Doctor of Philosophy / Department of Geography / John A. Harrington Jr / The Senegal River valley and delta (SRVD) are affected by long term climate variability.
Indicators of these climatic shifts include a rainfall deficit, warmer temperatures, sea level rise,
floods, and drought. These shifts have led to environmental degradation, water deficits, and
profound effects on human life and activities in the area. Geographic Information Science
(GIScience), including satellite-based remote sensing methods offer several advantages over
conventional ground-based methods used to map and monitor salt-affected soil (SAS) features.
This study was designed to assess the accuracy of information on soil salinization extracted from
Landsat satellite imagery. Would available imagery and GIScience data analysis enable an
ability to discriminate natural soil salinization from soil sodication and provide an ability to
characterize the SAS trend and pattern over 30 years? A set of Landsat MSS (June 1973 and
September 1979), Landsat TM (November 1987, April 1994 and November 1999) and ETM+
(May 2001 and March 2003) images have been used to map and monitor salt impacted soil
distribution. Supervised classification, unsupervised classification and post-classification change
detection methods were used. Supervised classifications of May 2001 and March 2003 images
were made in conjunction field data characterizing soil surface chemical characteristics that
included exchange sodium percentage (ESP), cation exchange capacity (CEC) and the electrical
conductivity (EC). With this supervised information extraction method, the distribution of three
different types of SAS (saline, saline-sodic, and sodic) was mapped with an accuracy of 91.07%
for 2001 image and 73.21% for 2003 image. Change detection results confirmed a decreasing
trend in non-saline and saline soil and an increase in saline-sodic and sodic soil. All seven
Landsat images were subjected to the unsupervised classification method which resulted in maps
that separate SAS according to their degree of salinity. The spatial distribution of sodic and
saline-sodic soils has a strong relationship with the area of irrigated rice crop management. This
study documented that human-induced salinization is progressively replacing natural salinization
in the SRVD. These pedologic parameters obtained using GIScience remote sensing techniques
can be used as a scientific tool for sustainable management and to assist with the implementation
of environmental policy.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/2354 |
| Date | January 1900 |
| Creators | Ndiaye, Ramatoulaye |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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