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Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis
Joint Authors
Pradhan, Biswajeet
Mohd Shafri, Helmi Zulhaidi
Rizeei, Hossein Mojaddadi
Mohamoud, Mohamed Ali
Kalantar, Bahareh
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-08
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The current study proposes a new method for oil palm age estimation and counting from Worldview-3 satellite image and light detection and range (LiDAR) airborne imagery.
A support vector machine algorithm (SVM) of object-based image analysis (OBIA) was implemented for oil palm counting.
The sensitivity analysis was conducted on four SVM kernel types with associated segmentation parameters to obtain the optimal crown coverage delineation.
Extracting tree’s crown was integrated with height model and multiregression methods to accurately estimate the age of trees.
The multiregression model with multikernel sizes was examined to achieve the most optimized model for age estimation.
Applied models were trained and examined over five different oil palm plantations.
The results of oil palm counting had an overall accuracy of 98.80%, while the overall accuracy of age estimation showed 84.91%, over all blocks.
The relationship between tree’s height and age was significant which supports the polynomial regression function (PRF) model with a 3×3 kernel size for under 10–12-year-old oil palm trees, while exponential regression function (ERF) is more fitted for older trees (i.e., 22 years old).
Overall, recent remote sensing dataset and machine learning techniques are useful in monitoring and detecting oil palm plantation to maximize productivity.
American Psychological Association (APA)
Rizeei, Hossein Mojaddadi& Mohd Shafri, Helmi Zulhaidi& Mohamoud, Mohamed Ali& Pradhan, Biswajeet& Kalantar, Bahareh. 2018. Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis. Journal of Sensors،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1200914
Modern Language Association (MLA)
Rizeei, Hossein Mojaddadi…[et al.]. Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis. Journal of Sensors No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1200914
American Medical Association (AMA)
Rizeei, Hossein Mojaddadi& Mohd Shafri, Helmi Zulhaidi& Mohamoud, Mohamed Ali& Pradhan, Biswajeet& Kalantar, Bahareh. Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1200914
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1200914