Fusion of satellite and aerial images for identification and modeling of nature types

Arnt B. Salberg; Lars Erikstad; Maciel Zortea

doi:10.1117/12.2029003

17 October 2013 Fusion of satellite and aerial images for identification and modeling of nature types

Arnt B. Salberg, Lars Erikstad, Maciel Zortea

Proceedings Volume 8892, Image and Signal Processing for Remote Sensing XIX; 889214 (2013) https://doi.org/10.1117/12.2029003
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

In this paper we propose a framework for fusion of very high resolution (VHR) optical aerial images, satellite images (optical or SAR) and other ancillary data (e.g. a digital elevation model) for identification and modeling of nature types typically present in mountain vegetation in Arctic alpine areas. The data fusion methodology consists of three steps. (i) Segmentation of VHR aerial photo into spectrally homogeneous regions (polygons). (ii) Estimation of complementary information for each polygon using geo-referenced data from other sources. (iii) Analysis of the constructed feature vectors. We also demonstrated the strength of satellite data by qualitatively evaluating the potential for creating high resolution snow cover maps. These maps may be used to describe important environmental variables. Using a set of data consisting of an aerial photo, two SPOT 5 images and a Radarsat-2 quad-pol image, we demonstrated the potential of the data fusion methodology by an example where the polygon-derived features were analysed using PCA.

Citation Download Citation

Arnt B. Salberg, Lars Erikstad, and Maciel Zortea "Fusion of satellite and aerial images for identification and modeling of nature types", Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 889214 (17 October 2013); https://doi.org/10.1117/12.2029003

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KEYWORDS

Snow cover

Satellites

Image segmentation

Earth observing sensors

Vegetation

Data fusion

Image fusion

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