MONITORING OF OIL PALM FIELDS USING UAV IMAGE USING GLCM METHOD

Abstract

Unmanned Aerial Vihicle (UAV) is a tool used to monitor oil palm land, from the beginning of the growth period so that it can be monitored which parts of the plantation land have fertile (growing perfectly), less fertile (growing but not perfect), or not growing at all. The orthophoto image produced by this UAV can be processed using Matlab, to distinguish fertile, less fertile and non- growing oil palm plants using the Gray Level Co-Occurrence Matrix (GLCM) method based on four parameters with gray degree directions of 0°, 45°, 90°, and 135° with 30 image samples. The four parameters are Contrast, Correlation, Energy or Entropy and Homogeneity. The results of image processing using the GLCM method are recalculated with statistics to map fertile, less fertile and non-growing areas. From the statistical results, the range value for the 0o contrast area is 7.7635, 45o contrast is 14.2758, 90o contrast is 8.2313, 135o contrast is 12.5904. The 0o correlation range value is 0.1998, 45o correlation is 0.3625, 90o correlation is 0.1729 and 135o correlation is 0.7310. The value range for 0o energy is 0.1137, 45o energy is 0.0965, 90o energy is 0.0988, 135o energy is 0.4215. The value range for 0o homogeneity is 0.2964, 45o homogeneity is 0.2870, 90o homogeneity is 0.2553 and 135o homogeneity is 0.2755