Trends Analysis of River Bank Erosion at Amu river Using Remote Sensing and Geographic Information System

Name: Abdul Basir Mahmoodzada

ID: – 

Title: Trends Analysis of River Bank Erosion at Amuriver Using Remote 
Sensing and GeographicInformation System

Type: Thesis


The  study  examined the  trend  of river bank  erosion  from 2000-2014,  detected  shoreline change and predicted the rivermigration from  2014-2030 in  Qarqin district.  The study is the  first of  its  kind as  no  previous study  has  been done  before.  In this research, landsat images  and very  high  resolution (IKONOS,  Quickbird  and Pleiades)  images  were used.. The image classification was done from 2000-2014.  Remote Sensing and Geographic Information  system  applications were  used  to categorize  eroded  area and  identify shorelines change locations.  Furthermore,liner extrapolation technique was employed to predict river movement from 2014to 2030 at five year intervals. The study found that the river movement wastoward Afghanistan side i.e., south.  The land lost from 2000 – 2014 was estimated at 5074 hectares in total. It was calculated as 1984 hectares from 2005 – 2010 a major increase noticed from other periods which were 1410 hectares from 2000-2015 and 1680 hectares from 2010-2014.  The shoreline was demarcated and categorizedinto three zones i.e., lower as moderate eroded zone, central as high erodedzone and upper as lower eroded zone. The predicted land lose from 2014-2030 was calculated 6160 hectares due  to  river migration  toward  Afghanistan side  primarily  because of  lack  of proper management.  The study willbe useful to government agencies responsible for river bank erosion managementin taking decisions. Based on trend analysis and shoreline migration, the  study has  concluded  that eroded  area  by river  and  those were  calculated  from the historical  data,  for the  better  understand shoreline  changes  and projected  future  river locations.  

Keywords:   Amu River,River, Bank Erosion,
Shoreline change, River prediction.

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