Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Ema Kurnia, I Nengah Surati Jaya, Widiatmaka

Judul : Satellite-Based Land Surface Temperature Estimation of Bogor Municipality, Indonesia

Abstrak :
The earth’s average temperature has been a big issue on the global warming. The warming of the earth is largely the results of emission of carbon dioxide and other greenhouse gasses (GHG) from human activities. As a hinterland of the Capital City, in the last two decades, Bogor is also getting warmer in comparison with the previous decades. This paper presents how the land surface temperature (LST) had been estimated using Split-Window (SW) algorithm and how its spatial distribution in Bogor Municipality was computed. The spectral radiance of Landsat-8 TIR bands 10 and 11, the emissivity values, and water vapor used as the input on SW Algorithm. The study revealed that the temperature within the built-up area, have warmer temperature than their surrounding ranging from 400C to 450C of 3,403.9 ha. The use of SW algorithm is quite reliable and accurate to estimate the LST derived from Landsat-8 having a mean deviation of only 2.7%, less than standard acceptable of 10%.

Tahun : 2016 Media Publikasi : Jurnal Internasional

Kategori : Jurnal No/Vol/Tahun : 1 / 2 / 2016

ISSN/ISBN : 2502-4752

PTN/S : Institut Pertanian Bogor (IPB) Program Studi : ILMU KOMPUTER

Bibliography :
[1] Taha HG, Akbari H, Sailor D, Ritschard R. Causes and Effect of Heat Islands: The Sensitivity of Urban Microclimates to Surface Parameters and Anthropogenic Heat. Lawrence Berkeley Laboratory. Report No. 29864. Lawrence Berkeley, Davis California, USA. 1990.

[2] Fan H, Sailor DJ. Modeling the Impacts of Anthropogenic Heating on the Urban Climate of Philadelphia: A Comparison of Implementations in Two Pbl Schemes. Atmospheric Environment. 2005; 39: 73–84.

[3] Arrau CP and Pena MA. The Urban Heat Island (UHI) Effect. 2010. Available online at http://www.urbanheatislands.com (Accessed January 3rd, 2016).

[4] Rose LA, Devadas MD. Analysis of and Surface Temperature and Land Use/ Land Cover Types Using Remote Sensing Imagery – A Case in Chennai City, India. Seventh International Conference on Urban Climate, Yokohama, Japan. 2009.

[5] Fukui Y. A study on surface temperature patterns in the Tokyo metropolitan area using aster data. Geoscience Journal. 2003; 7: 343-346.

[6] Mas’at A. 2008. The impact of development on climate variations in Jakarta. BMKG Bulletin. 2008; 4.

[7] Wan Z. New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sens. Environ. 2014; 140: 36–45.

[8] Dash, P. Land surface temperature and emissivity retrieval from satellite measurements. Dissertation. Institut fur Meteorologie und Klimaforschung. ISSN 0947-8620. 2005.

[9] Akhoondzadeh M, Saradjian MR. Comparison of Land Surface Temperature Mapping Using Modis and Aster Images in Semi-Arid Area. Remote Sensing Division, Surveying and Geomatics Dept., Faculty of Engineering, University of Tehran, Tehran, Iran. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing 2008

[10] Liu H, Zhang Shenglang Z.Land Surface Temperature Retrieval from the Medium Resolution Spectral Imager MERSI Thermal Data. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2014; 12: 7287-7298

[11] Liang S, Li X, Wang J. Advanced Remote Sensing: Terrestrial Information Extraction and Applications; Elsevier Science: Amsterdam, The Netherlands. 2012.

[12] Zhang Z, He G. Generation of Landsat surface temperature product for China, 2000–2010. Int. J. Remote Sens. 2013; 34: 7369–7375.

[13] Sobrino JA, Li ZL, Stoll MP, Becker F. Multi-channel and multi-angle algorithm for estimating sea and land surface temperature with ATSR data. International Journal of Remote Sensing. 1996; 17: 20892114.

[14] Xin W, Xiaobo D, Shenglan Z. Retrieving Atmospheric Precipitable Water Vapor Using Artificial Neural Network Approach. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2013; 11: 7174-7181.

[15] Qin Z, Karnieli A, Berliner P. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Int. J. Remote Sensing. 2001; 22(18): 3719–3746.

[16] Jimenez-Munoz JC, Sobrino JA, Skokovic D, Mattar C, Cristobal J. Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geosci. Remote Sens. Lett. 2014; 11: 1840–1843.

[17] Skokovic D, Sobrino JA, Jimenez-Munoz JC, Soria G, Julien Y, Mattar C, and Cristobal J. Calibration and Validation of Land Surface Temperature for Landsat 8 – TIRS Sensor. Land product Validation and Evolution, ESA/ESRIN Frascati (Italy). 2014: 6-9.

[18] Cheng KS, Su YF, Kuo FT, Hung WC, Chiang JL. Assessing the effect of land cover changes on air temperature using remote sensing images – a pilot study in northern Taiwan. Landscape Urban Plan. 2008; 86: 85–96.

[19] Lo CP, Quattrochi D, Luvall J. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing. 1997; 18:287–304.

[20] Weng Q. A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing. 2001; 22:1999–2014.

[21] Nichol JE. A GIS-Based Approach to Microclimate Monitoring in Singapore’s High-Rise Housing Estates. Photogrammetric Engineering and Remote Sensing. 1994; 60: 1225-1232.

[22] EPA. 2009. Heat Island Compendium: Urban Heat Island Basics. Available online at: http://www.epa.gov/heat-islands/heat-island-Compendium/UrbanHeatIslandBasics.pdf (Accessed January 3rd, 2016)

[23] Mostovoy GV, King RL, Reddy KR, Kakani VG, Filippova MG. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi. GISci. Remote Sens. 2006; 43: 78–110.

[24] Prihodko L, Goward SN. Estimation of air temperature from remotely sensed surface observations. Remote Sens. Environ. 1997; 60: 335–346.

[25] Unger J, Gal T, Rakonczai J, Mucsi L, Szatmari J, Tobak J, Leeuwen B, and Fiala K. 2009. Air temperature versus surface temperature in urban environment. The seventh international conference on urban climate. Yokohama, Japan.

[26] Li Z, Guo X, Dixon P, He Y. Applicability of Land Surface Temperature (LST) estimates from AVHRR satellite image composites in northern Canada. Prairie Perspectives. 2008; 11: 119.

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Detail Karya Ilmiah Dosen

Ema Kurnia, I Nengah Surati Jaya, Widiatmaka

Judul	:	Satellite-Based Land Surface Temperature Estimation of Bogor Municipality, Indonesia
Abstrak	:	The earth’s average temperature has been a big issue on the global warming. The warming of the earth is largely the results of emission of carbon dioxide and other greenhouse gasses (GHG) from human activities. As a hinterland of the Capital City, in the last two decades, Bogor is also getting warmer in comparison with the previous decades. This paper presents how the land surface temperature (LST) had been estimated using Split-Window (SW) algorithm and how its spatial distribution in Bogor Municipality was computed. The spectral radiance of Landsat-8 TIR bands 10 and 11, the emissivity values, and water vapor used as the input on SW Algorithm. The study revealed that the temperature within the built-up area, have warmer temperature than their surrounding ranging from 400C to 450C of 3,403.9 ha. The use of SW algorithm is quite reliable and accurate to estimate the LST derived from Landsat-8 having a mean deviation of only 2.7%, less than standard acceptable of 10%.
Tahun	:	2016	Media Publikasi	:	Jurnal Internasional
Kategori	:	Jurnal	No/Vol/Tahun	:	1 / 2 / 2016
ISSN/ISBN	:	2502-4752
PTN/S	:	Institut Pertanian Bogor (IPB)	Program Studi	:	ILMU KOMPUTER
Bibliography	:	[1] Taha HG, Akbari H, Sailor D, Ritschard R. Causes and Effect of Heat Islands: The Sensitivity of Urban Microclimates to Surface Parameters and Anthropogenic Heat. Lawrence Berkeley Laboratory. Report No. 29864. Lawrence Berkeley, Davis California, USA. 1990. [2] Fan H, Sailor DJ. Modeling the Impacts of Anthropogenic Heating on the Urban Climate of Philadelphia: A Comparison of Implementations in Two Pbl Schemes. Atmospheric Environment. 2005; 39: 73–84. [3] Arrau CP and Pena MA. The Urban Heat Island (UHI) Effect. 2010. Available online at http://www.urbanheatislands.com (Accessed January 3rd, 2016). [4] Rose LA, Devadas MD. Analysis of and Surface Temperature and Land Use/ Land Cover Types Using Remote Sensing Imagery – A Case in Chennai City, India. Seventh International Conference on Urban Climate, Yokohama, Japan. 2009. [5] Fukui Y. A study on surface temperature patterns in the Tokyo metropolitan area using aster data. Geoscience Journal. 2003; 7: 343-346. [6] Mas’at A. 2008. The impact of development on climate variations in Jakarta. BMKG Bulletin. 2008; 4. [7] Wan Z. New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sens. Environ. 2014; 140: 36–45. [8] Dash, P. Land surface temperature and emissivity retrieval from satellite measurements. Dissertation. Institut fur Meteorologie und Klimaforschung. ISSN 0947-8620. 2005. [9] Akhoondzadeh M, Saradjian MR. Comparison of Land Surface Temperature Mapping Using Modis and Aster Images in Semi-Arid Area. Remote Sensing Division, Surveying and Geomatics Dept., Faculty of Engineering, University of Tehran, Tehran, Iran. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing 2008 [10] Liu H, Zhang Shenglang Z.Land Surface Temperature Retrieval from the Medium Resolution Spectral Imager MERSI Thermal Data. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2014; 12: 7287-7298 [11] Liang S, Li X, Wang J. Advanced Remote Sensing: Terrestrial Information Extraction and Applications; Elsevier Science: Amsterdam, The Netherlands. 2012. [12] Zhang Z, He G. Generation of Landsat surface temperature product for China, 2000–2010. Int. J. Remote Sens. 2013; 34: 7369–7375. [13] Sobrino JA, Li ZL, Stoll MP, Becker F. Multi-channel and multi-angle algorithm for estimating sea and land surface temperature with ATSR data. International Journal of Remote Sensing. 1996; 17: 20892114. [14] Xin W, Xiaobo D, Shenglan Z. Retrieving Atmospheric Precipitable Water Vapor Using Artificial Neural Network Approach. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2013; 11: 7174-7181. [15] Qin Z, Karnieli A, Berliner P. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Int. J. Remote Sensing. 2001; 22(18): 3719–3746. [16] Jimenez-Munoz JC, Sobrino JA, Skokovic D, Mattar C, Cristobal J. Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geosci. Remote Sens. Lett. 2014; 11: 1840–1843. [17] Skokovic D, Sobrino JA, Jimenez-Munoz JC, Soria G, Julien Y, Mattar C, and Cristobal J. Calibration and Validation of Land Surface Temperature for Landsat 8 – TIRS Sensor. Land product Validation and Evolution, ESA/ESRIN Frascati (Italy). 2014: 6-9. [18] Cheng KS, Su YF, Kuo FT, Hung WC, Chiang JL. Assessing the effect of land cover changes on air temperature using remote sensing images – a pilot study in northern Taiwan. Landscape Urban Plan. 2008; 86: 85–96. [19] Lo CP, Quattrochi D, Luvall J. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing. 1997; 18:287–304. [20] Weng Q. A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing. 2001; 22:1999–2014. [21] Nichol JE. A GIS-Based Approach to Microclimate Monitoring in Singapore’s High-Rise Housing Estates. Photogrammetric Engineering and Remote Sensing. 1994; 60: 1225-1232. [22] EPA. 2009. Heat Island Compendium: Urban Heat Island Basics. Available online at: http://www.epa.gov/heat-islands/heat-island-Compendium/UrbanHeatIslandBasics.pdf (Accessed January 3rd, 2016) [23] Mostovoy GV, King RL, Reddy KR, Kakani VG, Filippova MG. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi. GISci. Remote Sens. 2006; 43: 78–110. [24] Prihodko L, Goward SN. Estimation of air temperature from remotely sensed surface observations. Remote Sens. Environ. 1997; 60: 335–346. [25] Unger J, Gal T, Rakonczai J, Mucsi L, Szatmari J, Tobak J, Leeuwen B, and Fiala K. 2009. Air temperature versus surface temperature in urban environment. The seventh international conference on urban climate. Yokohama, Japan. [26] Li Z, Guo X, Dixon P, He Y. Applicability of Land Surface Temperature (LST) estimates from AVHRR satellite image composites in northern Canada. Prairie Perspectives. 2008; 11: 119.
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