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Remote Sensing and disaster management in Africa

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Title: Remote Sensing and disaster management in Africa


1
  • Remote Sensing and disaster management in Africa
  • 10- 11 December 2007
  • ITU (Geneva - Switzerland)
  • Dr. Tesfaye Korme,
  • Director for Remote Sensing, GIS and Mapping
    Section
  • Regional Centre for Mapping of Resources for
    Development (RCMRD), Nairobi-Kenya

2
Outline of Presentation
  • About the Regional Centre (RCMRD)
  • Remote Sensing as a Tool
  • Major Disasters in Africa
  • Recent efforts and future perspective in Disaster
    management in Africa

3
II. About Regional Centre for Mapping of
Resources for Development (RCMRD) In Nairobi-
Kenya
4
History
  • RCMRD was established in Nairobi - Kenya in 1975
    under the auspices of the United Nations Economic
    Commission for Africa.
  • It is a non-profit making Inter-governmental
    Organization.
  •  
  •   Currently the Centre has 15 contracting member
    States namely Botswana, Comoros, Ethiopia,
    Kenya, Lesotho, Malawi, Mauritius, Namibia,
    Somalia, South Africa, Sudan, Swaziland,
    Tanzania, Uganda and Zambia.
  • The countries affiliated to the Centre are
    Angola, Mozambique, Zimbabwe, Rwanda, Burundi,
    Madagascar, Djibouti, Eritrea, Zaire and South
    Africa.

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6
Mission and Vision of the Centre
  •  
  • Its Mission To promote the standardization,
    harmonization and
  • development of geo-spatial data and
    information and strengthen
  • the capability and capacity of the member
    States in the use of
  • geo-spatial information for sustainable
    development.
  • Its Vision To become a Centre of Excellence in
    Geo-information in Africa.

7
Achievement Highlights
  • Helped in the establishment and capacity of
    building of mapping
  • agencies in its member States.
  •  
  • Trained over 4,500 technical / professional
    officers from its member
  • States and other African countries in the
    fields of Surveying, Cartography,
  • Remote Sensing and GIS.
  •   Implemented numerous (450) mapping and
    resource assessment projects
  • on behalf of its member States and development
    partners.
  •  
  •   Provided advisory and consultancy services in
    surveying, mapping,
  • engineering, environmental assessment,
    planning and management.
  •  

8
II. Remote Sensing as a Tool
  • ENVISAT EO-1
    EROS
    IKONOS
  • (ESA) (USA)
    (Russia)
    (USA-P)
  • IRS-1C KVR-1000
    Landsat 7
    TERRA
  • (India) (Russia)
    (USA)
    (USA)

  • METOP OrbView-4
    QuickBird Spot-5
    TRIMM
  • (ESA) (USA-P)
    (USA-P) (France)
    (USA)

9
Advantages of Remote Sensing
10
In disaster / risk management
Remote Sensing data is needed for
  • Disaster preparedness
  •  
  • Disaster mitigation
  •   Disaster monitoring
  • the current situation
  • before,
  • during and
  • after occurrence of Disaster.

11
III. Major Disasters Frequently Occurring in
Africa
  • Droughts
  • Flooding
  • Landslides
  • Fire
  • Volcanic Hazards
  • Epidemic Diseases
  • Land Degradation

12
1. Drought
  • Has become a recurrent phenomenon affecting
    millions of people in Africa each year

13
  • It is mainly related to climate change and
    variation
  • Meteosat and NOAA are used for weather
    forecasting and
  • impact of weather on crop/animal production.
  • Low/high resolution data has been and continue
    to be used in
  • assessment and monitoring of crop/biomass
    hectarage and
  • condition.

14
  • Satellite based rainfall estimation

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16
Identification of Hotspots
17
Ground Confirmation of hotspots
18
Ground Confirmation of areas with better
conditions
19
2. Flooding
  • High resolution satellite data (SPOT, Landsat 7,
    Ikonos) have
  • been extensively used in
  • the assessment of the impacts of floods on the
    local populace
  • monitoring floods
  • modeling floods
  • Examples Mozambique, Ethiopia, Kenya, Somalia,
    western Africa,
  • Nile flooding in Khartoum.

20
  • Warning, tracking, damage assessment

Flooded Dwellings
Extensive flooding
Tree tops
IKONOS 1-Meter Panchromatic
MOZAMBIQUE FLOODS Feb/Mar 2000
IKONOS 4-Meter Multispectral
Flooded Agricultural Fields
21
Hydro-meteorological conditions monitoring in
support of Early Warning of floods in Kenya
March May, 2003 rainfall season, Nzoia floods,
USGS and RCMRD team visited the area to validate
the Stream Flow Model notice the recent damage
and loss of property and livelihood
22
  • Production of flood inundation maps useful for
    response and contingency planning (case of Nzoia
    basin)

23
3. Landslides
Satellite data provides rapid data for
development of DEM and Land cover which are
necessary for landslide vulnerability assessment
and monitoring. Several historical landslide
scars were mapped from Landsat Images in Kenya
and Ethiopia Examples Western Kenya,
Ethiopia, Malawi
24
4. Fire
  • Multi-temporal infrared satellite data provides
    very important
  • information in forest fire detection.
  • In Africa every year thousands of hectares of
    tropical forest and
  • scrub are consumed by fire
  • The frequency of occurrence of forest fire has
    increased due to
  • the overall increase in temperature and aridity
  • Examples Congo, Kenya, Ethiopia, Angola, South
    Sudan

25
MODIS Data ANGOLA, AFRICA This remotely sensed
image was captured on May 5, 2004 by the Moderate
Resolution Imaging Spectroradiometer (MODIS) on
the Terra satellite. This photo shows numerous
fires throughout the countryside.
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5. Volcanic hazards
High resolution satellite data has been used in
the assessment of the extend and impact of
volcanic activities. Examples The application
in Goma in DRC and Mt. Etna, Italy
28
Nyiragongo Volcano lava flow DR Congo, 31 Jan 2002
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(Landast-7, Terra and Space Shuttle)
Goma Volcanic Eruption, January and
July, 2002
31
6. Epidemic diseases (predicting outbreaks of RVF
in GHA)
32
7. Land Degradation
  • Land degradation directly affects food
    productions and the
  • earths environmental wellbeing.
  • Satellite data and GIS has extensively been
    used in land
  • degradation assessments and monitoring i.e
  • - Forest depletion
  • - Soil erosion hazard
  • - Desertification hazard
  • - Coastal denudation
  • Example RCMRD has used these technologies in
    forest
  • depletion assessment, soil
    erosion mapping, etc.

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34

IV. Recent efforts by RCMRD in Disaster
management in Africa
1. Real-time data acquisition and the DDS (ESA -
Support)
  • DDS (Data Dissemination System) is an efficient
    microwave (Ku and C-bands) data transmission
    system has been installed in some of the regional
    centers .
  • It is mainly used in uploading and downloading
    data
  • The type of data transmitted via this system
    includes
  • ENVISAT MERIS and ASAR data
  • MSG (Meteosat Second Generation) data,
  • Processed data such as LAI, NDVI, FPAR, etc.
  • Other data such as ASTER and MODIS if upgraded

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36
2. Establishment of SERVIR Africa Node
  • Capacity building for the Centre
  • In data acquisition, archiving and dissemination
  • Data Processing and
  • Development of various applications
  • Landslide mapping
  • Epidemic diseases forecasting
  • Flooding early warning
  • Food security
  • Land management
  • Etc.

37
  • In Human resource capacity
  • Training in long and short-terms
  • Exchange of skills with other sister institutions
  • Provide support for SDI imitative
  • In developing standards and policy
  • In developing metadata and archiving mechanism

38
Conclusion
  • Remote Sensing and GIS technologies have a high
    potential for use in
  • Disaster management in Africa if the following
    are fulfilled
  • Putting in place the right policies and
    infrastructure
  • Build human capacity in rapid processing and
    interpretation of data
  • required in disaster management
  •   Make adequate budgetary provisions for timely
    acquisition and
  • processing of appropriate satellite data and
    RS software and
  • equipment
  • Creation of national and regional partnerships
    in disaster
  • management. for data and information sharing.
  • Development of National Spatial Data
    Infrastructure (NSDI)
  • for easy data and information sharing.

39
END!
  • Thank you for your attention!!
  • Merci Pour Votre Attention!!
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