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Monitoring Land Use and Land Cover Change Using Remote Sensing and GIS: A Case Study in Mersin, Türkiye

Year 2023, Volume: 5 Issue: 1, 43 - 51, 30.06.2023
https://doi.org/10.56130/tucbis.1300704

Abstract

The application was carried out in Mersin, which is located in the south of Turkey and is under the pressure of urbanization, in this case study, which intends to monitor land use (LU) / land cover (LC) change. Land use was classified into five categories using the LU / LC data set for the years 2000, 2006, 2012, 2018, and 2022 (“barren land”, “built-up area”, “vegetation”, “agriculture”, and “water body”). After that, the maps were generated. These maps were used to generate pairwise comparison maps, and graphs were used to depict areal changes. According to the findings, the built-up area (69.26%) increased significantly from 2000 to 2022, vegetation (%22.90) showed an increase, while the agricultural area (-65.45%), barren land (-%42.11), water body (-%20.99) decreased. The application indicates changes in the field of study, as well as the direction and scale of the development. As a result, monitoring the LU / LC change in the region under urbanization pressure is critical for sustainable urban management.

References

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  • Alshari E A, & Gawali B W (2021). Development of classification system for LULC using remote sensing and GIS. Global transitions proceedings, 2(1), 8-17. https://doi.org/10.1016/j.gltp.2021.01.002
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  • Bekçi R N & Kuşak L (2022). Mekânsal Çözünürlüğün Güneşlenme Potansiyeline Etkisi. Türkiye İnsansız Hava Araçları Dergisi. 4(1), 46-51. https://doi.org/10.51534/tiha.1142117
  • Bekçi R N (2022). Güneş Potansiyeli Analizi Ve İnternet Tabanlı CBS Uygulaması. Yüksek Lisans Tezi, Mersin Üniversitesi, Fen Bilimleri Enstitüsü, 112s.
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  • Bozkurt S G, Kuşak L & Akkemik Ü (2023). Correction to: Investigation of land cover (LC)/land use (LU) change affecting forest and seminatural ecosystems in Istanbul (Turkey) metropolitan area between 1990 and 2018. Environmental Monitoring and Assessment, 195:196, 399. https://doi.org/10.1007/s10661-022-10785-3
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  • Chen M, Atiqul Haq S M, Ahmed K J, Hussain A B & Ahmed M N Q (2021). The link between climate change, food security and fertility: The case of Bangladesh. PLoS One, 16(10), e0258196. https://doi.org/10.1371/journal.pone.0258196
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  • Doğan Y & Yakar M (2018). GIS and three-dimensional modeling for cultural heritages. International Journal of Engineering and Geosciences, 3(2), 50-55. https://doi.org/10.26833/ijeg.378257
  • Erdem F (2022). Risk assessment with the fuzzy logic method for Ankara OIZ environmental waste water treatment plant. Turkish Journal of Engineering, 6(4), 268- 275. https://doi.org/10.31127/tuje.975623
  • Fidan D & Ulvi A (2022). Coğrafi Bilgi Sistemleri ve Çok Kriterli Karar Verme Yöntemleri ile Alternatif Havalimanı Konumlarının Belirlenmesi; Ankara Örneği. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 4(2), 87-96. https://doi.org/10.56130/tucbis.1203136
  • Gull A & Mahmood, S. (2022). Spatio-Temporal Analysis and Trend Prediction of Land Cover Changes using Markov Chain Model in Islamabad, Pakistan. Advanced GIS, 2(2), 52-61.
  • Hussain S & Karuppannan S (2023). Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan. Geology, Ecology, and Landscapes, 7(1), 46-58. https://doi.org/10.1080/24749508.2021.1923272
  • Iban M C & Sahin E (2022). Monitoring land use and land cover change near a nuclear power plant construction site: Akkuyu case, Turkey. Environmental Monitoring and Assessment, 194(10), 724. https://doi.org/10.1007/s10661-022-10437-6
  • Kaya H E & Demir V (2022). Estimation of land use and land cover changes in Konya Closed Basin. Intercontinental Geoinformation Days (IGD), Tabriz, Iran, 180-183.
  • Kucukali U F & Kuşak L (2018). Environmental, Social, and Economic Indicators of Urban Land Use Conflicts: Evidence from Istanbul Metropolitan Area. In E-Planning and Collaboration: Concepts, Methodologies, Tools, and Applications IGI Global, 1014-1037, https://doi.org/10.4018/978-1-5225-5646-6.ch048
  • Kumar V & Agrawal S (2023). A multi-layer perceptron–Markov chain based LULC change analysis and prediction using remote sensing data in Prayagraj district, India. Environmental Monitoring and Assessment, 195(5), 619. https://doi.org/10.1007/s10661-023-11205-w
  • Kusak L, Unel F B, Alptekin A, Celik M O & Yakar M (2021). Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory mapping. Open Geosciences, 13(1), 1226-1244. https://doi.org/10.1515/geo-2020-0299
  • Mishra M, Santos C A G, do Nascimento T V M, Dash M K, da Silva R M, Kar D & Acharyya T (2022). Mining impacts on forest cover change in a tropical forest using remote sensing and spatial information from 2001–2019: A case study of Odisha (India). Journal of Environmental Management, 302, 114067. https://doi.org/10.1016/j.jenvman.2021.114067
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  • Orhan O (2021). Monitoring of land subsidence due to excessive groundwater extraction using small baseline subset technique in Konya, Turkey. Environmental Monitoring and Assessment, 193, 174 (2021). https://doi.org/10.1007/s10661-021-08962-x
  • Seyam M M H, Haque M R & Rahman M M (2023). Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh. Case Studies in Chemical and Environmental Engineering, 100293. https://doi.org/10.1016/j.cscee.2022.100293
  • Shafiq M & Mahmood S (2022). Spatial assessment of forest cover change in Azad Kashmir, Pakistan. Advanced GIS, 2(2), 62–69.
  • Shah A, Ali K & Nizami S M (2022). Spatio-temporal analysis of urban sprawl in Islamabad, Pakistan during 1979–2019, using remote sensing. GeoJournal, 87(4), 2935-2948. https://doi.org/10.1007/s10708-021-10413-6
  • Singh K T, Singh N M, Devi T T (2022). A Remote Sensing, GIS Based Study on LULC Change Detection by Different Methods of Classifiers on Landsat Data. In Innovative Trends in Hydrological and Environmental Systems: Select Proceedings of ITHES 2021, Singapore, (107-117). https://doi.org/10.1007/978-981-19-0304-5_9
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  • Tong X, Wang P, Wu S & Luo M (2022). Urbanization effects on high-frequency temperature variability over South China. Urban Climate, 42, 101092. https://doi.org/10.1016/j.uclim.2022.101092
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Arazi kullanımı ve Arazi Örtüsü Değişikliklerinin Uzaktan Algılama ve CBS Yöntemi ile İzlenmesi: Mersin, Türkiye Örneği

Year 2023, Volume: 5 Issue: 1, 43 - 51, 30.06.2023
https://doi.org/10.56130/tucbis.1300704

Abstract

Arazi kullanımı (AK) / arazi örtüsü (AÖ) değişikliğinin izlenmesini amaçlayan bu vaka çalışmasında, Türkiye’nin güneyinde yer alan ve kentleşme baskısı altında olan Mersin’de uygulama gerçekleştirilmiştir. 2000, 2006, 2012, 2018 ve 2022 yıllarına ait AK /AÖ veri seti kullanılarak arazi kullanımı 5 farklı sınıfa (“kıraç arazi”, “yerleşim yeri”, “bitki örtüsü”, “tarım alanı” ve “su kütlesi”) ayrılmış ve haritalar oluşturulmuştur. Bu haritalardan ikili karşılaştırma haritaları türetilmiş ve alansal değişimler grafikler ile sunulmuştur. Elde edilen bulgulara göre, 2000 yılından 2022 yılına gelindiğinde yerleşim yerinin (%69.26) önemli ölçüde artığı, bitki örtüsünün (%22.90) artış gösterdiği, tarım alanının (-%65.45), kıraç arazinin (-%42.11) ve su kütlesinin (-%20.99) ise azaldığı tespit edilmiştir. Uygulama, çalışma alanındaki değişimleri, gelişme yön ve büyüklüğünü gözler önüne sermektedir. Sonuç olarak, kentleşme baskısı altında olan bölgede AK / AÖ değişikliğinin izlenmesi sürdürülebilir kent yönetimi için önemlidir.

References

  • Alam M Z, Carpenter-Boggs L, Rahman A, Haque M M, Miah M R U, Moniruzzaman M, Qayum M A & Abdullah H M (2017). Water quality and resident perceptions of declining ecosystem services at Shitalakka wetland in Narayanganj city. Sustainability of Water Quality and Ecology, 9, 53-66. https://doi.org/10.1016/j.swaqe.2017.03.002
  • Alshari E A, & Gawali B W (2021). Development of classification system for LULC using remote sensing and GIS. Global transitions proceedings, 2(1), 8-17. https://doi.org/10.1016/j.gltp.2021.01.002
  • Ayazlı İ E, Boyraz S, Başcı M A & Ulusu E (2020) Kentleşmenin karmaşıklık düzeyinin belirlenmesi ve coğrafi dağılımının araştırılması. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 2(2), 57-63.
  • Bekçi R N & Kuşak L (2022). Mekânsal Çözünürlüğün Güneşlenme Potansiyeline Etkisi. Türkiye İnsansız Hava Araçları Dergisi. 4(1), 46-51. https://doi.org/10.51534/tiha.1142117
  • Bekçi R N (2022). Güneş Potansiyeli Analizi Ve İnternet Tabanlı CBS Uygulaması. Yüksek Lisans Tezi, Mersin Üniversitesi, Fen Bilimleri Enstitüsü, 112s.
  • BM (2018). BM Ekonomik ve Sosyal İşler Dairesi, [Erişim Tarihi: 15.05.2023], https://www.un.org/sw/desa/68-world-population-projected-live-urban-areas-2050-says-un
  • Bozkurt S G, Kuşak L & Akkemik Ü (2023). Correction to: Investigation of land cover (LC)/land use (LU) change affecting forest and seminatural ecosystems in Istanbul (Turkey) metropolitan area between 1990 and 2018. Environmental Monitoring and Assessment, 195:196, 399. https://doi.org/10.1007/s10661-022-10785-3
  • Çelik M A & Gülersoy A E (2018). Climate classification and drought analysis of Mersin. Manisa Celal Bayar University Journal of Social Sciences, 16(1), 1-26. https://doi.org/10.18026/cbayarsos.411475
  • Chen M, Atiqul Haq S M, Ahmed K J, Hussain A B & Ahmed M N Q (2021). The link between climate change, food security and fertility: The case of Bangladesh. PLoS One, 16(10), e0258196. https://doi.org/10.1371/journal.pone.0258196
  • Cheng L, Mi Z, Sudmant A & Coffman D M (2022). Bigger cities better climate? Results from an analysis of urban areas in China. Energy Economics, 107, 105872. https://doi.org/10.1016/j.eneco.2022.105872
  • Cheng Z & Hu X (2023). The effects of urbanization and urban sprawl on CO2 emissions in China. Environment, Development and Sustainability, 25(2), 1792-1808. https://doi.org/10.1007/s10668-022-02123-x
  • Copernicus (2023a). Copernicus Land Monitoring Service, [Erişim Tarihi: 27.04.2023], https://land.copernicus.eu/
  • Copernicus (2023b). Copernicus Land Monitoring Service [Erişim Tarihi: 27.04.2023], https://land.copernicus.eu/pan-european/corine-land-cover
  • Coruhlu Y E, Solgun N, Baser V, & Terzi F (2022). Revealing the solar energy potential by integration of GIS and AHP in order to compare decisions of the land use on the environmental plans. Land Use Policy, 113, 105899. https://doi.org/10.1016/j.landusepol.2021.105899
  • Çoruhlu Y E & Çelik M Ö (2022). Protected area geographical management model from design to implementation for specially protected environment area. Land Use Policy, 122, 106357. https://doi.org/10.1016/j.landusepol.2022.106357
  • Darem A A, Alhashmi A A, Almadani A M, Alanazi A K & Sutantra G A (2023). Development of a map for land use and land cover classification of the Northern Border Region using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science, 26(2), 341-350. https://doi.org/10.1016/j.ejrs.2023.04.005
  • Das B, Singh S, Jain S K & Thakur P K (2021). Prioritization of sub-basins of Gomti river for soil and water conservation through morphometric and LULC analysis using remote sensing and GIS. Journal of the Indian Society of Remote Sensing, 49, 2503-2522. https://doi.org/10.1007/s12524-021-01410-w
  • Das Barnali & Dhorde A (2022). Assessment of shoreline change and its relation with Mangrove vegetation: A case study over North Konkan region of Raigad, Maharashtra, India. International Journal of Engineering and Geosciences, 7(2), 101-111. https://doi.org/10.26833/ijeg.912657
  • Doğan Y & Yakar M (2018). GIS and three-dimensional modeling for cultural heritages. International Journal of Engineering and Geosciences, 3(2), 50-55. https://doi.org/10.26833/ijeg.378257
  • Erdem F (2022). Risk assessment with the fuzzy logic method for Ankara OIZ environmental waste water treatment plant. Turkish Journal of Engineering, 6(4), 268- 275. https://doi.org/10.31127/tuje.975623
  • Fidan D & Ulvi A (2022). Coğrafi Bilgi Sistemleri ve Çok Kriterli Karar Verme Yöntemleri ile Alternatif Havalimanı Konumlarının Belirlenmesi; Ankara Örneği. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 4(2), 87-96. https://doi.org/10.56130/tucbis.1203136
  • Gull A & Mahmood, S. (2022). Spatio-Temporal Analysis and Trend Prediction of Land Cover Changes using Markov Chain Model in Islamabad, Pakistan. Advanced GIS, 2(2), 52-61.
  • Hussain S & Karuppannan S (2023). Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan. Geology, Ecology, and Landscapes, 7(1), 46-58. https://doi.org/10.1080/24749508.2021.1923272
  • Iban M C & Sahin E (2022). Monitoring land use and land cover change near a nuclear power plant construction site: Akkuyu case, Turkey. Environmental Monitoring and Assessment, 194(10), 724. https://doi.org/10.1007/s10661-022-10437-6
  • Kaya H E & Demir V (2022). Estimation of land use and land cover changes in Konya Closed Basin. Intercontinental Geoinformation Days (IGD), Tabriz, Iran, 180-183.
  • Kucukali U F & Kuşak L (2018). Environmental, Social, and Economic Indicators of Urban Land Use Conflicts: Evidence from Istanbul Metropolitan Area. In E-Planning and Collaboration: Concepts, Methodologies, Tools, and Applications IGI Global, 1014-1037, https://doi.org/10.4018/978-1-5225-5646-6.ch048
  • Kumar V & Agrawal S (2023). A multi-layer perceptron–Markov chain based LULC change analysis and prediction using remote sensing data in Prayagraj district, India. Environmental Monitoring and Assessment, 195(5), 619. https://doi.org/10.1007/s10661-023-11205-w
  • Kusak L, Unel F B, Alptekin A, Celik M O & Yakar M (2021). Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory mapping. Open Geosciences, 13(1), 1226-1244. https://doi.org/10.1515/geo-2020-0299
  • Mishra M, Santos C A G, do Nascimento T V M, Dash M K, da Silva R M, Kar D & Acharyya T (2022). Mining impacts on forest cover change in a tropical forest using remote sensing and spatial information from 2001–2019: A case study of Odisha (India). Journal of Environmental Management, 302, 114067. https://doi.org/10.1016/j.jenvman.2021.114067
  • MODIS (2023). Moderate Resolution Imaging Spectroradiometer (MODIS), [Erişim Tarihi: 27.04.2023], https://modis.gsfc.nasa.gov/data/dataprod/mod12.php
  • Natarajan K, Latva-Käyrä P, Zyadin A & Pelkonen P (2016). New methodological approach for biomass resource assessment in India using GIS application and land use/land cover (LULC) maps. Renewable and Sustainable Energy Reviews, 63, 256-268. https://doi.org/10.1016/j.rser.2016.05.070
  • Oğuz E Oğuz K & Öztürk K (2022). Düzce bölgesi taşkın duyarlılık alanlarının belirlenmesi. Geomatik, 7(3), 220-234. https://doi.org/10.29128/geomatik.972343
  • Orhan O (2021). Monitoring of land subsidence due to excessive groundwater extraction using small baseline subset technique in Konya, Turkey. Environmental Monitoring and Assessment, 193, 174 (2021). https://doi.org/10.1007/s10661-021-08962-x
  • Seyam M M H, Haque M R & Rahman M M (2023). Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh. Case Studies in Chemical and Environmental Engineering, 100293. https://doi.org/10.1016/j.cscee.2022.100293
  • Shafiq M & Mahmood S (2022). Spatial assessment of forest cover change in Azad Kashmir, Pakistan. Advanced GIS, 2(2), 62–69.
  • Shah A, Ali K & Nizami S M (2022). Spatio-temporal analysis of urban sprawl in Islamabad, Pakistan during 1979–2019, using remote sensing. GeoJournal, 87(4), 2935-2948. https://doi.org/10.1007/s10708-021-10413-6
  • Singh K T, Singh N M, Devi T T (2022). A Remote Sensing, GIS Based Study on LULC Change Detection by Different Methods of Classifiers on Landsat Data. In Innovative Trends in Hydrological and Environmental Systems: Select Proceedings of ITHES 2021, Singapore, (107-117). https://doi.org/10.1007/978-981-19-0304-5_9
  • The World Bank (2023). Urban Development overview, [Erişim Tarihi: 15.05.2023], https://www.worldbank.org/en/topic/urbandevelopment/overview#:~:text=Today%2C%20some%2056%25%20of%20the,people%20will%20live%20in%20cities.
  • Tona A U, Demir V, Kuşak L & Yakar M (2022). Su Kaynakları Mühendisliğinde CBS’nin Kullanımı. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 4(1), 23-33. https://doi.org/10.56130/tucbis.993807
  • Tong X, Wang P, Wu S & Luo M (2022). Urbanization effects on high-frequency temperature variability over South China. Urban Climate, 42, 101092. https://doi.org/10.1016/j.uclim.2022.101092
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There are 49 citations in total.

Details

Primary Language Turkish
Subjects Geospatial Information Systems and Geospatial Data Modelling, Geological Sciences and Engineering (Other)
Journal Section Research Articles
Authors

Mehmet Özgür Çelik 0000-0003-4569-888X

Murat Yakar 0000-0002-2664-6251

Early Pub Date June 23, 2023
Publication Date June 30, 2023
Published in Issue Year 2023 Volume: 5 Issue: 1

Cite

APA Çelik, M. Ö., & Yakar, M. (2023). Arazi kullanımı ve Arazi Örtüsü Değişikliklerinin Uzaktan Algılama ve CBS Yöntemi ile İzlenmesi: Mersin, Türkiye Örneği. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 5(1), 43-51. https://doi.org/10.56130/tucbis.1300704

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