Soil Salinity Mapping Using Satellite Remote Sensing: A Case Study Of Lower Chenab Canal System

Muhammad Mohsin Waqas (), Yasir Niaz, Sikandar Ali, Ishfaq Ahmad, Haroon Rashid and Usman Khalid Awan
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Muhammad Mohsin Waqas: Department of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan
Yasir Niaz: Department of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan
Sikandar Ali: Department of Irrigation and Drainage, University of Agriculture, Faisalabad
Ishfaq Ahmad: Centre for Climate Research and Development, COMSAT, IslamabadAuthor-Name: Muhammad Fahad
Haroon Rashid: Department of Structures & Environmental Engineering, University of Agriculture Faisalabad
Usman Khalid Awan: International Centre of Agriculture Research in Dryland Areas, Islamabad

Earth Sciences Pakistan (ESP), 2020, vol. 4, issue 1, 7-9

Abstract: Salinity is the most important factor of consideration for the water management policies. The water availability from the rootzone reduced with the increase in the soil salinity due to the increase in the osmatic pressure. In Pakistan, salinity is the major threat to the agriculture land due to the tradition practices of irrigation and extensive utilization of the groundwater to meet the cope the irrigation water requirement of high intensity cropping system. The salinity impact is spatially variable on the canal commands area of the irrigation system. There is dire need to map the spatially distributed soil salinity with the high resolution. Landsat satellite imagery provides an opportunity to have 30m pixel information in seven spectral wavelength ranges. In this study, the soil salinity mapping was performed using pixel information on visible and infrared bands for 2015. These bands were also used to infer Normalized Difference Vegetation Index (NDVI). The raw digital numbers were converted into soil salinity information. The accuracy assessment was carried out using ground trothing information obtained using the error matrix method. Four major classes of non-saline, marginal saline, moderate saline and strongly, saline area was mapped. The overall accuracy of the classified map was found 83%. These maps can be helpful to delineate hot spots with severe problem of soil salinity in order to prepare reciprocate measures for improvement.

Keywords: Landsat; NDVI; Soil Salinity; LCC System (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnesp:v:4:y:2020:i:1:p:7-9

DOI: 10.26480/esp.01.2020.07.09

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