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Title: The MODIS (Collection V005) BRDF/albedo product: Assessment of spatial representativeness over forested landscapes

Journal Article · · Remote Sensing of Environment
 [1];  [2];  [2];  [2];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [8];  [9];  [10];  [11];  [11];  [10];  [11]
  1. NASA Goddard Space Flight Center
  2. Boston University
  3. Complex Systems Research Center, Durham, NH
  4. Ohio State University, The, Columbus
  5. Pennsylvania State University
  6. Indiana University
  7. University of California, Irvine
  8. ORNL
  9. NOAA, Oak Ridge, TN
  10. NOAA
  11. Harvard University

A new methodology for establishing the spatial representativeness of tower albedo measurements that are routinely used in validation of satellite retrievals from global land surface albedo and reflectance anisotropy products is presented. This method brings together knowledge of the intrinsic biophysical properties of a measurement site, and the surrounding landscape to produce a number of geostatistical attributes that describe the overall variability, spatial extent, strength of the spatial correlation, and spatial structure of surface albedo patterns at separate seasonal periods throughout the year. Variogram functions extracted from Enhanced Thematic Mapper Plus (ETM+) retrievals of surface albedo using multiple spatial and temporal thresholds were used to assess the degree to which a given point (tower) measurement is able to capture the intrinsic variability of the immediate landscape extending to a satellite pixel. A validation scheme was implemented over a wide range of forested landscapes, looking at both deciduous and coniferous sites, from tropical to boreal ecosystems. The experiment focused on comparisons between tower measurements of surface albedo acquired at local solar noon and matching retrievals from the MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V005) Bidirectional Reflectance Distribution Function (BRDF)/albedo algorithm. Assessments over a select group of field stations with comparable landscape features and daily retrieval scenarios further demonstrate the ability of this technique to identify measurement sites that contain the intrinsic spatial and seasonal features of surface albedo over sufficiently large enough footprints for use in modeling and remote sensing studies. This approach, therefore, improves our understanding of product uncertainty both in terms of the representativeness of the field data and its relationship to the larger satellite pixel.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge National Environmental Research Park
Sponsoring Organization:
USDOE
DOE Contract Number:
DE-AC05-00OR22725
OSTI ID:
1015714
Journal Information:
Remote Sensing of Environment, Vol. 113, Issue 11; ISSN 0034-4257
Country of Publication:
United States
Language:
English