Reflectance variation in boreal landscape during the snow melting period using airborne imaging spectroscopy

Anna Maaria Kirsikka Heinilä, Miia Salminen, Sari Metsämäki, Petri Kauko Emil Pellikka, Sampsa Koponen, Jouni Pulliainen

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

Abstrakti

We aim a better understanding of the effect of spring-time snow melt on the remotely sensed scene reflectance by using an extensive amount of optical spectral data obtained from an airborne hyperspectral campaign in Northern Finland. We investigate the behaviour of thin snow reflectance for different land cover types, such as open areas, boreal forests and treeless fells. Our results not only confirm the generally known fact that the reflectance of a melting thin snow layer is considerably lower than that of a thick snow layer, but we also present analyses of the reflectance variation over different land covers and in boreal forests as a function of canopy coverage. According to common knowledge, the highly variating reflectance spectra of partially transparent, most likely also contaminated thin snow pack weakens the performance of snow detection algorithms, in particular in the mapping of Fractional Snow Cover (FSC) during the end of the melting period. The obtained results directly support further development of the SCAmod algorithm for FSC retrieval, and can be likewise applied to develop other algorithms for optical satellite data (e.g. spectral unmixing methods), and to perform accuracy assessments for snow detection algorithms.

A useful part of this work is the investigation of the competence of Normalized Difference Snow Index (NDSI) in snow detection in late spring, since it is widely used in snow mapping. We conclude, based on the spectral data analysis, that the NDSI-based snow mapping is more accurate in open areas than in forests. However, at the very end of the snow melting period the behavior of the NDSI becomes more unstable and unpredictable in non-forests with shallow snow, increasing the inaccuracy also in non-forested areas. For instance in peatbogs covered by melting snow layer (snow depth <30 cm) the mean NDSI-0.6 was observed, having coefficient of variation as high as 70%, whereas for deeper snow packs the mean NDSI shows positive values.

Alkuperäiskielienglanti
LehtiInternational Journal of Applied Earth Observation and Geoinformation
Vuosikerta76
Sivut66-76
Sivumäärä11
ISSN1569-8432
DOI - pysyväislinkit
TilaJulkaistu - huhtikuuta 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

Tieteenalat

  • 1171 Geotieteet
  • 114 Fysiikka

Projektit

Geospatial monitoring and modelling of environmental change using geoinformatics (GIMMEC)

Pellikka, P., Hjort, J., Luoto, M., Stenberg, P., Anttila, S., Clark, B., Gonsamo Gosa, A., Heiskanen, J., Hendriks, J., Tokola, N., Hohenthal, J., Johansson, T., Maeda, E., Muukkonen, P., Mäkiaho, J., Mõttus, M., Heinilä, A. M. K., Omoro, L., Rautiainen, M., Salonen, M., Siljander, M., Toivonen, T. & Virtanen, T.

28/02/2011 → …

Projekti: Tutkimuksen arviointi 2011

AISARES: Graduate school in airborne imaging spectroscopy application and research in Earth sciences

Pellikka, P., Heinilä, A. M. K., Takala, T., Mõttus, M., Zou, X., Leppäranta, M., Hyyppä, J., Sucksdorff, Y., Hyvärinen, T., Kirsikka, H. & Zou, X.

01/03/201031/12/2014

Projekti: Tutkimusprojekti

Aktiviteetit

  • 1 Väitöskirjan ohjaaja tai sivuohjaaja

PhD studies supervision of Kirsikka Heinilä

Petri Pellikka (Ohjaaja)

2010 → …

Aktiviteetti: TutkimustyypitVäitöskirjan ohjaaja tai sivuohjaaja

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