Deteksi Perubahan Suhu Permukaan Menggunakan Data Satelit Landsat Multi-Waktu Studi Kasus Cekungan Bandung

Main Article Content

Widya Ningrum
Ida Narulita

Abstract

ABSTRACT

The rapid population growth and development of infrastructure in the Bandung basin has triggered an uncontrolled land use changes. The changes of land use will impact on land surface temperature distribution. Finally, these changes will give influence on climate. Land surface temperature is one of the important climatic elements in the energy balance. Changes in land surface temperature variations will potentially change other elements of the climate. The purpose of this paper is to obtain and to analyze the changes of surface temperature distribution in Bandung basin using multi temporal satellite data processing that is Landsat 5 and Landsat 8 in 2004, 2009 and 2014. Near Infrared Channel (Near Infrared/NIR) and visible wave channels (Visible band) have used to obtain the value Normalized Difference Vegetation Index/NDVI index and Albedo. Land and vegetation emissivity value and thermal band have used to determine land surface temperature. The results showed that the surface temperature distribution of Bandung basin has been changes characterized by the presence of two hotspot characters i.e. hot areas in urban and hot areas in non-urban area. The area is characterized by decreasing vegetation index values, increasing albedo values and increasing on surface temperature.  Land Surface Temperatures average value increased by 1.3°C. Land surface temperature tends to rise supposed as a result of changes in vegetated area into open area and the build area  

Keywords: land surface temperature, normalized difference vegetation index, albedo

ABSTRAK

Pesatnya pertumbuhan penduduk dan perkembangan infrastruktur di cekungan Bandung telah memicu perubahan tutupan lahan yang tidak terkendali. Perubahan tutupan lahan akan mempengaruhi distribusi suhu permukaan. Hal tersebut pada akhirnya nanti akan mempengaruhi iklim. Suhu permukaan merupakan salah satu unsur iklim yang penting dalam neraca energi. Perubahan variasi suhu permukaan berpotensi mengubah unsur unsur iklim yang lainnya. Tujuan makalah ini adalah untuk mengetahui dan menganalisis perubahan distribusi suhu permukaan di cekungan Bandung melalui pengolahan data satelit multi waktu yaitu Landsat 5 dan Landsat 8 tahun 2004, 2009, 2014 dan 2016. Kanal Inframerah Dekat (Near Infrared/NIR) dan kanal gelombang tampak (Visible band) digunakan untuk memperoleh nilai Indeks Kehijauan Vegetasi (Normalized Difference Vegetation Index/NDVI) dan Albedo. Nilai emisivitas dari tanah dan vegetasi serta Band termal digunakan untuk menentukan nilai Suhu Permukaan Tanah.Hasil penelitian menunjukkan bahwa di cekungan Bandung telah terjadi perubahan distribusi suhu permukaan yang dicirikan oleh adanya dua karakter hotspot yaitu daerah panas di daerah urban dan daerah panas di daerah non-urban. Daerah tersebut dicirikan menurunnya nilai indeks vegetasi, menurunnya nilai albedo dan meningkatnya nilai suhu permukaan tanah. Nilai rataan Suhu Permukaan Tanah tahun 2005 - 2014 meningkat sebesar 1.3°C. Kecenderungan naik ini diduga sebagai akibat adanya perubahan tutupan lahan bervegetasi menjadi daerah yang lebih terbuka dan daerah terbangun.

Kata kunci: suhu permukaan, indeks kehijauan vegetasi, albedo

 

Article Details

Section
RESEARCH ARTICLES
Author Biography

Widya Ningrum, Indonesian Institutes of Sciences

Water resillience dan Environment

References

Carmin, J., Anguelovski, I., & Roberts, D. (2012). Urban climate adaptation in the global south: planning in an emerging policy domain. Journal of Planning Education and Research, 32(1), 18-32.

Tokairin, T., Sofyan, A., & Kitada, T. (2009). Numerical study on temperature variation in the Jakarta area due to urbanization. In The Seventh International on Conference of Urban Climate, http://www.ide.titech.ac.jp/~ icuc7/extended_abstracts/pdf/375851-1-090515132251-004. pdf,(29 June 2012).

Voogt, J. A., & Oke, T. R. (1997). Complete urban surface temperatures. Journal of applied meteorology, 36(9), 1117-1132.

Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote sensing of environment, 86(3), 370-384.

Effat, H. A., & Hassan, O. A. K. (2014). Change detection of urban heat islands and some related parameters using multi-temporal Landsat images; a case study for Cairo city, Egypt. Urban Climate, 10, 171-188.

Carmin, J., Nadkarni, N., & Rhie, C. (2012). Progress and challenges in urban climate adaptation planning. Results of a global survey. Massachussetts Institute of Technology (MIT), Cambridge. Carter, JG, Cavan G., Connely A., Guy S., Handley J. and Kazmierczak A.(2015). Climate change and the city: Building capacity for urban adaptation. Progress in Planning, 95, 1-66.

Jauregui, E., & Romales, E. (1996). Urban effects on convective precipitation in Mexico City. Atmospheric Environment, 30(20), 3383-3389.

Yu, X., Guo, X., & Wu, Z. (2014). Land surface temperature retrieval from Landsat 8 TIRS—Comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote Sensing, 6(10), 9829-9852.

Tursilowati, L., Sumantyo, J. T. S., Kuze, H., & Adiningsih, E. S. (2012). Relationship between urban heat island phenomenon and land use/land cover changes in Jakarta-Indonesia. Journal of Emerging Trends in Engineering and Applied Sciences, 3(4), 645-653.

Rajeshwari, A., & Mani, N. D. (2014). Estimation of land surface temperature of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology, 3(5), 122-126.

Ramdani, F., & Setiani, P. (2014). Spatio-temporal analysis of urban temperature in Bandung City, Indonesia. Urban ecosystems, 17(2), 473-487.

Jatmiko, R. H., & Hartono, B. P. D. (2016). Penggunaan Citra Saluran Inframerah Termal untuk Studi Perubahan Liputan Lahan dan Suhu sebagai Indikator Perubahan Iklim Perkotaan di Yogyakarta (Doctoral dissertation, Universitas Gadjah Mada).

Grover, A., & Singh, R. B. (2015). Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): A comparative study of Delhi and Mumbai. Environments, 2(2), 125-138.

Taha, H. (1997). Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energy and buildings, 25(2), 99-103.

Weng, Q. (2001). A remote sensing? GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International journal of remote sensing, 22(10), 1999-2014.

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.

Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of environment, 90(4), 434-440.

Tursilowati, L. (2002). Urban heat island dan kontribusinya pada perubahan iklim dan hubungannya dengan perubahan lahan. In Seminar Nasional Pemanasan Global dan Perubahan Global. Fakta, mitigasi, dan adaptasi. Pusat Pemanfaatan Sains Atmosfer dan Iklim LAPAN, ISBN (pp. 978-979).

Myhre, G., & Myhre, A. (2003). Uncertainties in radiative forcing due to surface albedo changes caused by land-use changes. Journal of Climate, 16(10), 1511-1524.

Statistik, B. P. (2015). Kota Bandung Dalam Angka 2015, 350.

Narulita, I., Rahmat, A., & Maria, R. (2008). Aplikasi Sistem Informasi Geografi untuk Menentukan Daerah Prioritas Rehabilitasi di Cekungan Bandung. RISET Geologi dan Pertambangan, 18(1), 23-35.

Smith, R.B., 2010. The heat budget of the earth’s surface deduced from spaceavailable on