Indexing

Assessing Soil surface Salinity with Basic pixel Data Sensor TM

Author: Mohammad Zeinali*, Ali Asghar Jaafarzadeh**, Farzin Shahbazi***, Shahin Oustan*** and Khalil Valizadeh Kamran****

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Abstract

Soil salinity and salinization of lands, as one of the main problems of agriculture, has paramount importance and can be avoided with proper understanding of its progress. This is the first step in identifying areas of salt and salt mapping in these soils. With the development of remote sensing technology and efficient use of satellite imaging, this study compared the salinity maps produced by a variety of classification image algorithms (Maximum likelihood, Minimum distance and Parallelepiped) by Land sat 5 TM satellite data in the East of Khoy. In this study, 269soil samples were analyzed and the results obtained were implemented on TM image. For initial identification, topography maps, ENVI 4.8 software and satellite image processing were used but to increase the accuracy, geometric correction was performed with specific locations using GPS. The results indicate the existence of a correlation between bands 1, 4 and 5TMimage with soil salinity data and classification algorithms, usin

Keywords

Pixel-based, Classification Algorithm, Salinity, TM Sensor, Khoy.

Conclusion

Soil salinity and salinization of lands, as one of the main problems of agriculture, has paramount importance and can be avoided with proper understanding of its progress. This is the first step in identifying areas of salt and salt mapping in these soils. With the development of remote sensing technology and efficient use of satellite imaging, this study compared the salinity maps produced by a variety of classification image algorithms (Maximum likelihood, Minimum distance and Parallelepiped) by Land sat 5 TM satellite data in the East of Khoy. In this study, 269soil samples were analyzed and the results obtained were implemented on TM image. For initial identification, topography maps, ENVI 4.8 software and satellite image processing were used but to increase the accuracy, geometric correction was performed with specific locations using GPS. The results indicate the existence of a correlation between bands 1, 4 and 5TMimage with soil salinity data and classification algorithms, usin

References

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How to cite this article

Mohammad Zeinali*, Ali Asghar Jaafarzadeh, Farzin Shahbazi, Shahin Oustan and Khalil Valizadeh Kamran (2016). Assessing Soil surface Salinity with Basic pixel Data Sensor TM , Biological Forum – An International Journal 8(1): 190-198.