DOI: https://doi.org/10.14710/pwk.v22i1.78218

KOMPARASI METODE INDEKS SPEKTRAL UNTUK ANALISIS SPASIAL LAHAN TERBANGUN Di KOTA KENDARI

Ld. Asyravil Maolana Nusriah  -  Jurusan Geografi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kendari, Indonesia
Nurgiantoro Nurgiantoro  -  Jurusan Geografi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kendari, Indonesia
*Fitriani Fitriani  -  Jurusan Geografi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kendari, Indonesia
Tahir Tahir  -  Jurusan Geografi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kendari, Indonesia
Sawaludin Sawaludin  -  Jurusan Geografi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kendari, Indonesia
Alfirman Alfirman  -  Jurusan Ilmu Lingkungan, Fakultas Kehutanan dan Ilmu Lingkungan, Universitas Halu Oleo Kendari, Indonesia

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Abstract
Remote sensing technology in Indonesia began developing in the 1970s and continues to evolve along with improvements in the quality of satellite sensors and data processing methods. One of its uses is mapping built-up land using spectral indices, which provide fast and efficient spatial information. Built-up land indices such as the Urban Index (UI), Normalized Difference Built-Up Index (NDBI), and Visible Red Near Infrared-Built Up Index (VrNIR-BI) differ in the bands and formulas used. This study aims to compare the three indices using Landsat 8 OLI/TIRS imagery from 2023. The procedures include image cropping, cloud masking, radiometric correction, built-up land classification, accuracy testing using a confusion matrix, and correlation analysis with Land Surface Temperature (LST). The results show that the VrNIR-BI index has the highest accuracy with a kappa value of 96.59%, while the NDBI has the highest correlation with LST with an R² value of 0.5729. In conclusion, VrNIR-BI is recommended for high accuracy analysis, while NDBI is more suitable for surface temperature related analysis
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Keywords: Comparison, Built-Up Land, Remote Sensing, Urban Index, Normalized Difference Built-Up Index, Visible Red Near Infrared Built-Up Index, Landsat 8 OLI/TIRS, Kendari City

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