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Investigation:

LC-39 (DeFries / Shimabukuro)

LBA Dataset ID:

LC39_DECAF_MODEL

Originator(s):

1. MORTON, D.C.
2. DEFRIES, R.S.
      3. VAN DER WERF, G.R.
4. GIGLIO, L.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Dataset Abstract:

The DEforestation CArbon Flux (DECAF) model was designed to estimate monthly land use carbon fluxes in Amazon and Cerrado savanna/woodland ecosystems with very high (250m) spatial resolution (DeFries et al., 2008; van der Werf et al., 2009). In DECAF, monthly carbon fluxes from large deforestation events (>25 ha) are modeled based on post-deforestation land use (Morton et al., 2006) and the frequency and duration of active fires during the deforestation process (Morton et al., 2008). DECAF also estimates land use carbon fluxes associated with conversion of Cerrado to mechanized crop production (Morton et al., 2006) and fires in Cerrado and managed pasture cover types (Giglio et al., 2009). Annualized DECAF model input and output files include:

Beginning Date:

2000-10-01

Ending Date:

2006-09-30

Metadata Last Updated on:

2013-09-13

Data Status:

Archived

Access Constraints:

PUBLIC

Data Center URL:

http://daac.ornl.gov/

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Access Instructions:

PUBLIC

Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.
Datafile(s):

LBA-ECO LC-39 Modeled Carbon Flux from Deforestation, Mato Grosso, Brazil: 2000-2006:  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1190

Documentation/Other Supporting Documents:

LBA-ECO LC-39 Modeled Carbon Flux from Deforestation, Mato Grosso, Brazil: 2000-2006:  http://daac.ornl.gov/LBA/guides/LC39_DECAF_Model.html

Citation Information - Other Details:

Morton, D.C., R.S. DeFries, G.R. van der Werf, L. Giglio. 2013. LBA-ECO LC-39 Modeled Carbon Flux from Deforestation, Mato Grosso, Brazil: 2000-2006. Data set. Available on-line [http://daac.ornl.gov ] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1190

Keywords - Theme:

Parameter Topic Term Source Sensor
BIOMASS BIOSPHERE VEGETATION COMPUTER MODEL ANALYSIS
CARBON BIOSPHERE DEFORESTATION COMPUTER MODEL ANALYSIS
FIRE OCCURRENCE BIOSPHERE LAND USE/LAND COVER TERRA (MORNING EQUATORIAL CROSSING TIME SATELLITE) MODIS (MODERATE-RESOLUTION IMAGING SPECTRORADIOMETER)
VEGETATION INDEX BIOSPHERE VEGETATION TERRA (MORNING EQUATORIAL CROSSING TIME SATELLITE) MODIS (MODERATE-RESOLUTION IMAGING SPECTRORADIOMETER)

Uncontrolled Theme Keyword(s):  DECAF MODEL, FIRE EMISSIONS, MATP GROSSO

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
  MATO GROSSO -10.00000 -20.00000 -50.76290 -63.85070

Related Publication(s):

DeFries R.S., D.C. Morton, G.R. van der Werf GR, L. Giglio, G.J. Collatz, J.T. Randerson, R.A. Houghton, P.S. Kasibhatla. 2008. Fire-related carbon emissions from multiple land use transitions in southern Amazonia. Geophysical Research Letters 35, doi:10.1029/2008GL035689.

Morton D.C., R.S. DeFries, J.T. Randerson, L. Giglio, W. Schroeder, G.R. van der Werf. 2008. Agricultural intensification increases deforestation fire activity in Amazonia. Global Change Biology 14: 2262-2275.

Morton, D.C., R.S. DeFries, Y.E. Shimabukuro, L.O. Anderson, E.Arai, F. del Bon Espirito-Santo, R. Frietas and J. Morisette. 2006. Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon. PNAS 103: 14637-14641.

Morton, D.C., Y.E. Shimabukuro, B.F.T. Rudorff, A. Lima, R. Freitas, R.S. DeFries. 2007. Challenges for conservation at the agricultural frontier: deforestation, fire, and land use dynamics in Mato Grosso. Agua & Ambiente 2(1): 5-20.

van der Werf, G.R., D.C. Morton, R.S. DeFries, L. Gilgio, J.T. Randerson, G.J. Collatz, P.S. Kasibhatla. 2009. Estimates of deforestation-induced carbon fluxes in the southern Amazon based on satellite data and biogeochemical modeling. Biogeosciences 6: 239-245.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

The dataset is a compilation of 1) monthly and annual data layers used as inputs for the DECAF model and 2) key model outputs for three emissions scenarios (low, middle, and high), as described in DeFries et al. (2008) and van der Werf et al. (2009). Common characteristics for all data files are listed first, followed by specific information for each data product using the numbered order under the Summary section above. Please see the following links for more information about MODIS and the MODIS tile grid:

http://modis.gsfc.nasa.gov/

http://nsidc.org/data/docs/daac/mod10_modis_snow/landgrid.html



Data product details: All data files are have the same size (4800 samples by 4800 lines) as a standard MODIS h12v10 tile at MODIS 250m resolution (231.6564 m). All data products are saved as either binary files (.nvi) with header information (.hdr) or GeoTIFF files with embedded header information.



Details for data types included in the DECAF Input/Output dataset:

1) Monthly NDVI

Monthly NDVI data were generated from MODIS Collection 4 16-day NDVI composites (MOD13, Huete et al., 2002) after cloudy and missing data were replaced using a cubic spline function (see Morton et al., 2006; 2011). Individual months were generated using the following rules for combining data from 16-day composites:

January: 001 and 017

February: 33 and 49

March: 65 and 81

April: 97 and 113

May: only 129

June: 145 and 161

July: 177 and 193

August: 209 and 225

September: 241 and 257

October: 273 and 289

November: 305 and 321

December: 337 and 353

Individual data files have the following naming scheme:

MMMYY_ndvi.nvi

Where:

MMM = three digit month code (jan, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec)

YY= two digit year from 2000-2006

.nvi = extension indicating file in binary format.

Files for all years except 2004-2005 are in floating point format, with NDVI values (0-1) scaled by 1 x 105 (0.00-10000.00). Data for 2004-2005 are in integer format (0-10000).



2) Data Mask for Mato Grosso State

The Mato Grosso data mask indicates the regions within MODIS tile h12v10 that correspond to the Brazilian state of Mato Grosso (value = 1). The file, in GeoTIFF format, is: mato_grosso_h12v10_mask.tif



3) Land Cover

Annual land cover information for Mato Grosso State was generated using MODIS phenology metrics (Morton et al., 2006; Morton et al., 2011). In addition, annual land cover data was updated based on post-clearing land use (pasture or cropland) for deforestation and Cerrado conversion to mechanized cropland in previous years. Six land cover classes were included in DECAF:

DECAF Model Class Class Number

Forest 1

Cropland 2

Cerrado (woody savanna) 3

Grassland/Pasture 4

Woodland (cerradao) 5

Water 6



Annual land cover data layers for 2000-2004 in GeoTIFF format have the following file naming scheme:

decafY1Y2_land_cover_tiff.tif

Where:

Y1Y2 = DECAF model year start (October of year 1, Y1) and end (September of year 2, Y2). For example: decaf0102_land_cover_tiff.tif



4) Burn Trajectories

Annual burn trajectory information was assembled from three separate data sources. First, monthly burned area for fires in pasture and Cerrado savanna/woodland ecosystems were derived from MODIS 500m burned area maps (Giglio et al., 2009). Second, annual deforestation information was based on deforestation increment data from INPE PRODES program (http://obt.inpe.br/prodes). For large deforestation events (>25 ha), information on post-clearing land use (Morton et al., 2006; 2007) and the duration of active fire detections associated with forest conversion (Morton et al., 2008) were used to assign deforestation events to 1, 2, or 3-year conversions for pasture, cropland, or areas not in production (van der Werf et al., 2009). Small deforestation events (<25 ha) were assigned to land cover classes of pasture or cropland as described in van der Werf et al. (2009). Third, conversion of Cerrado savanna/woodland to cropland was estimated using annual land cover information from MODIS phenology metrics (see Morton et al., 2006; Morton et al., 2011).

In each data file, burning trajectories for each pixel are coded using the following legend:

Type Transition #

NONFOREST TRANSITIONS

Cerrado/Pasture Fire January 1

Cerrado/Pasture Fire February 2

Cerrado/Pasture Fire March 3

Cerrado/Pasture Fire April 4

Cerrado/Pasture Fire May 5

Cerrado/Pasture Fire June 6

Cerrado/Pasture Fire July 7

Cerrado/Pasture Fire August 8

Cerrado/Pasture Fire September 9

Cerrado/Pasture Fire October 10

Cerrado/Pasture Fire November 11

Cerrado/Pasture Fire December 12

Secondary transitions (Pasture-Cropland) 18

Cerrado-cropland 19

Pasture-cropland 20

DEFORESTATION TRANSITIONS

cropland 1 year (no fire) 21

cropland 1 year (early) 22

cropland 1 year (standard) 23

crop 1 year pre-fire and late 24

cropland 1 year (late) 25

cropland 2 year (no fire) 26

cropland 2 year (early) 27

cropland 2 year (standard) 28

cropland 3 year (no fire) 29

cropland 3 year (early) 30

cropland 3 year (standard) 31

pasture 1 year (no fire) 32

pasture 1 year (early) 33

pasture 1 year (standard) 34

pasture 1 year pre-fire and late 35

pasture 1 year (late) 36

pasture 2 year (no fire) 37

pasture 2 year (early) 38

pasture 2 year (standard) 39

pasture 3 year (no fire) 40

pasture 3 year (early) 41

pasture 3 year (standard) 42

NYIP (no fire) 43

NYIP (early) 44

NYIP (normal) 45

NYIP (late) 46

Small (<25ha) crop 47

Small (<25ha) pasture 48

For deforestation transitions:

Early: Active fires detected in the year prior to PRODES deforestation detection (e.g., fires in October, deforestation not detected until the following August).

No Fire: Deforestation transitions for which no MODIS active fires were detected within a 1 km radius.

Standard: Deforestation transition for which active fire information and phenology-based land cover classification indicate the same pace of conversion (e.g., 2 years).

Late: Deforestation transition in which MODIS active fire detections continue beyond the appearance of post-clearing land use phenology of pasture or cropland.



Monthly biomass burning activity associated with individual trajectories is described in greater detail in van der Werf et al. (2009).

The data file naming convention is: Decaf_burn_trajectory_YYYY.tif

Where YYYY = year of burning, e.g., 2001







5) DECAF Estimated Aboveground Biomass

The DECAF model estimates the live and dead biomass in various carbon pools (see van der Werf et al., 2009). Estimated aboveground biomass is one of the model outputs that can be compared to independent estimates of forest and Cerrado carbon stocks. These data files represent the estimated aboveground biomass (in grams biomass per m2, or g DM m-2) in 2000 and 2004. Estimated biomass in 2000 represents the model initial conditions following spin up using NDVI data from 2000-2001 (see van der Werf et al., 2009). 2004 biomass represents the aboveground biomass after simulating NPP and heterotrophic respiration, land cover changes, and biomass burning during 2001-2004. The data files (in binary format, with separate header file) are:

decaf_mt_biomass_2000.nvi

decaf_mt_biomass_2004.nvi



6) DECAF Biomass Burning Emissions Estimates

The DECAF emissions model was run under three scenarios, low, middle, and high (DeFries et al., 2009; van der Werf et al., 2009). These scenarios selected different levels of tree mortality, combustion completeness, and inclusion of below-ground biomass in burning activities (van der Werf et al., 2009). Emissions results for 2001-2005 were generated separately for runs under the low, middle, and high scenarios. GeoTIFF files for annual emissions represent the carbon emissions per pixel in grams carbon per m2 (g C m-2). The file naming convention is:

BBYYYY_scenario.tif

Where:

BB = Biomass Burning

YYYY = 4-digit year of biomass burning, 2001-2005

Scenario = low, middle, or high

Data Application and Derivation:

Mato Grosso is a hotspot of recent deforestation, accounting for more than 15% of tropical forest losses worldwide during 2001-2005 (Hansen et al., 2008). Carbon emissions associated with deforestation in Mato Grosso, combined with other fires for land management and conversion of Cerrado woodlands for agricultural use, constitute an important source of greenhouse gas emissions. Recent efforts to Reduce Emissions from Deforestation and forest Degradation (REDD) have placed further emphasis on improving estimates of historic emissions from forest lands. DECAF represents a substantial improvement over previous attempts to model deforestation carbon fluxes, both in terms of the DECAF spatial resolution (250m) and the use of multiple lines of satellite-based evidence to constrain the timing and amount of biomass burning associated with forest cover conversions. The DECAF approach to track individual deforestation and Cerrado conversions over the multi-year clearing process provides an example of the type of model architecture that could be used for monitoring, verification, and reporting of emissions from forest lands for REDD+.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

DECAF estimated aboveground biomass was compared with two recent data products for the Mato Grosso study region (Sales et al., 2007; Saatchi et al., 2007) in van der Werf et al. (2009). DECAF deforestation carbon fluxes were compared with fire emissions data from the Global Fire Emissions Database (GFED) in DeFries et al. (2008). Land cover data for the DECAF model were based on field observations in 2004, and validated using set-aside validation data from 2004 field observations and MODIS and field data from 2005 (Morton et al., 2011).

Process Description:

Data Acquisition Materials and Methods:

We used Collection 4 NDVI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board the Terra platform for South America from 2000-2006.

References:

DeFries, R.S., D.C. Morton, G.R. van der Werf GR, L. Giglio, G.J. Collatz, J.T. Randerson, R.A. Houghton, P.S. Kasibhatla. 2008. Fire-related carbon emissions from multiple land use transitions in southern Amazonia. Geophysical Research Letters 35, doi:10.1029/2008GL035689



Giglio, L., T. Loboda, D.P. Roy, B. Quayle, C.O. Justice. 2009. An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sensing of Environment, 113, 408-420.



Hansen, M.C., S.V. Stehman, P.V. Potapov, T.R. Loveland, J. Townshend, R.S. DeFries, K.W. Pittman, B. Arunarwati, F. Stolle, M.K. Steininger, M. Carroll, C. DiMiceli. 2008. Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data. Proceedings of the National Academy of Sciences, 105, 9439-9444.



Huete, A.R., K. Didan, T. Miura, E.P. Rodriguez, X. Gao, L.G. Ferreira. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195-213.



Morton, D.C., R.S. DeFries, Y.E. Shimabukuro, L.O. Anderson, E.Arai, F. del Bon Espirito-Santo, R. Frietas and J. Morisette. 2006. Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon. PNAS 103: 14637-14641.



Morton, D.C., R.S. DeFries, J.T. Randerson, L. Giglio, W. Schroeder, G.R. van der Werf. 2008. Agricultural intensification increases deforestation fire activity in Amazonia. Global Change Biology 14: 2262-2275.



Morton, D.C., R.S. DeFries, Y.E. Shimabukuro, L.O. Anderson, E. Arai, R. Freitas, F. Espirito-Santo. 2011. LBA-ECO LC-22 Land Cover from MODIS-based Vegetation Phenology, Mato Grosso, Brazil. Data set. Available on-line [http://daac.ornl.gov ] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.



Saatchi, S.S., R.A. Houghton, A.R. Dos Santos, J.V. Soares, Y. Yu. 2007. Distribution of aboveground live biomass in the Amazon basin. Global Change Biology, 13, 816-837.



Sales, M.H., C.M. Souza Jr., P.C. Kyriakidis, D.A. Roberts, E. Vidal. 2007. Improving spatial distribution estimation of forest biomass with geostatistics: A case study for Rondonia, Brazil. Ecological Modelling, 2005, 221-230.



van der Werf, G.R., D.C. Morton, R.S. DeFries, L. Gilgio, J.T. Randerson, G.J. Collatz, P.S. Kasibhatla. 2009. Estimates of deforestation-induced carbon fluxes in the southern Amazon based on satellite data and biogeochemical modeling. Biogeosciences 6: 239-245.

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