Electronic Theses and Dissertation

Kawasan geothermal Jaboi, Kota Sabang merupakan wilayah dengan aktivitas panas bumi aktif yang berpotensi memengaruhi distribusi dan komposisi vegetasi. Penelitian ini bertujuan menganalisis sebaran LST dan NDVI, mengidentifikasi komposisi vegetasi berdasarkan kelas LST, serta mengetahui korelasi antara keduanya. Data spasial diperoleh dari citra Landsat 8 OLI/TIRS tahun 2025 menggunakan Google Earth Engine (GEE), sedangkan data vegetasi dikumpulkan melalui stratified random sampling dengan petak 10×10 meter. Analisis vegetasi menggunakan Indeks Nilai Penting (INP) dan korelasi diuji dengan regresi linear sederhana. Sebaran LST berkisar antara 22°C- 28°C, kelas rendah (22°C - 25°C) menunjukkan vegetasi rapat, kelas sedang (25°C - 26°C) didominasi semak dan pertanian, serta kelas tinggi (26°C - 28°C) merupakan zona geothermal aktif dan lahan terbuka. Sebaran NDVI berkisar antara -0,137 hingga 0,569 dengan kelas cukup rapat (637,04 Ha) sebagai kelas dominan. Vegetasi kelas LST tinggi didominasi Knema sp. (INP 79,78%), sedangkan kelas LST sedang didominasi Cocos nucifera (INP 46,54%). Kelas LST rendah tidak dapat diinventarisasi akibat kelerengan sangat curam (>40%), namun NDVI tinggi (0,479 - 0,569) menunjukkan tutupan hutan lebat. Korelasi LST - NDVI bersifat negatif dengan persamaan LST = -7,3791 · NDVI + 28,252, R² = 0,4474, dan r = 0,6689, menunjukkan semakin tinggi kerapatan vegetasi maka semakin rendah suhu permukaan tanah di kawasan geothermal Jaboi.

Kata kunci: Analisis vegetasi, LST, NDVI, korelasi, Kawasan geothermal, Jaboi

The Jaboi geothermal area in Sabang City is a region with active geothermal activity that potentially influences vegetation distribution and composition. This study aimed to analyze the distribution of Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI), identify vegetation composition based on LST classes, and determine the correlation between the two. Spatial data were obtained from Landsat 8 OLI/TIRS imagery (2025) using Google Earth Engine (GEE), while vegetation data were collected via stratified random sampling using 10x10 meter plots. Vegetation analysis utilized the Importance Value Index (IVI), and the correlation was tested using simple linear regression. LST values ranged from 22°C to 28°C: the low class (22°C–25°C) exhibited dense vegetation; the medium class (25°C–26°C) was dominated by shrubs and agricultural land; and the high class (26°C–28°C) consisted of active geothermal zones and open land. NDVI values ranged from -0.137 to 0.569, with the moderately dense class (637.04 ha) being dominant. Vegetation in the high LST class was dominated by Knema sp. (IVI 79.78%), whereas the medium LST class was dominated by Cocos nucifera (IVI 46.54%). Vegetation in the low LST class could not be inventoried due to very steep slopes (>40%); however, high NDVI values (0.479–0.569) indicated dense forest cover. The correlation between LST and NDVI was negative, described by the equation LST = -7.3791 · NDVI + 28.252 (R² = 0.4474; r = 0.6689), indicating that higher vegetation density corresponds to lower land surface temperatures in the Jaboi geothermal area. Keywords: Vegetation analysis, LST, NDVI, correlation, geothermal area, Jaboi