Analýza území pomocí prostorových datasetů

Territory analysis with spatial datasets

journal article - other

Czech

Příspěvek zaměřen na zkoumání závislost geolokačních dat a cenových údajů naprostorových charakteristikách území v jednotlivých urbanistických strukturách. Datová sada prostorových charakteristik území byla získána z OpenStreetMap jako zdroje informací pro popis a rozbor území urbanistické struktury. Každá urbanistická struktura (typologie) ve městě má své vlastnosti dané charakterem veřejných prostranství, měřítkem staveb, vzájemnými vazbami aatmosférou. Pro potřeby srovnání sledovaných vybraných statistických dat jsem urbanistickou strukturu města Brna rozdělil do několika základních typů: kompaktní struktura, bloková struktura, smíšená struktura, novodobé obytné soubory, solitérní vily a rodinné domy. Provyhodnocení byla použita metoda Multiple-sample comparison, konkrétně analýza rozptylu (ANOVA). Analýza interakce mezi obyvateli a městským prostorem může pomoci ke správnému usměrnění tvorby životního prostředí a souvisejícího veřejného prostoru. Přínos spočívá vukázce inovativního přístupu ke sběru a využití informací pomocí otevřených prostorových dat prostřednictvím datových platforem.

Introduction This research seeks to comprehend and analyze the dynamic interplay between residents and urban spaces, emphasizing the use of geolocation data as an indicator of area quality, which, in turn, may influence property prices. Using OpenStreetMap as a valuable repository of spatial data can help planners and developers support critical decisions in shaping land development. The agglomeration benefits of cities, resulting from spatial concentration of activities, are also investigated, with anemphasis on understanding how cities evolve beyond their primary functions.OpenStreetMap is employed to scrutinize global geospatial data, offering empirical insights into street networks across different urban scales. Materials and methods Each urban structure (typology) in the city has its own characteristics determined by the character of public spaces, the scale of buildings, interrelationships and atmosphere. The data source is the open platform data.bno.cz, which accesses relevant data sets in various formats, including CSV, JSON and XML. For the purpose of comparison of the selected statistical data, Ihave divided the urban structure of Brno into several basictypes:Compact, Block, Mixed, Modern Residential Complexes, Villas, and Family Houses —the study utilizes the Multiple-sample comparison method, specifically Analysis of Variance (ANOVA), to discern significant differences in spatial characteristics among thesestructures.The analysis also incorporates Fisher's Least Significant Difference (LSD) method to identify specific mean differences between different urban structures. Visual representation through Box-and-Whisker Plots enhances the interpretation of results. Results The actual analysis involves an in-depth examination of spatial characteristics through various indicators extracted from OpenStreetMap data. These indicators include a spectrum offactors such as road network length, serviceability index, dust pollutant concentration, population density, park area, floor area index, number of dwellings, number of houses, occupancy index, crime incidence, sales area, development area as per the master plan, resident satisfaction index, resident presence index as per mobile operator data, and number of housing offers. The results show that urban structures can generally be divided into two groups: compact or block structures and modern residential complexes, single-family houses and villas. Mixed structures tend to fit more closely with the characteristics of the second group. Conclusions The paperconcludes that this innovative approach to utilizing open spatial data platforms contributes to transparency and innovation in municipal governance.Statistical tests reveal significant differences between structures for specific indicators, highlighting their diverse impact on the quality of life of residents. This papersheds light on the distinctive characteristics and influences of different urban structures, offering valuable insights for urban planning anddecision-making at the municipal and community levels. The detailed analysis of the interaction between residents and urban spaces contributes to informed development strategies, demonstrating the potential of innovative approaches to data collection andutilization through open spatial data platforms.

Geolokační data; charakteristika území; OpenStreetMap; prostorová data; urbanistická struktura.

Geolocation data; area characteristics; OpenStreetMap; spatial data; urban structure.

KLIMENT, D.

6. 12. 2023

Soudní inženýrství

2788-2764

Soudní inženýrství

34

02

Czech Republic

15

21

7

https://journals.lib.vutbr.cz/index.php/sinz/article/view/80