A global perspective on land use and cover change Alan Belward The Global Environment Monitoring Unit Institute for Environment and Sustainability European Commission Joint Research Centre 21027 Ispra (VA) Italy
http://www.tiem.utk.edu/bioed/webmodules/circadianrhythm.html Hourly
Alan Belward Ispra 22 Feb,, 22 Apr., 22 Jul.22 Oct. 2005 Nadine Gobron, fapar Images Daily and seasonally
Michael Glantz NCAR Annually and inter-annually Shanghai, China 1987 Shanghai, China 2004 Porto Velho, Brazil 1908 Porto Velho, Brazil 2007 http://www.ronet.com.br/marrocos/pv-antig/pv1-18.html http://www.skyscrapercity.com/showthread.php?t=344422
Source IPCC TAR, 2001 Land surface / atmosphere interactions
New demands for land cover land use information Forcing Inventory Variability & Uncertainty Attribution of Causes Up and downscaling Predictions and Scenarios Resource availability Resource quality Verification & planning Preservation & Conservation Figure IPCC AR4 2007
Using seasonal attributes In 1990 the IGBP identified major limitations to existing global land cover data sets The first global 1 km resolution AVHRR data set was begun in April 1992 The first 1 km land cover map, IGBP s DISCover, was released in 1997 GLC 2000 began in 1999 and was released in 2005 MODLAND began in 2001 the 500 m product was released in December 2008 GLOBCOVER 300 m began in 2004, V1.0 was released in 2007
Seasonal tracking no longer relies on Met. Satellites 23 rd June 1981 NOAA-7 21 st April 1995 ERS-2 ATSR-2 1 st August 1997 SeaWifs 24 th March 1998 VGT on SPOT-4 18 th December 1999 Terra s MODIS & MISR 1 st March 2002 ENVISAT MERIS 4 th May 2002 Aqua MODIS 14 th December 2002 GLI & POLDER on ADEOS VGT3 and Sentinel 2 and 3 National Land Imaging Program s LDCM
Overall accuracy 68.6%
GlobCover V2.2 October 2008 Overall accuracy 73.14%
Frederic Achard GLC- 2000 Eurasia GlobCover
Frederic Achard GlobCover MERIS Mosaic VGT Mosaic (GLC 2000)
Frederic Achard Croplands Cropland / grassland complexes Steppe Cultivated and Managed areas Mosaic cropland / vegetation Mosaic vegetation / cropland Sparse vegetation GLC 2000 Evergreen needle-leaved forest Deciduous broadleaved forest Closed to open broadleaved evergreen and/or semi-deciduous forest Closed broadleaved deciduous forest Closed needle-leaved evergreen forest Closed to open mixed broadleaved & needleaved forest GlobCover
Olivier Arino ESA
Hugh Eva, Pierre Defourney 1 km 300 m Google Copyright Google
Asia
Indonesia: Central Sumatra - Riau province Window size: 190 x 275 km Images MODIS (2004) and ALOS (2007)
Multi-annual change White Nile Irrigation Scheme pre expansion 1975 And after construction 2000 (images Landsat) Source Hugh Eva Andreas Brink 50,000 km2 of natural vegetation converted to agriculture every year since the 1970s 2000 1975 50 km
REDD; An International undertaking GOFC GOLD coordination Report prepared by: DeFries, Achard, Brown, Herold, Murdiyarso, Schlamadinger, De Souza, 2006. GTOS Report 46, 23 p Available at: www.fao.org/gtos/pubs. html
Gross carbon emissions Gross carbon emissions Gross deforestation Gross degradation C gr m + = A loss C ( i ) loss ( i ) i= 1 n j= 1 C _ em dgr ( j ) dgr ( j ) A Aloss = Area of deforestation (ha) Closs = Carbon emission from deforestation (t/ha) Adgr = Area affected by degradation (ha) Cdgr = Carbon emission from degradation (t/ha) for forest types i m for degrad. types j n Area change is most dynamic: can be observed from satellite
Setting a deforestation rate benchmark Future emissions will need to be compared to a national reference emission scenario Such a scenario will be based on historical deforestation and degradation rates (at country level) 1990 2000 2005
Monitoring gross changes in forest area Global observations Hot spot/large deforestation detection MODIS-type sensors Deforestation (~10-20 ha) (intra-) annual Hot spots of forest change National/local observations Wall-to-wall mapping Sampling approach Landsat-type sensors Deforestation (~0.5-1 ha) inter- annual (5 10 years) Regionally-tuned forest degradation mapping Change in forest area and density
Uncertainty Land to atmosphere emissions from land use changes during the 80s and 90s (GtC yr 1) from IPCC AR4
FAO FRA 2010 Remote Sensing Survey ystematic sample grid to estimate forest cover changes between 1990, 2000 & 2005 1990 2000 2010 Samples are 20km x 20km size
MSG 6 th March 2004 (Source copyright EUMETSAT)
350 km 2,400 km Background image VGT 2000 Mosaic (image source JRC, data source CNES )
Background image MODIS 10 th January 2005 (source NASA ) 35 km
3.5 km Background image SPOT HRV 10 m March 2005 (image source JRC, data source CNES )
January 2005 1 month before logging
March 2005 1 month after logging
January 2007 23 months after logging
REDD; a driver of land cover change services Global emissions from transport: 5 Gt CO2 eq/yr Emissions from EU-27: 5.2 Gt CO2 eq/yr Emissions from tropical deforestation: 5.9 Gt CO2 eq/yr Since 1990 the EU has decreased emissions by c.a. 0.4 Gt CO2 eq/yr
Commitment and progress
Commitment and progress GCOS Actions 22.Establish international standards and specifications for the production of land-cover characterization maps 23.Produce reliable accepted methods for land-cover map accuracy assessment 24.Commit to continuous 10-30m resolution optical satellite systems with data acquisition strategies at least equivalent to the Landsat 7 mission for land cover 25.Develop an in situ reference network and apply CEOS WGCV validation protocols for land cover 26.Generate annual products documenting global landcover characteristics at resolutions between 250m and 1km, according to internationally-agreed standards and accompanied by statistical descriptions of the maps accuracy 27.Generate maps documenting global land cover at resolutions between 10m and 30m every 5 years, according to internationally-agreed standards and accompanied by statistical descriptions of the maps accuracy
Emerging standards for legend definition (T22)
Emerging standards for validation (T23) http://lpvs.gsfc.nasa.gov/
LDCM, Sentinel 2 (T24)
MODLAND, GlobCover T26 https://lpdaac.usgs.gov/lpdaac/products/modis_product_table/land_cover/yearly_l3_global_500m/v5/combined http://ionia1.esrin.esa.int/
User Reported Primary Use of Landsat (Since Oct 1 st 2008*) *200,000 scenes downloaded OTHER 1.1% CRYOSPHERE 1.6% VISUALIZATION 3.6% WATER 3.0% NATURAL RESOURCES 3.8% TELECOMMUNICATIONS 0.3% TERR MONITORING 0.8% PLANNING 1.3% FIRE 0.5% ENERGY 1.0% Primary Data Usages HUMAN ECOLOGY 0.3% EMERGENCY RESPONSE 0.2% HUMAN HEALTH 0.2% INTERNATIONAL LAND ISSUES NATIONAL SECURITY 0.1% 0.1% SOCIOECONOMICS 0.0% AGRICULTURE 25.9% CLIMATE CHANGE 4.8% FORESTRY 5.2% ECOSYSTEM 5.7% GEOLOGY 6.0% EDUCATION 25.4% LAND CHANGE 9.3% Source Kristi Kline, Landsat Project Manager
User Reported Other Use of Landsat (Since Oct 1st 2008*) *200,000 scenes downloaded VISUALIZATION ENERGY 2.6% 2.8% HUMAN ECOLOGY 3.2% TERR MONITORING 4.3% Data Usages NATIONAL SECURITY 0.9% HUMAN HEALTH CRYOSPHERE 0.8% 1.0% INTERNATIONAL LAND ISSUES 1.8% PLANNING 2.4% INSURANCE 0.7% SOCIOECONOMICS 0.6% TELECOMMUNICATIONS 0.5% OTHER 0.3% AGRICULTURE 11.4% EDUCATION 9.1% EMERGENCY RESPONSE 4.7% LAND CHANGE 8.9% GEOLOGY 4.9% NATURAL RESOURCES 5.7% WATER 7.7% FIRE 5.8% ECOSYSTEM 6.4% CLIMATE CHANGE 6.6% FORESTRY 6.8% Source Kristi Kline, Landsat Project Manager
High resolution (T27) http://www.rapideye.de/gallery/04.html
Seasonal attributes 25 km Spring Cereals Legumes Winter Cereals Oilseed Rape Alan Belward Landsat MSS February, April, May, August 1983
Conclusions Malpensa Airport, as seen by US satellites 29 th August 1963, 9 th October 2006 Declassified KH series military (1963), Landsat (2006) Sputnik launch October 4th 1957 (history.nasa.gov) Considerable progress in global land cover mapping is being made, less in cover change, even less in land use One map won t serve all users Restricts use to specific modelling communities Compromises regional and national relevance Limited value for resource planning and management Lacks flexibility as a source of reference data for multiple environmental conventions New biophysical products negate the need for more of the same in global land cover mapping Suitable sensors must be matched by suitable data acquisition strategies, which is not always the case Annual global scale monitoring at high spatial resolution is the new priority Once every 5 years is unlikely to be enough 1963 2006