One of the more important elements of spatial information infrastructure is the organisational structure defining the obligations and dependencies between stakeholders that are responsible for the infrastructure. Many SDI practitioners and theoreticians emphasise that its influence on the success or failure of activities undertaken is significantly greater than that of technical aspects. Being aware of the role of the organisational structure in the creating, operating and maintenance of spatial information infrastructure (SII), Polish legislators placed appropriate regulations in the Spatial Information Infrastructure Act, being the transposition of the INSPIRE Directive into Polish Law. The principal spatial information infrastructure stakeholders are discussed in the article and also the scope of cooperation between them. The tasks and relationships between stakeholders are illustrated in UML, in both the use case and the class diagram. Mentioned also are the main problems and obstructions resulting from imprecise legal regulations.
Polish spatial data infrastructure dates back 2010, the year when the Spatial Information Infrastructure Act transposing INSPIRE Directive entered into force. The present study provides valuable insight into the current status of Polish spatial data infrastructure (PSDI) as well as lessons learnt from so far efforts in implementing the principles and provisions of the INSPIRE Directive. Particular respect is given to policy, interoperability of data as well as cooperation between actors involved in PSDI establishment and maintenance. Data managed by the Surveyor General (SG), perceived as a backbone of a spatial data infrastructure, are of special importance. Finally, some conclusions and recommendations for further developments are given to foster SDI implementation in Poland. Results of the analysis clearly show that Polish spatial data infrastructure is in line with INSPIRE, and in a half of way being fully operational.
Population data are generally provided by state census organisations at the pre- defined census enumeration units. However, these datasets very are often required at user- defined 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.