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“Global and regional land cover and land change monitoring: progress and needs”

Martin Herold Wageningen University (martin.herold@wur.nl). “Global and regional land cover and land change monitoring: progress and needs”. www.fao.org/gtos/gofc-gold. Global Observations of Forest Cover and Land Dynamics. What is GOFC-GOLD?.

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“Global and regional land cover and land change monitoring: progress and needs”

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  1. Martin Herold Wageningen University (martin.herold@wur.nl) “Global and regional land cover and land change monitoring: progress and needs” www.fao.org/gtos/gofc-gold Global Observations of Forest Cover and Land Dynamics

  2. What is GOFC-GOLD? A technical panel of the UN Global Terrestrial Observing System (GTOS/FAO) A coordinated international effort: to ensure a continuous program of space-based and field forest and land observations for global monitoring of terrestrial resources A network of participants implementing coordinated research, demonstration and operational projects A vision to share data, information and knowledge GOFC-GOLD operates through: Working with GEO (tasks) and GCOS Executive committee, science and technical board Implementation teams and 3 project offices (CA, US, Europe) Dedicated working groups (REDD, GEO task, biomass) 6 Regional networks (Central/West/East Africa, SE-Asia and Latin america)

  3. Activities & needs: land observation community • Global and regional land cover mapping • Monitoring and quantifying land change • Land cover, biophysical variables and carbon stocks & change • Recent drivers of observation progress

  4. Martin Herold GOFC-GOLD land cover team Wageningen University Land cover characterization: harmonization and validation www.fao.org/gtos/gofc-gold Global Observations of Forest Cover and Land Dynamics

  5. Concept of LCCS land cover classifiers Common land cover classifiers (LCCS) Cover type/ life form Trees Shrubs Herbaceous Bare Snow & Ice Leaf longevity Artificial Leaf type Evergreen Deciduous Needle-leaved Broadleaved Terrestrial / aquatic+ regularly flooded Cultivated and managed/ (semi-)natural Aquatic/ flooded Cultivated/ managed Global land cover datasets Translation

  6. Thematic standards Reference database (GLC2000) Comparative validation & assessment Based on generalized set of eleven LCCS classes

  7. SYNMAP – for carbon cycle modeling SYNMAP – a global synthesis product of existing global land cover maps to provide a targeted and improved land cover map for carbon cycle modelling purposes; here shown as life form assemblages (Source: M. Jung et al. 2006, Remote Sensing of Environment).

  8. MODIS Collection 5 Land Cover (2001-2008) Source: M.Friedl, Boston University / NASA

  9. GLOBCOVER (2005/6) Dataset release: September 2008

  10. GLOBCOVER 2009 • The most recent and most detailed global land cover map • 2009 MERIS data – map released Dec. 2010 • Based on the Globcover pre-processing chain • Demonstrates the ability to generate global products on-demand and systematically • Available online for download 50 000 downloads An initiative of: In cooperation with: GlobCover 2009 – Final Meeting – 9 February 2011, JRC, Italy

  11. TerraNorte RLC Map for 2010 The land cover map for Russia based on MODIS 250 m data Sergey Bartalev - Russian Academy of Sciences - Space Research Institute

  12. Needs: approaches to land cover characterization • Activities moving from independent datasets to synergy products need to continue • international community consensus building • Datasets can be produced on continuous basis • Support ongoing monitoring projects (data continuity) • Invest in better user interactions and data uptake • Comparative & operational accuracy assessments: • Synergy and “best” available datasets and information • Regional accuracy numbers • Error propagation and more user-relevant uncertainty analysis

  13. Martin Herold GOFC-GOLD land cover team Wageningen University Land cover change assessments www.fao.org/gtos/gofc-gold Global Observations of Forest Cover and Land Dynamics

  14. Integrated land cover observations high Assuming observation continuity and consistency IN-SITU (+ IKONOS type) periodically (usually 1-10 yrs) Detailed physiognomy Floristics and species distribution Land use: i.e. crop type/rotation Calibration and validation Spatial detail LANDSAT/SPOT – type inter-annual (1-5 yrs) Vegetation physiognomy Land change processes Effort for frequent update high MODIS/MERIS (intra-)annual pattern Long-term trends Land type/ Phenology low high Thematic detail From Herold et al 2008, IEEE Systems

  15. Global trends in vegetation dynamics 1981-2006 (AVHRR) Credit: R. De Jong WU/CGI, Remote sensing of Environment, 2011

  16. Percent gross forest cover loss 2000–2005 per 20x20 km sample block, Hansen et al., 2010, PNAS

  17. Global active fire observations Animated figure!

  18. EXAMPLE APPLICATIONS • 1 year of composite of MODIS burned areas, superimposed on surface reflectance to provide geographic context. • Burned area statistics for the same period, for vegetation type http://modis-fire.umd.edu/MCD45A1.asp Contact: Luigi Boschetti <luigi@hermes.geog.umd.edu>

  19. Needs: approaches to land change characterization • Continuity and consistency of observations • Need to fully explore and (re-)process archives • Assessing the complexity of land dynamics: • Seasonality, trends (non-monotonic), fire, disturbances and land use change • Address the limitations and potentials of satellite-based land change observations • Need for fine scale data to quantify change

  20. FAO FRA 2010 –remote sensing survey ~ 13,500 monitoring sites

  21. Martin Herold GOFC-GOLD land cover team Wageningen University Towards carbon stocks and change(i.e. GOFC-GOLD Biomass WG) www.fao.org/gtos/gofc-gold www.gofc-gold.uni-jena.de Global Observations of Forest Cover and Land Dynamics

  22. Large area biomass mapping Source: Alessandro Baccini Woods Hole Research Center Validation for Uganda Source: Valerio Avitabile WUR/FSU Jena

  23. First estimates of C emissions for South America Annual C emissions (Million t C per year) (C committed over 10 years from 1 year deforestation Representing loss of 69% biomass) Source: Eva, Beuchle et al. in prep.

  24. Contribution of CO2 emissions from deforestation and forest degradation JRC estimate (2002, 2004): 1.1 Pg C yr–1 for 1990s DeFries et al estimate (2002) 0.9 Pg C yr–1 for 1990s CO2 emissions from deforestation and forest degradation for 1997-2004: ~ 1.2 Pg C yr–1 (12% [6–17%] of total anthropogenic CO2 emissions) Peat land emissions: ~ 0.30 Pg C yr–1 (Deforestation + peatland emissions = 15% [8–20%] of total CO2 emissions) Source: van der Werf et al, 2009, Nature BiogeoSciences

  25. Needs: land and carbon change characterization • Global and regional biophysical parameters products exist with varying understanding of uncertainty • Synergy and consistency among land cover and biophysical information (i.e. biomass, LAI, fAPAR) is required • Integrated use of land change/activity data: • Link to carbon stock change assessments • Reduce uncertainty in policy relevant estimates • Address the limitations and potentials of satellite-based land change observations

  26. Martin Herold GOFC-GOLD land cover team Further areas of active progressECV and REDD www.fao.org/gtos/gofc-gold www.gofc-gold.uni-jena.de Global Observations of Forest Cover and Land Dynamics

  27. Land Cover Climate Change Initiative • Driven by GCOS requirements and climate user needs • Detailed climate user survey (several user groups) and existing global land cover users • 3 main ways land cover observations/data are used: • As proxy for a suite of land surface parameters that are assigned based on PFTs • As proxy for human activities in terms natural versus anthropogenic and tracking human activities, i.e. land use affecting land cover (land cover change as driver of climate change) • As datasets for validation of model outcomes (i.e. time series) or to study feedback effects (land cover change as consequence of climate change)

  28. Increasing overlap and synergies among climate science communities Hibbard et al., 2010, Int. J. Climatol.

  29. Variability in capacities for REDD+ monitoring Capacity gap Capacity gap: Consideration of factors: Requirements for monitoring forest carbon on national level (IPCC GPG) Existing national capacities for national forest monitoring Progress in national GHG inventory and engagement in REDD REDD particular characteristics: importance of forest fires, soil carbon, deforestation rate etc. Specific technical challenges (remote sensing): cloud cover, seasonality, topography, remote sensing data availability and access procedures Source: Herold, 2009 http://princes.3cdn.net/8453c17981d0ae3cc8_q0m6vsqxd.pdf

  30. Closing remarks • Essential Climate Variables (ECV) and REDD (post-Kyoto) as key observation drivers • Consistency, continuity and access to observations is a key requirement for all observation scales • Archives and future satellite missions and in-situ • International efforts are need to derived transparent, agreed data and estimates • Monitoring the complexity of land changes • Land cover and change linking to carbon dynamics is essential and requires further improvements • Validation, stability and uncertainty estimates • including change and biophysical variables

  31. Some documents Essential Climate Variable (ECV) report on standards for observation and reporting: http://www.fao.org/gtos/doc/ECVs/T09 GOFC-GOLD REDD Sourcebook: www.gofc-gold.uni-jena.de/redd Translation report for major global and regional land cover legends in LCCS (GOFC-GOLD 43): http://nofc.cfs.nrcan.gc.ca/gofc-gold/Report%20Series/GOLD_43.pdf IPCC background paper on use of remote sensing in LULUCF sector (GOFC-GOLD 33): http://www.fao.org/gtos/gofc-gold/series.html

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