Mr
Juval Cohen
(Finnish Meteorological Institution)
Satellite based snow cover monitoring is typically performed using SAR, optical-, and passive microwave sensors. Effects of forest canopy on the observed signal need to be considered with all of these sensor types. Various models describing the interaction of electromagnetic radiation with the forest canopy have been developed, but in particular for radar backscattering, many of these are overly complex with high computational- and ancillary data requirements. For retrieval purposes, simple, invertible models are preferred.
This work aims at increasing the understanding of the effect of forest canopy on remote sensing observations of snow-covered terrain for both microwave and optical regimes, and at quantifying the capability of simple, zeroth-order models in simulating these effects. To achieve these goals, a spatial analysis of X to Ku band SAR, optical-, and multi-frequency passive microwave remote sensing data in the northern boreal forest region of Finland was performed. Model parameters for vegetation transmissivity as well as the properties of the underlying surface were optimized by utilizing LiDAR- and Landsat based simplified proxy parameters describing forest canopy closure and stem volume.
The results demonstrated that despite using these relatively simple proxies, a zeroth-order model can accurately estimate the scattering behavior of the SAR signal in the boreal forest biome, as well as passive microwave and optical signatures. The SAR model successfully estimated the median of the observations, but compared to optical and passive microwave, a large scatter of the observations was reflected by higher RMSE and lower correlation with the model. Due to both good estimation accuracy and simplicity, the presented models can be considered to be applicable in existing retrieval algorithms for seasonal snow, e.g. the estimation of snow-covered area from SAR observations. The results are relevant also concerning potential future missions for e.g. retrieval of SWE including concepts based on dual frequency SAR observations.
Summary
In this study, the effect of forest canopy on remote sensing observations of snow-covered terrain is investigated, and the capability of simple zeroth-order models in simulating these effects is tested. For this purpose, X to Ku band SAR-, optical-, and passive microwave remote sensing data together with LiDAR based forest data were analyzed in the northern boreal forest region of Finland. The results demonstrated that a zeroth-order model can accurately estimate the extinction of electromagnetic signals in a forest. The SAR model successfully estimated the median of the observations, but compared to optical and passive microwave, the scatter of the observations was larger. Good estimation accuracy and model simplicity enables the use of the presented models in existing snow retrieval algorithms and potential future missions.
Prof.
Jouni Pulliainen
(Finnish Meteorological Institute)
Dr
Juha Lemmetyinen
(Finnish Meteorological Institution)
Mr
Juval Cohen
(Finnish Meteorological Institution)
Dr
Francesco Montomoli
(IFAC-CNR, Institute for Applied Physics)
Mr
Jaakko Seppänen
(Aalto University)
Mrs
Kirsikka Heinilä
(Finnish Environment Institute)
Prof.
Martti Hallikainen
(Aalto University)
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