title: Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments.
abstract: Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange.
authors.affiliation: Natural Resource Research Center, 2150 Centre Avenue, Building A, Room 368, Fort Collins, CO 80526, USA. nnikolov@fs.fed.us
authors.forename: Ned
authors.initials: N
authors.lastname: Nikolov
authors.forename: Karl
authors.initials: K
authors.lastname: Zeller
mesh_terms: D000465:Algorithms; D018533:Biomass; D017753:Ecosystem; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D004787:Environmental Pollution / Q000032:analysis* / Q000706:statistics & numerical data; D008962:Models, Theoretical; D018515:Plant Leaves; D017215:Satellite Communications; D012542:Scattering, Radiation; D013057:Spectrum Analysis / Q000379:methods; D014197:Trees