Ye, R., Niu, R., Jiang, Q., & Sahli, H. (2011). Soil Thickness zonation approach using Landsta ETM+, Geological Maps, DEM data and Field Investigation. In IEEE Int. Geosciences & Remote Sensing Symposium, IGARSS2011 IEEE.

@inproceedings{92d16bbaedf54e13820b91878f9cfec1,
title = "Soil Thickness zonation approach using Landsta ETM+, Geological Maps, DEM data and Field Investigation",
abstract = "Soil thickness is extensively concerned by engineering geology and slope hazards prevention. But it is not available from geological maps and traditional methods to obtain soil thickness information are costly and time consuming, such as drilling and geophysics methods. In this paper, we proposed a method for regional soil thickness zonation based on multi-sources data. Three essential parameters were chosen for soil thickness analysis, include slope, lithology and NDVI which extracted from DEM data, geological maps and Landsat image respectively. In combining the parameters with field survey data, Support Vector Machine was employed for soil thichness classification. Experiment results in the Three Gorges region show the usefulness of the approach.",
keywords = "remote sensing, classification, geoscience, soil thikness",
author = "Runqing Ye and Ruiqing Niu and Qiying Jiang and Hichem Sahli",
year = "2011",
language = "English",
booktitle = "IEEE Int. Geosciences & Remote Sensing Symposium, IGARSS2011",
publisher = "IEEE",
note = "Unknown ; Conference date: 01-01-2011",
}