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Tag Archives: 100×100 street Index

100×100 street index is a special 100×100 grid based purchasing power database of Hungary for location based analysis. Demography, net income, type of residential areas, purchasing power clusters, and special traffic indexes like: Pedestrian Traffic Index, Downtown index, Public Transport Index and more…

100×100 Purchasing power clusters of Hungary

100×100 Purchasing power clusters of Hungary 100×100 Purchasing power clusters of Hungary shows the street level differences of neigbourhood profiles and purchasing power of settlements in Hungary. Settlements of database The map based street level database is available for 136 settlements in Hungary: County seats in Hungary: Debrecen, Győr, Miskolc, Pécs, Szeged, Kecskemét, Nyíregyháza, Székesfehérvár, Békéscsaba, Eger,  Szolnok, […]

Purchasing power, population map – new database 2017

New database is available in 100×100 street level purchasing power map of cities of Hungary. The GIS database contains several street level (100×100 meters grid) base data – population, age groups, net income, etc – and complex indicators for 136 settlements in Hungary. Sample map using this database in CartoDB » Purchasing power, net income datasource […]

100×100 database settlements – 2018

100×100 street level purchasing power database is availabele for 246 hungarian settlement: Budapest – capital (by districts too) county seats, small region centers (NUTS4) cities (more than 20 000 inhabitants) settlements of suburb of Budapest

Differences of city districts in Hungary

ZIP codes or districts are the basic elements of Business GIS analysis in data collection or data vizualization. Districs of Cities In ArcHungary – administrative vector map of Hungary, the ZIP codes and districts of cities (for more than 70 cities) are independent layers with several attributum data as name of districs and settlement, or […]

GeoIndeX 100×100 database indicators – 2017

GeoIndeX 100×100 database indicators – 2017 Street level purchasing power database for 136 cities in Hungary. Map based database (; ESRI.shape; txt with coordinates). More than 20 indicators: population density, age groups, net income per capita, different kind of indexes to describe the spatial differences of a city. Special location based data analysis services.

100×100 database – Price list by settlement – 2018

100×100 database – Price list by settlement – 2018 contains the names, types and price of database by settlements: 100×100 – street level statistical database GeoXRaster – raster map of the cities DSM-10 – street level vector map of cities Valid from 01.01.2018

KFC Restaurant in Óbuda – location analysis

A new KFC restaurant opened last month near our office in Óbuda. We try to visualise the characteristic of surrounding area of the location using GeoIndeX database. Downtown index Locations of public services, and public transport changes shows the downtown index. Residential types Proportion of housing estates, townhouse or block of flats and family houses […]

Interactive purchasing power map of Hungarian cities

Now is available GeoIndeX interactive purchasing power map of Hungarian cities. Click the picture!   Datasource of tematic maps is GeoIndeX 100×100 street level purchasing power database. Database is available for Budapest, county seats and settlementos of Hungary with more than 20 000 inhabitants. Let’s see the map » Purchasing power indicators The interactive purchasing power map […]

Street level purchasing power – new data not only for Budapest – 2014

Now available the dataset of 2014. which help to understand the differences of purchasing power of Budapest and surrounging area (the agglomeration of Budapest) in street level. Let’s see the list of settlements! » New indicators for analyse the spatial differences of purchasing power With the update of dataset year 2014, new indicators were integrated to the […]

Population by age groups in Hungarian cities – 2013.

Young – Middle age – Elderly The purchasing power of an area depends on the young or old age dependency ratio too. For example it could be an important question: How many juvenile live in our target region? Is high the old age dependency ratio in this city? GeoIndeX database helps to answer these questions. […]



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