Determination of the age of oil palm from crown projection area detected from WorldView-2 multispectral remote sensing data: the case of Ejisu-Juaben district, Ghana

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Abstract

Information about age of oil palm is important in sustainability assessments, carbon mapping, yield projections and precision agriculture. The aim of this study was to develop and test an approach to determine the age of oil palm plantations (years after planting) by combining high resolution multispectral remote sensing data and regression techniques using a case study of Ejisu-Juaben district of Ghana. Firstly, we determined the relationship between age and crown projection area of oil palms from sample fields. Secondly, we did hierarchical classification using object based image analysis techniques on WorldView-2 multispectral data to determine the crown projection areas of oil palms from remote sensing data. Finally, the crown projection areas obtained from the hierarchical classification were combined with the field-developed regression model to determine the age of oil palms at field level for a wider area. Field collected data showed a strong linear relationship between age and crown area of oil palm up to 13 years beyond which no relationship was observed. A user’s accuracy of 80.6% and a producer’s accuracy of 68.4% were obtained for the delineation of oil palm crowns while for delineation of non-crown objects a user’s accuracy of 65.6% and a producer’s accuracy of 78.6% were obtained, with an overall accuracy of 72.8% for the OBIA delineation. Automatic crown projection area delineation from remote sensing data produced crown projection areas which closely matched the field measured crown areas except for older oil palms (13+ years) where the error was greatest. Combining the remote sensing detected crown projection area and the regression model accurately estimated oil palm ages for 27.9% of the fields and had an estimation error of 1 year or less for 74.6% of the fields and an error of a maximum 2 years for 92.4% of the fields. The results showed that 6 and 11 year old oil palm stands were dominating age categories in the study area. Although the method could be reliably applied for estimating oil palm age at field level, more attention is required in improving crown area delineation to improve the accuracy of the approach
Original languageEnglish
Pages (from-to)118-127
JournalISPRS journal of photogrammetry and remote sensing
Volume100
DOIs
Publication statusPublished - 2015

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Ghana
Palm oil
remote sensing
Remote sensing
oils
projection
oil
delineation
regression analysis
WorldView
planting
precision agriculture
agriculture
image analysis
Error analysis
Agriculture
Image analysis
Sustainable development

Keywords

  • METIS-309097
  • ITC-ISI-JOURNAL-ARTICLE

Cite this

@article{2da7e24bda024e10bc60d98d3fe4fe7b,
title = "Determination of the age of oil palm from crown projection area detected from WorldView-2 multispectral remote sensing data: the case of Ejisu-Juaben district, Ghana",
abstract = "Information about age of oil palm is important in sustainability assessments, carbon mapping, yield projections and precision agriculture. The aim of this study was to develop and test an approach to determine the age of oil palm plantations (years after planting) by combining high resolution multispectral remote sensing data and regression techniques using a case study of Ejisu-Juaben district of Ghana. Firstly, we determined the relationship between age and crown projection area of oil palms from sample fields. Secondly, we did hierarchical classification using object based image analysis techniques on WorldView-2 multispectral data to determine the crown projection areas of oil palms from remote sensing data. Finally, the crown projection areas obtained from the hierarchical classification were combined with the field-developed regression model to determine the age of oil palms at field level for a wider area. Field collected data showed a strong linear relationship between age and crown area of oil palm up to 13 years beyond which no relationship was observed. A user’s accuracy of 80.6{\%} and a producer’s accuracy of 68.4{\%} were obtained for the delineation of oil palm crowns while for delineation of non-crown objects a user’s accuracy of 65.6{\%} and a producer’s accuracy of 78.6{\%} were obtained, with an overall accuracy of 72.8{\%} for the OBIA delineation. Automatic crown projection area delineation from remote sensing data produced crown projection areas which closely matched the field measured crown areas except for older oil palms (13+ years) where the error was greatest. Combining the remote sensing detected crown projection area and the regression model accurately estimated oil palm ages for 27.9{\%} of the fields and had an estimation error of 1 year or less for 74.6{\%} of the fields and an error of a maximum 2 years for 92.4{\%} of the fields. The results showed that 6 and 11 year old oil palm stands were dominating age categories in the study area. Although the method could be reliably applied for estimating oil palm age at field level, more attention is required in improving crown area delineation to improve the accuracy of the approach",
keywords = "METIS-309097, ITC-ISI-JOURNAL-ARTICLE",
author = "A. Chemura and {van Duren}, I.C. and {van Leeuwen}, L.M.",
year = "2015",
doi = "10.1016/j.isprsjprs.2014.07.013",
language = "English",
volume = "100",
pages = "118--127",
journal = "ISPRS journal of photogrammetry and remote sensing",
issn = "0924-2716",
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T1 - Determination of the age of oil palm from crown projection area detected from WorldView-2 multispectral remote sensing data: the case of Ejisu-Juaben district, Ghana

AU - Chemura, A.

AU - van Duren, I.C.

AU - van Leeuwen, L.M.

PY - 2015

Y1 - 2015

N2 - Information about age of oil palm is important in sustainability assessments, carbon mapping, yield projections and precision agriculture. The aim of this study was to develop and test an approach to determine the age of oil palm plantations (years after planting) by combining high resolution multispectral remote sensing data and regression techniques using a case study of Ejisu-Juaben district of Ghana. Firstly, we determined the relationship between age and crown projection area of oil palms from sample fields. Secondly, we did hierarchical classification using object based image analysis techniques on WorldView-2 multispectral data to determine the crown projection areas of oil palms from remote sensing data. Finally, the crown projection areas obtained from the hierarchical classification were combined with the field-developed regression model to determine the age of oil palms at field level for a wider area. Field collected data showed a strong linear relationship between age and crown area of oil palm up to 13 years beyond which no relationship was observed. A user’s accuracy of 80.6% and a producer’s accuracy of 68.4% were obtained for the delineation of oil palm crowns while for delineation of non-crown objects a user’s accuracy of 65.6% and a producer’s accuracy of 78.6% were obtained, with an overall accuracy of 72.8% for the OBIA delineation. Automatic crown projection area delineation from remote sensing data produced crown projection areas which closely matched the field measured crown areas except for older oil palms (13+ years) where the error was greatest. Combining the remote sensing detected crown projection area and the regression model accurately estimated oil palm ages for 27.9% of the fields and had an estimation error of 1 year or less for 74.6% of the fields and an error of a maximum 2 years for 92.4% of the fields. The results showed that 6 and 11 year old oil palm stands were dominating age categories in the study area. Although the method could be reliably applied for estimating oil palm age at field level, more attention is required in improving crown area delineation to improve the accuracy of the approach

AB - Information about age of oil palm is important in sustainability assessments, carbon mapping, yield projections and precision agriculture. The aim of this study was to develop and test an approach to determine the age of oil palm plantations (years after planting) by combining high resolution multispectral remote sensing data and regression techniques using a case study of Ejisu-Juaben district of Ghana. Firstly, we determined the relationship between age and crown projection area of oil palms from sample fields. Secondly, we did hierarchical classification using object based image analysis techniques on WorldView-2 multispectral data to determine the crown projection areas of oil palms from remote sensing data. Finally, the crown projection areas obtained from the hierarchical classification were combined with the field-developed regression model to determine the age of oil palms at field level for a wider area. Field collected data showed a strong linear relationship between age and crown area of oil palm up to 13 years beyond which no relationship was observed. A user’s accuracy of 80.6% and a producer’s accuracy of 68.4% were obtained for the delineation of oil palm crowns while for delineation of non-crown objects a user’s accuracy of 65.6% and a producer’s accuracy of 78.6% were obtained, with an overall accuracy of 72.8% for the OBIA delineation. Automatic crown projection area delineation from remote sensing data produced crown projection areas which closely matched the field measured crown areas except for older oil palms (13+ years) where the error was greatest. Combining the remote sensing detected crown projection area and the regression model accurately estimated oil palm ages for 27.9% of the fields and had an estimation error of 1 year or less for 74.6% of the fields and an error of a maximum 2 years for 92.4% of the fields. The results showed that 6 and 11 year old oil palm stands were dominating age categories in the study area. Although the method could be reliably applied for estimating oil palm age at field level, more attention is required in improving crown area delineation to improve the accuracy of the approach

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