Name
Abstract | ||
|---|---|---|
The goal of this study was the quantitative mapping of soil salinity from soil reflectance spectroscopy using airborne and/ or spaceborne optical data. Generally, the reflectance spectra of agricultural lands contain a mixture of information of soil and vegetation. In addition, the spectra observed at the sensor are affected by the atmosphere and the aspect of topography. In this study, we corrected for atmospheric effects using the Second order derivative algorithm (SODA) method, which canceled the effect of the differences due to topography, and removed the effect of vegetation, to obtain pure soil spectra and estimate the degree of soil salinity. The soil salinity estimation map was found to correspond well to the electrical conductivity (EC) values that were used for validation. These validation results show that this method is effective for the estimation of soil salinity regardless of soil color and topography. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | Dryland salinity, Hyperspectral data, Scale-up problem |
Field | DocType | ISSN |
Atmosphere,Soil science,Soil color,Vegetation,Computer science,Remote sensing,Hyperspectral imaging,Reflectance spectroscopy,Reflectivity,Soil salinity | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chiaki Kobayashi | 1 | 2 | 1.70 |
| Ian C. Lau | 2 | 18 | 4.14 |
| buddy wheaton | 3 | 16 | 2.77 |
| Lindsay Bourke | 4 | 0 | 0.34 |
| Satomi Kakuta | 5 | 0 | 0.68 |
| Tetsushi Tachikawa | 6 | 8 | 4.67 |