The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Vol. 16 No. 1 (2019)

DETECTING AND COUNTING COCONUT TREES IN PLEIADES SATELLITE IMAGERY USING HISTOGRAM OF ORIENTED GRADIENTS AND SUPPORT VECTOR MACHINE

Yudhi Prabowo (Unknown)
Kenlo Nishida Nasahara (Unknown)



Article Info

Publish Date
25 Nov 2025

Abstract

This paper describes the detection of coconut trees using very-high-resolution optical satelliteimagery. The satellite imagery used in this study was a panchromatic band of Pleiades imagery with aspatial resolution of 0.5 metres. The authors proposed the use of a histogram of oriented gradients(HOG) algorithm as the feature extractor and a support vector machine (SVM) as the classifier for thisdetection. The main objective of this study is to find out the parameter combination for the HOGalgorithm that could provide the best performance for coconut-tree detection. The study shows that thebest parameter combination for the HOG algorithm is a configuration of 3 x 3 blocks, 9 orientation bins,and L2-norm block normalization. These parameters provide overall accuracy, precision and recall ofapproximately 80%, 73% and 87%, respectively.

Copyrights © 2019






Journal Info

Abbrev

ijreses

Publisher

Subject

Earth & Planetary Sciences

Description

The International Journal of Remote Sensing and Earth Sciences (IJReSES), published by Badan Riset dan Inovasi Nasional (BRIN) in collaboration with the Ikatan Geografi Indonesia (IGI) and managed by the Department of Geography Universitas Indonesia, is a pivotal platform in the global dissemination ...