Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data
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- 作者：Md. Manjur Morshed ; Md. Tazmul Islam…
- 关键词：Salinity indices ; Regression ; Landsat image ; Remote sensing ; Bangladesh
- 刊名：Environmental Monitoring and Assessment
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：188
- 期：2
- 全文大小：1,369 KB
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Md. Tazmul Islam (1)
Raihan Jamil (1)
1. Department of Urban and Regional Planning, Khulna University of Engineering & Technology, LE-303, Khulna, 9203, Bangladesh - 刊物类别：Earth and Environmental Science
- 刊物主题：Environment
Monitoring, Environmental Analysis and Environmental Ecotoxicology
Ecology
Atmospheric Protection, Air Quality Control and Air Pollution
Environmental Management - 出版者：Springer Netherlands
- ISSN：1573-2959
文摘
This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R 2 value, low P value, and low Akaike’s Information Criterion. About 20 % variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.