Land Cover and InSAR : Land Cover and InSAR InSAR Workshop
October 21, 2004, Oxnard, CA
Land-Cover and Land-Cover Change: What is it? : 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
Land Cover Considered as Ecosystems is Multi-Dimensional : 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
Slide4 : Use of Interferometry for Estimationg Vegetation Height When the signal return comes from multiple heights, a unique signature is observed by the interferometer terrain height hv • 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
Multi-baseline Interferometry Provides Vertical Structure of Vegetation : 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.
Slide6 : Carbon Cycle and Ecosystems T T 2002 2010 2012 2014 2015 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 CO2 (OCO) 2006 2008 Process controls identified; errors in sink reduced NA Carbon NA Carbon Global C Cycle T = Technology development Regional carbon sources/sinks quantified for planet IPCC 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 CO2 T Carbon export to deep ocean Sub-regional sources/sinks Integrated global analyses CH4 sources characterized and quantified 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 CH4; 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
Slide7 : 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
Land-Cover Grand Challenges for InSAR (Breakout 1 Results) : 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)
Existing Sensors/Data : 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
Near-Term Sensors/Data : 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
Potential L-HH InSAR Mission : 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)
Augmentation of L-HH InSAR Mission (in ascending cost order) : 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
Long-Term InSAR Mission Strategies “Wish-list” : 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
Land-Cover Group Conclusions : 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
Annapolis Vegetation Structure Workshop : 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