Mapping the Boreal zone forest cover and forest cover loss 2000 to 2005
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1 Matthew Hansen a, Peter Potapov a, Steve Stehman b, Kyle Pittman a, Thomas Loveland c, Mark Carroll d, Charlene DiMiceli d Mapping the Boreal zone forest cover and forest cover loss 2000 to 2005 a - South Dakota State University, GIScCE b - State University of New York, SUNY-ESF c USGS, EROS Data center d - University of Maryland
2 MODIS Vegetation Continuous Fields 2000 Percent cover Bare ground Grass/shrubs/moss 0% 100% Trees
3 Major forest biomes of the World Boreal forests Temperate forests Humid tropical forests Dry tropical and subtropical forests and savannas
4 Mapping boreal forest cover and forest cover loss, 2000 to 2005 Use a sampling approach with Landsat data to estimate area of change Employ MODIS to stratify boreal biome into high, medium and low areas of change Also use MODIS in the analysis phase via a regression estimator procedure Integrated approach enables rapid assessment of biome-scale change with known uncertainty The approach employs MODIS data on an annual basis and Landsat data for years 2000 and 2005 Maps presence or absence of tree cover, disregarding forestry land use definitions
5 Biome-scale MODIS-based forest cover loss monitoring MODIS data time series analysis is based on annual metrics instead of monthly composites alone Classification and regression tree (CART) classification algorithm employed as primary tool for intellectual data analysis and change mapping Single supervised classification model used for biomewide annual data analysis Sub-pixel percent forest cover change training were used as a dependent variable. Coarse resolution training data set developed from higher resolution imagery
6 MODIS time-series data analysis MODIS 32-day composites composites per year Change detection using single-day MODIS images Training data Selected MODIS inputs Annual forest loss results Data aggregation Annual metrics annual metrics Regression tree data analysis Threshold applied Change hotspot map
7 Example of annual MODIS metrics boreal region R band 7 (SWIR) mean of 3 months G band 2 (NIR) with highest NDVI B band 1 (Red)
8 Change signal on MODIS metrics Reflectance, % NDVI / / / / / / / / / / / /02 Area affected by clearcut (Québec, Canada) SWIR band Mean SWIR-band value for 3 greenest month NIR band Monthly NDVI mean NDVI of 3 greenest mont
9 Method Change signal on MODIS metrics Reflectance, % NDVI / / / / / / / / / / / /02 Area affected by standreplacement fire (Québec, Canada) SWIR band Mean SWIR-band value for 3 greenest month NIR band Monthly NDVI mean NDVI of 3 greenest mont
10 Training sites distribution Boreal biome Boreal biome boundaries Training sites
11 Training site example Boreal biome MODIS NIR band (250m) Multi-temporal composite Classification results 10 km Main areas of forest removal Forest cover loss areas
12 Annual forest cover loss in Alaska (USA) and Yukon (Canada) Cumulative areas of forest canopy loss 0% 100% Tree canopy density* *from Vegetation Continuous Fields dataset, km
13 Annual forest cover loss in Quebec (Canada) Cumulative areas of forest cover loss 0% 100% Tree canopy density* *from Vegetation Continuous Fields dataset, km
14 Annual forest cover loss in European Russia Cumulative areas of forest cover loss 0% 100% Tree canopy density* *from Vegetation Continuous Fields dataset, km 15 km
15 Average change hotspot for 18.5x18.5 km blocks 0% 100% Forest cover loss hotspot , 500m % change per 18.5x18.5 km blocks
16 Hotspot map change into change likelihood strata Low change Medium change High change Low change Medium change High change Stratified samples
17 2000 Landsat sample blocks analysis Boreal biome
18 2005 Landsat sample blocks analysis Boreal biome
19 Landsat sample blocks analysis Boreal biome Image classification Change Classification results RED change GREEN forest mask
20 Landsat sample blocks analysis Boreal biome Image classification Change Classification results RED change GREEN forest mask MODIS results
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24 Boreal biome 118 sample blocks MODIS-derived change estimates, % change area per sample block y = 1.14x R 2 = Landsat-derived change estimates, % change area per sample block
25 Landsat-calibrated forest cover and forest cover loss estimates for Boreal biome
26 Landsat-calibrated forest cover and forest cover loss estimates for Humid Tropical biome
27 MODIS change analysis validation using independent datasets NFDP burned areas data for Canada Comparison of annual burned area per province Annual area burned per province, thousand ha. MODIS y = 0.61x R 2 = Annual area burned per province, thousand ha. NFDP
28 MODIS change analysis validation using independent datasets NFDP burned areas data for Canada Comparison of annual burned area for Canada NFDP MODIS 2500 Area burned, thousand ha
29 Forest cover loss area for continents and selected countries within the boreal biome Region By continent By country Percent of total biome area Within-region forest cover loss as percent of land area (s.e.) Within-region forest cover loss as percent of year 2000 forest area Percent forest cover loss within the region attributed to fire North America (0.12) Eurasia (0.12) Canada (0.15) Russia (0.19) Biome total 1.63 (0.10)
30 Biome-wide forest cover loss area estimation, Boreal Humid Tropics Biome area, million ha 2, ,962.4 Forest area 2000, million ha % forest loss (standard error) 1.63 (0.10) 1.39 (0.08) Area of forest loss , million ha % Forest loss area of forest 2000 area excluding fire 2.36
31 Conclusion A monitoring strategy combining data from sensors at multiple temporal and spatial resolutions offers a feasible and cost-effective methodology to produce timely, precise and internally consistent estimates of biome-wide forest cover loss. Results of this analysis illustrate the regional and temporal variability of forest cover loss within the boreal biome and point the way forward for combining such information with available carbon stock data to improve carbon accounting
32 Next Steps Complete temperate and dry tropical biomes Investigate other possibilities Estimating tree cover gain 1990 to 2000 using AVHRR as a stratifier 2005 to 2010 continuation of present approach
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