[M-SD41] Geospatial applications for natural resources, environment and agriculture

[MSD41-05] Black Pepper Growth Monitoring using Time Series Analysis of Landsat 8 OLI and Ground Data

*Wan Nor Zanariah Zainol Abdullah ¹, Siti Zul Lailee Kamsan¹, Nik Norasma Che'Ya¹ (1.Univeristi Putra Malaysia (UPM))

Keywords:Crop growth monitoring , Non-destructive method, Black pepper, Landsat 8 OLI, Support Vector Machine (SVM)

With the advancement of geospatial technology, mapping and monitoring of crop growth facilitate better crop management and prediction especially during this Covid-19 pandemic era. Its ability to deliver informative data enables users to monitor and manage their crops with optimum supervision. Thus, this study was focused on black pepper farm monitoring with the objective to establish an informative map of black pepper farm in Sungai Plan, Bintulu, Sarawak using Landsat 8 OLI time series analysis and ground truth data. A collection of Landsat 8 OLI imageries were retrieved and classified using a Support Vector Machine (SVM) classifier. Extraction of farmland elevations was produced using ground control points of black pepper veins and processed through ArcGIS 10.4 software. Two main black pepper growth’s parameters were used in this study which are the height of the tree and diameter at breast height (DBH) since this study focuses on the non-destructive crop growth monitoring method. It was identified in this study that; (1) mapping black pepper farm using Landsat 8 OLI and SVM provide overall accuracy of more than 70% and kappa coefficient more than 60% and, (2) the optimum black pepper growth was observed at elevation range between 39m to 50m. This study concluded that detailed information on black pepper’s location and growth can enhance farm management and its productivity.