Analysis of Land Use Land Cover and Land Surface Temperature in Karst Area: A Case Study Wonogiri Regency
Abstract
Urban development and global climate change drive increased Land Surface Temperature (LST). Wonogiri Regency is an area that is within the development range of Surakarta City. Analysis of land surface temperature has become Important in Wonogiri Regency as a mitigation measure for urban heat islands. This study aims to measure Land Surface Temperature (LST) in Wonogiri Regency and determine the controlling factor in the form of Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), seasons, and zones by landform. Using the Google Earth Engine platform, LST calculations, LULC classifications, and NDVI calculations can compute imagery. The dataset used is USGS Landsat 8. The analytical technique used in this study is comparative descriptive, which compares other controlling factors. The analysis results show the vital role of LULC, NDVI, seasonality, and landform on LST. LULC types of built-up land, low NDVI values, dry season, and southern zone (karst) tend to have higher LST than other factors.
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1. Chen, M., Zhou, Y., Hu, M., & Zhou, Y. (2020). Influence of urban scale and urban expansion on the urban heat island effect in metropolitan areas: Case study of beijing–tianjin–hebei urban agglomeration. Remote Sensing, 12(21), 1–19. https://doi.org/10.3390/rs12213491
2. Amir Siddique, M., Boqing, F., & Dongyun, L. (2023). Modeling the Impact and Risk Assessment of Urbanisation on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020). Sustainability (Switzerland), 15(7). https://doi.org/10.3390/su15076043
3. Hidayati, I. N., Suharyadi, R., & Danoedoro, P. (2018). Developing an Extraction Method of Urban Built-Up Area Based on Remote Sensing Imagery Transformation Index. Forum Geografi, 32(1), 96–108. https://doi.org/10.23917/forgeo.v32i1.5907
4. Putra, A. K., Sukmono, A., & Sasmito, B. (2018). Analisis Hubungan Perubahan Tutupan Lahan Terhadap Suhu Permukaan Terkait Fenomena Urban Heat Island Menggunakan Citra Landsat (Studi Kasus: Kota Surakarta). Jurnal Geodesi Undip, 7(3), 22–31.
5. Noviani, R., Ahmad, Sarwono, Sugiyanto, & Prihadi, S. (2022). Urbanisation rate in SUBOSUKAWONOSRATEN. IOP Conference Series: Earth and Environmental Science, 986(1). https://doi.org/10.1088/1755-1315/986/1/012073
6. Selang, M. A., Iskandar, D. A., & Widodo, R. (2018). Tingkat Perkembangan Urbanisasi Spasial Di Pinggiran Kpy (Kawasan Perkotaan Yogyakarta) Tahun 2012-2016. Kota Layak Huni "Urbanisasi Dan Pengembangan Perkotaan, 32–40.
7. Liu, R., Dong, X., Wang, X. chao, Zhang, P., Liu, M., & Zhang, Y. (2021). Study on the relationship among the urbanization process, ecosystem services and human well-being in an arid region in the context of carbon flow: Taking the Manas river basin as an example. Ecological Indicators, 132, 108248. https://doi.org/10.1016/j.ecolind.2021.108248
8. Çolakkadioğlu, D. (2023). The Effects of Urbanization and Vegetation Cover on Urban Heat Island: A Case Study in Osmaniye Province. International Journal of Environment and Geoinformatics, 10(1), 120–131. https://doi.org/10.30897/ijegeo.1144167
9. Prastyo, F. U., Nurjani, E., & Giyarsih, S. R. (2022). Distribusi Spasial Surface Urban Heat Island (SUHI) Kawasan Permukiman Perkotaan di Kota Yogyakarta. Media Komunikasi Geografi, 23(1), 73–83. https://doi.org/10.23887/mkg.v23i1.34300
10. Sugestiadi, M. I., & Basuki, Y. (2020). Pengaruh Interaksi Spasial Antara Kota Surakarta Dengan Kawasan Perkotaan Sekitarnya Terhadap Pertumbuhan Perkotaan. Jurnal Pembangunan Wilayah Dan Kota, 16(3), 173–186. https://doi.org/10.14710/pwk.v16i3.21948
11. Purnomo, D. (2009). Fenomena Migrasi Tenaga Kerja Dan Perannya Bagi Pembangunan Daerah Asal: Studi Empiris Di Kabupaten Wonogiri. Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi Dan Pembangunan, 10(1), 84. https://doi.org/10.23917/jep.v10i1.810
12. Zhang, B., Zhang, J., & Miao, C. (2022). Urbanisation Level in Chinese Counties: Imbalance Pattern and Driving Force. Remote Sensing, 14(9). https://doi.org/10.3390/rs14092268
13. Zhang, J., Zhang, X., Tan, X., & Yuan, X. (2022). Extraction of Urban Built-Up Area Based on Deep Learning and Multi-Sources Data Fusion—The Application of an Emerging Technology in Urban Planning. Land, 11(8). https://doi.org/10.3390/land11081212
14. Xiong, L., Li, S., Zou, B., Peng, F., Fang, X., & Xue, Y. (2022). Long Time-Series Urban Heat Island Monitoring and Driving Factors Analysis Using Remote Sensing and Geodetector. Frontiers in Environmental Science, 9(February), 1–14. https://doi.org/10.3389/fenvs.2021.828230
15. Afif Farhan, M. (2022). ANALISIS HUBUNGAN PERKEMBANGAN LAHAN TERBANGUN DENGAN DENGAN URBAN HEAT ISLAND DI KOTA PADANG PADA TAHUN 2010, 2015 DAN 2020.
16. Kadri, N., Jebari, S., Augusseau, X., Mahdhi, N., Lestrelin, G., & Berndtsson, R. (2023). Analysis of Four Decades of Land Use and Land Cover Change in Semiarid Tunisia Using Google Earth Engine. Remote Sensing, 15(13), 3257. https://doi.org/10.3390/rs15133257
17. Rushayati, S. B., Shamila, A. D., & Prasetyo, L. B. (2018). The Role of Vegetation in Controlling Air Temperature Resulting from Urban Heat Island. Forum Geografi, 32(1), 1–11. https://doi.org/10.23917/forgeo.v32i1.5289
18. Hidayati, I. N., & Suharyadi, R. (2019). A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI. Forum Geografi, 33(2), 162–172. https://doi.org/10.23917/forgeo.v33i2.9179
19. Ullah, N., Siddique, M. A., Ding, M., Grigoryan, S., Khan, I. A., Kang, Z., Tsou, S., Zhang, T., Hu, Y., & Zhang, Y. (2023). The Impact of Urbanization on Urban Heat Island: Predictive Approach Using Google Earth Engine and CA-Markov Modelling (2005–2050) of Tianjin City, China. International Journal of Environmental Research and Public Health, 20(3). https://doi.org/10.3390/ijerph20032642
20. Latue, P. C., Rakuasa, H., Somae, G., & Muin, A. (2023). Analisis Perubahan Suhu Permukaan Daratan di Kabupaten Seram Bagian Barat Menggunakan Platform Berbasis Cloud Google Earth Engine. Sudo Jurnal Teknik Informatika, 2(2), 45–51. https://doi.org/10.56211/sudo.v2i2.261
21. Guha, S., & Govil, H. (2020). Land surface temperature and normalized difference vegetation index relationship: a seasonal study on a tropical city. SN Applied Sciences, 2(10), 1–14. https://doi.org/10.1007/s42452-020-03458-8
22. Fariz, T. R., Suhardono, S., Sultan, H., Rahmawati, D., & Arifah, E. Z. (2022). Land Cover Mapping in Lake Rawa Pening Using Landsat 9 Imagery and Google Earth Engine. Journal of Environmental and Science Education, 2(1), 1–6. https://doi.org/10.15294/jese.v2i1.55851
23. Floreano, I. X., & de Moraes, L. A. F. (2021). Land use/land cover (LULC) analysis (2009–2019) with Google Earth Engine and 2030 prediction using Markov-CA in the Rondônia State, Brazil. Environmental Monitoring and Assessment, 193(4), 1–17. https://doi.org/10.1007/s10661-021-09016-y
24. Pande, C. B., Moharir, K. N., Varade, A. M., Abdo, H. G., Mulla, S., & Yaseen, Z. M. (2023). Intertwined impacts of urbanization and land cover change on urban climate and agriculture in Aurangabad city (MS), India using google earth engine platform. Journal of Cleaner Production, 422(August), 138541. https://doi.org/10.1016/j.jclepro.2023.138541
25. Gandharum, L., Hartono, D. M., Karsidi, A., & Ahmad, M. (2022). Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis. Scientific World Journal, 2022(Sdg 2). https://doi.org/10.1155/2022/3123788
26. Rwanga, S. S., & Ndambuki, J. M. (2017). Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS. International Journal of Geosciences, 08(04), 611–622. https://doi.org/10.4236/ijg.2017.84033
27. Wulansari, H. (2017). Uji Akurasi Klasifikasi Penggunaan Lahan dengan Menggunakan Metode Defuzzifikasi Maximum Likelihood Berbasis Citra Alos Avnir-2. BHUMI: Jurnal Agraria Dan Pertanahan, 3(1), 98. https://doi.org/10.31292/jb.v3i1.96
28. Saputra, K. E. A. (2016). Studi komparatif prestasi belajar mahasiswa jurusan pendidikan ekonomi ditinjau dari jalur penerimaan mahasiswa baru tahun 2011. Jurnal Jurusan Pendidikan Ekonomi, 6(1), 1–10.
29. Cahyono, B. E., Rahagian, R., Agung, D., & Nugroho, T. (2023). Analisis Produktivitas Padi Berdasarkan Indeks Kekeringan (Ndwi Dan Nddi) Lahan Sawah Menggunakan Data Citra Sentinel-2a Di Kecamatan Ambulu. Indonesian Journal of Applied Physics (IJAP), 13(1), 88.
30. Arsiso, B. K., Tsidu, G. M., & Abegaz, N. T. (2023). Impact of land use and land cover change on land surface temperature over Lake Tana Basin. Journal of African Earth Sciences, 207(August), 105047. https://doi.org/10.1016/j.jafrearsci.2023.105047
31. Ning, J., Gao, Z., Meng, R., Xu, F., Gao, M., Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., Chen, F., & Qian, Q. (2018). Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, 8(2014), 1–13. http://dx.doi.org/10.1038/s41598-017-19088-x
32. Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., Chen, F., & Qian, Q. (2018). Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, 8(1), 1–12. https://doi.org/10.1038/s41598-017-19088-x
33. Hussain, S., Raza, A., Abdo, H. G., Mubeen, M., Tariq, A., Nasim, W., Majeed, M., Almohamad, H., & Al Dughairi, A. A. (2023). Relation of land surface temperature with different vegetation indices using multi-temporal remote sensing data in Sahiwal region, Pakistan. Geoscience Letters, 10(1), 33. https://doi.org/10.1186/s40562-023-00287-6
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