Vitenskapelig artikkel   2013

Salberg, Arnt-Børre; Erikstad, Lars; Zortea, Maciel

Publikasjonsdetaljer

Tidsskrift:

Proceedings of SPIE, the International Society for Optical Engineering, vol. 8892, p. 12, 2013

Utgiver:

SPIE - International Society for Optical Engineering

Internasjonale standardnumre:

Trykt: 0277-786X
Elektronisk: 1996-756X

Lenker:

DOI: doi.org/10.1117/12.2029003

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.