Joanna Nowak Da Costa

An important issue in the redevelopment of post-industrial sites, e.g., into housing, is the resolution of contaminated land issues, including health risks and environmental protection. The purpose of this article is to examine awareness of this aspect from the perspective of city or such site residents, using Warsaw as an example. Using a survey-style form data collection technique, a total of 55 fully completed survey questionnaires were collected and analysed using cross-tabulation. Furthermore, a desk research methodology was used to study the availability of sources on industrial areas and their transformation from the perspective of different stakeholder groups involved in the development of such areas in Poland. Similarly, information management was assessed from the viewpoint of information communities participating or being affected by redevelopment processes. The survey results evidenced that respondents are aware that post-industrial sites may be contaminated, but do not associate the possibility of potential health risks when residing on or near such sites. The analysis of the management of information on the reurbanisation of post-industrial sites in urban areas in Poland, including the availability of data on location and contamination, revealed a problematic data flow between central and local level authorities and mootable consistency of legal acts. Public awareness of negative phenomena, such as contamination and the consequent health risks associated with dwelling in such sites, can positively influence, as an input to monitoring and enforcement, the actions taken by other stakeholders in the clean-up processes of contaminated sites and force improvements in the management of such information. The flow of information, the activities forming the information function, and the decision-making process can be improved by technologies, such as spatial information systems and their infrastructures, by facilitating the integration of data from multiple sources and consequently enabling the analysis to be extended to include further relevant data.

The paper presents a coherent, original theory and an effective algorithm to calculate the surface area of a geodesic polygon, i.e. the area on an ellipsoid of revolution limited by geodesics, connecting pairs of subsequent vertices of known geographical coordinates. Using the cylindrical coordinate system and introducing an equatorial geodesic triangle, the novel strict recursive formulas were derived for the longitude on the ellipsoid and the distance along the geodesic and the area of a geodesic polygon. The area is determined by constant coefficients, not the values of finite series. The orthodromic properties of geodesics, which led to the detection of bifurcation lines composed of the double solutions of the inverse geodetic problem were analysed. The novel algorithm presented, integrating the problem with geodesic polygon area calculation, is based on the newly proposed parameterisation with two alternative working unknowns and a new formula to obtain the initial value of the geodesic C parameter. It allows solutions for all cases, including near-antipodal or near-vertices, and offers two solutions if bifurcation occurs. The algorithm presented was tested and verified using numerical examples from known publications. The numerical tests proved the accuracy of 1m² of the computed geodesic area using standard IEEE 754 Double Floating Point PC arithmetic, for geodesic lengths up to ten thousand km.

An increase in temperature causes higher evaporation of water from water bodies; consequently, the water content in the atmosphere also increases. The precipitable water (PW), as the water content in the atmospheric air column, is therefore an important parameter to consider when studying climate change. The aim of this study was to analyse multi-annual precipitable water data derived from a dense Global Navigational Satellite Systems (GNSS) network. Twelve years of observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values over Poland. The data were validated by comparison with the available radio-sounding data. The analysis of the GPS-based PW values showed an upward trend in the PW value of 0.078 mm/year. The spatio-temporal distribution of the mean PW values and their fluctuations over the years were studied and visualised in the form of maps. The results are congruent with the fact that Poland lies on the border of influence of both continental and oceanic climates. Our results are also consistent with other climate research concerning this region.

As an important facilitator in e-government and society in general, Open SDI merits an assessment of its characteristics and the monitoring of its development. The aim of the study was the proposal of the SDI openness assessment approach based on existing openness assessment frameworks, as well as the presentation of the Polish Spatial Data Infrastructure (PSDI) development towards openness. The results indicated that ten geodetic and cartographic databases fulfilled ten out of eleven criteria of data openness, according to the methodological assumptions, and reached a 3-star level of openness. The need for further development of the infrastructure towards sharing public administration data is recognized, as well as non-governmental data that meet the open data criteria, thus contributing to the openness of the SDI. The proposed assessment method, referenced to a five-level data openness system and providing clear scoring benchmarking for assessing SDI openness, may be used for comparative analysis of SDI openness in different countries, including EU Member States that draw on the experience of the implementation of the INSPIRE Directive.

The provision of detailed information on the impact of potential fluvial floods on urban population health, quantifying the impact magnitude and supplying the location of areas of the highest risk to human health, is an important step towards (a) improvement of sustainable measures to minimise the impact of floods, e.g., by including flood risk as a design parameter for urban planning, and (b) increase public awareness of flood risks. The three new measures of the impact of floods on the urban population have been proposed, considering both deterministic and stochastic aspects. The impact was determined in relation to the building’s function, the number of residents, the probability of flood occurrence and the likely floodwater inundation level. The building capacity concept was introduced to model population data at the building level. Its proposed estimation method, an offshoot of the volumetric method, has proved to be successful in the challenging study area, characterised by a high diversity of buildings in terms of their function, size and density. The results show that 2.35% of buildings and over 122,000 people may be affected by 500-year flooding. However, the foreseen magnitude of flood impact on human health is moderate, i.e., on average ten persons per residential building over the 80% of flood risk zones. Such results are attributed to the low inundation depth, i.e., below 1 m.

Standards and legislation are already in place to provide the necessary building requirements to improve mobility access for everyone. However, these requirements are not always adhered to for a variety of reasons even in cases of new constructions. Moreover, already existing structures and/or historical buildings built prior to such mobility requirements were put into force must be retrofitted. Consequently, a significant number of potential interesting locations are not accessible to persons with reduced mobility. For this reason, the focus of our research is on the expected content and availability of detailed mobility related information and how to improve the communication of accessibility information to users in order to evaluate the accessibility potential of public places and spaces to help persons with reduced mobility plan their outings by taking advantage of smart data and people in cities.

Population density is one of the key parameters for assessing the magnitude of population exposed to risk, and the better quality data we have, the better the assessment of risk. The aim of this study is to elaborate a high-resolution spatially distributed population density grid, which estimates population at the commune scale with a reliability of over 90%. The novelty of the approach is population density estimation in a regular European grid, based on buildings vector data collected in the national topographic database. Using abductive reasoning in combination with statistics and spatial analysis, the authors extract approximate information about a population from the large-scale topographic data. Moreover, linking the obtained population data with the cadastral data – by unique building identifier – allows for regular, quick and census survey-independent updates of the population surface. A shortcoming of the approach is the issue of the possible existence of two houses per family, which leads to an overestimation of population. However, in the study area it affected only two of the total 14 communes by 7%–9%.

The aim of this study is to describe uncertainty of the Global Rural-Urban Mapping Project (GRUMP) data based on Polish population reference grid created by the Central Statistical Office of Poland, using INSPIRE grid coding system. The adopted population data uncertainty analysis methodology combined three different approaches, i.e. simple change detection algorithm to obtain discrepancies at the grid cell level, statistical analytical approach to investigate these discrepancies’ frequency distribution, and GIS approach to analyse spatial pattern of distinguished population difference classes. The results showed significant differences in population count at the grid cell level. The maximum magnitude of GRUMP vs. Polish Reference Grid overestimation equals 4087 people per 1 sq. km, while the underestimation equals 20,086 people per 1 sq. km. Very few grid cell shows no difference in population count, i.e. 1.5% of total grid cell count. GRUMP data overestimates Polish total population by 0.15%, while it underestimates the average population density by 50%. The highest population underestimations were identified in the centers of the cities, while suburban areas were characterised by the large and regular population overestimations within GRUMP dataset. These GRUMP dataset imperfections can be attributed to country-specific administrative divisions and to the varying effectiveness of the urban centers delimitation mapping using the night sky light intensity, including blooming effects as well as not frequently illuminated small settlements.

This study presents the creation of semantic correspondence rules for an attribute of interest and the framework for the analysis of thematic data semantic similarity between corresponding building entities in different databases. The analysis was based on the Polish Database of Topographic Objects, the official National Mapping Agency dataset, and Volunteered Geographic Information available from the OpenStreetMap (OSM) project. The work required proposing a user oriented approach to tackle several specific issues, namely: variable data conceptualizations and content organizations manners, and unambiguous one-to-one correspondence lack between two classification schemas, patchy OSM completeness, and language medium -- British English vs. Polish.