Spatial Data Processing Research Articles

A Protocol to Retrieve and Curate Spatial and Climatic Data from Online Biodiversity Databases Using R.

Ecological and evolutionary studies often require high quality biodiversity data. This information is readily available through the many online databases that have compiled biodiversity data from herbaria, museums, and human observations. However, the process of preparing this information for analysis is complex and time consuming. In this study, we have developed a protocol in R language to process spatial data (download, merge, clean, and correct) and extract climatic data, using some genera of the ginseng family (Araliaceae) as an example. The protocol provides an automated way to process spatial and climatic data for numerous taxa independently and from multiple online databases. The script uses GBIF, BIEN, and WorldClim as the online data sources, but can be easily adapted to include other online databases. The script also uses genera as the sampling unit but provides a way to use species as the target. The cleaning process includes a filter to remove occurrences outside the natural range of the taxa, gardens, and other human environments, as well as erroneous locations and a spatial correction for misplaced occurrences (i.e., occurrences within a distance buffer from the coastal boundary). Additionally, each step of the protocol can be run independently. Thus, the protocol can begin with data cleaning, if the database has already been compiled, or with climatic data extraction, if the database has already been parsed. Each line of the R script is commented so that it can also be run by users with little knowledge of R.

Геоинформационное картографирование эколого-магнитного состояния почв г. Краснокамска

The article is devoted to geoinformation mapping of the ecological and magnetic state of soils in the city of Krasnokamsk. The study included point determinations of the volumetric magnetic susceptibility of soils and the concentration of heavy metals, followed by mathematical-cartographic modeling of the results obtained. Mapping the magnetic susceptibility of soils makes it possible to form areas of the ecological and magnetic state of soils, along which samples are taken for the determination of heavy metals. Thus, the sample size of soil samples for heavy metal studies is reduced without a significant decrease in the representativeness of the final results, which determines the relevance of the studies performed. The purpose of the research is geoinformation mapping of the ecological and magnetic state of soils in the central part of the city of Krasnokamsk. The boundaries of research from the south are limited by the industrial zone of the city, which is mainly represented by pulp and paper industry enterprises. In the eastern part of the survey area, Zakamskaya CHPP-5 and a machine-building plant are located. The soil cover of Krasnokamsk is represented by urbanozems and technogenic surface formations. The total number of magnetic susceptibility measurement points was 77, and heavy metals were determined in 10 samples. During processing spatial data, the methods of mathematical-cartographic modeling, spatial overlay and binary classification were used. The interpolation was performed by the geostatistical method ordinary kriging using the Spatial Analyst tool of the ArcGIS 10.8 program. The creation of the Web GIS “Geoinformation system of magnetic susceptibility and heavy metals in the soils of Krasnokamsk” was performed on the basis of QGIS open geotechnologies using the qgis2web tool, the VS Code code editor. The Web GIS is hosted on the free GitHub platform. Based on the results of mapping, soil contamination with nickel and copper was established. The total area of pollution was 0.55 km2.

Геоинформационное картографирование в образовательных программах кафедры географии и картографии Казанского университета

The article describes educational programs of Geography and Cartography Department of Kazan (Volga Region) Federal University — bachelor’s and master’s degree programs in the field of “Cartography and Geoinformatics”. The most important professional competencies in the field of geoinformatics mapping are enlightened, including those aimed at improving methodological skills and abilities related to the processing and analysis of spatial data, obtained from various sources. The main feature of the developed system of courses on geoinformation mapping is the variety of modern educational and geoinformation technologies. Due to them, each course provides an opportunity to master a wide range of problem-solving skills in the environment of various geoinformation systems, and can be used for both full-time and online learning forms of education. The effectiveness of educational programs is revealed, inter alia, through interaction with employers. Among partners of Geography and Cartography Department of Kazan Federal University are State Budgetary Institution “Spatial Data Foundation of the Republic of Tatarstan”, Innopolis University, Municipal Budgetary Institution “Institute of City Development” (Kazan), State Budgetary Institution “Institute of Spatial Planning of the Republic of Tatarstan”, Limited Liability Company “GC-group”, etc.; companies providing consulting services and performing expertise—Limited Liability Company “Geoconsulting”, Limited Liability Company “Expert Consulting Center ‘Industrial Safety’ ”, Limited Liability Company “Multifunctional Engineering Center”, large companies working in the field of technical inventory of real estate, surveying, land management, such as Joint-Stock company “Bureau of Technical Inventory and Cadastral Works of the Republic of Tatarstan”; Ministries of Construction, Agriculture and Food, Forestry of the Republic of Tatarstan and a number of other organizations and enterprises.

РОЛЬ ГЕОДЕЗІЇ В МОНІТОРИНГУ ГЕОЛОГІЧНИХ ПРОЦЕСІВ ТА ПРИРОДНИХ КАТАСТРОФ ДЛЯ ПОПЕРЕДЖЕННЯ НЕГАТИВНИХ НАСЛІДКІВ

The purpose of the study is to analyze the contribution of geodetic methods and technologies to the detection, assessment and monitoring of geological processes and natural disasters in order to minimize their dangerous consequences for society and the environment. Research methodology. remote sensing of the Earth, the use of satellite images and aerial photography to collect data on geological processes and the state of the environment. Method of geodetic monitoring. tracking changes in the position of objects over time, which allows detecting soil micromovements, potential landslides and other deformations. GIS technologies (geoinformation systems). Integrating and analyzing geodata to model geological processes and natural disasters, creating thematic maps that can display potential risks and assist in response planning. The results. The task of monitoring geological changes and natural disasters using cartographic methods designed to work with many users has been set and solved, significantly increasing the level of safety and prompt response to emergency events. An important aspect in the implementation of geodetic observations is the use of an integrated approach that includes field research, geodetic analysis and remote sensing data. This ensures higher accuracy and efficiency of monitoring. Scientific novelty. The research focuses on identifying effective approaches to the collection, processing and analysis of spatial data that can be used for timely prediction and prevention of catastrophic events, as well as for emergency response planning. The developed adapted model of risk assessment of natural emergency situations, which is based on the analysis of terrain conditions at various times, allows to increase the accuracy of risk assessments. Practical significance. The use of remote monitoring methods ensures prompt receipt of information and the possibility of taking measures for nature protection in a timely manner. The conceptual model made it possible to identify the factors of man-made influence, assess the condition of soils and vegetation, as well as perform a cartographic analysis of disturbed lands in order to develop measures for their restoration. The created thematic maps of the dynamics of disturbed lands serve as a basis for making management decisions aimed at systematic restoration and reduction of negative man-made impacts, opening up new perspectives for the use of interactive technologies in geodesy.

Literature review of mobile spatial data collection and related to reality as a basis for the geomatics applications

The evolution of new information communication strategies has been aided by the development of new technology, devices, and applications over the last two decades. The utilization of digital media platforms, ubiquitous technologies, and technologies based on spatial data has blurred the lines between virtual and physical locations, with access via digital devices, particularly mobile devices. This paper aims to review the mobile spatial data MSD collection literature and related empirical approaches worldwide and demonstrates how researchers have analysed human mobility utilizing smartphone-GPS sensors, and call detail records CDRs spatial data collection methods. We offered an in-depth analysis of 129 publications from several databases that exhibit relevant solutions or prototypes, examining their emphasis areas, design aims, and contributions to design and approach. The article argued the techniques of mobile spatial data collection, processing, and technology applications and summarized the outcomes of articles correlated with Urban Transportation Modem, urban spatial data, and public health and infection domains over recent decades. The paper is concluded that mobile spatial data enables planners, policymakers, and stakeholders to analyse, specify, and customize crucial information to help and support decision-making. finally, it is possible to integrate the newest information and technology fields such as machine learning and artificial intelligence to gain more accurate features in estimating, predicting and studying several phenomena whether natural, socioeconomic, environmental, etc. Also, the article involves highlights the benefits and drawbacks of each spatial data collection technique.

Автоматизация выделения границ медицинских участков на примере Санкт-Петербурга

The article describes an approach to the desktop geographic information system application to optimization and (partial) automation of the spatial and non-spatial medical data processing and analysis when estimating the grid of medical lots in an area of medical service, and when forming (considering current morbidity and demographic indicators) updated boundaries of medical lots. Software tools of the QGIS platform were used to process spatial data (QGIS itself and its extension modules, including the GeoMedic module designed with the participation of the authors for medical statistics data geocoding). All medical statistics data used in the study were previously depersonalized in accordance with the requirements of Russian laws. A methodology prototype is elaborated for preparation, analysis, and processing of the data on patients (potential patients) number in the medical service area, together with spatial data (geographical map) of this area. The data of the St. Petersburg city tuberculosis service were used for experimental purposes in the study. Specialists of the St. Petersburg Research Institute of Phthisiopulmonology are involved in the work. Developed methodological toolset prototype ensures partially automated processing of initial data with the formation of boundaries of the medical lots in the analyzed area of medical service. Formation of the boundaries is carried out taking into account the normative number of patients, which must be ensured for the formed lots. The study was performed on the city scale, on the example of St. Petersburg (Russia). Data analysis was performed for the Moskovsky, Petrogradsky, Primorsky and Nevsky Administrative Districts of St. Petersburg. A grid of medical lot boundaries was formed and mapped in the results of the performed analysis. The methodology prototype proposed in the result of the conducted study can be applied in the analysis of existing schemas of medical lots and their updating.

СТРАТЕГИЧЕСКОЕ УПРАВЛЕНИЕ: КЛАССИЧЕСКИЙ КОНЦЕПТ ИЛИ ИНСТРУМЕНТ РАЗВИТИЯ КОМПАНИЙ

The article examines the application of the concept of strategic management as a methodological tool for creating an additional competitive advantage. It has been established that the choice of a company’s location can ensure competitive stability from the standpoint of forming strategic management. Scientific research in the field of choosing a company location is fragmentary; in practice, the discovery and selection of a location is carried out intuitively. The proposed concept was tested using the example of choosing the location of a Korean cosmetics store in Belgorod. The study made it possible to determine the strategic factors of the attractiveness of objects: marketing (pricing policy, service and interior) and geographical (availability of parking, number of infrastructure facilities), digital (information processing of spatial data). The optimal location option for opening a MYSKIN store in the city of Belgorod has been determined.

Machine Learning-based Predictive and Virtual Mapping Algorithms, Immersive Metaverse and Holographic Telepresence Technologies, and 3D Generative Modeling and Multiscale Spatial Data Processing Tools in Extended Reality Environments

Machine Learning-based Predictive and Virtual Mapping Algorithms, Immersive Metaverse and Holographic Telepresence Technologies, and 3D Generative Modeling and Multiscale Spatial Data Processing Tools in Extended Reality Environments

Development of an Integrated System to Enhance Spatial Data Processing & Management for Planning Authorities

In a world where there is constant data generation and processing, the need for an integrated system cannot be overemphasized. The systems that enable storage of large amounts of spatial data and must be made available to multiple users in real time. Studies have shown that standalone desktop spatial systems are often rigid and inflexible to support multiple data processing or demands from multiple users. The integrated spatial management system was designed to address the above highlighted challenges by bringing enhanced possibilities of utilization of spatial data though improving accessibility, visualization, and processing spatial information. The present work employed a mixed approach of qualitative and quantitative techniques to obtain the desired result. Qualitative data collection tools were used to collect field data required to design the prototype. The research sought to establish whether the integrated systems are in use by the targeted institutions, the findings highlighted that 71.4% have no integrated spatial data systems while 28.6% have partial-integrated systems. An overview of the architecture of integrated spatial systems consists of a well distributed database linked to multiple tools and platforms to query both the spatial and non-spatial data. The WEB-GIS and Mobile GIS interfaces were developed to allow multiple users to access information through the web in real time and data collection, respectively.

Mapping the Potential of Tourism Villages Using Geographical Information System in Bintan Regency, Riau Islands, Indonesia

Tourist villages are typically formed to provide at least three major benefits to the local community, namely economic, social, and environmental benefits. Pengudang and Busung villages have the potential to be used as tourist destinations, but this potential has not been fully realized. Pengudang and Busung Villages have been unable to provide economic benefits to the surrounding community due to a lack of utilization and development of natural resources. So far, the hub of tourist activity in Bintan Regency has only been Sebong Lagoi Village and its environs. Despite the fact that there are many villages in Bintan Regency with interesting development potential. As a result, a strategy must be developed so that Pengudang Village and Busung Village, in addition to Sebong Lagoi Village, can be developed as alternative tourist destinations. The use of geographic information systems can aid in the mapping of potential tourist villages. The goal of this study is to use a geographic information system to identify and map the tourism potential in Pengudang and Busung villages. This study employed a spatial analysis based on attractiveness and supporting facilities. According to the results of spatial data processing and field surveys, Pengudang Village has five tourism potentials, while Busung Village has four.

Potensi Geoarkeologi Wilayah Trenggalek dan Peluangnya bagi Pengembangan Geopark

Trenggalek Regency is one of the regencies in the southern part of East Java Province, which its landscape strongly expresses the historical influence of ancient volcanism and tectonics. Unlike the three neighboring districts, namely Ponorogo, Pacitan, and Tulungagung, the archaeological potential related to the condition of the Trenggalek region's landscape has not been studied much. Hills and mountains with steep slopes form nearly 80% of the Trenggalek area. In the south, karst hills and coastal areas are stretch from west to east, connecting with the East Pacitan karst area on the west and the Tulungagung karst area on the east. The lowlands are only found in the central part, forming an intermontane basin with the Ngasinan River as the main river. A geoarchaeological approach is needed to explore the archaeological potential by studying the uniqueness of its landscape (history and geological formations). Through this approach, this research leads to the pilot development of a geopark based on the features and uniqueness of the Trenggalek region's natural history and its correlation with the accompanying non-geological aspects, namely the diversity of archaeological and biological sites. Initial efforts were made by finding, recording, and assessing the features and uniqueness of locations that could potentially be used as geosites. This concept combines earth, cultural and biological aspects to conserve geological heritage, enhance the local economy, and education. The analysis of each element is based on a geoarchaeological perspective through spatial data processing based on the Geographic Information System (GIS). The final result is in the form of scientific knowledge about the geoarchaeological potential of the Trenggalek area and recommendations for geopark development according to the potential level of each geosite.

Геопорталы как инструмент доступа к облачным хранилищам данных о метагеосистемах

The article is devoted to solving the scientific problem of spatial data storage management using geoportal systems on the basis of solving the scientific problem of analyzing the patterns of spatiotemporal organization of complex dynamic hierarchically organized metageosystems. The paper proves that the problem of integrating large arrays of spatial information in spatial data infrastructures (SDIs) can be solved by designing multi-model storages operating on the basis of database management systems of different classes. To improve the reliability of spatial data integration systems, it is advisable to focus on a microservice architecture that involves organizing the interaction of separate services, each of which performs its own specific task. The following microservices usage contexts can be distinguished in the IPD: geoportals, spatial data analysis, processing and management systems, as well as distributed cloud storages.

Characteristics of Sediment and Physical Oceanography at Shoreline Movement of Rhu Bay Riau Province Indonesia

Rhu Bay is located in Rupat Island, Bengkalis Regency, Riau Province, Indonesia, under influence of the Malacca Strait. The main purpose of this study is to analyze shoreline changes in the Rhu Bay Coastal Area for 18 years, from 2012 to 2022 based on characterstics of sediment and physical Oceanography. Analysis of shoreline changes using Google Earth (Landsat Copernicus) covering the entire Rhu Bay area in 2002, 2008, 2014 and 2020. This research was carried out in Rhu Bay in June 2022 through two research stages:1) processing of secondary data in using Lansat Imagery Data and 2) the sediment samples were collected using sediment grab and oceanographic observation (currents, tides and waves) was also carried out at the coast. Digital Shoreline Analysis System (DSAS) is empowered in processing spatial data to calculate the rate of abrasion and accretion in Rhu Bay, using the methods applied of Net Shoreline Movement (NSM) and End Point Rate (EPR). The results of the study show that the coastline changes dominantly in Rhu Bay experiencing abrasion of 7.87 - 11.24 meters/year in a period of 18 years. The oceanographic parameters in Rhu Bay showed that the waves had a height of 0.2 m with a period of 3 second, current velocity of 0.36 m/s to the northwest. The change in shoreline is thought to be due to the current that flows from the Malacca Strait at high and low tide, as well as the transport of coastal sediment (dominated by medium sand fraction) towards the Malacca Strait by the currents.

Seismotectonics of Shallow-Focus Earthquakes in Venezuela with Links to Gravity Anomalies and Geologic Heterogeneity Mapped by a GMT Scripting Language

This paper presents a cartographic framework based on algorithms of GMT codes for mapping seismically active areas in Venezuela. The data included raster grids from GEBCO, EGM-2008, and vector geological layers from the USGS. The data were iteratively processed in the console of GMT, converted by GDAL, formatted, and mapped for geophysical data visualisation; the QGIS was applied for geological mapping. We analyzed 2000 samples of the earthquake events obtained from the IRIS seismic database with a 25-year time span (1997–2021) in order to map the seismicity. The approach to linking geological, topographic, and geophysical data using GMT scripts aimed to map correlations among the geophysical phenomena, tectonic processes, geological setting, seismicity, and earthquakes. The practical application of the GMT scripts consists in automated mapping for the visualization of geological risks and hazards in the mountainous region of the Venezuelan Andes. The proposed method integrates the approach of GMT scripts with state-of-the-art GIS techniques, which demonstrated its effectiveness as a tool for mapping spatial datasets and rapid data processing in an iterative regime. In this context, using GMT and GIS to find similarities between the regional earthquake distribution and the geological and topographic setting is essential for hazard risk assessment. This study can serve as a basis for predictive seismic analysis in geologically vulnerable regions of Venezuela. In addition to a technical demonstration of GMT algorithms, this study also contributes to geological and geophysical mapping and seismic hazard assessments in South America. We present the full scripts used for mapping in a GitHub repository.

Mapping of Electrical Distribution Networks at Jampit Distribution Substations Using ArcGIS

In the Ijen sub-district, care must be taken to avoid overlapping uses of PTPN XII-owned plantations, resident fields, and the medium-voltage power distribution network. To lessen the interference factor in the distribution of electricity, the proper power distribution path must be chosen. The contact between trees and lightning is one of the variables that disturbs the distribution pathway. It is well known that the Jampit distribution substation in the Ijen district is situated in a region with plantations and private fields, making it susceptible to lightning and contact with trees. The position of distribution substations, medium-voltage overhead lines, and the location of energy users are among the issues examined in this study. In order to create a map of the electricity distribution network at Jampit distribution substations that pass through agricultural land and plantation areas, ArcGIS is used to help process spatial data including regional administration data, type of conductor, power capacity, distribution substation poles and electricity users.

Population Analysis Using Gis Software Tools – Case Study of Romania

Population management is difficult and complex due to its dynamic and complexity. When we talk about demography, we talk about human population in a defined geographic area, meaning, demography is a spatial science. Geographic Information System (GIS) is a modern tool used in many fields, to manage attribute data and spatial data, including population management. The aim of this study is to present the size of population for each county and urban/rural area on two different years: 2012 and 2020, and the estimation of population growth until the year of 2050. Used for processing spatial data, ArcGIS package from ESRI, allows spatial and geostatistical analysis, mathematical calculations and the visualizations of data. Modern cartography is using GIS technologies to create maps in an easier and flexible way. GIS can use the existing analog maps after digitizing them. Using GIS, specialists can create maps at any scale, centered on any location and showing any selected information. ArcGIS tools permit to visualize, query and overlay the data bases related to the maps. Using ArcGIS applications, we determined the counties which present an increasing of population, and those presenting a decreasing of population, as well as the evolution of population in urban and rural area. In order to determine which counties are affected more by the population decline, we calculated the growth rate using the three major demographic variables: Birth, Death and Migration. In conclusion, we can say that the population in Romania has decreased in the past 8 years and is going to decrease even more in the next 30 years. This happened due to the low birth rate and high emigration rate.

Regional metal pollution risk assessment based on a big data framework: A case study of the eastern Tianshan mining area, China

With the increasing maturity of big data technology, its application in the field of environmental assessment has become an important issue. The mining of mineral resource can affect the balance in the ecological environment surrounding mining areas and the normal life activities of humans through groundwater. To solve this problem, big data-based methods were used to evaluate the pollution risk in mining areas in this article. Based on a spatial big data management framework, in this paper, high-risk areas in eastern Tianshan were quantitatively analyzed and delineated via a new comprehensive heavy metal pollution assessment system. A distributed storage environment, unstructured management method and spatial index coding were used to uniformly manage spatial data in vector and raster formats retrieved from different sources. A system involving 18 geological environment indicators was used to evaluate the risk level in the study area and in delineated areas with a high risk of heavy metal pollution. The results indicated that the proposed framework could efficiently store and process spatial data and realize environmental pollution risk assessment in a big data environment. In addition, some of the high-pollution risk areas identified based on the assessment results were consistent with actual mine locations. Overall, the results show that integrating multi-source geological characteristics through a comprehensive evaluation system based on big data can have a positive effect on improving the accuracy of heavy metal pollution risk assessment. Heavy metal pollution assessment can provide a reference for environmental monitoring and governance of the eastern Tianshan region and offer new solutions to large-scale heavy metal pollution assessment.

Wetland mapping based on feature optimization and Google Earth Engine in Zhalong Nature Reserve

Wetlands have very important and irreplaceable ecological service functions in protecting biodiversity and maintaining ecological balance. Due to the unique hydrological characteristics of wetlands, large-scale wetland mapping methods are usually time-consuming, labor intensive, and expensive. With the rise of big data and cloud computing platforms, there are opportunities for long time series and large-scale spatial data processing that improve large-scale wetland mapping. In this study, the Sentinel-1, Sentinel-2, and digital elevation model derived from the Google Earth Engine were used to extract the wetland extent in the Zhalong Nature Reserve based on the Jeffries–Matusita (JM) distance for feature optimization and random forest. Research shows the following: (1) The JM distance for each feature showed that the optical features had the highest separation in all five features and (2) the classification after feature optimization performed best. User accuracy (UA) and producer accuracy (PA) for wetland reached 89.64% and 83.00%, respectively, and overall accuracy reached 90.76%. After feature optimization, PA and UA of wetland were each increased 4.26% and 1.07%, respectively, and the number of features was reduced from 46 to 28. The method used in this study is highly accurate in wetland mapping and can effectively avoid the problem of data redundancy.

GEOVISUALIZATION ANALYSIS OF GENDER-BASED VIOLENCE IN MEXICO CITY USING 3D MAPPING APPROACH

Abstract. The study of criminal acts is a topic of great interest to society and with the increase of violence against women in the world makes working with this type of data an important subject, where it can be used to detect areas with high crime rates to help in decision making. This work uses open data sets available from government entities of Mexico City, where three sectors of interest were studied: economic, education, and transportation around the criminal investigation reports made by the government. For the processing and analysis of spatial data, QGIS was used with the help of open-source libraries, the 2D and 3D modelling was carried out to create heatmaps and detect hotspots. It was found that the Historic center of Mexico City is the most insecure and that the Cuauhtémoc district stands out as the most dangerous zone, for transport stations, the ones that had the most intersections with other stations are the ones that presented greater problems of gender violence, in the economic sector there was a high incidence in the limits of each district, contrary to the results obtained on the educational services.

Real-time identification of eye fixations and saccades using radial basis function networks and Markov chains

• Identification of eye saccades and fixations is critical in many applications. • We present a Concept Drift approach, called RBFNMC, designed to monitor eye movements. • RBFNMC combines Radial Basis Function Networks and Markov Chains to detect drifts. • RBFNMC models fixations as network nodes and saccade probabilities as weighted edges. • Results show robust, online and unsupervised drift detections, meeting XAI standards. Analysis of eye-movements is crucial to many applications, from medical diagnosis to gaming. A critical step in this process lies in segmenting raw gaze coordinates provided by the eye-tracker into eye saccade and fixation events. This detection is generally executed offline, as most methods require a complete dataset or large temporal windows. Many of these algorithms also rely on heuristics such as fixed velocity thresholds, yielding variations in the results depending on the user’s choice of parameters. To overcome such limitations, we designed a new approach, named RBFNMC, which combines Radial Basis Function Network (RBFN) and Markov Chains (MC) in a Concept Drift framework. Our approach is capable of automatically categorizing saccades and fixations in an online scenario. Comparisons with previous detection techniques revealed accurate predictions, while not requiring fixed threshold parameters. Our results were estimated from real eye-movement datasets collected in experiments with: (i) monkeys in a free-viewing paradigm; (ii) human subjects looking at different types of stimuli. Comparing RBFNMC with several other methods widely cited in the literature, our contribution constitutes a new computational approach to process spatial data streams in an online and unsupervised fashion. As a consequence, we provide an efficient mechanism to detect saccade and fixations which support eye-tracking research in neuroscience and other areas. Finally, it is worth emphasizing that our work additionally provides the possibility of interpreting the decision process by inspecting graph-based visualizations of RBFN and of the transition probabilities in MC.