Land Cover and InSAR

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

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. Land Cover Considered as Ecosystems is Multi-Dimensional Macroclimate Biota Landform Soils Groundwater Bedrock 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)

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

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. Integrated global analyses Report Carbon Cycle and Ecosystems Human-Ecosystems-Climate Interactions (Coupling, Model-Data Fusion, Assimilation) Sub-regional sources/sinks Funded T High-Resolution Atmospheric CO2 Unfunded Carbon export to deep ocean T Profiles of Ocean Particles Partnership Models w/improved ecosystem functions T= Technology development Physiology & Functional Groups T Process controls identified; errors in sink reduced Southern Ocean Carbon Program = Field Campaign T New Ocean Carbon / Coastal Event Observations Reduced uncertainties in fluxes and coastal C dynamics Goals: Global productivity and land cover change at fine resolution; biomass and carbon fluxes quantified; useful ecological forecasts and improved climate change projections T Vegetation 3-D Structure, Biomass, & Disturbance Terrestrial carbon stocks & species habitat characterized Global CH4;Wetlands, Flooding & Permafrost CH4 sources characterized and quantified Knowledge Base Global Atmospheric CO2 (OCO) Regional carbon sources/sinks quantified for planet N. American Carbon Program N. America’s carbon budget quantified Land Use Change in Amazonia Effects of tropical deforestation quantified; uncertainties in tropical carbon source reduced 2002: Global productivity and land cover resolution coarse; Large uncertainties in biomass, fluxes, disturbance, and coastal events Models & Computing Capacity Process Understanding Case Studies Improvements: P Land Cover (Landsat) Land Cover (LDCM) Land Cover (LDCM II) Systematic Observations Ocean Color (SeaWiFS, MODIS) Ocean Color/Vegetation (VIIRS/NPP) Ocean/Land (VIIRS/NPOESS) Vegetation (AVHRR, MODIS) Vegetation, Fire (AVHRR, MODIS) IPCC IPCC 2008 2010 2012 2014 2015 2002 2004 2006 Global C Cycle Global C Cycle NA Carbon NA Carbon

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. 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. 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 Existing Sensors/Data

10. 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 Near-Term Sensors/Data

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. 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. 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. 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

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