A Synchronous Investigation of Soil Geometric Mean Particle Diameter and Lime, Using Remote Sensing Technology (Case Study: Pol-e-Dokhtar, the Southwest of Lorestan Province, Iran) release_bcts3qboovepzojn5cuzk54sye

by M Danesh, H Bahrami, S Alavipanah, A Noroozi

Released as a article-journal .

2010   Volume 12

Abstract

The geometric mean particle diameter (dg) and lime are two of the most important properties from the viewpoint of soil management. Nowadays remote sensing technology which has emerged walking with science development throughout the world, has made soil study faster, more facile and more cost-efficient. An investigation of soil dg and lime was performed in Pole -Dokhtar area by use of four sets of spectral data of IRS P 6 , LISS III obtained from the Organizations of Geography of Armed Forces and Aerospace of Iran, in September 7 th 2007. Subsequently, Principle Component Analysis, Normalized Difference Vegetation Index, Soil Line Euclidean Distance and Unsupervised Classification was carried out for satellite data sets following image preprocessing operations. Through stratified randomized sampling method and according to the false color composite and photomorphic units of the main image, 95 samples were selected and eventually collected from 0-5cm depth of soil surface, likewise 43 samples from 5-20cm. Afterwards, dg and lime contents were determined for each sampled point in soil laboratory. By means of multivariate regression operations there were eventually shown pronounced relationships (P< 0.01) between soil dg and lime with green (R 2 adj = 0.78) and NIR (R 2 adj = 0.77) bands in the first sampling depth. In addition, this was true for the second sampling depth with green (R 2 adj = 0.57), NIR (R 2 adj = 0.55) and red (R 2 adj = 0.59) bands with lower coefficients of determination. Consequently it has been substantiated with evidence that dg and lime contents are able to impress soil spectral reflectance. So it is possible to find out about these parameters using satellite and ancillary data.
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