1 / 9

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

Fractional snow cover estimation in the complex alpine-forested areas using MODIS and Landsat. research conducted under guidance of Dr. K. Hirschboeck. Elzbieta Czyzowska – Wisniewski. Why do we have to study winter precipitation and snow cover in the Southwest USA.

yazid
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Fractional snow cover estimation in the complex alpine-forested areas using MODIS and Landsat research conducted under guidance of Dr. K. Hirschboeck Elzbieta Czyzowska – Wisniewski

  2. Why do we have to study winter precipitation and snow cover in the Southwest USA - winter precipitation and snow cover supply up to 90% of annual precipitation; - winter precipitation and snow cover is very sensitive to global climate change; - estimation of snow cover and SWE is needed for better understanding of spatial and temporal variation of these elements in the decadal and century time scales; - estimation of snow water equivalent (SWE) based on instrumental data – remote sensing data complement sparse ground data;

  3. Ground Satellite 30 m 30 m 30 m 30 m 30 m 30 m 30 m 30 m Remote sensing – introduction

  4. 30 m 30 m Present day snow classification snow snow < snow > non snow non snow non snow 30 m 30 m Normalized Difference Snow Index Snow detection – current methods: NDSI Ground Satellite 30 m 30 m

  5. Ikonos 1 m 4 m Ikonos as a source information for snow cover monitoring Landsat snow 30 m how much of the pixel is covered by snow ? 30 m

  6. Ikonos 1 m forest road water house fresh snow old snow metamorphosed snow Ikonos as a source information for snow cover monitoring Landsat 30 m % snow cover 1 Landsat pixel (30m) = 900 Ikonos pixels (1m); 1 MODIS pixel (500m) = 278 Landsat pixels = 250 000 Ikonos

  7. C – Verification A –LandsatFSC development B – ModisFSC development Ikonos classification map Ikonos ANN1 training snow 10 m DEM 30 m DEM ANN 2 ANN 1 snow 4 ANN2 training / snow snow GIS snow ANN1 parameters ANN2 parameters 4 / ModisFSC LandsatFSC NOHRSC, SNOTEL MODIS, Landsat NDSI snow MODIS Terra/Aqua Landsat TM/ETM+ classification map - near infrared - panchromatic Legend: - visible - shortwave infrared - thermal Landsat and MODIS fractional snow cover

  8. snow snow snow snow snow 1972 1980 1972 snow 2006 1980 snow 2006 Future plans: 2005 - 2008 IIa. Comparison of fractional snow area distribution with snow maps produced by: MODIS NDSI;Landsat NDSI; NOAA; SNOTEL; I. Neural network based fractional snow cover estimator DEM MODIS Terra & Aqua Ikonos Fractional snow cover in mountain areas GIS Landsat ETM+ Model IIb. Weekly and annual MODIS fractional snow cover distribution; IV. SWE at 1st April (1972 – 2007) Models IIIa. Spatial and temporal changes of SWE based on MODIS fractional snow cover; & ANN V. Reconstruction of SWE and snow days (1400 – 2007);

More Related