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COMPARISON OF SPLIT WINDOWS ALGORITHM AND PLANCK METHODS FOR SURFACE TEMPERATURE ESTIMATION BASED ON REMOTE SENSING DATA IN SEMARANG

Jurnal Geografi · Vol. 14 No. 1 (2022) · hlm. 11–21

DOI
10.24114/jg.v14i1.24603
ISSN
2549-7057, 2085-8167
Terbit
2022-02-01
Penerbit
Universitas Negeri Medan
Bahasa
en

Abstrak

Inggris

Surface temperature is one of the parameters in land“surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperature estimates using the SWA and Planck methods and determine the surface temperature distribution based on the condition of land cover and its changes. The remote sensing data used are Landsat-8 OLI/TIRS Aqua MODIS images on August 27, 2013, and October 1, 2020. The results showed that Landsat 8 could obtain land cover information with an accuracy of 90% in 2013 and 91% in 2020. Planck surface temperature in 2013 was 1-3°C higher than SWA, while in 2020, Planck was 0.001-0.05°C lower than SWA but had similar distribution and pattern. The vegetation in the study area's central and south sides has a lower surface temperature than the built-up area on the north side. Land cover changes from non-built up to build-up area cause surface temperatures to increase. Each land cover has a different emissivity value and affects the surface temperature value, i.e., the lower the emissivity, the higher the surface temperature. The emissivity with surface temperature has a pearson correlation value ≥-0.8**.Keywords: Surface Temperature, Split Windows Algorithm, Planck

Inggris

Surface temperature is one of the parameters in land“surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperature estimates using the SWA and Planck methods and determine the surface temperature distribution based on the condition of land cover and its changes. The remote sensing data used are Landsat-8 OLI/TIRS Aqua MODIS images on August 27, 2013, and October 1, 2020. The results showed that Landsat 8 could obtain land cover information with an accuracy of 90% in 2013 and 91% in 2020. Planck surface temperature in 2013 was 1-3°C higher than SWA, while in 2020, Planck was 0.001-0.05°C lower than SWA but had similar distribution and pattern. The vegetation in the study area's central and south sides has a lower surface temperature than the built-up area on the north side. Land cover changes from non-built up to build-up area cause surface temperatures to increase. Each land cover has a different emissivity value and affects the surface temperature value, i.e., the lower the emissivity, the higher the surface temperature. The emissivity with surface temperature has a pearson correlation value ≥-0.8**.Keywords: Surface Temperature, Split Windows Algorithm, Planck

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  • Universitas Gadjah Mada
  • University of Bengkulu
  • National Research and Innovation Agency
  • Indonesian National Institute of Aeronautics and Space
  • Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Hokkaido University
  • Universitas Muhammadiyah Gorontalo
  • Organisasi lain
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  • Organisasi berbeda
  • Organisasi sama
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Rekan penulisOrganisasiArtikel bersama
Hartono HartonoUniversitas Gadjah Mada5
Totok GunawanUniversitas Gadjah Mada4
Bambang SulistyoUniversity of Bengkulu3
Muhammad KamalUniversitas Gadjah Mada3
Prima WidayaniUniversitas Gadjah Mada3
Ratih Dewanti DimyatiNational Research and Innovation Agency2
Kustiyo KustiyoIndonesian National Institute of Aeronautics and Space2
Iswari Nur HidayatiUniversitas Gadjah Mada2
R. SuharyadiUniversitas Gadjah Mada2
Sigit HerumurtiAfiliasi tidak diketahui2
Prama Ardha AryagunaUniversitas Esa Unggul2
Yanuar Adji NugrohoUniversitas Gadjah Mada2
Pramaditya WicaksonoUniversitas Gadjah Mada2
Hartono HartonoUniversitas Islam Negeri Sultan Syarif Kasim Riau1
Deha Agus UmarhadiHokkaido University1
Rochmat MartantoUniversitas Gadjah Mada1
Nursida ArifUniversitas Muhammadiyah Gorontalo1
Muhammad Sufwandika WijayaUniversitas Gadjah Mada1
Novi Susetyo AdiMinistry of Marine Affairs and Fisheries1
. HartonoState University of Semarang1
Junun SartohadiUniversitas Gadjah Mada1
M. Pramono HadiUniversitas Gadjah Mada1
Saparis SoedarjantoAfiliasi tidak diketahui1
Uji Astrono PribadiCenter for International Forestry Research1
Gilang Aria SetaAfiliasi tidak diketahui1
Sugeng Juwono MardihusodoUniversitas Gadjah Mada1
Muhammad DimyatiUniversity of Indonesia1
Syamani D. AliLambung Mangkurat University1
Candra Sari Djati KartikaUniversitas Gadjah Mada1
Irvan Nurrahman AnandaUniversitas Gadjah Mada1
Assyria F. UmelaUniversitas Gadjah Mada1
Alvidita Beatrix IndayaniUniversitas Gadjah Mada1
Abimanyu Putra PratamaUniversitas Gadjah Mada1
Intan LestariUniversitas Gadjah Mada1
Diwyacitta Dirda GupitaNorwegian University of Science and Technology1
Muhammad Zayyanul AfwaniUniversitas Gadjah Mada1
Haeydar Anggara HadiUniversitas Gadjah Mada1

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Sumber metadata: OAI-PMH (metadata jurnal) http://jurnal.unimed.ac.id/2012/index.php/geo/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">COMPARISON OF SPLIT WINDOWS ALGORITHM AND PLANCK METHODS FOR SURFACE TEMPERATURE ESTIMATION BASED ON REMOTE SENSING DATA  IN SEMARANG</dc:title>
	<dc:title xml:lang="en-US">COMPARISON OF SPLIT WINDOWS ALGORITHM AND PLANCK METHODS FOR SURFACE TEMPERATURE ESTIMATION BASED ON REMOTE SENSING DATA  IN SEMARANG</dc:title>
	<dc:creator xml:lang="en">Zahrotunisa, Siti</dc:creator>
	<dc:creator xml:lang="en">Danoedoro, Projo</dc:creator>
	<dc:creator xml:lang="en">Arjasakusuma, Sanjiwana</dc:creator>
	<dc:description xml:lang="en">Surface temperature is one of the parameters in land“surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperature estimates using the SWA and Planck methods and determine the surface temperature distribution based on the condition of land cover and its changes. The remote sensing data used are Landsat-8 OLI/TIRS Aqua MODIS images on August 27, 2013, and October 1, 2020. The results showed that Landsat 8 could obtain land cover information with an accuracy of 90% in 2013 and 91% in 2020. Planck surface temperature in 2013 was 1-3°C higher than SWA, while in 2020, Planck was 0.001-0.05°C lower than SWA but had similar distribution and pattern. The vegetation in the study area's central and south sides has a lower surface temperature than the built-up area on the north side. Land cover changes from non-built up to build-up area cause surface temperatures to increase. Each land cover has a different emissivity value and affects the surface temperature value, i.e., the lower the emissivity, the higher the surface temperature. The emissivity with surface temperature has a pearson correlation value ≥-0.8**.Keywords: Surface Temperature, Split Windows Algorithm, Planck</dc:description>
	<dc:description xml:lang="en-US">Surface temperature is one of the parameters in land“surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperature estimates using the SWA and Planck methods and determine the surface temperature distribution based on the condition of land cover and its changes. The remote sensing data used are Landsat-8 OLI/TIRS Aqua MODIS images on August 27, 2013, and October 1, 2020. The results showed that Landsat 8 could obtain land cover information with an accuracy of 90% in 2013 and 91% in 2020. Planck surface temperature in 2013 was 1-3°C higher than SWA, while in 2020, Planck was 0.001-0.05°C lower than SWA but had similar distribution and pattern. The vegetation in the study area's central and south sides has a lower surface temperature than the built-up area on the north side. Land cover changes from non-built up to build-up area cause surface temperatures to increase. Each land cover has a different emissivity value and affects the surface temperature value, i.e., the lower the emissivity, the higher the surface temperature. The emissivity with surface temperature has a pearson correlation value ≥-0.8**.Keywords: Surface Temperature, Split Windows Algorithm, Planck</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Medan</dc:publisher>
	<dc:date>2022-02-01</dc:date>
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	<dc:identifier>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/24603</dc:identifier>
	<dc:identifier>10.24114/jg.v14i1.24603</dc:identifier>
	<dc:source xml:lang="en">JURNAL GEOGRAFI; Vol. 14 No. 1 (2022): JURNAL GEOGRAFI; 11-21</dc:source>
	<dc:source>2549-7057</dc:source>
	<dc:source>2085-8167</dc:source>
	<dc:source>10.24114/jg.v14i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/24603/17781</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2021 JURNAL GEOGRAFI</dc:rights>
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