Estimating Residential Property Values on the Basis of Clustering and Geostatistics

The article presents a two-stage model for estimating the value of residential property. The research is based on the application of a sequence of known methods in the process of developing property value maps. The market is divided into local submarkets using data mining, and, in particular, data clustering. This process takes into account only a property’s non-spatial (structural) attributes. This is the first stage of the model, which isolates local property markets where properties have similar structural attributes. To estimate the impact of the spatial factor (location) on property value, the second stage involves performing an interpolation for each cluster separately using ordinary kriging. In this stage, the model is based on Tobler’s first law of geography. The model results in property value maps, drawn up separately for each of the clusters. Experimental research carried out using the example of Siedlce, a city in eastern Poland, proves that the estimation error for a property’s value using the proposed method, evaluated using the mean absolute percentage error, does not exceed 10%. The model that has been developed is universal and can be used to estimate the value of land, property, and buildings

Interactive map of refugee movement in Europe

Considering the recent mass movement of people fleeing war and oppression, an analysis of changes in migration, in particular an analysis of the final destination refugees choose, seems to be of utmost importance. Many international organisations like UNHCR (the United Nations High Commissioner for Refugees) or EuroStat gather and provide information on the number of refugees and the routes they follow. What is also needed to study the state of affairs closely is a visual form presenting the rapidly changing situation. An analysis of the problem together with up-to-date statistical data presented in the visual form of a map is essential. This article describes methods of preparing such interactive maps displaying movement of refugees in European Union countries. Those maps would show changes taking place throughout recent years but also the dynamics of the development of the refugee crisis in Europe. The ArcGIS software was applied to make the map accessible on the Internet. Additionally, online sources and newspaper articles were used to present the movement of migrants. The interactive map makes it possible to watch spatial data with an opportunity to navigate within the map window. Because of that it is a clear and convenient tool to visualise such processes as refugee migration in Europe

Usefulness of OSM and BDOT10k Data for Developing Tactile Maps of Historic Parks

A map, being a scaled-down image of a fragment of the Earth, reflects the actual relationships between objects in a way that allows for comprehensive exploration of large areas. In particular, a map is an ideal tool for exploring the layout of historic parks, as it shows their character according to their style. Depending on the style of the parks, their maps will differ in terms of the appropriate selection of the scope of content and the system of cartographic signs. Nowadays, distribution maps of parks for the visually impaired are increasingly popular. Depending on the purpose of a map, it is essential to obtain the relevant spatial data before creating it. Spatial data are also important to convey knowledge about the form of the given park and its function, elements, small garden architecture, plant compositions, and garden arrangements. The purpose of this study is to assess the usefulness of OSM (OpenStreetMap) and BDOT10k (the Topographic Objects Database) data for the development of tactile maps of historic parks, with five garden styles. Data features, such as accessibility of spatial objects and descriptive attributes, including names that allow identification of the object type or completeness of object occurrence, were taken into consideration. The assessment was conducted for three levels of map detail and separately for each garden style. The results showed that almost half of the tactile maps’ content items could be taken from BDOT10k or OSM. The Data Usefulness Index (DUI) confirmed a slight advantage of BDOT10k, taking almost the same values as OSM (0.49:0.48 at the first level of map detail and 0.40:0.38 at the second level of map detail). Complementing information on park objects obtained from OSM and BDOT10k data with data from orthophotomaps or field measurements makes it possible to develop maps that convey information about the composition of a park as a whole and about the cultural assets that blind or visually impaired people have not yet been able to fully experience in a direct way

Multi-Criteria Analysis for Solar Farm Location Suitability

Currently the number of solar farms, as a type of renewable sources of energy, is growing rapidly. Photovoltaic power stations have many advantages, which is an incentive for their building and development. Solar energy is readily available and inexhaustible, and its production is environmentally friendly. In the present study multiple environmental and economic criteria were taken into account to select a potential photovoltaic farm location, with particular emphasis on: protected areas, land cover, solar radiation, slope angle, proximity to roads, built-up areas, and power lines. Advanced data analysis were used because of the multiplicity of criteria and their diverse influence on the choice of a potential location. They included the spatial analysis, the Weighted Linear Combination Technique (WLC), and the Analytic Hierarchy Process (AHP) as a decisionmaking method. The analysis was divided into two stages. In the first one, the areas where the location of solar farms was not possible were excluded. In the second one, the best locations meeting all environmental and economic criteria were selected. The research was conducted for the Legionowo District, using data from national surveying and mapping resources such as: BDOT10k (Database of Topographic Objects), NMT (Numerical Terrain Model), and lands and buildings register. Finally, several areas meeting the criteria were chosen. The research deals with solar farms with up to 40 kW power. The results of the study are presented as thematic maps. The advantage of the method is its versatility. It can be used not only for any area, but with little modification of the criteria, it can also be applied to choose a location for wind farms

Towards sustainable development exemplified by monitoring land use efficiency in Europe using SDG 11.3.1

Monitoring land use efficiency (LUE) is of great importance for the sustainable development of each country. The identification of regions where land consumption prevails over demographic growth should prompt public administrations to act and establish a recovery programme. This paper took Europe as the research area, and CORINE Land Cover and statistical population data to assess changes and spatial diversity of the LUE status from 2006 to 2018. Results show that, during the 2006–2012 period, LUE was more diversified than in 2012–2018. The differences concern both values of the indicator and the spatial differentiation between regions. Between 2012 and 2018, the number of countries moving towards efficient land use doubled compared to 2006–2012. Great progress towards achieving SDG 11.3.1 was seen in Portugal and Germany, and almost all Balkan countries are moving towards more efficient land use

Reliability Analysis of LandScan Gridded Population Data. The Case Study of Poland

The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the reliability of LandScan based on the official Polish Population Grid. The adopted methodology was based on the change detection approach, spatial pattern and continuity analysis, as well as statistical analysis at the grid-cell level. Our results show that the LandScan data can estimate the Polish population very well. The number of grid cells with equal people counts in both datasets amounts to 10.5%. The most and highly reliable data cover 72% of the country territory, while less reliable ones cover only 4.3%. The LandScan algorithm tends to underestimate people counts, with a total value of 79,735 people (0.21%). The highest underestimation was noticed in densely populated areas as well as in the transition areas between urban and rural, while overestimation was observed in moderately populated regions, along main roads and in city centres. The underestimation results mainly from the spatial pattern and size of Polish rural settlements, namely a big number of shadowed single households dispersed over agricultural areas and in the vicinity of forests. An excessive assessment of the number of people may be a consequence of the well-known blooming effect

Redistribution population data across a regular spatial grid according to buildings characteristics

Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory

Spatial pattern of ASG-EUPOS sites

The article presents the spatial pattern analysis of the ASG-EUPOS permanent GNSS stations in Poland. Using different methods and tools (nearest neighbour, Riplay’s K-function, morphology of Thiessen polygons) we proved that the station distribution model changes within scales. At short distances up to 65 km, which are typical lengths in the network, stations are irregularly dispersed. Increasing this distance to 130 km and over could result in a clustered pattern

The Ratio of the Land Consumption Rate to the Population Growth Rate: A Framework for the Achievement of the Spatiotemporal Pattern in Poland and Lithuania

Indicator 11.3. 1 of the 2030 sustainable development goals (SDG) 11, i.e., the ratio of the land use to the population growth rate, is currently classified by the United Nations as a Tier II indicator, as there is a globally-accepted methodology for its calculation, but the data are not available, nor are not regularly updated. Recently, the increased availability of remotely sensed data and products allows not only for the calculation of the SDG 11.3. 1, but also for its monitoring at different levels of detail. That is why this study aims to address the interrelationships between population development and land use changes in Poland and Lithuania, two neighboring countries in Central and Eastern Europe, using the publicly available remotely sensed products, CORINE land cover and GHS-POP. The paper introduces a map modelling process that starts with data transformation through GIS analyses and results in the geovisualisation of the LCRPGR (land use efficiency), the PGR (population growth rate), and the LCR (land use rate). We investigated the spatial patterns of the index values by utilizing hotspot analyses, autocorrelations, and outlier analyses. The results show how the indicators’ values were concentrated in both countries; the average value of SDG 11.3. 1, from 2000 to 2018 in Poland amounted to 0.115 and, in Lithuania, to −0.054. The average population growth ratio (PGR) in Poland equaled 0.0132, and in Lithuania, it was −0.0067, while the average land consumption ratios (LCRs) were 0.0462 and 0.0067, respectively. Areas with an increase in built-up areas were concentrated mainly on the outskirts of large cities, whereas outliers of the LCRPGR index were mainly caused by the uncertainty of the source data and the way the indicator is interpreted

Fine scale population density data and its application in risk assessment

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%