Contemporary cities require excellent walking conditions to support human physical activity, increase humans’ well-being, reduce traffic, and create a healthy urban environment. Various indicators and metrics exist to evaluate walking conditions. To evaluate the spatial pattern of objective-based indicators, two popular indices were selected—the Walkability Index (WAI), representing environmental-based indicators, and Walk Score (WS), which applies an accessibility-based approach. Both indicators were evaluated using adequate spatial units (circle buffers with radii from 400 m to 2414 m) in two Czech cities. A new software tool was developed for the calculation of WS using OSM data and freely available network services. The new variant of WS was specifically designed for the elderly. Differing gait speeds, and variable settings of targets and their weights enabled the adaptation of WS to local conditions and personal needs. WAI and WS demonstrated different spatial pattern where WAI is better used for smaller radii (up to approx. 800 m) and WS for larger radii (starting from 800 m). The assessment of WS for both cities indicates that approx. 40% of inhabitants live in unsatisfactory walking conditions. A sensitivity analysis discovered the major influences of gait speed and the β coefficient on the walkability assessment.

Web services support the integration and interoperability of Web-based applications and enable machine-to-machine interaction. The concepts of web services and open distributed architecture were applied to the development of T-DSS, the prototype customised for web based hydro-information systems. T-DSS provides mapping services, database related services and access to remote components, with special emphasis placed on the output flexibility (e.g. multilingualism), where SOAP web services are mainly used for communication. The remote components are represented above all by remote data and mapping services (e.g. meteorological predictions), modelling and analytical systems (currently HEC-HMS, MODFLOW and additional utilities), which support decision making in water management.

One of the ways of improving the attractiveness of public transport is to bring it closer to its potential users. A long walking distance from a stop is often one of the critical factors limiting its more frequent and extensive use. Studies dealing with the accessibility of transport networks usually work only with the closest stop. This article analyses the actual walking distance from the place of residence to the preferred stop. The survey used a questionnaire method and was conducted in two cities in the Czech Republic—Ostrava and Olomouc. Based on the results of the study, the average walking distance was assessed and the impact of demographic characteristics (gender, age, education, number of members in the household, economic activity, the presence of a child in the household, and car ownership), transport behavior (preferred mode of transportation, car convenience and opinions on public transport), and urban characteristics (prevailing housing type) on the walking distance were analyzed. The main findings prove a significant impact on walking distance by a number of these factors, but the preferred use of a car for commuting or unemployment does not significantly affect walking distance.

With the development of remote sensing techniques, optical images become more efficient compare to field survey. However, the quality of optical images would influenced by cloud. Radar is known to be very sensitive to vegetation physiognomy and biomass. The sensitivity of synthetic aperture radar (SAR) to the structural features of terrain leads to landcover classification into simple and easily interpreted structural classes. In this paper, the potential of using free of charge Sentinel-1 SAR imagery for land cover mapping in the Moravian-Silesian region, is investigated. The images recorded in 2018 were used for a per-pixel and object-based classification of agricultural land. The per-pixel classification was performed by the maximum likelihood algorithm, the object-based classification then using the support vector machine algorithm. The legend was taken from the Land Parcel Identification System (LPIS) and contained the following three classes – grassland, arable land and a class that involves hop fields, vineyards, and orchards. Post processing of the classification results has been done using the confusion matrix (also known as error matrix) and corresponding overall accuracy and Kappa coefficients of all the classification methods have been calculated. Significantly better results were achieved through object-oriented classification. In both areas of interest, the highest processing and user precision was achieved for the arable land class.

The accessibility evaluation of public transport is based on commuting conditions in the Czech Republic, where still a significant part of jobs are organised in 2 or 3 work shifts. The usual indicators in such conditions suffer from time of day dependency. The analysis of time dependency is provided for commuting between Czech municipalities for several working time intervals. To conduct such a research, large database with public transport connections must be built using software solution and parallel processing of valid time tables. The sensitivity of results to time selection was partly approved. Even more, important differences in accessibility evaluation between evaluated regions are discovered - the largest changes in accessibility are in the central part (Vysocina) and the modest one in Prague and surroundings.