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Space Applications Institute Global Vegetation Monitoring Unit Operational Implementation of Burnt Area Algorithms for GBA2000: Initial Results for Australia.

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Presentation on theme: "Space Applications Institute Global Vegetation Monitoring Unit Operational Implementation of Burnt Area Algorithms for GBA2000: Initial Results for Australia."— Presentation transcript:

1 Space Applications Institute Global Vegetation Monitoring Unit Operational Implementation of Burnt Area Algorithms for GBA2000: Initial Results for Australia and Africa Kevin J. Tansey & Jean-Marie Grégoire Global Vegetation Monitoring Unit (GVM) Joint Research Centre (JRC) TP-440, I-21020, Ispra (VA), Italy Tel: +39 0332 785769 E-mail: kevin.tansey@jrc.it GOFC-Fire Satellite Product Validation Workshop

2 Space Applications Institute Global Vegetation Monitoring Unit Pre-processing Objective oTo produce a ‘clean’, daily, global dataset oPossible cleaning measures: BRDF correction Extreme view zenith masked Maximum NDVI composite masked Cloud masked Cloud shadow masked Non-burnable area masked

3 Space Applications Institute Global Vegetation Monitoring Unit Maximum off-nadir observation angle = 50.5  Extreme Viewing Zenith Mask Saint, G., 1998, The VEGETATION Programme Maximum viewing zenith angle  60  Viewing zenith angle threshold <= x 

4 Space Applications Institute Global Vegetation Monitoring Unit Max. NDVI Problems oBoreal forest fire scar detection oSpeckle in cloud and cloud shadows oBRDF correction algorithms could be used oNDVI comp. areas could be masked

5 Space Applications Institute Global Vegetation Monitoring Unit Cloud Masking oSeveral approaches available: Compositing of cloud-free data Thresholding of SPOT VGT radiance values Use the status map provided with S products oThresholding of b0 (blue) and mir (swir) Values suggested by Kempeneers et al. Vegetation 2000 Meeting, 3-6 April 2000, Lake Maggiore http://vegetation.cnes.fr:8080/vgtprep/vgt2000/kempeneers.html Different thresholds are tested for S products to capture all of the cloud

6 Space Applications Institute Global Vegetation Monitoring Unit Cloud Shadow Masking oBurnt areas and shadow have similar spectral properties oCalculate cloud -> shadow vector Using available sun and viewing angles Using the latitude and longitude of each pixel oAssume a cloud height (e.g. 10km) Variable input parameter (test on small areas) Or, assume a maximum tropopause height oMask pixels between cloud and shadow Cloud pixel Intermediate shadow pixels Shadow pixel Cloud – shadow vector

7 Space Applications Institute Global Vegetation Monitoring Unit CLOUD + CLOUD SHADOW

8 Space Applications Institute Global Vegetation Monitoring Unit Non-Burnable Area Mask oUtilize global land cover products IGBP DIS landcover dataset Loveland, T.R. et al., 2000, IJRS, Vol. 21, 1303-1330 http://edcdaac.usgs.gov/glcc/glcc.html Uni. of Maryland global landcover dataset Hansen, M.C. et al., 2000, IJRS, Vol. 21, 1331-1364 http://glcf.umiacs.umd.edu/data.html oMask urban, snow/ice & bare soil classes

9 Space Applications Institute Global Vegetation Monitoring Unit Compositing Criteria o10-day min-NIR composites No Masking Applied Masking Applied Australia’s Cape York

10 Space Applications Institute Global Vegetation Monitoring Unit Compositing Improvements o‘Salt and pepper’ speckle removed oPermanently cloudy areas removed oCloud shadow masked oBurnt areas more clearly delimited

11 Space Applications Institute Global Vegetation Monitoring Unit Compositing Improvements o1 month min-NIR composites No Masking Applied Masking Applied Mozambique

12 Space Applications Institute Global Vegetation Monitoring Unit Compositing Improvements o1 month min-NIR composites No Masking Applied Masking Applied Mozambique

13 Space Applications Institute Global Vegetation Monitoring Unit Operational Implementation oSeries of discrete modules oPrograms designed to have maximum functionality and flexibility oWell documented and repeatable oProvide feedback on results to respective partners oTest algorithms over other regions easily oExample of NRI algorithm in C. Africa Boschetti, L. et al., (submitted), A multitemporal change-detection algorithm for the monitoring of burnt areas with SPOT-Vegetation data, MultiTemp 2001 Workshop, 13-14 September 2001, Trento, Italy

14 Burnt Area Map (November 1999 - March 2000) November 1999December 1999January 2000February 2000March 2000 Algorithm defined by NRI, UK

15 Comoe National Park: Ivory Coast Burnt Dec/Jan National Parks in Benin, Niger and Burkina Fasso Burnt Nov/Dec/Jan Kainji Lake National Park: Nigeria Burnt Dec/Jan Garamba National Park: Zaire Burnt Jan/Feb Murchison Falls National Park: Uganda Burnt Jan/Feb Gambella, Jikoa, Tedo National Parks and CHA’s: Ethiopia Burnt Jan/Feb/March Burning in National Park & Controlled Hunting Areas (CHA’s) November 1999 – March 2000 Algorithm defined by NRI, UK


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