Monitoring The Crowns of Palm Oil Plants in Central Lampung Regency using Remote Sensing Techniques

Abstract

Crude palm oil (CPO) productivity in Central Lampung Regency, at 2.25 tons/ha/year, remains below the national average of 3.90 tons/ha/year. One of the contributing factors is that oil palm plants are not growing optimally. This is reflected by the fact that the canopy cover is not dense or uniform. The objective of this study was to assess the dense or crown of oil palm trees using remote sensing technology from satellite imagery. In this study, Sentinel-2 imagery was used to oil palm canopy closure, and Landsat 8 imagery was used for land suitability analysis. The research method includes the vegetation index analysis by Normalized Difference Vegetation Index (NDVI), land moisture index by the Normalized Difference Moisture Index (NDMI), Land Surface Temperature (LST), and land suitability parameters. The results of the analysis are then macthed with the conditions of oil palm plants in the field. The results obtained from this study indicate that oil palm plantations in the Bekri District can be categorised into two discrete classes: Class S2 (sufficiently suitable) and Class S3 (marginally suitable). The total area encompassed by these classes is 8,903 hectares, with Class S2 covering 7,615 hectares and Class S3 covering 218 hectares. Moreover, the study revealed that 3,721 hectares were conducive to optimal plant growth with a dense crown, 765 hectares exhibited normal crown and growth, and 310 hectares displayed suboptimal growth with an indicated uniform dense crown. The overall accuracy rate of the study is 81.82%. There is a positive correlation between NDVI and NDMI values with a correlation coefficient (R2) of 0.8426, but there is a negative correlation between the NDVI and LST values with a correlation coefficient of -0.586.