Application of Satellite Remote Sensing to find Soil Fertilization by using Soil Colour: study area Vellore District, Tamil Nadu, India.

N Suresh Kumar,M Prabu,S Margret Anouncia

doi:10.3991/ijoe.v9i2.2530

Abstract

Nowadays the usage of Remote Sensing and GIS techniques are too vast and many Earth observations had been done by Remote Sensing and GIS techniques. The innovation of this work is to use the LANDSAT image data and GIS Techniques to assess land information and soil classification in the most coming up area of Vellore district and propose the possible fertilization for this study area. Landsat image is classified by minimum distance classification algorithm and according to the reflectance characteristics of the surface material. From the classified data we can find out the best fertilization for the best soil using colour of the soil. It is proved that, within limitations the classification algorithms and threshold parameters have an important influence on the classification result

Highlights

Remote sensing techniques and Geographical Information System (GIS) techniques are used to estimate soil types and its spatial distribution with reasonable costs and much better accuracy in very larger earth spaces
Here we propose novel idea for combining these two vast methodologies to find the soil fertilization for the better cultivation on the study area
This research work describes about the use of Satellite images (LANDSAT data) for the study of soil conditions and the Classifications and preprocessing have an important influence on the classification results

Summary

Introduction

Remote sensing techniques and Geographical Information System (GIS) techniques are used to estimate soil types and its spatial distribution with reasonable costs and much better accuracy in very larger earth spaces. Soil erosions were estimated by remote sensing, geographical information system and. Remote sensing data were used to create the cover management factor image by land cover classifications, while Geographical Information System tools were used for derive the topographic factor from DEM (Data Elevation Model) data RUSLE [1]. Remote sensing methods provided perspective for spatial and instantaneous measurement of soil content. Less amount of water in a soil that emits low amount of microwave radiation. Soil series were calculated by active microwave remote sensing via synthetic aperture radata data. Microwave radiometer widely used for mapping largearea soil types [2]

Methods

Results

Conclusion