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About this book

This book is intended for researchers, practitioners and students who are interested in the current trends and want to make their GI applications and research dynamic. Time is the key element of contemporary GIS: mobile and wearable electronics, sensor networks, UAVs and other mobile snoopers, the IoT and many other resources produce a massive amount of data every minute, which is naturally located in space as well as in time. Time series data is transformed into almost (from the human perspective) continuous data streams, which require changes to the concept of spatial data recording, storage and manipulation.

This book collects the latest innovative research presented at the GIS Ostrava 2017 conference held in 2017 in Ostrava, Czech Republic, under the auspices of EuroSDR and EuroGEO. The accepted papers cover various aspects of dynamics in GIscience, including spatiotemporal data analysis and modelling; spatial mobility data and trajectories; real-time geodata and real-time applications; dynamics in land use, land cover and urban development; visualisation of dynamics; open spatiotemporal data; crowdsourcing for spatiotemporal data and big spatiotemporal data.

Table of Contents

Frontmatter

Comparison with the Reference Value on the Example of GIS-Based Applications

Abstract
The article gives a new approach to the assessment of objects in terms of various criteria which by its nature belong to the issue of multi-criteria decision making and analysis. The proposed variant of multi-criteria decision-making is based on a comparison of the real considered object model that is created according to user’s requirements with the reference value. The geographic object means a real object in this case the object is stored in digital geo-database in the geographic information system (GIS). The reference value represents optimal geographic object which is the most suitable for user’s purposes. The comparison of the values of individual criteria is based on the theory of tolerance and metric spaces. Supplementary GIS-based application to calculate the weights of the criteria, which have served to comparison was used. The proposed procedure for the evaluation of various criteria has been validated on a pilot project “SMART Regions” in the city Brno district of Nový Lískovec neighbourhood in the Czech Republic. Around the city district known by its typical of prefabricated blocks of flats it is necessary to compare the different options for renewal urban housing development. Urbanization city prefabricated housing estates using GIS opportunities will be ready to quick respond to the call of various changes in the field of energy sustainability. Therefore, it is important to utilize the available environmental resources for energy sustainability.
Dalibor Bartoněk, Stanislava Dermeková, Ján Škurla

Representing Buildings for Visibility Analyses in Urban Spaces

Abstract
The availability of detailed and precise digital surface models based on LiDaR data allows accurate calculation of visibility analysis even in urban areas. Lately, the viewshed analysis, which is implemented in geographical information systems, is often used to determine the visibility of buildings or other structures in both natural and urban environments. Such utilization of viewshed tool, which is originally designed to assess visibility from point to its neighbourhood, however, brings issues regarding partial visibility of the target that are usually neglected. The core of the problem here is that the target building is often represented as a single point in the viewshed analysis. This simplification can lead to an incorrect assessment of the visibility as the specific point of the building can be invisible for the observer while other parts of the building are visible. To properly analyse visibility of a building it is necessary to consider partial visibility of the target. To allow the assessment of partial visibility more than one point that represents the building needs to be defined. In this contribution, the theoretical aspects of reverse viewshed, an area from which a target point is visible, are considered with a focus on the proper representation of target building in the reverse visibility analysis. A practical study of building visibility is conducted with the building represented as single and multiple points. The results are compared and the differences are explored.
Jan Caha

Comparison of Fuzzy AHP Algorithms for Land Suitability Assessment

Abstract
Weighted Linear Combination (WLC) is one of the most popular methods for Multiple Criteria Decision-making (MCDM) in the field of geoinformatics. A typical utilization of WLC is in land suitability assessment and optimal location detection. The application of WLC requires the determination of weights for each criterion used in the MCDM problem. In this paper, we focus on a fuzzy Analytical Hierarchy Process (AHP) which is based on pairwise comparisons of criterion importance and, unlike the classic (crisp) AHP, it can contain uncertainty. This allows the user to include imprecise or incomplete knowledge in an MCDM problem. The theoretical part of the paper briefly describes fuzzy AHP and provides the necessary mathematical background. The practical part of the contribution is focused on testing two algorithms for weight determination in fuzzy AHP—the extent analysis method and a method based on constrained fuzzy arithmetic. The methods are described in terms of the amount of uncertainty in the result, the resulting value, and overall appropriateness. A four level fuzzy AHP problem containing one main goal, three criteria and twenty-four subcriteria is solved as a case study using both methods. Based on the results obtained, the recommendations for fuzzy AHP utilization in spatial suitability assessment are made.
Jan Caha, Jaroslav Burian

Project Catastrum Grenzsteine—State of the Art in Czechia

Abstract
This paper summarizes information on project Catastrum Grenzsteine and its state of the art in Czechia. Project Catastrum Grenzsteine aims at submitting selected historical boundary marks and related infrastructure for the UNESCO World Heritage title. Reasons for this proposal—example of continuity of administrative units, example of technical knowledge, etc.—are given briefly while the rest of the paper presents several researches that have already been accomplished in this scope—reconstruction of boundaries of former administrative units is based on written documentation of former cadastres. Classification of boundary lines expressing probability of the presence of historical boundary marks is based on analyses of landscape and coincidence of former boundaries. Finally, the web application for crowdsourcing of historical boundary marks data is described.
Václav Čada, Ondřej Dudáček

Dynamics of Legal Changes in Polish Cadastre

Abstract
In more developed countries, contemporary cadastral system design is premised on the need for credibility, accuracy, timeliness, flexibility, completeness, and availability. Cadastral Systems as the official land information systems for the entire country operate on the basis of clearly defined principles contained in the legislation. Any need to modernize the system require changes in legislation. This paper focuses specifically on cadastral system flexibility, which stems directly from the dynamics of law. The method used to develop the approach is based upon dynamics of legal changes in the context of the international development concepts. The approach is then applied to the Polish cadastral system. It is found that a measure of real estate cadastre legal flexibility is it’s ability to react to dynamic, changing rules and situation. Globally, this means that the proposed approach can be adopted to determine cadastral flexibility in terms of its legal framework.
Agnieszka Dawidowicz, Anna Klimach, Ryszard Źróbek

Automatic Detection and Monitoring of Cyanobacterial Blooms in the Context of the Marine Cadastre

Abstract
In the wake of the European and global spatial data infrastructures (SDI) it is important to build information systems which use and serve thematic data in compliance with the INSPIRE Directive. In the context of hydrographic data, the Directive requires EU member states to collect and share information on maritime areas divided into regions and sub-regions, as well as coastal zone management areas. These data are part of recently developed marine cadastres. According to the INSPIRE Directive the marine cadastres should be supplemented with information on the physical condition of the seas as well as on the specific natural characteristics and phenomena occurring in the seas. The latter can include dynamic information on marine pollution such as cyanobacterial blooms. The paper presents the concept of dynamic satellite-based cyanobacteria bloom detection for the purpose of its analysis in the context of marine cadastre.
Agnieszka Dawidowicz, Marcin Kulawiak, Krzysztof Bruniecki, Marek Ogryzek

Fuzzy Spatio-Temporal Querying the PostgreSQL/PostGIS Database for Multiple Criteria Decision Making

Abstract
Multiple criteria decision making usually means selection of the best objects or their parameters which best meet conditions or criteria. Human decision making often involves also uncertain and vague criteria. The terms as a short distance, a high building or long time are commonly used in human speech. Nevertheless, it is not necessary to describe them exactly. In case of decision making based on lot of data and multiple criteria, data are usually stored in databases and a query language is used for handling and querying them. In this case, the criteria should be defined in a formal computer language. The standard for querying data in relational databases is the Structured Query Language (SQL). All objects and phenomena, and everything people do, is experience in space and time. Space and time, therefore, should be used as a framework for querying and reasoning about information stored in database systems. Databases, in which spatial and temporal data types are included and functions for their handling are supported, are called the spatio-temporal databases. To spatio-temporal query a database, an extension of standard SQL to support spatial and temporal data is needed. Uncertain spatio-temporal queries are not yet standardized and they are a current topic of research. For uncertain queries creation and expression of uncertain decision criteria, development of new methods and techniques is required. One of the most widely used approach to model, analyse and process uncertain and vague data is fuzzy set theory. Therefore, in this paper, we propose a new way of application fuzzy set theory to spatio-temporal querying. For the case study realisation, the open source PostgreSQL database system extended by the PostGIS we have used. The implementation of the proposed principles of fuzzy set theory to spatio-temporal querying databases can bring an opportunity for the efficient decision making based on multiple uncertain criteria.
Renata Ďuračiová, Jana Faixová Chalachanová

Dynamic Visualization of Transit Information Using Genetic Algorithms for Path Schematization

Abstract
In this paper, we present a genetic algorithm for path octilinear simplification. The octilinear layout, recognized worldwide in metro maps, has the special property that edge orientations are restricted to eight angles. The proposed search technique combines possible solutions to find a solution with a desired balance between faithfulness to the original shape and reduction of bends along the path. We also aim the genetic algorithm to real-time response for dynamic web visualizations so we can experiment on how algorithms for the visualization of schematic maps can be availed in a context of mobile web devices in order to empower efficiency in transmitting transit and navigation information. A prototype of a web application and real transit data of the city of Castellón in Spain were used to test the methodology. The results have shown that real-time schematizations open possibilities concerning usability that add extra value to schematic transit maps. Additionally, performance tests show that the proposed genetic algorithms, if combined with topological data and scale variation transformation, are adequate to sketch bus transit maps automatically in terms of efficiency.
Marcelo Galvao, Francisco Ramos, Marcus Lamar, Pastor Taco

Configuration of Wireless Sensor Network in Olomouc

Abstract
Wireless sensor network is a new fast evolving technology used in both environmental and socioeconomic applications. The usage of this technology in a city environment is influenced by many factors dealing with technical parameters of the nodes, parameters of terrain and other disturbing factors in a city such as signal interruptions, etc. The biggest advantage of this technology is the real-time monitoring. Every wireless sensor network has technical parameters that are tested in a real terrain deployment. Distribution of nodes under the real conditions is adjusted to the results of the technical tests. These parameters include determination of the least loaded communication channel, computation of data delivery ratio (DDR), testing of battery consumption under defined conditions and determination of received signal strength indicator (RSSI). Experimental wireless sensor network was established in Olomouc in 2015. Wireless nodes Waspmote Plug and Sense produced by Spanish company Libelium are used. Olomouc wireless sensor network is oriented on meteorological monitoring. The attention is aimed at air pollutants related to traffic. The nodes are situated to two clusters—the first cluster is located to the uptown part of Olomouc, the second one is located to the centre of Olomouc. The communication between nodes and gateway is carried out using IEEE 802.15.4 protocol. The goal of this paper is to evaluate technical data from the real deployment of the nodes and to use it for the design of optimal wireless sensor network using Libelium devices equipped with 802.15.4 radio.
Vendula Hejlová, Tomáš Pohanka

Risk Management as a Stimulus for a Settlement and Landscape Transformation? Soil Erosion Threat Assessment in the Fields of Four Deserted Villages Based on LiDAR-Derived DEMs and ‘USLE’

Abstract
This paper draws attention to the dynamics beyond the shaping of historical landscape and deals with the settlement abandonment and landscape transformation during the Later Middle Ages. Despite long-lasting debate about the reasons of this process, explicit explanation is still missing. Among others, ecological issues, including soil erosion, have been frequently mentioned, although not always supported by data. We examine four deserted villages in the Czech Republic—Bzík and Kamenice in Pilsner region (Bohemia) and Bouchenec and Novošice in the Drahany Uplands (Moravia). Their remains have been preserved in woodlands and, therefore, the extent of medieval ploughlands could be reconstructed. LiDAR-derived DEMs and Universal Soil Loss Equation (USLE) have been applied to assess the soil erosion threat of the village fields. The results of the modelling indicate a high erosion threat for the majority of fields. This factor, together with resulting soil degradation, can be considered as a reason for the abandonment and subsequent landscape transformation.
Lukáš Holata, Jiří Kapička, Radek Světlík, Daniel Žížala

Multidimensional Evaluation of Public Transport Accessibility

Abstract
Public transport conditions are analysed using simulated commuting to important employers and recording data about significant features of all simulated trips. Two forms of overall public transport accessibility evaluation are compared—rule based and multivariate based classifications. Rule based classification was developed in several variants integrating two or four indicators, average and non-aggregated values. More valuable results were obtained using extended set of indicators for non-aggregated trips. The multivariate classification utilizes a novel approach to K-means cluster analysis using decile values. The comparison of both classifications shows a primary role of expert based classification. K-means cluster analysis based on deciles or median values are suitable for establishing more common typology but not for a local accessibility evaluation.
Jiří Horák, Igor Ivan, Vít Voženílek, Jan Tesla

Verification of the Movement Speed on Communication Network and the Vehicle Movement Modelling Possibilities for Defence and Crisis Management

Abstract
The road transport is one of the basic types of moving people and material during situations of crisis. As far as it can be said the movement of vehicles is connected to the existing road network. Vehicles of military units and rescue teams must be able to move also outside communications. Knowledge of speed restrictions doe to the influence of individual landscape objects is therefore important for proper transport planning. That is the reason why part of the research is focused on monitoring of the vehicle movements on communications and on field and forest roads. To monitor the vehicles there are used GNSS receivers. Position and velocity records are then analysed according to characteristics of the communications and their surroundings. Based on previously conducted and processed measurements it is possible to demonstrate the influence of road type and curvature on the vehicle speed. Indeterminate results occurred in cases of the slope and obstacles around communications. The results and conclusions after completion of the research will help with more realistic planning of vehicle movements in situations of crisis.
Martin Hubáček, Martin Bureš, Kateřina Šimková, Vlastimil Kratochvíl

Retrieving of GNSS Tropospheric Delays from RTKLIB in Real-Time and Post-processing Mode

Abstract
Global Navigation Satellite Systems (GNSS) allow a precise estimation of atmospheric water vapour what is successfully used in weather forecasting, namely in Numerical Weather Prediction (NWP) models. In this study the quality of real-time and post-processed zenith total delay (ZTD) values from GPS (Global Positioning System) Precise Point Positioning (PPP) technique processing is investigated. GPS observations from a month-long period and eight European stations were processed in RTKLIB program package. Two versions of real-time processing solutions using different real-time IGS (International Global Navigation Satellite Systems Service) products (IGS01, IGS03) and two versions of post-processed solutions using different strategies were evaluated. Obtained ZTDs were compared with the final IGS ZTD product. The mean RMSE (root-mean-square error) was 10.3 mm for real-time solution based on the IGS03 real-time product and 12.2 mm for the other solution based on the IGS01 product. Both post-processed solutions reached a mean RMSE of about 5 mm. The better real-time ZTD solution from RTKLIB using IGS03 product was therefore close to the 10 mm value defined as a target ZTD accuracy necessary for their usage in NWP models and nowcasting applications in meteorology.
Michal Kačmařík

Geo-Dynamic Decision Support System for Urban Traffic Management

Abstract
The paper presents the geo-dynamic decision support system (DSS) for urban traffic management issues. For this purpose, ArcGIS and Tableau softwares were used. Additionally, a self-defined transportation model based on Dijkstra’s algorithm was created. The use of our own calculation model allowed for the full accessibility to all parameters of the analysed scenarios which was one of the key assumptions of the research. Functionality of the proposed DSS was tested on three scenarios. Each scenario presents congestion on the road network after the conclusion of events in main landmarks in Wrocław (Poland): the city stadium, the National Forum of Music and the Centennial Hall. The proposed DSS allows for dynamic analysis of urban traffic, including recalculation processes according to the changing congestion on a road network. Moreover, cumulative urban traffic assessment allows you to define hot spots on a network, which should be especially monitored by public services. An interactive dashboard reduces technical details of an analysis which helps to avoid the cognitive problems of the decision making process for a layman. The results prove the feasibility of the integration of the ArcGIS, self-defined transportation model and Tableau. The proposed solution enables full access to the transportation analysis’ assumptions, as well as the use of a simple and intuitive interactive dashboard for the decision making process.
Jan Kazak, Mieczysław Chalfen, Joanna Kamińska, Szymon Szewrański, Małgorzata Świąder

Probabilistic Map-Matching for Low-Frequency GPS Trajectories

Abstract
The ability to infer routes taken by vehicles from sparse and noisy GPS data is of crucial importance in many traffic applications. The task, known as map-matching, can be accurately approached by a popular technique known as ST-Matching. The algorithm is computationally efficient and has been shown to outperform more traditional map-matching approaches, especially on low-frequency GPS data. The major drawback of the algorithm is a lack of confidence scores associated with its outputs, which are particularly useful when GPS data quality is low. In this paper, we propose a probabilistic adaptation of ST-Matching that equips it with the ability to express map-matching certainty using probabilities. The adaptation, called probabilistic ST-Matching (PST-Matching) is inspired by similarities between ST-Matching and probabilistic approaches to map-matching based on a Hidden Markov Model. We validate the proposed algorithm on GPS trajectories of varied quality and show that it is similar to ST-Matching in terms of accuracy and computational efficiency, yet with the added benefit of having a measure of confidence associated with its outputs.
Kira Kempinska, Toby Davies, John Shawe-Taylor, Paul Longley

Multilingual Sentiment Mapping Using Twitter, Open Source Tools, and Dictionary Based Machine Translation Approach

Abstract
Online social networks are a popular communication tool for internet users. Millions of users share opinions on different aspects of everyday life. Therefore, microblogging websites are rich sources of data for opinion mining and sentiment analysis. Our current research based on the analysis of migration using various social networks required to implement a tool for automated multilingual analysis of sentiment from as many languages as possible. Usually, all available tools handle to work only with English written texts which are the most common on the social media. Few open source tools which can process French, German and Spanish texts exist too, but it is not optimal to reimplement and join different approaches together. Another requirement is the ability to process dynamic data streams and static historical datasets with high efficiency. Lesser accuracy and completeness of evaluated messages is acceptable as a counterweight for these general requirements. The paper presents sample data collection from Twitter for the opinion mining purposes. We perform multilingual sentiment analysis of the collected data and briefly explain experimental results. The analysis is made with the use of custom built solution utilising the AFINN-165 which is manually evaluated dictionary of English words. This dictionary was translated into other languages using Google Translate API that was tested during the process. It is then possible to determine positive, negative and neutral sentiment. Results of the research bring new insights, offer a possibility for wider use and allow optimisation of the wordlists/tool resulting in the better results of future research. Geospatial analysis of first experimental results undercovers interesting relation between time, location and a sentiment which enables readers to think of various use cases.
David Kocich

Dynamic Zoning in the Course of GIS-Based Football Game Analysis

Abstract
This paper is one of a series of articles about GIS-based game analysis in association football and presents an approach to dynamic zoning of football pitches based upon the players’ movements. For this purpose, tracking data are employed, which were kindly provided by ProzoneSports. Since football is highly dynamic, spaces are constantly changing over the entire game’s period. Therefore, it is reasonable to capture these alterations in the team’s use of space and to analyse them. In order to do so a Python script which automatically trisects the pitch vertically in a defenders’, midfielders’, and forwards’ zone was developed. It can be executed as a custom tool in ArcGIS and determines the zones’ height, width and area. Furthermore, its functionality can be considered the basis for manifold analysis opportunities. To provide an example, in the paper’s second part another custom tool for ArcGIS is presented, which applies the conception of dynamic zoning for analysing the teams’ offensive qualities based upon the defenders’ zone’s vertical height. This paper’s overall objective is to highlight the benefits of dynamic zoning in the course of football game analyses. Moreover, the demonstration of the tools’ functionality is intended to foster the discussion about the presented conception’s methodological principles as well as its potential application areas. In addition to this, an expert survey was conducted interviewing professional game analysts from Austria and Germany. The results provide evidence that the conception of dynamic zoning is worth to refine, as it provides a novel approach of analysing the game.
Gilbert Kotzbek, Wolfgang Kainz

Spatio-Temporal Traffic Flow Forecasting on a City-Wide Sensor Network

Abstract
Intelligent transportation systems (ITS) all around the world are collecting and processing huge amounts of data from numerous sensors to generate a ground truth of urban traffic. Such data has set the foundation of traffic theory, planning and simulation to create rule-based systems but it can also be very useful for time-series analysis to predict future traffic flow. Still, the acceptance for data-driven forecasting is quiet low in productive systems of the public sector. Without enough probe data from floating cars (FCD) ITS owners feel unable to reach an accuracy like private telecommunication or car manufacturing companies. On the other hand, investigating into FCD requires a thoughtful treatment of user privacy and a close look on data quality which can also be very time consuming. With this paper we prove that a modern deep learning framework is capable to operate on city-wide sensor data and produces very good results with even simple artificial neural networks (ANN). In order to forecast space-time traffic dynamics we are testing a Feed Forward Neural Network (FFNN) with different geotemporal constraints and can show where and when they have a positive but also a negative effect on the prediction accuracy.
Felix Kunde, Alexander Hartenstein, Petra Sauer

Applications of GIS in Analysis of Mars

Abstract
This article presents the results of the project that aims to demonstrate the possibility of using images from space probes and satellite images for the analysis and creation of databases of spatial information systems. The introduction contains basic information about the planet Mars. The scope of work involves a combination of satellite images mosaic. On the basis of these images a 3D model was created, showing the landing place for Mars rovers. It presents the largest craters, canyons and other characteristic objects. All the information is contained in the database. Places that may be suitable for settlement have been determined on the basis of analyses carried out on a 3D model. The analysis took into account the temperature, slope inclination, the distance from craters and volcanoes and the occurrence of dust and sandstorms, as well as other factors favouring the colonization of the surface of Mars. The project was prepared to constitute a future basis for determining potential areas of habitation on Mars.
Marta Kuźma, Łukasz Gładysz, Mateusz Gralewicz, Paweł Krawczyk

Czech System for Exploitation of Land Dynamics Using Copernicus Sentinel-1 Data

Abstract
The topic of this work covers current implementation of satellite radar (SAR) interferometry (InSAR) techniques for routine identification of dynamic land processes such as downhill creep and landslide activity, subsidence or displacements of various objects of infrastructure. With the emerge of European Copernicus programme, the need of effectivity in satellite Big Data processing increased. There are two Sentinel-1 satellites observing the Earth with 6 days revisit time, sending daily 100 TB of data to be archived. In case of the relatively small area of Czechia, the amount of data to be archived in a Czech national mirror is around 24 GB per day. Czech CESNET e-infrastructure has accepted the role of assessing Copernicus Ground Segment programme. A database mirroring Sentinel data over Czechia is established, however still in its early stage. A potential service based on an interferometric processing of Sentinel-1 data from this database has been prepared in Czech national supercomputing center IT4Innovations. As a basis of the system, several open-source projects were deployed, including MySQL-based burst metadatabase (TU Leeds), ISCE TOPS Processor (NASA/JPL), Doris coregistration algorithm (TU Delft) and StaMPS Small Baselines processor (Stanford University). Though more functionality can be rapidly developed, incorporating some of the own post-processing algorithms, even current early version of the system can yield interesting results by a fully automatic processing chain.
Milan Lazecký, Ivana Hlaváčová, David Kocich

Prediction Models for Landscape Development in GIS

Abstract
Ameliorating the impacts of global change on the physical and socioeconomic environment is essential for the restoration and sustainability of our ecosystems. Landscape modifications have been discovered as one of the primary causes of the environmental change and has therefore gained reasonable attention in the modeling techniques, because understanding the land use-land cover change (LULCC), the drivers and processes provides the solution to the environmental challenge. Sequel to this, several empirical methods and software for modeling LULCC have been developed and applied such as the spatial-statistical based (regressions, Artificial Neural Networks, GISCAME), Markov Chain, Cellular automata, the hybrid (CA-Markov), Agent-Based, CLUE, Land Change Modeler (LCM), Dinamica EGO, GEOMOD, and Scenarios for InVEST. This paper reviews the implementations, prospects, and the limits of these modeling software packages. Comparative assessment review of the models including their capabilities, applications and output were also highlighted. Finally, two of the models (LCM and CLUE) were used to predict the LULCC in a municipal area in south-east, Nigeria (a case study), and this helps to illustrate the afore-mentioned explanations and variations about the outputs of different models in assessing the LULCC of same location in time. Different models can behave differently when applied in same location at the same time as demonstrated by the applications of LCM and CLUE in our study. In addition to other LULC type dynamics in the models outputs, we have prediction map from CLUE showing higher built-up areas (42.7 km2) compared with that of LCM result (35.2 km2) while, the LCM projection revealed more areas for light vegetation cover (29.5 km2) in comparison with the 16.5 km2 from the CLUE model result.
Chukwudi Nwaogu, Antonín Benc, Vilem Pechanec

Land Use—Land Cover Change and Soil-Gully Erosion Relationships: A Study of Nanka, South-Eastern Nigeria Using Geoinformatics

Abstract
This study aimed at identifying the land use-land cover (LULC) types and their changes by mapping the soil erodibility intensity, and estimating the LULC change caused by soil-gully erosion in Nanka region using geoinformatics tools. Data covering 1991, 2003 and 2015 were acquired from the Global Land Cover Facility (GLCF)-an Earth Science Data Interface, and from the National Space Research and Development Agency, Abuja (NASRDA). In addition, land use-land cover (LULC) data of Nanka and its environs were generated from the local government boundary map and Nigerian Administrative map at 1: 50,000 topographic scale. ENVI (version 4.7), ArcGIS 10.1, the RUSLE model and statistica software packages were used to process and analyse the data. The results revealed that areas with steep slopes have high and severe erosion levels except for Isuofia community which is on steep slope yet, has slight erosion because of the prevalence of dense forest vegetation cover. Integration of Remote Sensing, GIS and the RUSLE model has shown technical benefit, cost-effectiveness with reliable result and should be applied in the future assessment of erosion in Nigeria and other African countries.
Chukwudi Nwaogu, Onyedikachi Joshua Okeke, Simon Assuah Adu, Edeko Babine, Vilém Pechanec

Conditional Stochastic Simulation of Carbon Dioxide Concentrations

Abstract
This paper deals with conditional stochastic simulation. Old, abandoned coal mines contain the vestiges of coal mine gas. Coal mine gas usually consists of methane, nitrogen and carbon dioxide. But despite that they no longer produce coal, these sites are still contributing to climate change by leaking carbon dioxide into the atmosphere. The concentrations of carbon dioxide were studied and used as input parameters for stochastic simulation. Kriged surface underestimates the high values and overestimates the low values. The simulation model is conditioned to reproduce the data at known sample points to minimize the variability between the simulated data and the true field data. The main aim of this investigation is to compare selected interpolation methods that are currently used in practice with stochastic simulation, based on the development of the values. The advantages and disadvantages of each approach are discussed. The study shall provide users with recommendations for selecting the optimal interpolation method and its application to real data.
Lucie Orlíková

Spatial and Temporal Comparison of Safety Perception in Urban Spaces. Case Study of Olomouc, Opava and Jihlava

Abstract
Subjective and participatory mapping has become an important tool for urban planners and city administrations. Perceptions of safety can affect the quality of life and property prices. The presented paper describes participatory mapping exercises in three Czech cities, where questions were asked concerning people’s subjective perceptions of safety during the day and at night. Respondents in Olomouc (n = 661), Opava (n = 901) and Jihlava (n = 106) respectively indicated 1516 (Olomouc); 3491 (Opava) and 894 (Jihlava) places as unsafe. The data was gathered over a period of two years; in Olomouc data was collected between 1st October and 2nd December 2015, in Opava the survey took place between 19th October 2016 and 30th December 2016, and in Jihlava in the period from 30th November 2015 until 4th March 2016. The data collected included information about the gender of the respondents and the day-time/night-time division of perceived safety, so it was possible to analyse gender differences as well as time specifics from the collected data. The results suggest that there are certain areas in all three cities that have similar patterns (train stations, city parks, dark and narrow streets, excluded communities).
Jiří Pánek, Vít Pászto, Petr Šimáček

Prediction of Land-Use Development Under Influence of Climate Change

Abstract
Land-use change is considered one of the most critical processes when attempting to understand and model the global change. Land-use change has an interdependent relationship with the climate change. Climate change in the Czech Republic incurs a substantial pressure on human society and natural ecosystems through the increase of temperature and higher occurrence of droughts and floods. The principal purpose of the study was to model and assess the future land-use distribution in the Czech Republic based on historical land-use data and climate change information. For assessment of future ecosystem services, the current rate of ecosystem service fulfillment is set and compared in time and space with modeled situations. TerrSet’s Land Change Modeller was used to create land-use projection models based on principles of historical trends and business as usual projection scenario. The land-use prediction was performed for the entire Czech Republic using HadGEM2-ES climate model with RCP 4.5 and RCP 8.5 emission scenarios. The output of the modeling was a set of raster maps which presented the future land coverage for each category and location. A spatio-temporal analysis was then performed to determine the difference in representation of each land cover category for a period 2012–2050. The results show that most severe change in the land cover appears in loss of agricultural sites mainly caused by increase in urban areas and forests. Planners and policymakers can use the results of this study to incorporate adaptation measures including the change of land use to more natural habitats and implementation of more ecological management to mitigate the adverse effect of urbanization and climate change. The contribution of the study is in presenting selected tools for modeling expected future land use and development of maps displaying future spatial distribution and quantification of land use categories for the Czech Republic.
Vilém Pechanec, Alexander Mráz, Antonín Benc, Karel Macků, Pavel Cudlín

Methods of Using Self-organising Maps for Terrain Classification, Using an Example of Developing a Military Passability Map

Abstract
The classification of terrain by its passability plays a significant role in the process of Intelligence Preparation of the Battlefield (IPB). In the process of developing passability maps, the classification of terrain to a specific class (GO, SLOW-GO, NO-GO). In this paper the problem of terrain classification to the respective category of passability was solved by the application of Self Organizing Maps by generating a continuous Index of Passability (IOP), which characterizes the terrain in a range from 0 (the impassable area) to 1 (the area of high manoeuvrability). The article describes the methodology of using this type of network to develop a terrain passability map. As a “case of use”, three voivodeships located in the north-eastern part of Poland were selected. To prepare a training set, topographic vector data from VMap L2 and SRTM (Shuttle Radar Topography Mission) digital terrain model were used. Research was conducted on a primary grid field with dimensions 1 km × 1 km. As a result of the research conducted, normalised parameters associated with terrain cover were introduce into the neural network. As a result of the network learning, the analysed area was divided into classes, to which the index of passability (IOP) was arbitrarily subordinated. In the research results, the influence of the method of organisation of the input data on the generated maps of passability was defined. The tests were conducted on two sizes of a Kohonen map: 10 × 10 and 5 × 5 neurons. The described experiments proved that a properly taught artificial neural network is very well suited to the analysis of an area in terms of passability. The presented methodology is universal in nature and after the modification of parameters may be used to solve tasks of terrain classification associated with various subjects (division of soils, marking out areas for development, etc.).
Krzysztof Pokonieczny

Dynamical Flash Flood Risk Forecast

Abstract
Flash floods represent very dynamical natural phenomenon. Mostly, they are the result of torrential rains which can rise suddenly in any part of a country and are tough to predict. Of course, there are many weather forecasting systems, but their spatial and temporal resolution is usually insufficient for these purposes. There are also monitoring systems which can either register precipitation over the ground (a network of rain gauge stations) or runoff in riverbeds (a network of hydrometric stations). Again, spatial (and possibly temporal) resolution is not sufficient, and in the case of runoff monitoring, there is a substantial delay between actual rainfall and registration of runoff in riverbeds. And, of course, when the hydrometric station registers higher runoff than the flash floods is running or even over. From the point of early warning, all these systems reveal disadvantages. Aside from these systems, there is one which provides us with timely information about the spatial and temporal distribution of precipitation intensity over the ground. That is weather radar. We will demonstrate possible usage of these data for dynamic prediction of flash flood risk distribution in space and time over the monitored area. Proper processing of these data in combination with soil saturation indicator established using Flash flood guidance methodology developed by the US Hydrologic Research Center can generate timely information usable for early warning with a substantially reduced level of false warnings.
Petr Rapant, Jaromír Kolejka

Interpolation Techniques for Predicting the Movement of Cyclists

Abstract
Planning the development of cycling infrastructure underlines the importance of predicting the movement of cyclists inside cities. The main goal of the paper is to examine different interpolation techniques in order to estimate the most accurate predicts. The research was conducted with primarily collected data on pre-selected intersections. The data set included 30 input points measured during cyclists’ rush hour in the morning, 5:30–9:00 a.m., and in the afternoon, 2:00–5:00 p.m. To choose an appropriate interpolation method IDW, EBK, RBF, Ordinary Kriging (OK) with spherical variogram, Ordinary Kriging (OK) with linear variogram, Simple Kriging (SK) with spherical variogram and Simple Kriging (SK) with linear variogram) were considered based on state of the art analysis and further examined. For selecting a suitable interpolation technique, the cross validation was taken into account comparing Mean Error (ME), Root Mean Square Error (RMSE), Root Mean Square Standardized Error (RMSSE) and Average Standard Error (ASE). The cross-validation showed that IDW and RBF have worst results although IDW was the most accurate in prediction of furthest point. Opposite, EBK and OK (spherical variogram) achieved very similar values bringing best predicts. Though kriging is very accurate interpolator, the behaviour of cyclists is determined by many other factors which can not be completely included during kriging.
Aleš Ruda, Ludmila Floková

New Approach to Import 3D Geodata for Remcom Wireless Insite

Abstract
The paper is focused on developing a new approach how automatically process 3D geospatial data for Remcom Wireless InSite. Remcom Wireless InSite is a software tool which provides efficient and accurate predictions of an electromagnetic waves propagation and a communication channel characteristics in complex urban, indoor, rural and mixed path environments. The Wireless InSite is able to import a 3D geospatial model, that consists of a DTM (Digital Terrain Model) and objects (buildings). To be able to perform any predictions, we need to import different geodata objects into Wireless InSite and run calculations in an automated way. We tested several available functions for importing geodata to Wireless InSite. All of them have some drawbacks that made us do free import/export tool that reads data from 3D GIS (Geographic Information System) database and exports them to the form that can be directly read by Wireless InSite. The main advantage of this approach is complete control over the import and export processes. For example, we can specify the LOD (Level of Detail) for import, or we can specify for each different object the type of material.
Jan Růžička, Libor Michálek, Kateřina Růžičková

Floreon+: A Web-Based Platform for Flood Prediction, Hydrologic Modelling and Dynamic Data Analysis

Abstract
The main goal of this article is to describe the overview of Floreon+ system, an online flood monitoring and prediction system, which was primarily developed for the Moravian-Silesian region in the Czech Republic. Moreover, the article specifies the basic processes, which are implemented for running automatic and on-demand simulations that utilize the High Performance Computing (HPC) infrastructure. The main purpose of hydrodynamic models in the disaster management context is to provide an accurate overview of hydrologic situation in a given river catchment. In the event of extreme weather conditions, such as unusually heavy rainfall, these models could provide valuable information about imminent flood risk endangering a particular area. In the disaster management context, time plays a very significant role. Up to date and accurate results obtained in a short time can be very helpful. The availability of such results can be significantly improved by utilization of HPC resources and tools. The article describes the individual parts of the system in terms of data types, dynamic data processing, visualization, and the overall architecture.
Vaclav Svatoň, Michal Podhoranyi, Radim Vavřík, Patrik Veteška, Daniela Szturcová, David Vojtek, Jan Martinovič, Vít Vondrák

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