Flood hazard assessment by means of remote sensing and spatial analyses in the Cuvelai basin : case study, Ohangwena region, northern Namibia
(2010) In Lunds universitets Naturgeografiska institution - SeminarieuppsatserDept of Physical Geography and Ecosystem Science
- Abstract
- Popular summary: Amongst other affected countries, Namibia endures seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study concentrated only on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using satellite images and Geographical Information Systems (GIS).
The main data used in the analysis was the Oshana water area for years from 2003 to... (More) - Popular summary: Amongst other affected countries, Namibia endures seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study concentrated only on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using satellite images and Geographical Information Systems (GIS).
The main data used in the analysis was the Oshana water area for years from 2003 to 2010. This was extracted from the Landsat satellite images by means of Modified Normalized Difference Water Index (MNDWI) method. The effectiveness of the MNDWI to extract water from the images was assessed by means of accuracy matrix, with data obtained via homestead survey. The other data used was the spatial location of homesteads in the area, digitized from the 2007 orthophoto. Analysis was conducted by means of spatial overlaying of delineated Oshana water and the homesteads. Those homesteads that are within the Oshana flood waters were considered as flooded homesteads and the rest were considered as non-flooded homesteads. Further analyses were conducted by calculating the frequency of flooding per homesteads and the percentage of homesteads flooded per village. Lastly, analysis was conducted on the impacted villages to determine the geographical distribution of the impacted villages, whether they are clustered or randomly distributed.
Based on the assessment, a soaring increase in the water area was detected as from 2008 to 2010, specifically the introduction of significant water towards the northeast side of the study area. Similarly, the number of impacted homesteads increased significantly from 2003 to 2008, mostly toward the east of the study area. The most affected villages were also clustered on the northern side of the study area, this are areas that are usually not prone the Cuvelai annual flooding.
Considering the high accuracy obtained for the delineated water, one can accurately map the flooded areas and eventually determine the affected homesteads. Thus, the result can aid in identifying flood impact areas that require humanitarian assistance during and post flooding. Moreover, it can help in allocating further studies to the considerably impacted villages. However, the limitation the study was that the actual number of homesteads flooded per villages was unknown to further validate the flooded homesteads results obtained from this study. In addition, the method depend primary on satellite images, thus unavailability of cloud free images might hampered the study. On the clouds limitation, alternatively, imaging radar data can be used to detect water bodies to ease the problem of clouds. (Less) - Abstract
- Floods are one of the most frequent natural disasters in the world that causes substantial damage to quality of life, livelihood, and properties. Many countries, in particular developing countries, lack knowledge of the phenomenon and infrastructures to deal with the disaster. So they tend to deal with disasters after it has occurred. Recently, there has been major flooding in the central northern Namibia, in the Cuvelai basin. These floods affected about 30% of the population and caused major damage and loss of life and the Government of the Republic of Namibia (GRN) does not have an early warning system for the floods nor mitigation measures in place. Further, post flooding information on the level of damage in specific locations is also... (More)
- Floods are one of the most frequent natural disasters in the world that causes substantial damage to quality of life, livelihood, and properties. Many countries, in particular developing countries, lack knowledge of the phenomenon and infrastructures to deal with the disaster. So they tend to deal with disasters after it has occurred. Recently, there has been major flooding in the central northern Namibia, in the Cuvelai basin. These floods affected about 30% of the population and caused major damage and loss of life and the Government of the Republic of Namibia (GRN) does not have an early warning system for the floods nor mitigation measures in place. Further, post flooding information on the level of damage in specific locations is also not made available. For these reasons, this study aims to assess the impact of floods and determine flood hazard areas in the Cuvelai Basin in the Ohangwena region, using Remote Sensing and Geographical Information Systems (GIS). This was achieved by delineating Oshana flood waters from Landsat ETM+ imagery by means of (MNDWI) method. Thereafter, the delineated Oshana flood waters were used to determine the flooded homesteads for each year and further assess the impact of flood in each village. Lastly, spatial cluster analysis was applied on the villages, based on the number of flooded homesteads per village, to assess the spatial distribution of the flooded homesteads and create hazard maps.
Based on the delineated Oshana flood water, an increase in the water area was recorded as from 2007 to 2010. Major changes in the Oshana flood water area were noticeable as from the year 2008 to 2010, specifically the introduction of more water toward the eastern side of the flood area. The number of flooded homesteads increased significantly as from 2008, when compared to previous years. The most affected villages are those that are located on the northern side of the study area. Results show that about 19% of the villages are in high hazard level 1, meaning they have significantly affected by the floods more than other villages as from 2003 to 2010.
Results of this study can be used to identify villages that are severely impacted by flood for humanitarian assistance. The method to assess and identify the impacted areas can be used mainly for post and pre-flood event to identify potentially affected areas and the number of impacted villages and homesteads. (Less) - Abstract
- Scientific summary: Amongst other affected countries, Namibia endured seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study was only conducted on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using Remote Sensing and Geographical Information Systems (GIS).
The primary factor used in the analysis was the Oshana water area for years from... (More) - Scientific summary: Amongst other affected countries, Namibia endured seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study was only conducted on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using Remote Sensing and Geographical Information Systems (GIS).
The primary factor used in the analysis was the Oshana water area for years from 2003 to 2010. This was extracted from the Landsat satellite imagery by means of Modified Normalized Difference Water Index (MNDWI) method. The accuracy of the MNDWI to extract water was assessed with accuracy matrix, with data obtained homestead survey. The other factor used was the spatial location of homesteads in the area, digitized from the 2007 orthophoto. Analysis was fulfilled by means of spatial overlaying of delineated Oshana water and the homesteads, to determine the flooded and non flooded homesteads. Further analyses were conducted by calculating the frequency of flooding per homestead, the percentage of homesteads flooded per village and the spatial clustering of the impacted villages.
Based on the assessment, a soaring increase in the water area was detected as from 2008 to 2010, specifically the introduction of significant water towards the northeast side of the study area. Similarly, the number of impacted homesteads increased significantly from 2003 to 2008, mostly toward the east of the study area. The most affected villages were also mapped on the northern side of the study area, this are areas that are normally not prone the Cuvelai annual flooding.
Considering the high accuracy obtained for the delineated water, one can accurately map the flooded areas and eventually determine the affected homesteads. Thus, the result can aid in identifying impacted areas that require humanitarian assistance during and post-flooding. Moreover, it can help in allocating further studies the considerably impacted villages. However, the limitation the study was that the actual number of homesteads flooded per villages was unknown to further validate the flooded homesteads results obtained from this study. In addition, the method depend primary on satellite imagery, thus unavailability of cloud free imagery might be hampered the study. On the clouds limitation, alternatively, imaging radar data can be used to detect water bodies to ease the problem of clouds. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/3015096
- author
- Kuliwoye, Edward
- supervisor
- organization
- year
- 2010
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- flood hazard assessments, remote sensing, MNDWI, Getis-Ord Gi*, spatial analysis, geography, physical geography
- publication/series
- Lunds universitets Naturgeografiska institution - Seminarieuppsatser
- report number
- 218
- language
- English
- id
- 3015096
- date added to LUP
- 2012-08-21 12:06:46
- date last changed
- 2012-08-21 14:25:32
@misc{3015096,
abstract = {{Scientific summary: Amongst other affected countries, Namibia endured seasonal floods in different parts of the country namely, Karas, Kavango, Caprivi, Ohangwena, Omusati, and Oshana regions. However, the study was only conducted on the floods within the Ohangwena region. Major flooding in this region became eminent from 2007, and only rapid appraisal assessments were conducted. As a consequence, up-to-date post flood information is not available nor do mitigation measures to cater for the floods. Therefore, the study aim was to assess the impact of the floods and determine flood hazard areas using Remote Sensing and Geographical Information Systems (GIS).
The primary factor used in the analysis was the Oshana water area for years from 2003 to 2010. This was extracted from the Landsat satellite imagery by means of Modified Normalized Difference Water Index (MNDWI) method. The accuracy of the MNDWI to extract water was assessed with accuracy matrix, with data obtained homestead survey. The other factor used was the spatial location of homesteads in the area, digitized from the 2007 orthophoto. Analysis was fulfilled by means of spatial overlaying of delineated Oshana water and the homesteads, to determine the flooded and non flooded homesteads. Further analyses were conducted by calculating the frequency of flooding per homestead, the percentage of homesteads flooded per village and the spatial clustering of the impacted villages.
Based on the assessment, a soaring increase in the water area was detected as from 2008 to 2010, specifically the introduction of significant water towards the northeast side of the study area. Similarly, the number of impacted homesteads increased significantly from 2003 to 2008, mostly toward the east of the study area. The most affected villages were also mapped on the northern side of the study area, this are areas that are normally not prone the Cuvelai annual flooding.
Considering the high accuracy obtained for the delineated water, one can accurately map the flooded areas and eventually determine the affected homesteads. Thus, the result can aid in identifying impacted areas that require humanitarian assistance during and post-flooding. Moreover, it can help in allocating further studies the considerably impacted villages. However, the limitation the study was that the actual number of homesteads flooded per villages was unknown to further validate the flooded homesteads results obtained from this study. In addition, the method depend primary on satellite imagery, thus unavailability of cloud free imagery might be hampered the study. On the clouds limitation, alternatively, imaging radar data can be used to detect water bodies to ease the problem of clouds.}},
author = {{Kuliwoye, Edward}},
language = {{eng}},
note = {{Student Paper}},
series = {{Lunds universitets Naturgeografiska institution - Seminarieuppsatser}},
title = {{Flood hazard assessment by means of remote sensing and spatial analyses in the Cuvelai basin : case study, Ohangwena region, northern Namibia}},
year = {{2010}},
}