MS EXCEL Spreadsheets:
Table 1: Monthly burned area (km2), number of scars (all clusters and individual pixels),average size of the scar (km2), % of total area of country burned (shown for the year 2000 synthesis only) estimates for all countries reporting burned areas.XLS
Table 2: Monthly burned area (km2) estimates andmonthly totals for all countries reporting burned areas.XLS
Table 3: Year 2000 burned area (km2),number of scars, average burn scar size (km2), and % of the categoryburned per country and broad vegetation type (derived from the University ofMaryland global land cover product, see point 5 below for further information).XLS
Graphs and Tables:
The following results are illustrative of the complete GBA2000 statistical dataset.
The datasets are comprised of non-accumulative, monthly products and an annual product (i.e. burnt area in the year 2000).
- The datasets in geographic projection were projected into a cylindrical equal area projection with a pixel spacing of 1000m.
- Most estimates of burnt areas are displayed in units of ha x103 = 10 km2.
- In all cases, the year 2000 (ann.) product is a sum of the monthly (m) products. This binary (0/1) product reflects the total land area burnt in the year 2000. However, for some countries the same areas burns twice, once in the 1999-2000 fire season and again in the 2000-2001 fire season. This is not reflected in the year 2000 product which is coded only burnt or not burnt. Therefore, for emission studies, the amount of vegetation burnt in the year 2000 is greater than the year 2000 product suggests for some areas. For studies such as these, use the monthly products to derive your statistics and not the year 2000 product. See Africa at country scale for an illustration of this point.
- Statistical data are presented, in some cases, per vegetation type (v). Information on the vegetation cover type was derived from the University of Maryland's global 1km land cover product. From the home page, click on the link to 'Sources' for further information.
- The reference for the vegetation information used in the statistics is:
University of Maryland's 1km Global Land Cover Product Hansen, M., DeFries, R., Townshend, J. R. G. and Sohlberg, R., 2000, Global land cover classification at 1km resolution using a decision tree classifier, International Journal of Remote Sensing, Vol. 21, pp. 1331-1365. http://www.geog.umd.edu/landcover/1km-map.html
Click on the image icons to view:
a chart; a table or a map.
* Fires statistics for modeling of emissions and transport of Greenhouse Gases and Aerosols
** TREES Tropical Forest project (see Sources for reference)
|Global/Continental level reporting||Country level reporting||Sub-country level reporting||Burning in protected areas (P.A.)||Modelling of emissions*||Disturbance to vegetation cover**|
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