Evaluation of Synergies between VNIR-SWIR and TIR imagery in a Mediterranean-climate Ecosystem • Dar A. Roberts 1 , Keely Roth 1 , Michael Alonzo 1 • Contributors: Dale A. Quattrochi 2 , Glynn C. Hulley 3 , Simon J. Hook 3 , and Robert O. Green 3 • 1 UC Santa Barbara Dept. of Geography • 2 NASA Marshall Space Flight Center • 3 NASA Jet Propulsion Laboratory NASA HyspIRI Preparatory Program
21
Embed
Evaluation of Synergies between VNIR- SWIR and TIR imagery in a Mediterranean- climate Ecosystem Dar A. Roberts 1, Keely Roth 1, Michael Alonzo 1 Contributors:
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Evaluation of Synergies between VNIR-SWIR and TIR imagery in a Mediterranean-
climate Ecosystem
• Dar A. Roberts1, Keely Roth1, Michael Alonzo1
• Contributors: Dale A. Quattrochi2, Glynn C. Hulley3, Simon J. Hook3, and Robert O. Green3
• 1 UC Santa Barbara Dept. of Geography
• 2 NASA Marshall Space Flight Center
• 3 NASA Jet Propulsion Laboratory
NASA HyspIRI Preparatory Program
Research Questions
• What is the potential for improved temperature emissivity separation (TES) using VNIR-SWIR column water vapor?
• What is the relationship between moisture content and emissivity?
• What is the relationship between common hyperspectral measures of plant stress and physiological function (i.e., PRI, leaf water content) and canopy temperature in imagery and observed in ground-based measurements?
• How does canopy temperature vary as a function of plant functional type (PFT) and species at native and HyspIRI spatial scales?
• How is canopy temperature and emissivity impacted by changes in canopy cover, notably changes in green vegetation (GV) fraction, non-photosynthetic vegetation (NPV) and bare soil? How is temperature partitioned among the various components of cover?
General Approach• AVIRIS Analysis
– Reflectance Retrieval with 7.5, 15 and 60 m radiance data• Reflectance, retrieval products (water vapor, liquid water)
– Fused field and AVIRIS-derived spectral library (7.5 m)
– Iterative Endmember Selection, cover class (i.e., bark, composite shingle, oak), species
– Multi-level fusion (2, 3, 4 em models, selected based on an RMS threshold)
– AVIRIS water content, hyperspectral stress indices (PRI)
• MASTER Analysis– Atmospheric correction
• Modtran simulated, AVIRIS column water vapor
– Temperature Emissivity Separation (TES): • TES, using ASTER algorithm (Gillespie et al.)
• Combined analysis of image pairs
• Full spectral analysis (VSWIR-TIR) of plant materials seasonally
Santa Barbara Study Site
• Pre-fire– August 6, 2004 (16 m)– August 6-12, 2007 (4 m): urban– June 19, 2008: AVIRIS-MASTER Pair
• Post-fire– March 10, 2009 (post Gap & Tea, pre-Jesusita)– March 31, 2009 (post Gap & Tea, pre-Jesusita)– May 8, 2009 (Active Jesusita)– June 17, 2009– August 26, 2009– April 30, 2010– October 26, Nov 1, 2010– July 19, 2011: AVIRIS-MASTER Pair
True Color: August 6, 2004
AVIRIS Species and Plant Functional Types
• Existing, accurate maps of species, PFT generated using MESMA and Iterative Endmember Selection
• Existing network of species polygons
• Existing reference spectral library of natural and anthropogenic materials
Synergies between VNIR-SWIR and TIR in an urban Environment: RSE, in press
• Mixed urban-natural systems, ~ 150,000 people
• AVIRIS-MASTER pair, June 19, 2008– 7.5 m AVIRIS, 15 m MASTER
– Spatial degradation, 15 m AVIRIS, 60 m AVIRIS/MASTER
Methods• Preprocessing
– AVIRIS-MASTER georectified to high resolution DOQQ
• AVIRIS Analysis– ACORN 5, applied to 7.5, 15 and 60 m radiance data
• Reflectance, water vapor, liquid water, albedo (Modo 4.3 Irradiance)
– Surface Composition• VIS Model (Vegetation, Impervious, Soil expanded to include NPV)
• Multiple Endmember Spectral Mixture Analysis– Fused field and AVIRIS-derived spectral library (7.5 m)