Fractional snow cover Fractional snow cover estimation estimation in the complex alpine-forested in the complex alpine-forested areas using MODIS and areas using MODIS and LandsatLandsat

Elzbieta Czyzowska – Wisniewski

research conducted under guidance ofDr. K. Hirschboeck

Why do we have to study winter precipitation Why do we have to study winter precipitation and snow cover in the Southwest USAand snow cover in the Southwest USA

- winter precipitation and snow cover supply - winter precipitation and snow cover supply up to up to 90%90% of annual precipitation; of annual precipitation;

- winter precipitation and snow cover - winter precipitation and snow cover is is very sensitive very sensitive to global climate change;to global climate change;

- estimation of - estimation of snow water equivalent (SWE)snow water equivalent (SWE) based based on on instrumental data – remote sensing data complement instrumental data – remote sensing data complement sparse ground datasparse ground data;;

- estimation of snow cover and SWE is needed for better - estimation of snow cover and SWE is needed for better understanding understanding of spatial and temporal variationof spatial and temporal variation of these elements of these elements

in the decadal and century time scales;in the decadal and century time scales;

30 m

30 m

30 m

30 m

Ground Satellite

Remote sensing – introduction

30 m

30 m

30 m

30 m

30 m

30 m

30 m

30 m

Ground Satellite

Present day snow classification

< snow > non snow

snow

non snow

nonsnow

snow

30 m

30 m52

52

bandTMbandTM

bandTMbandTMNDSI

52

52

bandTMbandTM

bandTMbandTMNDSI

Normalized Difference Snow IndexNormalized Difference Snow Index

Snow detection – current methods: NDSI

Ikonos as a source information

for snow cover monitoring

30 m

30 m

Landsat

Ikonos

1 m

4 m

snow

52

52

bandTMbandTM

bandTMbandTMNDSI

52

52

bandTMbandTM

bandTMbandTMNDSI

how much of the pixel is covered by snow ?

Ikonos as a source information

for snow cover monitoring

30 m

Landsat

Ikonos

1 m

1 Landsat pixel (30m) = 900 Ikonos pixels (1m);1 MODIS pixel (500m) = 278 Landsat pixels = 250 000 Ikonos

forest

road

water

housefresh snow

old snow

metamorphosed snow

% snow cover

Ikonos

Landsat TM/ETM+ classification map

snow

snow

MODIS Terra/Aqua

snow

10 m DEM

ModisFSC

snow

GIS

snow

ANN1

/ 4

/4

ANN2

A –LandsatFSC development B – ModisFSC development C – Verification

Ikonos classification map

30 m DEM

ANN1 training

ANN2training

LandsatFSC

snow

MODIS, Landsat NDSI

NOHRSC, SNOTEL

- panchromatic - visible - near infrared - shortwave infrared - thermalLegend:

ANN2

parameters

ANN1

parameters

Landsat and MODIS fractional snow cover

IIa. Comparison of fractional snow area distribution with snow maps produced by: MODIS NDSI;Landsat NDSI; NOAA; SNOTEL;

Ikonos

Landsat ETM+

snow

snow

MODIS Terra & Aqua

snow

DEM

Fractional snow cover in mountain areas

IV. SWE at 1st April (1972 – 2007)

snow

IIb. Weekly and annual MODISfractional snow cover distribution;

19721980

snow2006

ModelsIIIa. Spatial and temporal changes of SWE based on MODIS fractional snow cover;

Model

19721980

snow2006

ANN&

GIS

V. Reconstruction of SWE and snow days (1400 – 2007);

snow

I. Neural network based fractional snow cover estimator

Future plans: 2005 - 2008