Pemanfaataan Penginderaan Jauh dan Sistem Informasi Geografis Berbasis Transformasi Spektral Indeks Vegetasi Untuk Estimasi Produksi Tanaman Teh - Natzratul Zahira; Muhammad Ismail; Wikan Jaya Prihantarto; Triyatno Triyatno; Dilla Angraina (Forum Kerjasama Pendidikan Tinggi (FKPT), 2026)
Tea is a leading plantation commodity in Indonesia, but production estimation through manual field surveys has limitations in terms of cost, time, and accuracy, and is less able to describe spatial variations between blocks representatively. This study aims to estimate tea production in Afdeling B PTPN IV Danau Kembar using PlanetScope imagery with the Transformed Vegetation Index (TVI) approach, and to test the accuracy of the estimation compared to actual production data. The methods used include image pre-processing (radiometric calibration), TVI calculation, field data collection through sample plots, simple linear regression analysis, and production estimation at the block level using zonal aggregation and Jenks Natural Breaks classification. The results show that the TVI value ranges from 0.79–1.13 with a productive land area reaching 240 ha (84.21%) of the total 285 ha. The regression analysis yielded a coefficient of determination (R²) of 0.7933 with the equation y = 1388.8x – 1458.4, while the model validation results showed an R² of 0.7005. The total estimated tea shoot production in Afdeling B reached 119.5 tons, with the highest production in block 24 (8.80 tons) and the lowest in block 46 (0.48 tons). Although the model displayed good accuracy results at the sample scale, the resulting estimate was less precise compared to company data due to differences, namely the temporality of the data. However, the approach using TVI based on PlanetScope imagery has proven to have advantages in presenting spatial information on the distribution of tea plant productivity per block that cannot be obtained from conventional methods, thus supporting more efficient and sustainable spatial data-based tea plantation management. The contribution of this research is to provide a TVI- and PlanetScope-based tea production estimation model applied to the highland tea plantations of West Sumatra, while also generating a spatial productivity distribution map per block as a basis for more practical plantation management decision-making.