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Remote Sensing and carbon cycle

Remote Sensing and carbon cycle . Zhouxin Xi GEOG 8901 11/5/2012. Outline. Introduction of carbon cycle and eco-system process models What the remote sensing can do? Two case studies Some issues.

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Remote Sensing and carbon cycle

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  1. Remote Sensing and carbon cycle Zhouxin Xi GEOG 8901 11/5/2012

  2. Outline • Introduction of carbon cycle and eco-system process models • What the remote sensing can do? • Two case studies • Some issues David P. Turner, Scott S. Ollinger, and John S. Kimball.2004. Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle. BioScience 54(6).

  3. Carbon cycle wiki

  4. Ecosystem models & Global climate Katharine Hayhoe, Bruce Jones, and John Gross, 2010.

  5. Indicators • Net ecosystem production (NEP) • Net primary production (NPP) Carbon cycle process rates

  6. Some of the ecosystem models Requirements of the United Nations Framework Convention on Climate Change

  7. Jonathan A. Foley et al.,1996

  8. What the remote sensing can do? • Land cover • spectral, spatial, temporal • Forest stand age class • Mid-infrared wavelengths • Differences in red and near-infrared reflectances • Leaf area index • MODIS(250 m) or other optical imagery • Airborne lidar (light detecting and ranging) sensors • The relationship to the field-measured LAI (LAI-2200 Plant Canopy Analyzer, Hemispherical photography, etc.) • Foliar nitrogen • hyperspectraldata (e.g., the space-based Hyperion instrument) • Biomass • Optical remote sensing (statistical regression models) • Active microwaves (Synthetic aperture radar [SAR]) • Canopy height • Lidarand InSAR sensors

  9. Case Study : Northeastern US (I) • Region: Greater Northeast • PnET forest ecosystem model (e.g.,Aber et al. 1995, Ollinger et al. 1998) • Classification map from the AVHRR (Advanced Very High Resolution Radiometer) imagery (1km) • Station data (Coverages for climate, radiation, and atmospheric nitrogen deposition) • Digital terrain model (1km)

  10. Case Study : Northeastern US (I) Controlling factors for NPP in deciduous & evergreen forests different

  11. Case Study : Northeastern US (II) • Smaller landscape surrounding the Bartlett Experimental Forest (BEF) in northern New Hampshire • PnET model was run at 18-m spatial resolution using AVIRIS-derived canopy nitrogen inputs

  12. Case Study : Northeastern US (II) R2: 0.74 Scale & location matter! Upscale to 5 by 5 km Variation in productivity was most impacted by foliar nitrogen Not climate variable!

  13. Case Study:Boreal Ecosystem-Atmosphere Study • Data: • Biophysical and meteorological measurements, including tower-based eddy covariance measurement • Satellite-based active and passive microwave remote sensing • long-term simulations of stand carbon exchange • Method: Multiple ecological models for the temporal and spatial extrapolation of forest biomass,productivity,andnet carbon exchange.

  14. The date: interval during which thaw occurred. Case Study:Boreal Ecosystem-Atmosphere Study Figure 3. Satellite remote sensing (left) of the 1997 primary spring thaw event for the BOREAS study region, Graph(right) shows the relationship between measurements of aboveground NPP for different forest types and corresponding estimates of snowpack depletion.

  15. Boreal Ecosystem-Atmosphere Study • Three problems • Optical remote sensing • The role of disturbance (e.g., fire, land management, insects) • Subgrid-scale land-cover heterogeneity

  16. Some of the ecosystem models

  17. Remote Sensing research issues • Algorithm development - integration? • Scale dependence: comparison patterns or process between different scales • Fine temporal? • Structural properties vs bio-chemical variables • Validating: coarse spatial resolutions?

  18. Thank you!

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