Name
Abstract | ||
|---|---|---|
Multiple scattering within a mixed pixel results in a nonlinear effect on the measured spectra in remotely sensed imagery. This study provides a quantitative assessment of multiple scattering in the reflectance of semiarid shrublands and explores its relationship to the characteristics of shrubs (density and height) and imaging parameters (wavelength and viewing angles). Field measurements were conducted at the southern fringe of the Otindag Sandy Land in China. A Monte Carlo ray tracing model, the Forest LIGHT interaction model (FLIGHT), was applied to simulate the multiple scattering results. FLIGHT simulation results were first evaluated against field measurements and then compared with a Landsat-8 OLI image. Results show that: 1) the contribution of multiple scattering to the spectra of a scene increases linearly with the fractional cover of vegetation and crown height; 2) in general, multiple scattering has a stronger effect on the near-infrared (NIR) domain than on the visible bands; 3) shadows significantly strengthen the multiple scattering effect, specifically within the visible bands; and 4) 80 to 100% of the total multiple scattering is caused by the second-order scattering within the visible bands and 60% to 90% within the NIR band. This study helps to improve our understanding of the multiple scattering effect and to select between linear and nonlinear spectral unmixing models to solve the abundances of shrubs and soil in mixed pixels. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TGRS.2015.2413409 | Geoscience and Remote Sensing, IEEE Transactions |
Keywords | Field | DocType |
multiple scattering effect,nonlinear spectral mixture analysis (nsma),spectral unmixing,the forest light interaction model (flight) | Shrubland,Remote sensing,Scattering,Reflectivity,Mathematics | Journal |
Volume | Issue | ISSN |
PP | 99 | 0196-2892 |
Citations | PageRank | References |
3 | 0.48 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianmin Wang | 1 | 12 | 1.65 |
| Xin Cao | 2 | 19 | 4.62 |
| Jin Chen | 3 | 259 | 31.87 |
| Xiuping Jia | 4 | 1424 | 126.54 |