Urban Green Space Analysis and its Effect on the Surface Urban Heat Island Phenomenon in Denpasar City, Bali

Authors

DOI:

https://doi.org/10.24259/fs.v7i1.24526

Keywords:

Urban green spaces, Urban heat island, Remote sensing , Spatial analysis, Spatial autocorrelation

Abstract

The Urbanization process in Indonesia’s big cities causes adverse environmental impacts such as climate change and land cover change. Urban climate change causes the warming of urban areas compared to rural areas; it is called Urban Heat Island phenomenon. Loss of vegetation due to urban development is one of several causes that contribute to urban heat islands. This study examines the availability of green spaces and their effects on the surface urban heat island in Denpasar city. This study used the spatial approach for Urban Green space mapping with digitizing methods. Landsat 8's thermal band is used for land surface temperature mapping and to conduct a spatial pattern analysis of the SUHI phenomena. The Global Moran’s Index and Local Indicator of Spatial Association (LISA) were used to determine the correlation between urban green space and SUHI. The study result shows that Denpasar City's urban green space area covers 28.22 km2. That's equal to 22.1% of the Denpasar City Administrative area. Denpasar Selatan district has the largest urban green space cover, with 14.19 km2 covered, or 50.27% of all the green space in Denpasar City. The majority of Denpasar is affected by UHI occurrences, except the northern region of North Denpasar and the southern region of South Denpasar. The maximum UHI level reaches 4-5°C, located on the east side of South Denpasar, especially in the Sanur coastal area. According to the spatial pattern study, the association between urban green space and SUHI only exists on the north side of Denpasar. The correlation between low-SUHI intensity clusters and high cover of green space is shown in the same area. However, the association between High-UHI intensity and low green space cover has not significantly happened. It indicated that other factors besides green space could affect the land surface temperature.

References

Akbari, H., Pomerantz, M., & Taha, H. (2001). Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar energy, 70(3), 295-310. https://doi.org/10.1016/S0038-092X(00)00089-X

Anselin, L. (1994). Exploratory spatial data analysis and geographic information systems. New Tools for Spatial Analysis, 17, 45–54.

Asmiwyati, I. G. A. A. R., Sugianthara, A. A. G., & Wardi, I. N. W. (2020). Identifikasi suhu permukaan terhadap penutupan lahan dari Landsat 8: Studi Kasus Kota Denpasar. Jurnal Arsitektur Lansekap, 6(2), 240–246. https://doi.org/10.24843/JAL.2020. v06.i02.p11

As-syakur, A. R., Nuarsa, I. W., Arthana, I. W., Mahendra, M. S., Adnyana, I. W. S., Merit, I. N., ... & Lila, K. A. (2012). Remote Sensing Image-Based Analysis of The Urban Heat Island in Denpasar, Indonesia. 8th International Symposium on Lowland Technology, 997–1004.

Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241–252. https://doi.org/10.1016/S0034-4257(97)00104-1

Estoque, R. C., Murayama, Y., & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349-359. https://doi.org/10.1016/j.scitotenv.2016.10.195

Fawzi, N. I. (2014). Pemetaan emisivitas permukaan menggunakan indeks vegetasi. Majalah Ilmiah Globe, 16(2), 133-139.

Gittleman, J. L., & Kot, M. (1990). Adaptation: statistics and a null model for estimating phylogenetic effects. Systematic Zoology, 39(3), 227-241. ehttps://doi.org/ 10.2307/2992183

Griffith, D. (2005). Spatial Autocorrelation. Syracuse University.

Grimm, N. B., Foster, D., Groffman, P., Grove, J. M., Hopkinson, C. S., Nadelhoffer, K. J., ... & Peters, D. P. (2008). The changing landscape: ecosystem responses to urbanization and pollution across climatic and societal gradients. Frontiers in Ecology and the Environment, 6(5), 264-272. https://doi.org/10.1890/070147

Johnson, J. M. F., Franzluebbers, A. J., Weyers, S. L., & Reicosky, D. C. (2007). Agricultural opportunities to mitigate greenhouse gas emissions. Environmental Pollution, 150(1), 107-124. https://doi.org/10.1016/j.envpol.2007.06.030

Karl, T. R., Diaz, H. F., & Kukla, G. (1988). Urbanization: Its detection and effect in the United States climate record. Journal of Climate, 1(11), 1099-1123.

Lee, J., & Wong, D. W. S. (2001). Statistical analysis with ArcView GIS. John Wiley & Sons.

Li, J., Song, C., Cao, L., Zhu, F., Meng, X., & Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China. Remote Sensing of Environment, 115(12), 3249-3263. https://doi.org/10.1016/j.rse.2011.07.008

Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.

Lo, C. P., & Quattrochi, D. A. (2003). Land-use and land-cover change, urban heat island phenomenon, and health implications: A remote sensing approach. Photogrammetric Engineering and Remote Sensing, 69(9), 1053- 1063. https://doi.org/10.14358/PERS.69.9.1053

Ma, Y., Kuang, Y., & Huang, N. (2010). Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery. International Journal of Applied Earth Observation and Geoinformation, 12(2), 110-118. https://doi.org/10.1016/j.jag.2009.12.002

Memon, R. A., Leung, D. Y., & Chunho, L. (2008). A review on the generation, determination and mitigation of Urban Heat Island. Journal of Environmental Sciences, 20(1), 120-128. https://doi.org/10.1016/S1001-0742(08)60019-4

Quattrochl, D. A., Luvall, J. C., Rickman, D. L., Estes Jr, M. G., Laymon, C. A., & Howell, B. F. (2000). A decision support information system for urban landscape management using thermal infrared data. Photogrammetric Engineering & Remote Sensing, 66(10), 1195-1207.

Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. IEEE Transactions on Geoscience Electronics, 11(1), 3-76. https://doi.org/10.1109/TGE.1973.294284

Sass, R. L., & Cicerone, R. J. (2002). Photosynthate allocations in rice plants: Food production or atmospheric methane? Proceedings of the National Academy of Sciences, 99(19), 11993–11995. https://doi.org/10.1073/pnas.20248359

Setiawan, H., Mathieu, R., & Thompson-Fawcett, M. (2006). Assessing the applicability of the V-I-S model to map urban land use in the developing world: A case study of Yogyakarta, Indonesia. Computers, Environment and Urban Systems, 30(4), 503–522. https://doi.org/10.1016/j.compenvurbsys.2005.04.003

Stathopoulou, M., & Cartalis, C. (2007). Daytime urban heat islands from Landsat ETM+ and Corine land cover data: An application to major cities in Greece. Solar Energy, 81(3), 358–368. https://doi.org/10.1016/j.solener.2006.06.014

United States Environmental Protection Agency. (2008). Urban Heat Island basics. In Reducing Urban Heat Islands: Compendium of Strategies; Chapter 1; Draft Report.

USGS. (2013). Using the USGS Landsat Level-1 Data Product.

Utomo, A. W., Suprayogi, A., & Sasmito, B. (2017). Analisis hubungan variasi land surface temperature dengan kelas tutupan lahan menggunakan data citra satelit landsat (Studi Kasus: Kabupaten Pati). Jurnal Geodesi Undip, 6(2), 71–80.

Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote Sensing of Environment, 86(3), 370–384. https://doi.org/10.1016/S0034-4257(03)00079-8

Weng, Q., Lu, D., & Schubring, J. (2004). Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467–483. https://doi.org/10.1016/j.rse.2003.11.005

Yamamoto, Y. (2006). Measures to Mitigate Urban Heat Islands. NISTEP Science & Technology Foresight Center, 18, 67–83.

Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3), 583–594. https://doi.org/10.1080/01431160304987

Additional Files

Published

2023-04-04

How to Cite

Urban Green Space Analysis and its Effect on the Surface Urban Heat Island Phenomenon in Denpasar City, Bali. (2023). Forest and Society, 7(1), 150-168. https://doi.org/10.24259/fs.v7i1.24526

Similar Articles

1-10 of 132

You may also start an advanced similarity search for this article.