Pregled bibliografske jedinice broj: 1281867
Creation of a very High Resolution Dasymetric Model Using the Advanced Geospatial Technologies
Creation of a very High Resolution Dasymetric Model Using the Advanced Geospatial Technologies // Demographic Challenges in Bosnia and Herzegovina and the World
Sarajevo, Bosna i Hercegovina, 2023. str. 62-63 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1281867 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Creation of a very High Resolution Dasymetric Model
Using the Advanced Geospatial Technologies
Autori
Šiljeg, Ante ; Marić, Ivan ; Šiljeg, Silvija ; Domazetović, Fran
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Demographic Challenges in Bosnia and Herzegovina and the World
/ - , 2023, 62-63
Skup
Demographic Challenges in Bosnia and Herzegovina and the World
Mjesto i datum
Sarajevo, Bosna i Hercegovina, 08.06.2023. - 09.06.2023
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
dasymetric model ; geospatial technologies ; multi-sensor approach ; Metković
Sažetak
The spatial distribution of the population at a higher level of detail is a useful tool for decision-making in the planning and management process, as well as in numerous socio-economic researches. Dasymetric modeling ia s technique for redistribution of population data from census- designated administrative units into raster data with higher spatial resolution. The main aim of this paper is to apply different geospatial technologies to create a very high-resolution dasymetric model at the level of individual buildings. A new proposed methodology for mapping of population within IB integrates and synthesizes data from different sensors. This paper describes in detail the steps that lead to the identification of buildings using a multi- data/sensor approach. The building footprints were extracted using geographic object-based image analysis, based on the created multispectral model. Heigh data and shape of buildings were obtained by collection and processing of aero- LiDAR data using the artificial intelligence tools. To generate a better model, spatial plan data were used, which enabled the classification of buildings into residental and non-residental ones. Residental buildings were further classified into houses and buildings. The accuracy of the created model was tested using the area under curve measure based on the reference data. The applied approach and obtained data can be used to solve a number of problematic issues, such as characterization of the population at risk from natural hazards and assessing human induced pressure on the environment.
Izvorni jezik
Engleski
Znanstvena područja
Geografija
POVEZANOST RADA
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