PEMANFAATAN CITRA PENGINDERAN JAUH MULTI-TEMPORAL UNTUK DETEKSI URBAN HEAT ISLAND (UHI) TERHADAP PERUBAHAN PENGGUNAAN LAHAN DI KABUPATEN BULELENG

A Sediyo Adi Nugraha, Dewa Made Atmaja

Abstract


Fenomena Urban Heat Island (UHI) sering dipengaruhi oleh kepadatan penduduk dan perubahan penggunaan lahan. Perubahan tesebut memiliki hubungan dengan peningkatan suhu permukaan (Land Surface Temperature/LST) sebagai awal terjadinya UHI. Deteksi perubahan penggunaan lahan dan suhu permukaan dilakukan dari tahun 2000, 2010, dan 2018 pada daerah Kabupaten Buleleng dan berfokus pada Kecamatan Buleleng karena memiliki perubahan lahan terbangun lebih cepat dibandingkan kecamatan lain. Tujuannya untuk mengetahuii bagaimana fenomena UHI itu terjadi akibat dari perubahan penggunaan lahan. Selain itu, seberapa besar peningkatan suhu permukaan selama 18 tahun khususnya di Kecamatan Buleleng dengan mengetahui kondisi ditribusi dan intensitas UHI. Metode yang digunakan dalam deteksi UHI menggunakan citra penginderaan jauh multi-temporal yaitu citra Landsat 7 ETM+ dan citra Landsat 8 OLI/TIRS (The Operational Land Imager and the Thermal Infrared Scanner) sebagai data primer. Pengolahan data akan berfokus pada ekstraksi suhu permukaan dengan metode Split-Windows Algorithm Sobrino (SWA-S) untuk Landsat 8 dan metode Brightness Temperature Emissivity Correction untuk Landsat 7, kemudian Maximum Likelihood sebagai metode penggunaan lahan. Hasil pengolahan menunjukkan bahwa penggunaan metode yang berbeda memberikan dampak terhadap fenomena UHI. Perbedaan suhu selama 18 tahun sebesar sebesar ±5°C hal itu dipengaruhi dari kondisi awan dan bayangan. Perubahan penggunaan lahan dari tahun 2000 hingga 2018 terdapat peningkatan lahan terbangun di Kecamatan Buleleng dan peningkatan suhu permukan sebesar 2°-7°C dari lahan terbangun. Fenomena UHI untuk distribusi dan instensitas UHI terjadi di daerah pusat perkotaan dan kenaikan intensitas UHI sebesar 1.75°C. kesimpulannya bahwa perubahan lahan terbangun memberikan dampak kenaikan suhu permukaan dan menyebabkan fenomena UHI.

Keywords


UHI; Citra Landsat; Suhu Permukaan; Distribusi UHI; Intensitas UHI

Full Text:

PDF

References


Adiningsih, E. S. (2014). Tinjauan Metode Deteksi Parameter Kekeringan Berbasis Data Penginderaan Jauh. Seminar Nasional Penginderaan Jauh, 211–220.

Ahmad, A., & Quegan, S. (2013). Comparative analysis of supervised and unsupervised classification on multispectral data. Applied Mathematical Sciences, 7(74), 3681–3694. https://doi.org/10.12988/ams.2013.34214

Al-Ahmadi, F. S., & Hames, A. S. (2009). Comparison of Four Classification Methods to Extract Land Use and Land Cover from Raw Satellite Images for Some Remote Arid Areas, Kingdom of Saudi Arabia. Journal Kingdom of Saudi Arabia, 20(1), 167–191. https://doi.org/10.4197/Ear.20-1.9

Alves, E. D. L., & Lopes, A. (2017). The Urban Heat Island Effect and the Role of Vegetation to Address the Negative Impacts of Local Climate Changes in a Small Brazilian City. Atmosphere, MDPI, 8(2), 1–14. https://doi.org/10.3390/atmos8020018

Artis, D. A., & Carnahan, W. H. (1982). Survey of Emissivity Variability in Thennography of Urban Areas. 329, 313–329.

Badan Pusat Statistik. (2016). Kabupaten Buleleng dalam Angka 2016.

Baik, J. J., Kim, Y. H., Kim, J. J., & Han, J. Y. (2007). Effects of boundary-layer stability on urban heat island-induced circulation. Theoretical and Applied Climatology, 89(1–2), 73–81. https://doi.org/10.1007/s00704-006-0254-4

Bakker, M. M., Alam, S. J., van Dijk, J., & Rounsevell, M. D. A. (2014). Land-use change arising from rural land exchange: an agent-based simulation model. Landscape Ecology, 30(2), 273–286. https://doi.org/10.1007/s10980-014-0116-x

Bonafoni, S., Baldinelli, G., & Verducci, P. (2017). Sustainable strategies for smart cities: Analysis of the town development effect on surface urban heat island through remote sensing methodologies. Sustainable Cities and Society, 29, 211–218. https://doi.org/10.1016/j.scs.2016.11.005

Chander, G., Markham, B. L., Helder, D. L., & Ali, E.-. (2009). Remote Sensing of Environment Summary of current radiometric calibration coef fi cients for Landsat MSS , TM , ETM + , and EO-1 ALI sensors. Remote Sensing of Environment, 113(5), 893–903. https://doi.org/10.1016/j.rse.2009.01.007

Coll, C., Galve, J. M., Sánchez, J. M., & Caselles, V. (2010). Validation of landsat-7/ETM+ thermal-band calibration and atmospheric correction with groundbased measurements. IEEE Transactions on Geoscience and Remote Sensing, 48(1), 547–555. https://doi.org/10.1109/TGRS.2009.2024934

Colunga, M. L., Cambrón-Sandoval, V. H., Suzán-Azpiri, H., Guevara Escobar, A., & Luna-Soria, H. (2015). The role of urban vegetation in temperature and heat island effects in Querétaro city, Mexico. Atmosfera, 28(3), 205–218. https://doi.org/10.20937/ATM.2015.28.03.05

Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35–46. https://doi.org/10.1016/0034-4257(91)90048-B

Coutts, A., Harris, R., Phan, T., J. Livesley, S., Williams, N., & Tapper, N. (2016). Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning. In Remote Sensing of Environment, 186. https://doi.org/10.1016/j.rse.2016.09.007

Delarizka, A., Sasmito, B., & Hani’ah. (2016). Analisis Fenomena Pulau Bahang (Urban Heat Island) di Kota Semarang berdasarkan Hubungan antara Perubahan Tutupan Lahan dengan Suhu Permukaan menggunakan Citra Multi Temporal Landsat. Geodesi Undip, 5(4), 165–177.

dos Santos, A. R., de Oliveira, F. S., da Silva, A. G., Gleriani, J. M., Gonçalves, W., Moreira, G. L., Silva, F. G., Branco, E. R. F., Moura, M. M., da Silva, R. G., Juvanhol, R. S., de Souza, K. B., Ribeiro, C. A.

A. S., de Queiroz, V. T., Costa, A. V., Lorenzon, A. S., Domingues, G. F., Marcatti, G. E., de Castro, N. L. M., … Mota, P. H. S. (2017). Spatial and temporal distribution of urban heat islands. Science of the Total Environment, 605–606(December), 946–956.

https://doi.org/10.1016/j.scitotenv.2017.05.275

Fawzi, N. I. (2017). Mengukur Urban Heat Island Menggunakan Penginderaan Jauh , Kasus Di Kota Yogyakarta ( Measuring Urban Heat Island using Remote Sensing , Case of Yogyakarta City ). Majalah Ilmiah Globe, 19(2), 195–206.

Fawzi, N. I., & Jatmiko, R. H. (2015). Heat Island Detection in Coal Mining Areas using Multitemporal Remote Sensing. Proceedings the 36th Asian

Conference of Remote Sensing (ACRS 2015), Metro Manila, Philippines, October 2015.

Fawzi, N. I., & Naharil M, N. (2013). Kajian Urban Heat Island di Kota Yogyakarta - Hubungan antara Tutupan Lahan dan Suhu Permukaan. Simposium Nasional Sains Geoinformasi-III, 275–280.

Huang, F., Zhan, W., Voogt, J., Hu, L., Wang, Z.-H., Quan, J., Ju, W., & Guo, Z. (2016). Temporal upscaling of surface urban heat island by

incorporating an annual temperature cycle model: A tale of two cities. In Remote Sensing of Environment, 186.

https://doi.org/10.1016/j.rse.2016.08.009

Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195–213.

https://doi.org/10.3390/rs4103201

Iyengar, S. (2003). Environmental Damage to Land Resource: Need to Improve Land Use Data Base. In Economic and Political Weekly (Vol. 38).

https://doi.org/10.2307/4413941

Jensen JR. (2005). Introductory Digital Image Processing (Third Ed). South California: Pearson Prentice Hall.

Kuenzer, C., Zhang, J., & Dech, S. (2015). Thermal Infrared Remote Sensing: Principles and Theoretical Background.

Levermore, G., Parkinson, J., Lee, K., Laycock, P., & Lindley, S. (2017). The increasing trend of the urban heat island intensity. In Urban Climate, 24. https://doi.org/10.1016/j.uclim.2017.02.004

Li, F., Jackson, T. J., Kustas, P., Schmugge, T. J., French, A. N., Cosh, H., & Bindlish, R. (2004). Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX. Remote Sensing of Environment, 92, 521–534. https://doi.org/10.1016/j.rse.2004.02.018

Li, Z. L., & Becker, F. (1993). Feasibility of land surface temperature and emissivity determination from AVHRR data. Remote Sensing of Environment, 43(1), 67–85. https://doi.org/10.1016/0034-

(93)90065-6

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. In International Journal of Applied Earth Observation and Geoinformation, 12.

https://doi.org/10.1016/j.jag.2009.12.002

Magee, N., Curtis, J., & Wendler, G. (1999). The urban heat island effect at Fairbanks, Alaska. Theoretical and Applied Climatology, 64(1–2), 39–47. https://doi.org/10.1007/s007040050109

Mindali, O. R., Michael, Y., Helman, D., & Lensky, I. (2015). The role of local land-use on the urban heat island effect of Tel Aviv as assessed from satellite remote sensing. In Applied Geography, 56.

https://doi.org/10.1016/j.apgeog.2014.11.023

Nugraha, A. S.A., Gunawan, T., & Kamal, M. (2019). Comparison of Land Surface Temperature Derived from Landsat 7 ETM+ and Landsat 8 OLI/TIRS for Drought Monitoring. IOP Conference Series: Earth and Environmental Science, 313(1), 0–10. https://doi.org/10.1088/1755-1315/313/1/012041

Nugraha, A Sediyo Adi. (2019). Pemanfaatan Metode Split-Windows Algorithm ( SWA ) pada Landsat 8 Menggunakan Data Uap Air MODIS Terra (The Application of Split-Windows Algorithm (SWA) Methods on Landsat 8 Using Modis Terra Water Vapor). Geomatika, 25(1), 9–16.

https://doi.org/http://doi.org/10.24895/JIG.2019.25-

877

Nugraha, A Sediyo Adi, Gunawan, T., & Kamal, M. (2019). Downscaling land surface temperature on multi-scale image for drought monitoring. Sixth Geoinformation Science Symposium, November, 6. https://doi.org/10.1117/12.2544550

Nugroho, S. A. (2011). Analisis Kelembaban Tanah Permukaan Melalui Citra Landsat 7 ETM+ Di Wilayah Dataran Kabupaten Purworejo. Universitas Muhammadiyah Surakarta.

Oke, T. R. (2002). Boundary Layer Climates (2nd Ed). Taylor & Francis.

https://doi.org/https://doi.org/10.4324/9780203407219

Pinho, O. S., & Orgaz, M. D. M. (2000). The urban heat island in a small city in coastal Portugal. In International journal of biometeorology, 44.

https://doi.org/10.1007/s004840000063

Qian, L.-X., Cui, H.-S., & Chang, J. (2006). Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta. Pedosphere, 16(6), 681–689.

https://doi.org/https://doi.org/10.1016/S1002-0160(06)60103-3

Qin, Z., Dall, G., Karni, A., & Berliner, P. (2001). Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-advanced very high resolution radiometer data. Journal of Geophysical Research, 106(19), 22655–22670. https://doi.org/10.1029/2000JD900452

Rajasekar, U., & Weng, Q. (2009). Spatio-temporal modelling and analysis of urban heat islands by using Landsat TM and ETM+ imagery. In International Journal of Remote Sensing, 30. https://doi.org/10.1080/01431160802562289

Robert A, S. (2007). Remote Sensing, Third Edition: Models and Methods for Image Processing (Third). Elsevier Science & Technology (2009).

Roth, M., Oke, T. R., & Emery, W. J. (1989). Satellitederived Urban Heat Island from Three Coastal Cities and The Utilization of such Data in Urban

Climatology. International Journal of Innovative Science, Engineering & Technology, 10(11), 1699–1720.

Rozenstein, O., Qin, Z., Derimian, Y., & Karnieli, A. (2014). Derivation of land surface temperature for landsat-8 TIRS using a split window algorithm. Sensors (Switzerland), 14(4), 5768–5780. https://doi.org/10.3390/s140405768

Sabins, F. F. (2007). Remote Sensing: Principles and Application, Third Edition. Waveland Press, Inc.

Septiani, R., Citra, I. P. A., & Nugraha, A. S. A. (2019). Perbandingan Metode Supervised Classification dan Unsupervised Classification terhadap Penutup Lahan di Kabupaten Buleleng. Jurnal Geografi :

Media Informasi Pengembangan Dan Profesi Kegeografian, 16(2), 90–96.

https://doi.org/10.15294/jg.v16i2.19777

Skokovic, D., Sobrino, J. a., Jiménez Muñoz, J. C., Soria,G., Julien, Y., Mattar, C., & Cristóbal, J. (2014). Calibration and Validation of land surface temperature for Landsat8- TIRS sensor TIRS LANDSAT-8 CHARACTERISTICS. Land Product Validation and Evolution ESA/ESRIN, 27. https://doi.org/10.1063/1.452862

Sobrino, J. A., El Kharraz, J., & Li, Z. L. (2003). Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote

Sensing, 24(24), 5161–5182. https://doi.org/10.1080/0143116031000102502

Sobrino, J. A., Li, Z. L., Stoll, M. P., & Becker, F. (1996). Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with atsr data. International Journal of Remote Sensing, 17(11), 2089–2114. https://doi.org/10.1080/01431169608948760

Sobrino, J., Raissouni, N., & Li, Z.-L. (2001). A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data. In Remote Sensing of

Environment, 75. https://doi.org/10.1016/S0034-4257(00)00171-1

Srivanit, M., Hokao, K., & Phonekeo, V. (2012). Assessing the Impact of Urbanization on Urban Thermal Environment : A Case Study of Bangkok

Metropolitan. International Journal of Applied Science and Technology, 2(7), 243–256.

Streutker, D. R. (2003). Satellite-measured growth of the urban heat island of Houston, Texas David. Remote Sensing of Environment, 85(3), 282–289.

Susca, T., Gaffin, S., & Dell’Osso, G. (2011). Positive effects of vegetation: Urban Heat Island and green roofs. In Environmental pollution (Barking, Essex : 1987), 159.

https://doi.org/10.1016/j.envpol.2011.03.007

Tsou, J., Zhuang, J., Li, Y., & Zhang, Y. (2017). Urban Heat Island Assessment Using the Landsat 8 Data : A Case Study in Shenzhen and Hong Kong. Urban Science, 1(10), 1–22.

https://doi.org/10.3390/urbansci1010010

Tursilowati, L., Tetuko, J., Sumantyo, S., Kuze, H., & Adiningsih, E. S. (2015). Relationship between Urban Heat Island Phenomenon and Land

Use/Land Cover Changes in Jakarta – Indonesia. Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS), 3(4), 645–653.

U.S. Environmental Protection Agency. (2008). Reducing Urban Heat Island: Compendium of Strategies Cool pavements (pp. 1–32).

https://doi.org/10.2174/9781608054718113010008

U.S. Geology Survey Department. (2010). Landsat 7 Science Data Users Handbook. https://doi.org/10.1001/archinternmed.2011.606

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

Wan, Z., Zhang, Y., Zhang, Q., & Li, Z. L. (2004). Quality assessment and validation of the MODIS global land surface temperature. International Journal of Remote Sensing, 25(1), 261–274.

https://doi.org/10.1080/0143116031000116417

Wang, Y., & Akbari, H. (2016). The effects of street tree planting on Urban Heat Island mitigation in Montreal. Sustainable Cities and Society, 27(2016), 122–128. https://doi.org/10.1016/j.scs.2016.04.013

Xu, H., Chen, Y., Dan, S., & Qiu, W. (2011). Dynamical Monitoring and Evaluation Methods to Urban Heat Island Effects Based on RS & GIS. Procedia Environmental Sciences, 10(Esiat), 1228–1237. https://doi.org/10.1016/j.proenv.2011.09.197

Xu, L., Xie, X. D., & Li, S. (2013). Correlation analysis of the urban heat island effect and the spatial and temporal distribution of atmospheric particulates using TM images in Beijing. In Environmental pollution (Barking, Essex : 1987), 178C.

https://doi.org/10.1016/j.envpol.2013.03.006

Zhao, S., Qin, Q., Yang, Y., Xiong, Y., & Qiu, G. (2009). Comparison of two split-window methods for retrieving land surface temperature from MODIS data. Journal of Earth System Science, 118(4), 345–353. https://doi.org/10.1007/s12040-009-0027-4




DOI: http://dx.doi.org/10.24895/MIG.2020.22-2.1046

Article Metrics

Abstract view : 120 times
PDF - 87 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 MAJALAH ILMIAH GLOBE

Majalah Ilmiah Globe Indexed by:

Copyright of Majalah Ilmiah Globe

Creative Commons License