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Journal of Forests

June 2020, Volume 7, 1, pp 18-31

Color-Based Forest Cover Type Image Segmentation using K-Means Clustering Approach

Yeong Nain Chi

Yeong Nain Chi 1

  1. Department of Agriculture, Food and Resource Sciences University of Maryland Eastern Shore Princess Anne, MD, USA. 1

on Google Scholar
on PubMed

Pages: 18-31

DOI: 10.18488/journal.101.2020.71.18.31

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Article History:

Received: 25 March, 2020
Revised: 30 April, 2020
Accepted: 03 June, 2020
Published: 29 June, 2020


In order to understand forest composition, classifying forest cover type can help research regarding forest resilience, carbon sequestration, and climate change concerns. The purposes of this study were to develop and implement some image processing functions based on the histogram of forest cover type color image, and to classify forest cover type using its color feature sets of image pixels. Color-based image segmentation that is based on the color feature of image pixels assumes that homogeneous colors in the image correspond to separate clusters and hence meaningful objects in the image. The Image Processing Toolbox of MATLAB R2019a was used to convert the original forest cover type image to the enhance contrast image, including histogram of enhance contrast image. Furthermore, It was also used to analyze color-based forest cover type image segmentation using the enhance contrast image for this study. Using K-Means clustering analysis, a three-cluster solution was developed, labeled as Hardwoods (Yellow Color) Cover Type, Hardwoods (Gray Color) Cover Type, and Loblolly Pines Cover Type. There was a significant difference among three different forest cover type clusters in terms of histograms and L*a*b* color space features visually.
Contribution/ Originality
This study is one of very few studies which have classified forest cover type using its color feature sets of image pixels in order to understand forest composition. This study also addresses that K-Means clustering analysis can be utilized to develop and implement the classification of forest cover type image.


Forest cover type, Color-based, Image segmentation, Histogram, K-means clustering, MATLAB.


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This work is supported by the USDA National Institute of Food and Agriculture, McIntire Stennis project [Accession No. 1019401].

Competing Interests:

The author declares that there are no conflicts of interests regarding the publication of this paper.


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