The Evolution of Land Cover Data, in a South African Context, in Line with Ever Increasing User...

IGARSS 2009 - 16 July 2009

THE EVOLUTION OF LAND COVER DATA

IN A SOUTH AFRICAN CONTEXT

IN LINE WITH EVER INCREASING USER DEMANDS

Sharon Cundill, Pieter Sevenhuysen, Mark ThompsonGeoTerraImage (Pty) Ltd

IGARSS 2009 - 16 July 2009

• Introduction

• Specifications

• Drivers

• Enablers

• Conclusion

• Questions

Overview

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• SA’s first national land cover in 1990’s

• Used by national government departments

• Environmental applications

• Current land cover datasets

• Used by diverse industries and end-users

• Commercial applications

Introduction

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• Scales

• Detail

• Legends

Specifications

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• Planning and decision-making requirements

• Demand for higher spatial resolution land cover data

• National land cover 1994 at 1:250 000 scale

• National land cover 2000 at 1:50 000 scale

• Current local land cover at 1:10 000 scale

Specifications - Scales

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National Land Cover 1994: use at 1:250 000

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National Land Cover 2000 : use at 1:50 000

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Port Elizabeth Land Cover 2008 : use at 1:10 000

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• Shift from cover mapping

• Soft boundaries

• Indicate presence and extent of broad categories

• To specific feature/object mapping

• Actual boundaries of features

Specifications - Detail

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National Land Cover 2000 : cover mapping

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Port Elizabeth Land Cover 2008 : feature mapping

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• Shift from generic legends

• To meet needs of wide spectrum of users

• To customised legends

• For specific end-users

• Legends may be more complex or simpler

Specifications - Legends

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• Example: more complex


National Land Cover 2000 Gauteng Land Cover 2006

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• Example: more simple


Tshwane Land Cover 2006 Tshwane sealed surfaces 2008

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• Technology

• Applications

• Legislation

Drivers

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Drivers - Technology

• Technologies in various sectors have improved

• Demand for accurate, high resolution data

• Example 1:

• Telecommunications industry: evolved from first to third generation (3G) technology

• Requires greater level of detail for planning and implementation

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• Example 2:

• Business sector becoming more spatially aware in terms of decision making

• Internet mapping (Google and Google Earth, Microsoft) and GPS devices and satellite navigation systems (Tom Tom and Garmin)

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• Example 2 cont:

• Increased use of complex databases, including spatially-enabled databases (i.e. GIS)

• Requires high level of detail to support applications and queries running on database

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Drivers - Applications

• 1990’s

• National government departments

• Environmental applications

• Regional and provincial levels

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Drivers - Applications

• Current

• Business sector and local government

• Financial, risk assessment, engineering, urban planning, land management, infrastructure, public safety and security, environmental monitoring

• Local levels

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Drivers - Legislation

• 1994: SA’s first democratic election

• Many changes to national, provincial and local legislation

• Numerous changes require a spatial component

• Land cover datasets often fulfill these requirements

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• Example: direct legislation

• National Water Act (Act 36 of 1998)

• Requires historical spatial component in order to assess water usage pre- and post-1998

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• Example: indirect legislation

• The Constitution of the Republic of South Africa (Act 108 of 1996)

• Everyone has the right to adequate housing and sufficient food and water

• Demand forecasting and planning requires spatial component

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• Imagery

• Methods

• Equipment

Enablers

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• Increasing spatial resolution available from commercial providers

• Higher cost of high resolution imagery more feasible for commercial users

• Cost off-set by benefit

• Reduction in absolute cost of high resolution imagery

• Due to increase in demand, competition and technology

Enablers - Imagery

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• 1999: imagery constituted 30% to 50% of total project cost

• 2009: imagery cost is comparatively negligible or free

Enablers - Imagery

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Enablers - Imagery

Port Elizabeth Landsat 7 pan merge 15m pixel (RGB: 453)

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Enablers - Imagery

Port Elizabeth Spot 5 pan merge 2.5m pixel

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Enablers - Imagery

Port Elizabeth digital aerial photography 0.5m pixel

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• Developments in imagery and level of detail necessitates changes in methods

• Shift from manual mapping on acetate prints

• To simple unsupervised classifications

• To complex integration of on-screen digitising, object-orientated segmentation and supervised classifications

• Use of ancillary datasets in modelling process

Enablers - Methods

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• 1999: Top of the range image processing hardware system

• 2x 9GB hard drives

• Cost: R45 000 / $6000

• 2009: Standard image processing hardware system

• 2x 1.5TB hard drives

• Cost: R25 000 / $3300

• Can manage a single 18GB image

Enablers - Equipment

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• High resolution land cover datasets allow for complex and specific modelling for wide-ranging purposes

• BUT the need for coarse scale and generic land cover datasets is not obsolete

• Still needed at national and regional levels

• Ensure continuity of data

Conclusion

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• The new high resolution datasets are invaluable in decision support for the future development of South Africa

Conclusion

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Questions and comments

Contact: [email protected]

[email protected]@geoterraimage.com

IGARSS 2009 - 16 July 2009

The Evolution of Land Cover Data, in a South African Context, in Line with Ever Increasing User...

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