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Distribusi Suhu Permukaan Lahan (spl) Di Kota Malang Berdasarkan Citra Landsat 8 [PAPER]

INTISARI Pemanfaatan data penginderaan jauh saat ini berkembang cepat seiring meningkatnya kebutuhan pemenuhan data spasial di Indones...



INTISARI

Pemanfaatan data penginderaan jauh saat ini berkembang cepat seiring meningkatnya kebutuhan pemenuhan data spasial di Indonesia. Landsat 8 adalah salah satu citra satelit yang sering dimanfaatkan karena kemudahan perolehan data atau gratis. Salah satu pemanfaatan citra Landsat 8 adalah untuk memetakan persebaran suhu permukaan lahan. Estimasi Suhu Permukaan lahan bertujuan untuk mengetahui distribusi suhu di Kota Malang secara luas dan menganalisis hubungannya dengan penutup lahan di daerah perkotaan menggunakan metode Split Window Algorithm

Split Window Algorithm  merupakan metode yang dapat mengekstrak data Suhu Permukaan Lahan dengan membutuhkan nilai brightness temperature yang diturunkan dari nilai TOA Reflectance band 10 (inframerah termal) dan band 11(inframerah termal) pada sensor TIRS citra Landsat 8 serta nilai LSE ( Land Surface Emissivity ) yang diturunkan dari nilai FVC ( fractional vegetation cover ) dari band 4 (merah) dan band 5 (inframerah dekat) pada sensor OLI.

Hasil penelitian menunjukkan bahwa Suhu Permukaan Lahan perekaman 5 Juni 2017 di Kota Malang memiliki suhu rata-rata 35,0 ÂșC, suhu minimum 25,1 oC dan suhu maksimum 44,9 oC. Peningkatan suhu permukaan dipengaruhi oleh penutup lahan berupa lahan terbangun dan menurunnya kerapatan vegetasi. Suhu yang tinggi berada di tengah kota dan suhu yang rendah berada di timur tenggara
Kota Malang. Distribusi Suhu Permukaan Lahan dengan metode Split Window Algorithm  memberikan informasi persebaran nilai suhu yang detail, cepat, akurat dan memiliki variasi yang beragam per piksel sehingga menjangkau seluruh daerah kajian. 

Kata Kunci: Penginderaan Jauh, Landsat 8, Inframerah Termal, Suhu Permukaan Lahan, Land Surface Temperature, Split Window Algorithm, Penutup Lahan


ABSTRACT
Utilization of remote sensing data is now rapidly growing with the increasing of fulfillment necessary of spatial data in Indonesia. Landsat 8 is one of satellite imagery which is oftenly used because of the ease of data acquisition or free. One of the utilization of Landsat 8 is to map the distribution of land
surface temperature. Estimation of land surface temperature aims to find out the temperature distribution in the city of Malang and analyze its relationship with land cover in urban areas using Split Window Algorithm. 

Split Window Algorithm is a method that can extract the data of land surface temperature with temperature brightness value requires derived from thevalue TOA Reflectance band 10 (thermal infrared) and 11 (thermal infrared) sensors on TIRS Landsat image of 8 as well as the value of the LSE (Land Surface Emissivity) derived from the value of FVC (fractional vegetation cover) from the
band 4 (red) and band 5 (near infrared) sensor in the OIL.

The results showed that the Land surface temperature recording 5 June 2017 in Malang has an average temperature of 35.0 ° C, the minimum temperature 25.1 ° c and maximum temperature 44.9 ° c. The increase in surface temperature is affected by land cover in the form of land developed and the
decrease in the density of vegetation. High temperatures are in the middle of the city and the low temperatures in the East South-East of Malang. The distribution of Land surface temperature Split Window Algorithm methods provide information distribution temperature value detail, fast, accurate and have a diverse variations per pixel so that reach all areas of study.

Keywords: Remote Sensing, Landsat 8, Thermal Infrared, Land Surfacettemperature, Split Window Algorithm, Land Cover


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RSGIS INDONESIA: Distribusi Suhu Permukaan Lahan (spl) Di Kota Malang Berdasarkan Citra Landsat 8 [PAPER]
Distribusi Suhu Permukaan Lahan (spl) Di Kota Malang Berdasarkan Citra Landsat 8 [PAPER]
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RSGIS INDONESIA
https://www.rsgis.info/2019/07/distribusi-suhu-permukaan-lahan-spl-di-kota-malang-berdasarkan-citra-landsat-8.html
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https://www.rsgis.info/2019/07/distribusi-suhu-permukaan-lahan-spl-di-kota-malang-berdasarkan-citra-landsat-8.html
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