Sushant Tripathy1, C. Barban2, K. Jain1, S. Kholikov1 and ...
Atul Jain1*, Prasanth Meiyappan 1, Ramakrishna Nemani 2...
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Objectives Satellite-Based LCLUC Data Satellite-Based LAI Data Use data-modeling framework to pursue three principal objectives: ¾ Improve our understanding of the historical effects of land cover and land use change (LCLUC) dynamics on the quantities and pathways of biogeochemical carbon and nitrogen fluxes achieve by linking the satellite-based historical rates of LCLUCs with the biophysical model ¾ Project future LCLUC in the study region in the next 50 years achieve by linking the biophysical and socio-economic models ¾ Quantify the impacts of current and future LCLUC on carbon and nitrogen dynamics in the study region achieve by applying an improved version of the biophysical model Atul Jain 1* , Prasanth Meiyappan 1 , Ramakrishna Nemani 2 , Sangram Ganguly 2 , David Skole 3 , Walter Chomentowski 3 , Brian O’Neill 4 1 University of Illinois at Urbana-Champaign, 2 NASA Ames, 3 Michigan State University, 4 NCAR *Email: [email protected] Land Use Change Due to Different Human Activities LAI ISAM Land Surface Model and Results ISAM Land Surface Model Calculate fluxes of carbon, nitrogen, energy, water, and the dynamical processes that alter these fluxes 21 Biome types 0.5 x 0.5 degree resolution 30 minutes temporal scale Season-to-interannual variability (penology) References: Jain and Yang (2005, GBC) Jain et al. (2005, GRL) Jain et al. (2006, JGR) Jain et al. (2009, GBC) Yang et al (2009, GBC) Yang et al.(2010, Biogeoscience) ISAM Model Estimated GPP vs. MODIS Data Comparison of (a) ISAM estimated annual GPP averaged for the time period 2000-2006 with (b) MODIS GPP. MODIS GPP figure (b) is directly downloaded from the MODIS data website (a) (b) ISAM Model Estimated C & N 2 O Emissions due to LCLUC ISAM estimated (a) C emissions (Unit: gC/m 2 /yr), (b) N 2 O emissions (Unit: kg N/ha/yr) from LCLUCs in the 2005. Positive values represent net C/N release to the atmosphere and negative values represent net C/N storage in the terrestrial biosphere (a) (b) Linking Socio-Economic and Biophysical Systems PET Model IPCC A2 LU Scenario Development: Computable General Equilibrium model 9 world regions 5 economic sectors Input • A2 ;and use input assumptions - IIASA • Economic & land data - GTAP • Energy data - IEA PET-ISAM IPCC A2 Scenario Results Cropland Area (ha) in 2050 Pastureland Area (ha) in 2050 Secondary Forest Area (ha) in 2050 Acknowledgements LAI LAI Peak LAI Averaged for the Winter Months (Dec., Jan., Feb) Peak LAI Averaged for the Summer Months (Jun., Jul., Aug) Monthly climatological (2003-2008) LAI values for monsoon Asia region are estimated using a radiative transfer model. The input to the model are 250 m MODIS surface reflectance data, 250 m MODIS resampled LC data. All the data and modeling simulations are performed using the TOPS modeling framework on NASA’s Earth Exchange (NEX) platform. Remotely sensed LCLU data for India region at 56 m resolution (2004-2005) based on Indian satellite IRS-P6 (AWiFS) (Courtesy: P.S. Roy, ISRO) . Remotely sensed forest fraction data for South East Asia at 30 m resolution (2005) based Landsat satellite. MODIS LCLU data resampled at 250 meter resolution for the year 2005. The land classifications are based on University of Maryland scheme. (a) Cropland (b) Pastureland (c) Wood Harvest (d) Urban Land (e) Secondary Forest LCLUCs due different human activities compiled based on different sources. The data is compiled over the period 1765-2005. The data is shown here for the year 2005 in unit km 2 . The sources for different data sets are : (a) Cropland - updated based on Ramankutty, N., and J.A. Foley (1999), (b) Pastureland - Ramankutty, N., and J.A. Fole (personal communication), (c) Wood harvest – Hurtt et al. (2006), (d) Urban land – Goldewijk et al. (2010), (e) Secondary forest – Yang et al. (2010).
Transcript of Atul Jain1*, Prasanth Meiyappan 1, Ramakrishna Nemani 2...
Objectives
Satellite-Based LCLUC Data
Satellite-Based LAI DataUse data-modeling framework to pursue three principal objectives:
Improve our understanding of the historical effects of land cover and landuse change (LCLUC) dynamics on the quantities and pathways ofbiogeochemical carbon and nitrogen fluxes
achieve by linking the satellite-based historical rates of LCLUCs with the biophysicalmodel
Project future LCLUC in the study region in the next 50 yearsachieve by linking the biophysical and socio-economic models
Quantify the impacts of current and future LCLUC on carbon and nitrogendynamics in the study region
achieve by applying an improved version of the biophysical model
Atul Jain1*, Prasanth Meiyappan1, Ramakrishna Nemani2, Sangram Ganguly2, David Skole3, Walter Chomentowski3, Brian O’Neill41University of Illinois at Urbana-Champaign, 2NASA Ames, 3Michigan State University, 4NCAR
*Email: [email protected]
Land Use Change Due to Different Human ActivitiesLAI
ISAM Land Surface Model and ResultsISAM Land Surface Model
Calculate fluxes of carbon, nitrogen,energy, water, and the dynamicalprocesses that alter these fluxes21 Biome types 0.5 x 0.5 degree resolution30 minutes temporal scaleSeason-to-interannual variability (penology)
References:Jain and Yang (2005, GBC)Jain et al. (2005, GRL)Jain et al. (2006, JGR)Jain et al. (2009, GBC)Yang et al (2009, GBC)Yang et al.(2010, Biogeoscience)
ISAM Model Estimated GPP vs. MODIS Data Comparison of (a) ISAMestimated annual GPPaveraged for the timeperiod 2000-2006 with(b) MODIS GPP. MODISGPP figure (b) is directlydownloaded from theMODIS data website
(a) (b)
ISAM Model Estimated C & N2O Emissions due to LCLUC ISAM estimated (a) Cemissions (Unit:gC/m2/yr), (b) N2Oemissions (Unit: kgN/ha/yr) from LCLUCs inthe 2005. Positive valuesrepresent net C/Nrelease to theatmosphere and negativevalues represent net C/Nstorage in the terrestrialbiosphere
(a) (b)
Linking Socio-Economic and Biophysical Systems
PET Model IPCC A2 LU Scenario Development:Computable General Equilibrium model9 world regions5 economic sectors
Input• A2 ;and use input assumptions - IIASA• Economic & land data - GTAP• Energy data - IEA
PET-ISAM IPCC A2 Scenario Results
Cropland Area (ha) in 2050 Pastureland Area (ha) in 2050 Secondary Forest Area (ha) in 2050
Acknowledgements
LAI LAI
Peak LAI Averaged for the Winter Months (Dec., Jan., Feb)
Peak LAI Averaged for the Summer Months (Jun., Jul., Aug)
Monthly climatological (2003-2008) LAI values for monsoon Asia region are estimated using aradiative transfer model. The input to the model are 250 m MODIS surface reflectancedata, 250 m MODIS resampled LC data. All the data and modeling simulations are performedusing the TOPS modeling framework on NASA’s Earth Exchange (NEX) platform.
Remotely sensed LCLU data for Indiaregion at 56 m resolution (2004-2005)based on Indian satellite IRS-P6 (AWiFS)(Courtesy: P.S. Roy, ISRO) .
Remotely sensed forest fraction data forSouth East Asia at 30 m resolution (2005)based Landsat satellite.
MODIS LCLU data resampled at 250 meter resolution for the year2005. The land classifications are based on University of Marylandscheme.
(a) Cropland (b) Pastureland
(c) Wood Harvest (d) Urban Land
(e) Secondary Forest
LCLUCs due different human activitiescompiled based on different sources.The data is compiled over the period1765-2005. The data is shown here forthe year 2005 in unit km2. The sourcesfor different data sets are :(a) Cropland - updated based on
Ramankutty, N., and J.A. Foley(1999),
(b) Pastureland - Ramankutty, N., andJ.A. Fole (personal communication),
(c) Wood harvest – Hurtt et al. (2006),(d) Urban land – Goldewijk et al. (2010),(e) Secondary forest – Yang et al.
(2010).
