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Use of Digital Analysis and GIS in Identification of Soil MapUunits of West Makhool Area of Salahddin Province | ||
| Journal of Tikrit University For Agriculture Sciences | ||
| Article 1, Volume 12, Issue 1, 2012, Pages 147-165 | ||
| Author | ||
| Ammar S. Ismaeel | ||
| Abstract | ||
| Abstract : This study was posed to understand the ability of remote sensing technology and GIS as a tool to inhance soil survey operations throughout identification of soil map units . Three space images taken by Thematic Mapper sensor (TM) of Landsat 7 as well as geological , topographic, and soil survey map were used as reference data . Erdas 8.6 arc GIS 9.2. were used as softwares . Spectral bands of highest coefficent of variation (c.v) were selected to be used for identification of band surface variation of the study area . Digital analysis of space images was carried out and supervised and unsupervised classification were also performed for the study area. Results of remote sensing indicated that selected spectral bands 2,3 and 7 of image taken during the year 2000 and bands 3,5, and 7 of images taken during the year 2007 represent the best combination to be used in image classification for soil map units identification purposes. However sand dunes and sand sheet units appeared to be distiguished and isolated classes where as salt-affected , calcareous and gypsiferous soils appeared in some cases as distiguished classes and in other cases overlaped . Results also indicated that unsupervised classification consisted of six classes was the best choice for identification of soil map units in this particular area .The unsupervised classification had a high capability of preparing preliminary soil maps , and providing similar classes of those prepared by the 9 – classes supervised classification . Results also indicated that the role of GIS software in map correction is very important throughout over lapping similar features appeared on space image and other maps .In addition, soil map units can be identified and drawn depending on supervised and unsupervised classification methods which may reduce efforts and costs of soil survey operations. Moreover data results can be stored and reused again whenever are needed. | ||
| Keywords | ||
| Digital Analysis; GIS; Salahddin | ||
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