1. Land Cover and InSAR InSAR Workshop October 21, 2004, Oxnard, CA

2. 2 Land-Cover and Land-Cover Change: What is it? Land Cover: Most of the Earth’s Land- Mass is Covered by Vegetation –Forest and Shrublands (Temperate, Tropical, Woodlands, Semi-desert) –Herbaceous (Grassland, Agriculture, Tundra) –Human Dominated (Urban, Peri-Urban) –Wetland-Coastal Land-Cover Change: Drivers and Consequences –Anthropogenic: Land-Cover Conversion, Urbanization –Natural Hazards: Fire, Wind, Earthquakes, Flooding, Volcanoes, Landslides, Desertification, Insects/Pests –Global climate change

3. 3 Land Cover Considered as Ecosystems is Multi-Dimensional Ecosystem “A topographic unit, a volume of land and air plus organic content that extend areally over a particular part of the Earth’s surface for a certain time.” (Rowe, 1961; Bailey, 1996) Macroclimate Biota Landform Soils Groundwater Bedrock

4. 4 X-band RCS Slicer and GeoSAR Tree Heights Use of Interferometry for Estimationg Vegetation Height When the signal return comes from multiple heights, a unique signature is observed by the interferometer altitude, H baseline, B path length difference,  terrain height, h terrain height hvhv SLICER tree height (blue line) GeoSAR X- minus P-band height (red line) GeoSAR X-band interferometric estimate of tree height (green circles) Comparison between LIDAR and Radar Height Estimates GeoSAR Swath: 10km

5. 5 Multi-baseline Interferometry Provides Vertical Structure of Vegetation Reigber, A., Moreira, A., “First Demonstration of Airborne SAR Tomography Using Multibaseline L-Band Data,” IEEE Trans. Geosci. Rem. Sens., 38(5), 2000.

6. 6 Carbon Cycle and Ecosystems T T 2002 2010201220142015 2004 Reduced uncertainties in fluxes and coastal C dynamics Funded Unfunded Profiles of Ocean Particles New Ocean Carbon / Coastal Event Observations N. America’s carbon budget quantified Global Atmospheric CO 2 (OCO) 2006 2008 Process controls identified; errors in sink reduced NA Carbon Global C Cycle T = Technology development Regional carbon sources/sinks quantified for planet IPCC Effects of tropical deforestation quantified; uncertainties in tropical carbon source reduced = Field Campaign T Goals: Global productivity and land cover change at fine resolution; biomass and carbon fluxes quantified; useful ecological forecasts and improved climate change projections Vegetation 3-D Structure, Biomass, & Disturbance T Terrestrial carbon stocks & species habitat characterized Models w/improved ecosystem functions High-Resolution Atmospheric CO 2 T Carbon export to deep ocean Sub-regional sources/sinks Integrated global analyses CH 4 sources characterized and quantified Report P Vegetation (AVHRR, MODIS) Ocean Color (SeaWiFS, MODIS) Land Cover (Landsat)Land Cover (LDCM)Land Cover (LDCM II) Vegetation, Fire (AVHRR, MODIS) Ocean Color/Vegetation (VIIRS/NPP) Ocean/Land (VIIRS/NPOESS) Models & Computing Capacity Case Studies Process Understanding Improvements: Human-Ecosystems-Climate Interactions (Coupling, Model-Data Fusion, Assimilation) Physiology & Functional Groups Partnership Southern Ocean Carbon Program N. American Carbon Program Land Use Change in Amazonia Global CH 4 ; Wetlands, Flooding & Permafrost Global C Cycle Knowledge Base 2002: Global productivity and land cover resolution coarse; Large uncertainties in biomass, fluxes, disturbance, and coastal events Systematic Observations

7. 7 MULTI-DIMENSIONAL FORESTED ECOSYSTEM STRUCTURE: REQUIREMENTS FOR REMOTE SENSING OBSERVATIONS Final Report of the NASA Workshop, June 26-28, 2003, Annapolis Maryland Kathleen Bergen, Robert Knox, Sassan Saatchi, Editors Workshop Organizing Committee Co-chairs Robert Knox, NASA Goddard Space Flight Center Kathleen Bergen, University of Michigan Diane Wickland, NASA Headquarters Committee Craig Dobson, NASA Headquarters/University of Michigan Bill Emanuel, NASA Headquarters/University of Virginia Carolyn Hunsaker, USDA Forest Service Sassan Saatchi, NASA Jet Propulsion Laboratory Hank Shugart, University of Virginia

8. 8 Land-Cover Grand Challenges for InSAR (Breakout 1 Results) 1. 3D Vegetation structure (for habitat, biomass, fire behavior, classification, economic valuation, windfall, and more) 2. Change detection over time. a) Detection of landcover disturbance/change, natural hazard assessment & monitoring b) 3D vertical profile change: height (first order), profile change (higher order) 3. Conversion of vegetation height and profile into biomass/carbon (global carbon cycle) 4. Below-canopy topography and mapping of topographic change 5. Characterization of ecophysiology (net primary productivity, moisture conditions of soil and vegetation, vegetation stress/disease)

9. 9 Existing Sensors/Data Airborne –AIRSAR –GeoSAR Shuttle-borne –SIR-C –SRTM c-band x-band Space-borne –Envisat –Radarsat Utility –Answer specific but limited science questions; Confirm desired InSAR parameters –C-band has some utility to vegetation science Limitations –Airborne and Shuttle: limited spatio-temporal coverage Data may have limited or difficult access –Spaceborne: repeat-pass C-band has limitations in vegetation capabilities due to temporal decorrelation

10. 10 Near-Term Sensors/Data ALOS-PALSAR –L-band pol UAV SAR –airborne –L-band pol –interferometric Utility –PALSAR good experimental platform –good parameters –could contribute to change detection –UAV L-band SAR will do repeat pass and can be used to study temporal decorrelation and vegetation structure Limitations –ALOS-PALSAR has long repeat causing large temporal decorrelation –UAV somewhat limited coverage/access

11. 11 Potential L-HH InSAR Mission L-band InSAR has strong capabilities in the area of land-cover and land-cover change Zero Baseline L-HH InSAR –Can be used for temporal decorrelation –Yet to be developed empirical models may be related to vegetation characteristics Non-Zero Baselines L-HH InSAR (km scale equatorial separation), –Provides topographic map (useful for both vegetation structure and permanent scatterer deformation measurement) –Correlation signature related to vegetation structure –1 to 4 (optimal) occurrences per year useful – Repeat period that minimizes temporal decorrelation is desirable (useful for both vegetation and deformation)

12. 12 Augmentation of L-HH InSAR Mission (in ascending cost order) Bandwidth (from 15 Mhz to 80Mhz) –Better spatial resolution (current 100 m is useful, 15-30 also would be good) Polarization - polarimetric capability –Pol InSAR - improved vertical structure accuracy & land- cover type discrimination Dual frequency –Add X-band to the L-band –Provides two height estimates that can be used to expand observation Single pass formation flying –Two identical L-HH sensors (solves the temporal decorrelation and choice of baseline/s issues) –Possible to implement multi-baseline interferometry for 3- D structure mapping

13. 13 Long-Term InSAR Mission Strategies “Wish-list” Vegetation 4D Structure Observatory –with parameters and spatial and temporal resolutions ideal for vegetation structure and biomass –fusion of InSAR (wide-swath 4D structure) –multifrequency –polarimetric –multibaseline Lidar (small-swath, sampling, profiles) Hyperspectral (canopy chemistry) Improved Data Access Improved education and training

14. 14 Land-Cover Group Conclusions Land-Cover & Vegetation InSAR needs are converging with Solid Earth Science Strong interest in: 3D Vegetation Structure, Disturbance/Natural Hazards, Biomass/Carbon, Topography, Ecophysiology/moisture stress L-HH InSAR orbiting sensor would be significant step forward in InSAR capabilities for land-cover and vegetation structure; enthusiastic participants! –Additional considerations primary: encourage flexibility in incorporating non-zero baseline opportunities secondary: have identified list of potential enhancements Long-term Mission includes fusion of –InSAR - height, biomass, structure over swaths –Lidar - high resolution profiles –Hyperspectral - canopy chemistry

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16. 16 Annapolis Vegetation Structure Workshop 50% Ecological Science Community –academic, agency, and other scientists funded by NASA, NSF, USDA USFS, Conservation & Science Non-profit 50% Technological Science Community –NASA HQ and Science Centers, academic –Canadian and European Scientists & Science Centers Results Indicated Very Strong interest in: –Biomass/Carbon, Ingesting 3-D data into Ecological Models, Biodiversity and Habitat Management, Disturbance –Vegetation Height & Vegetation Profiles, Biomass at several scales –Imaging SAR, InSAR and fusing of SAR-lidar- hyperspectral