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Foliage Clumping Index Over China's Landmass Retrieved From the MODIS BRDF Parameters Product.
- Source :
-
IEEE Transactions on Geoscience & Remote Sensing . Jun2012, Vol. 50 Issue 6, p2122-2137. 16p. - Publication Year :
- 2012
-
Abstract
- The three-dimentional plant canopy architecture is often characterized using the foliage clumping index useful for ecological and land surface modeling. In this paper, an algorithm is developed to retrieve the foliage clumping index with the Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (BRDF) parameter product (MCD43A1), which is generated using the RossThick-LiSparse Reciprocal (Ross-Li) model. First, the Ross-Li model is modified to improve the simulation of the reflectance at hotspot using the Polarization and Directionality of Earth Reflectance measurements as benchmarks to determine BRDF parameters. Then, the modified model (Ross-Li-H) is used to simulate the reflectance at hotspot and darkspot, which is used to calculate the normalized difference between hotspot and darkspot (NDHD). With the relationship between clumping index and NDHD simulated by the 4-Scale geometrical model, the clumping index over China's landmass at 500-m resolution is retrieved every 8 days during the period from 2003 to 2008. Finally, The effect of topography on the retrieved clumping index is corrected using a topographic compensation function calculated from the digital elevation model at 90-m resolution. The topographically corrected clumping index values correlate well with field measurements at five sites over China, indicating the feasibility of the algorithm for retrieving the clumping index from the MCD43A1 product. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 50
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 101186171
- Full Text :
- https://doi.org/10.1109/TGRS.2011.2172213