SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA

The objectives of this study are: to create land-use maps by 5-year interval from 1995 to 2015, to analyse the land use change and urban development, and to estimate future land-use pattern and urban growth for the years: 2030, 2045 and 2060. Antalya, which is the 5th biggest city of Turkey, was sel...

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Main Authors: N. Aslan, D. Koc-San
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/657/2020/isprs-archives-XLIII-B3-2020-657-2020.pdf
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spelling doaj-38d408de36694803bed2020628e151752020-11-25T03:18:46ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B3-202065766210.5194/isprs-archives-XLIII-B3-2020-657-2020SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYAN. Aslan0D. Koc-San1Akdeniz University, Faculty of Science, Department of Space Sciences and Technologies, 07058, Antalya, TurkeyAkdeniz University, Faculty of Architecture, Department of Urban and Regional Planning, 07058, Antalya, TurkeyThe objectives of this study are: to create land-use maps by 5-year interval from 1995 to 2015, to analyse the land use change and urban development, and to estimate future land-use pattern and urban growth for the years: 2030, 2045 and 2060. Antalya, which is the 5th biggest city of Turkey, was selected as study area. In this study, there are basically three stages: (i) preprocessing and preparing additional bands, (ii) spatiotemporal land use detection using image classification and (iii) land use simulation using urban growth models. Firstly, atmospheric correction was applied to the Landsat 5 TM and Landsat 8 OLI images and land-cover indices, ASTER Global Digital Elevation Model (GDEM), and Nighttime data were prepared to use them as additional bands during the classification process. Secondly, Landsat images were classified using Random Forest (RF) machine-learning algorithm. Thirdly, urban simulations were performed for the years 2005, 2010, and 2015 and land-use pattern and urban growth was estimated for the years 2030, 2045 and 2060. The RF classification accuracies range from 84.44% to 92.82%. The urban areas increased from 49.56&thinsp;km<sup>2</sup> to 96.25&thinsp;km<sup>2</sup> from 1995 to 2015. The simulation accuracies were computed above 80%. According to the 2030, 2045 and 2060 simulation results, the urban areas were computed as 133.61&thinsp;km<sup>2</sup>, 148.27&thinsp;km<sup>2</sup> and 156.85&thinsp;km<sup>2</sup>, respectively. As a result, it was seen that the urban area of Antalya has almost doubled between the years 1995–2015 and the urban expansion is expected to continue increasing up to 1960.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/657/2020/isprs-archives-XLIII-B3-2020-657-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author N. Aslan
D. Koc-San
spellingShingle N. Aslan
D. Koc-San
SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet N. Aslan
D. Koc-San
author_sort N. Aslan
title SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
title_short SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
title_full SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
title_fullStr SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
title_full_unstemmed SPATIOTEMPORAL LAND USE CHANGE ANALYSIS AND FUTURE URBAN GROWTH SIMULATION USING REMOTE SENSING: A CASE STUDY OF ANTALYA
title_sort spatiotemporal land use change analysis and future urban growth simulation using remote sensing: a case study of antalya
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2020-08-01
description The objectives of this study are: to create land-use maps by 5-year interval from 1995 to 2015, to analyse the land use change and urban development, and to estimate future land-use pattern and urban growth for the years: 2030, 2045 and 2060. Antalya, which is the 5th biggest city of Turkey, was selected as study area. In this study, there are basically three stages: (i) preprocessing and preparing additional bands, (ii) spatiotemporal land use detection using image classification and (iii) land use simulation using urban growth models. Firstly, atmospheric correction was applied to the Landsat 5 TM and Landsat 8 OLI images and land-cover indices, ASTER Global Digital Elevation Model (GDEM), and Nighttime data were prepared to use them as additional bands during the classification process. Secondly, Landsat images were classified using Random Forest (RF) machine-learning algorithm. Thirdly, urban simulations were performed for the years 2005, 2010, and 2015 and land-use pattern and urban growth was estimated for the years 2030, 2045 and 2060. The RF classification accuracies range from 84.44% to 92.82%. The urban areas increased from 49.56&thinsp;km<sup>2</sup> to 96.25&thinsp;km<sup>2</sup> from 1995 to 2015. The simulation accuracies were computed above 80%. According to the 2030, 2045 and 2060 simulation results, the urban areas were computed as 133.61&thinsp;km<sup>2</sup>, 148.27&thinsp;km<sup>2</sup> and 156.85&thinsp;km<sup>2</sup>, respectively. As a result, it was seen that the urban area of Antalya has almost doubled between the years 1995–2015 and the urban expansion is expected to continue increasing up to 1960.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/657/2020/isprs-archives-XLIII-B3-2020-657-2020.pdf
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