Utilization of Remote Sensing and GIS For The Calculation of Eucalypthus Productivity at BKPH Sukun - Lutfi Ailuul Waahidati; Eko Budiyanto (Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan, 2021)
The Sukun Forest Management Unit (BKPH) is the manager of both protection and production forest, which includes eucalyptus trees covering an area of 3,701 ha. One of the efforts to optimize eucalyptus production is to estimate the productivity of eucalyptus. Advances in remote sensing technology and geographic information systems (GIS) can provide fast and accurate specific data to be able to estimate the production of eucalyptus leaves. The purpose of this research is to build a model for calculating eucalyptus production based on remote sensing data and to estimate the amount of eucalyptus production by applying remote sensing data. This research uses remote sensing and geographic information system (GIS) with Soil Adjusted Vegetation Index (SAVI) and the number of trees of eucalyptus as parameters to analyze the productivity of eucalyptus leaves. The results showed that the spectral value of SAVI and the number of trees were able to explain the yield of eucalyptus leaves with an accuracy of 98%. Estimation of eucalyptus production can be done through multiple linear regression models between the variable number of trees and the SAVI spectral value. The result showed an accuracy of 78% with the equation y = 0.405 + 1.190x1 + 0.001x2 and the Standard Error of Estimate are 0.052. The highest production estimate is 1.239 tonnes/pixel, while the lowest estimate is 0.633 tonnes/pixel.