Soil Type Classification Analysis

CLASSIFICATION OF SOIL USING SATELLITE IMAGES

Devaki M1,Girinath R2, Kiruthika R3, BalaGuru C4, Balaji J5 Assistant Professor,Department of ECE, K.S.Rangasamy College of Technology, Tiruchengode,India1,UG Student,Department of ECE, K.S.Rangasamy College of Technology, Tiruchengode,India2,3,4,5.

ABSTRACT Soil type classification using satellite images. The prediction and classificaton of the soil type will be more accurate when compared to conventional techniques. It also provides better result. Soil types are identified by using satellite images. Colour and colour patterns provide indications of mineral and organic content, as well as moisture levels, in soils. Remote sensing techniques are used to estimate soil types

Usually, such work can be done by some software . The software used here is MATLAB. The input of clustering is a colour remote sensing image, a set of pixels each of which represented by RGB value. The output, after the k-means algorithm, is k subsets of pixels, within each subset the pixels have the most similar colour. The k-means clustering is one of the most common methods of data analysis in the field of pattern recognition, image processing etc..

4. Image segmentation Segmentation partitions an image into distinct regions containing each pixels with similar attributes. The segmentation can be done using various methods like Otsu’ method, k-means clustering, converting RGB image into HIS model etc. Image segmentation is typically used to locate objects and boundaries in images. The result of image segmentation is a set of segments that collectively cover the entire image or a set of contours extracted from the image.

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The satellite image of Salem district is collected. The images are preprocessed using image Segmentation. It is the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. It is a useful technique to improve the accuracy of soil and land use mapping based upon the remote sensing data and the LANDSAT data are very suitable for soil mapping. From the colour of sandy loam to clay,we known that it is alluvial soil, black colour it is black soil, red colour it is red soil, reddish brown it is laterite soil, light brown it is mountain soil and yellow for desert soil.

FUTURE WORK This work elaborates the possible classification of soil and a method to identifies the soil type using satellite images using k means clustering algorithm. Mapping process continue with k-means clustering segmentation process. This technique is much better than previously used techniques to find the suitable soil for the fertilization mapped image of study area Salem is shown in figure 2. By using image processing and GIS, we can easily find out the close relationship between the distribution of soils