressing urgent health issues and providing meaningful smart services. This paper initially provides examples of smart geospatial services based on COVID-19 pandemic-related data, such as algorithms for measuring social distancing through CCTV and proximity contract tracing protocols and applications. Indeed, smart destinations, as an evolutionary step of smart cities, very quickly became a practical and research framework in various other disciplines, from leisure and service-oriented to technical and geospatial domains. However, various technologies employed and interests of different stockholders create a constant need for rescaling of smart data to facilitate their usability in providing optimized smart tourism services. One of the pressing concerns is the functional alignment of geospatial data with tourism-related data. Thus, we aim to pinpoint the growing importance of smart geospatial services, by pointing to the main downturn of the current smart destination issue with geospatial data resolutions, and, by building upon the relations of the geospatial layer of data with the tourism-specific layer. To this end, we pinpoint two further research directions - reinvestigating spatial and temporal resolution as a core of data smartness and the need for contextual (tourism-oriented) scaling of smart technology. This could be of keen interest in post-pandemic tourism, where smart geospatial services will be of pressing concern, but also it still an issue to be resolved in further smart destination development.