Shape-constrained segmentation approach for Arctic multiyear sea ice floe analysis

Yuliya Tarabalka 1 Ludovic Brucker 2 Alvaro Ivanoff 2 James Tilton 2
1 AYIN - Models of spatio-temporal structure for high-resolution image processing
CRISAM - Inria Sophia Antipolis - Méditerranée
2 GSFC - NASA Goddard Space Flight Center
Abstract : The melting of sea ice is correlated to increases in sea surface temperature and associated climatic changes. Therefore, it is important to investigate how rapidly sea ice floes melt. For this purpose, a new TempoSeg method for multitemporal segmentation of multiyear ice floes is proposed. The microwave radiometer is used to track the position of an ice floe. Then, a time series of MODIS images are created with the ice floe in the image center. A TempoSeg method is performed to segment these images into two regions: Floe and Background. First, morphological feature extraction is applied. Then, the central image pixel is marked as Floe, and shape-constrained best merge region growing is performed. The resulting two-region map is post-filtered by applying morphological operators. We have successfully tested our method on a set of MODIS images and estimated the area of a sea ice floe as a function of time.
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Yuliya Tarabalka, Ludovic Brucker, Alvaro Ivanoff, James Tilton. Shape-constrained segmentation approach for Arctic multiyear sea ice floe analysis. IEEE IGARSS - International Geoscience and Remote Sensing Symposium, IEEE, Jul 2012, Munich, Germany. ⟨hal-00729033⟩

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