Hamid reza Matin far; Kazem Alavi panah; Ammar Rafiei Emam
Volume 16, Issue 4 , January 2010, , Pages 560-573
Abstract
One of the apparent characteristics of soil is color which shows high correlation with soil characteristics and spectral reflectance. Soil color is identified using visual comparison of sample and colored chips of Munsell color charts .In arid regions due to the prolonged sunny days, low soil moisture, ...
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One of the apparent characteristics of soil is color which shows high correlation with soil characteristics and spectral reflectance. Soil color is identified using visual comparison of sample and colored chips of Munsell color charts .In arid regions due to the prolonged sunny days, low soil moisture, sparse vegetation cover and close relation between land units and soils, there is an ideal condition for application of remote sensing data especially for study of relation between satellite data and color of surface features. The soil color and the most effective factors on color and spectral reflectance of soil are explained in brief. Color composite images produced from TM7, TM4 and TM2 as red, green and blue respectively used in order to choose sample sites. The 20 sample sites were chosen based on resample 3×3 pixels (90×90 m). In each site, the soil surface conditions and the munsell color of the soil surface were investigated in the field. Some physico-chemical properties of soil samples were also determined in the laboratory. The results of this study indicates that munsell notation of hue, value and Chroma are significantly correlated to the visible bands of Landsat (TM) data. From this study it may be concluded that visible reflectance of Landsat can be used to estimate soil color, if very precise result is not expected .More investigation are necessary in order to improve the obtained results.
Hamid reza Matinfar; Frydoon Sarmadian; Syed Kazem Alavi panah; Rechard Heck
Volume 14, Issue 4 , February 2008, , Pages 589-602
Abstract
Remotely sensed data has high potential for characterizing land use/cover types. Traditionally, most of remote sensing image classification techniques are based on pixel-based procedures. In contrast to pixel-based procedure, image objects can carry more attributes than only spectral information. ...
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Remotely sensed data has high potential for characterizing land use/cover types. Traditionally, most of remote sensing image classification techniques are based on pixel-based procedures. In contrast to pixel-based procedure, image objects can carry more attributes than only spectral information. Object-based processing not only considers contextual information but also information about the shape of and the spatial relation between the image region .In this paper, we address the concepts of object-based image processing and presents an approach that integrates the concepts of object-based processing into the image classification and land use land cover type determination. The scheme proposed in this study is applied to classification of Landsat7 (ETM+) data of Kasha area. This study shows the applicapability of object-based approach for classification of Landsat7 (ETM+) data as well as show high overall accuracy (95%)of land use/land cover map. From the obtained results, we concluded that the main land cover types of the arid region could be discriminated with a high level of accuracy by object oriented approach