Modeling of Urban Sprawl Hazard in AL-Qalubia Governorate, Egypt Using Remotely Sensed Data and GIS

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Modeling of Urban Sprawl Hazard in AL-Qalubia
Governorate, Egypt Using Remotely Sensed Data and
GIS
Dr. Islam Abou El-Magd NARSS
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Overview

• Introduction
• Objective
• Methodology
• Results
• Conclusion

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Introduction - 1

• Limited arable land (?6)
• Over population (?75m)

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Introduction - 2

• Al-Qalubia represents 0.1 from Egypt Territory
• Al-Qalubia represents 10 of the arable
  productive land
• Total population 4,251,672

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Introduction - 3
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State of Problem

• Urban Sprawl to accommodate the over increase of
  population density
• The highly productive land of River Nile is under
  severe encroachment by urbanization
• Consequently the demographic attributes will be
  deformed

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Main Objective

• Produce a Timely GIS Database to
• Monitor the urban encroachment over agriculture
  land
• Estimate the loss of the fertile cultivated land
• Predict the life-time of the arable land
• Provide decision makers with reliable information
  for sensible solutions

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Study Area

• Al-Qalubia Govenorate
• It is situated in south of the Nile Delta
• It includes 8 Districts

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Data Source

• SPOT 4 Satellite Data (1995 2007)
• Typical SPOT 4 Technical Specs
• 60 x 60 km scene coverage
• Multispectral Mode
• Spatial Resolution 20 meters
• visible band B1 0.50 to 0.59 mm
• visible band B2 0.61 to 0.68 mm
• visible band B3 0.78 to 0.89 mm
• Panchromatic Mode with spatial resolution of 10 x
  10 meters
• Topographic and other thematic maps (150k)
• Field Survey

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Example of Resolution Merge of SPOT 4 XS
Panchromatic
Cairo
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Methodology Framework
Satellite Image 1995
Satellite Image 2007
Topographic maps
Classification
Agriculture area
Linear Networks
Mask
FAO LCCS
Land use / Land cover map
Change Detection of Urban Areas
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Remote Sensing

• 1 - Visual Interpretation Classification
• To detect urban areas
• To identify the crop patterns
• To determine the soil characteristics
• To identify the linear networks (e.g. main roads,
  railways, water canals, etc..)
• To generate thematic maps

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FAO LCCS

• 2 FAO Classification System (LCCS) is used
  which is a conceptual software assists in
  establishing the land cover legend
• Field checks and verifications

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Land Cover Classes Within Each District - 1
District Herbáceos Crops (ha) Trees Crops (ha) Cultivated Area (ha)
Al Kanater 5327 2540 7867
Al Khanka 4675 1665 6339
Banha 8976 4261 13237
Kafr Shukr 4164 1099 5263
Qaluob 6739 2359 9098
Shibin Al-Kanater 8168 3726 11895
Shoubra Al-Khaima 458 109 568
Toukh 9343 10171 19513
Total 47850 25930 73780
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Land Cover Classes Within Each District - 2
District Bare Area (ha) Urbanized Area (ha) Linear Features Area (10-45m) (ha)
Al Kanater 1256 430
Al Khanka 1222 4222.7 460
Banha 3907 730
Kafr Shukr 1062.6 240
Qaluob 2063 280
Shibin Al-Kanater 1818 540
Shoubra Al-Khaima 2138 80
Toukh 172 2945 800
Total 1394 17383 3560
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The identified land cover classes in Qalubia
Governorate
25930 ha
47850 ha
1394 ha
17383 ha
3560 ha
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The identified land cover classes in each
individual District (e.g. Al Khanka)
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The identified land cover classes in each
individual District (Al Kanater District)
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The identified land cover classes in each
individual District ( Qaluob)
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The identified land cover classes in each
individual District ( Banha District)
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The identified land cover classes in each
individual District (Kafr Shokr District)
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The identified land cover classes in each
individual District (Shoubra Al Khaima District)
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The identified land cover classes in each
individual District (Shebeen Al Kanater District)
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The identified land cover classes in each
individual District (Touk District)
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The Total Area of Qalubia Governorate
2007
1995
Urban area
Loss 62 km2 (6.3)
Area/ km2 102
Area/km2 164
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Life-Time of Arable Land Urbanization Rate

• Total Area 983 km2
• Net loss of arable land per year is 5.64 km2
• Loss rate is 6.3 per year
• Predicted lifetime of Qalubia Governorate is 158
  Year

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Accelerators

• Newly developed infrastructures

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Accelerators

• Abandoned services such as drainages, railways,
  etc.

Source Google Earth
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Prediction Model of Urban Sprawl
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Negative Consequences

• Deteriorating a unique physiographic soil unit,
  that is hardly to be recreated again
• Deteriorating a highly suitable land for specific
  economical and strategic crops (cotton)
• Disturb the local demographic attributes of the
  community
• Disturb both micro ecological and climatic systems

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Recommendations

• Urgent call to legitimately protectorate the
  arable land in the Nile Delta as a National
  Protectorate,
• Setting up a near real-time monitoring system of
  the newly constructed roads which acting as a
  catalyst for unplanned urban development,
• Issuing strict rules against urban aggression
  over the productive agricultural land,
• Promoting public awareness to the local community
  about both the value of the arable land and the
  new rules, and
• Enforcing the rules to be implemented

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• Otherwise we will be in a mess!!!!

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Thank You