The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 79–82, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-79-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 79–82, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-79-2020

  04 Nov 2020

04 Nov 2020

EVALUATION OF TREE SPECIES CLASSIFICATION METHODS USING MULTI-TEMPORAL SATELLITE IMAGES

A. Saha, S. Sastry, V. A. Dave, and R. Ghosh A. Saha et al.
  • Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India

Keywords: Multispectral, Temporal matching, DTW

Abstract. Tree species classification is an important step towards forest monitoring and biodiversity conservation. This research study evaluates several multispectral image classification techniques for tree species over Ahwa village in Dang district, South Gujarat, India. Multispectral images consisting of 4 bands-R, G, B and NIR collected over 4 months was used. Object-based segmentation using mean shift, cluster-based using K-Means and Gaussian Mixture Model (GMM) and pixel-based methods have been analyzed. Additionally, a new method of classification has been described using the Dynamic Time Warping (DTW) algorithm. It outperformed supervised classification techniques with accuracy over 95%. The GMM+DTW model accurately reflected the actual species distribution found in the ground truth.