Advanced

Land use/ land cover change detection and quantification : a case study in eastern Sudan

Arfat, Yasar (2010) In Lunds universitets Naturgeografiska institution - Seminarieuppsatser
Dept of Physical Geography and Ecosystem Science
Abstract
Remote sensing with high temporal resolution images has become a very strong tool
for monitoring the Land use/Land cover (LULC) changes. Sudan has long been
experiencing intense LULC changes. These LULC changes have resulted in
widespread land degradation. The conversion of natural woodland and forest is still
the main source for agricultural expansion in Sudan. Rainfed mechanized farming
(RMF) is not new in Sudan, it started in the early 1940s near Gadarif state the eastern
Sudan. The current study examines the temporal and spatial extent of LULC changes
from 1972 to 2006 in Gadarif state. This area is famous for its sorghum and sesame
production. A periori defined seven LULC classes in the classification scheme were
water... (More)
Remote sensing with high temporal resolution images has become a very strong tool
for monitoring the Land use/Land cover (LULC) changes. Sudan has long been
experiencing intense LULC changes. These LULC changes have resulted in
widespread land degradation. The conversion of natural woodland and forest is still
the main source for agricultural expansion in Sudan. Rainfed mechanized farming
(RMF) is not new in Sudan, it started in the early 1940s near Gadarif state the eastern
Sudan. The current study examines the temporal and spatial extent of LULC changes
from 1972 to 2006 in Gadarif state. This area is famous for its sorghum and sesame
production. A periori defined seven LULC classes in the classification scheme were
water bodies, RMF, mixed rangeland, irrigated land, dense forest, sparse forest and
settlement. Individual classifications were employed using the both supervised and
unsupervised classification. Iterative Self Organizing Data Analysis (ISODATA) was
used to see the cluster of different classes in the images. Maximum likelihood
classifier (MLC) was used in the LULC classification of the individual images. The
accuracy assessment of image classification was checked by aerial photographs and
high resolution images from Google maps. The overall accuracy of LULC maps for
each period (1984 and 2006) range from 86, 88 and kappa statistics are from 0.84 and
0.86 respectively. For change detection post-classification technique was applied.
Image pairs of consecutives dates were compared by overlaying the LULC maps and
cross- tabulating the LULC statistics.
The amount of conversion from sparse forest to mixed range occurred as large as
14247 km2 during the first period (1972-1984) and 1060 km2 during the second period
(1984-2006). The conversions to RM have mainly been occurred from mixed range
land and sparse forest as large as 4063 km2, 4701 km2 during the first period (1972-
1984) and 18743 km2, 5449 km2 respectively during the second period (1984-2006) of
study. Conversions to RMF occurred at high amounts. A total of 29615 km2 area
changed from mixed rangeland and sparse forest to RMF. Settlement area increased in
the second period from 23 km2 to 123 km2. The LULC change study plays an
important role for better understanding of land utilization and sustainable
development of the region. (Less)
Abstract (Swedish)
Fjärranalys har med hjälp av bilder med hög temporär upplösning blivit ett kraftigt
verktyg för att övervaka Land use/Land cover (LULC) förändringar. Sudan har under
lång tid varit utsatt för intensiv Markanvändning/Markytsförändringar (LULC). Dessa
LULC förändringar har resulterat i omfattande land degradering. Omvandlingen av
naturskog och skog är fortfarande den vanligaste orsaken till expansion av jordbruk i
Sudan. Regnbevattnat mekaniserat jordbruk (RMJ) är inte en ny förekomst i Sudan
utan uppkom i början av 1940 vid Gadarif staten i östra Sudan. Denna studie
undersöker den temporära och rumsliga omfattning av LULC förändringar från 1972
till 2006 i Gadarif staten. Detta område är känt för dess hirs och sesam produktion.
En... (More)
Fjärranalys har med hjälp av bilder med hög temporär upplösning blivit ett kraftigt
verktyg för att övervaka Land use/Land cover (LULC) förändringar. Sudan har under
lång tid varit utsatt för intensiv Markanvändning/Markytsförändringar (LULC). Dessa
LULC förändringar har resulterat i omfattande land degradering. Omvandlingen av
naturskog och skog är fortfarande den vanligaste orsaken till expansion av jordbruk i
Sudan. Regnbevattnat mekaniserat jordbruk (RMJ) är inte en ny förekomst i Sudan
utan uppkom i början av 1940 vid Gadarif staten i östra Sudan. Denna studie
undersöker den temporära och rumsliga omfattning av LULC förändringar från 1972
till 2006 i Gadarif staten. Detta område är känt för dess hirs och sesam produktion.
En periori fastställde sju LULC klasser i klassificeringssystemet vilka var följande;
vattenansamlingar, RMF, blandad betesmark, konstbevattnad mark, tät skog, gles
skog och bosättning. Individuell klassificering utnyttjades vid användning av både
övervakad och oövervakad klassificering. Iterative Self Organizing Data Analysis
(ISODATA) användes för att se kluster eller olika klasser i bilderna. Maximum
likelihood classifier (MLC) användes i LULC klassificeringen av de individuella
bilderna. Utvärderingen av noggrannheten vid bild klassificeringen var kontrollerad
med hjälp av flygfoton och bilder med hög upplösning från Google maps. Den
övergripande noggrannheten av LULC kartor för varje period (1984 och 2006)
varierar från 86, 88 och kappa statistik är från 0.84 respektive 0.86. Vid
förändringsupptäckt applicerades post-klassificeringsteknik. Bild par tagna vid ett
senare datum jämfördes med överliggande LULC kartor och cross-tabulating LULC
statistiken.
Omfattningen av konverteringen från gles skog till blandad betesmark förekom på
ytor så stora som 14247 km2 under den första perioden och 1060 km2 under den andra
perioden (1984-2006). Konverteringen av RMJ har i huvudsak skett på blandad
betesmark och gles skog med en areal så stor som 4063 km2 4701 km2 during the first
period (1972- 1984) and 18743 km2, 5449 km2 respectively during the second period
(1984-2006) of study. Konvertering till RMJ inträffade vid höga belopp. Totalt har ett
område på 29615 km2 konverterats från blandad betesmark och gles skog till RMJ.
Bosättningsarealer ökade under den andra perioden från 23 km2 till 123 km2. Studien
på LULC förändringar spelar en viktig roll för en ökad förståelse av markanvändning
och hållbar utveckling i regionen. (Less)
Please use this url to cite or link to this publication:
author
Arfat, Yasar
supervisor
organization
year
type
H2 - Master's Degree (Two Years)
subject
keywords
geography, physical geography, land use/land cover changes, landsat MSS, TM and ETM+, Sudan, Gadarif, remote sensing, ISODATA, maximum likelihood classifier, post classification change detection
publication/series
Lunds universitets Naturgeografiska institution - Seminarieuppsatser
report number
194
language
English
additional info
Imad-eldin A Ali Babiker, PhD
Soil-Water Management Scientist Arid Lands Section, Forestry Research Center
Agricultural Research Corporation (ARC)
Soba-Khartoum, Sudan.
id
2255865
date added to LUP
2011-12-21 11:25:13
date last changed
2011-12-21 11:25:13
@misc{2255865,
  abstract     = {Remote sensing with high temporal resolution images has become a very strong tool
for monitoring the Land use/Land cover (LULC) changes. Sudan has long been
experiencing intense LULC changes. These LULC changes have resulted in
widespread land degradation. The conversion of natural woodland and forest is still
the main source for agricultural expansion in Sudan. Rainfed mechanized farming
(RMF) is not new in Sudan, it started in the early 1940s near Gadarif state the eastern
Sudan. The current study examines the temporal and spatial extent of LULC changes
from 1972 to 2006 in Gadarif state. This area is famous for its sorghum and sesame
production. A periori defined seven LULC classes in the classification scheme were
water bodies, RMF, mixed rangeland, irrigated land, dense forest, sparse forest and
settlement. Individual classifications were employed using the both supervised and
unsupervised classification. Iterative Self Organizing Data Analysis (ISODATA) was
used to see the cluster of different classes in the images. Maximum likelihood
classifier (MLC) was used in the LULC classification of the individual images. The
accuracy assessment of image classification was checked by aerial photographs and
high resolution images from Google maps. The overall accuracy of LULC maps for
each period (1984 and 2006) range from 86, 88 and kappa statistics are from 0.84 and
0.86 respectively. For change detection post-classification technique was applied.
Image pairs of consecutives dates were compared by overlaying the LULC maps and
cross- tabulating the LULC statistics.
The amount of conversion from sparse forest to mixed range occurred as large as
14247 km2 during the first period (1972-1984) and 1060 km2 during the second period
(1984-2006). The conversions to RM have mainly been occurred from mixed range
land and sparse forest as large as 4063 km2, 4701 km2 during the first period (1972-
1984) and 18743 km2, 5449 km2 respectively during the second period (1984-2006) of
study. Conversions to RMF occurred at high amounts. A total of 29615 km2 area
changed from mixed rangeland and sparse forest to RMF. Settlement area increased in
the second period from 23 km2 to 123 km2. The LULC change study plays an
important role for better understanding of land utilization and sustainable
development of the region.},
  author       = {Arfat, Yasar},
  keyword      = {geography,physical geography,land use/land cover changes,landsat MSS,TM and ETM+,Sudan,Gadarif,remote sensing,ISODATA,maximum likelihood classifier,post
classification change detection},
  language     = {eng},
  note         = {Student Paper},
  series       = {Lunds universitets Naturgeografiska institution - Seminarieuppsatser},
  title        = {Land use/ land cover change detection and quantification : a case study in eastern Sudan},
  year         = {2010},
}