Oil Palm Plantation Detection in Indonesia Using Sentinel-2 and Landsat-8 Optical Satellite Imagery (Case Study: Rokan Hulu Regency, Riau Province)

Yunita Nurmasari and Arie Wahyu Wijayanto (2021) Oil Palm Plantation Detection in Indonesia Using Sentinel-2 and Landsat-8 Optical Satellite Imagery (Case Study: Rokan Hulu Regency, Riau Province). International Journal of Remote Sensing and Earth Sciences, 18 (1). pp. 1-18. ISSN 0216-6739

[img] Text
Jurnal_Yunita Nurmasari_STIS_2021.pdf

Download (1MB)

Abstract

The objective of this work is to assess the capability of multispectral optical Landsat and Sentinel images to detect oil palm plantations in Rokan Hulu, Riau, one of the largest palm oil producers in Indonesia, by combining multispectral bands and composite indices. In addition to comparing two different sets of satellite images, we also ascertain which gives the best performance among the supervised machine learning classifiers CART Decision Tree, Random Forest, Support Vector Machine, and Naive Bayes. With the use of multispectral bands and derived composite indices, the best classifier achieved an overall accuracy of up to 92%. The findings and contributions of the study include: (1) insight into a set of feature combinations that provides the highest model accuracy, and (2) an extensive evaluation of machine learning-based classifiers on two different optical satellite imageries. Our study could further be beneficial for the government in providing more scalable plantation statistics

Item Type: Article
Uncontrolled Keywords: remote sensing, oil palm detection, Sentinel-2, Landsat-8, supervised machine learning
Subjects: Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Teknologi dan Data Penginderaan Jauh > Perolehan Data > Satelit
Depositing User: Dinar Indrasasi
Date Deposited: 23 Nov 2021 08:20
Last Modified: 23 Nov 2021 08:20
URI: http://repositori.lapan.go.id/id/eprint/1476

Actions (login required)

View Item View Item