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This presentation by Dr. Christopher Bennett discusses the role of kinematic GPS surveys in improving road management within developing countries. Drawing from experiences in Laos and Samoa, the session covers essential concepts such as precision, accuracy, and referencing methods for road data. It highlights the practical challenges faced during surveys and emphasizes the need for integration with existing data. Dr. Bennett explores the dual utility of remote sensing and driving for data collection and the importance of training local teams, ultimately advocating for the enhancement of road management through technology.
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Experiences With Kinematic GPS Surveys in Developing Countries Dr Christopher Bennett chris@htc.co.nz
An Introduction • Consultant to World Bank • Preparing Terms of Reference • Executing Surveys • Developer of the ROMDAS road measurement system • Used for kinematic GPS and other data collection • 130+ systems in over 30 developed and developing countries
Overview • A road engineer’s view of centreline surveys • Some experiences • Lao PDR • Samoa
Role of GPS? • Interface with data • GIS the most intuitive method • Referencing the base network • GPS vs Linear • Referencing data • GPS not suitable for all attributes
Interfacing With Data • GIS offers the most intuitive way of interfacing with data • Layers can be used which reflect the desired level of detail
Referencing the Road Network • Historically roads referenced linearly • In adopting GPS must provide link to existing data • Use of GPS for referencing not practical for many types of data • Need to carefully consider field procedures and staff capabilities
For Each Data Item Must Consider: • PRECISION • Positional error using different technologies • ACCURACY • The tolerance for the required position • RESOLUTION • Level of detail • EXTENT • Physical characteristics in terms of length, breadth and depth
NZ Example • Level 1: (+/- 3 m) • Reference stations • Level 2: (+/- 5 m) • Other referencing (section start) • High speed data (roughness, texture, skid) • Traffic facilities • Level 3: (+/- 10 m) • Visual condition • Signs, roadmarkings • Structures • Accidents
Not Every Item Should Be Referenced With GPS • General rule: Only those data which are most suited to spatial referencing should be spatially referenced • Examples of spatially referenced data: • Reference Stations and other key referencing features • The road centreline • Off road objects, such as signs, which cannot be referenced using linear system
Remote Sensing vs Driving? • Each method have a role • For developing countries driving preferable because: • Often do not know which roads belong to the agency • Can collect additional data at same time • Can easily locate intermediate referencing markers (eg km markers)
Summary • For most countries linear referencing will continue to be used by road engineers • Need to adopt GPS technology to enhance road management • Cannot underestimate: • Effort required to collect the data • Effort required to maintain the data • Effort required to use the data
Opportunities and Challenges of Centreline Surveys In Developing Countries
The Situation • Developing countries often do not have a proper record of their roads • Maps are usually incomplete and out of date (if available at all!) • Centreline surveys provide this information as well as other key data
Technology • Depends upon accuracy requirements • Users have done surveys have been done with: • Garmin 12 channel consumer • Trimble Pro-XRS • Pro-XRS with Base Station • Pro-XRS with RTCM • OmniStar
Accuracy? • Comparison of Garmin GPS distance with DMI distance from Lao PDR
Inertial Navigation • Gyroscopes are useful when loss of satellites • Typically can lose 5-20% of your data but depends on location
Lao Peoples Democratic Republic • Laos the Country • South East Asia • 236,800 sq km • Pop. ~5.5 Million • National & Provincial Roads • 15,600 km • 3,600 paved
The Project • Component of WB Third Highway Improvement Project • Survey of All National and Provincial Roads including: • One location reference point survey (LRS) • Road roughness survey (IRI) • Visual assessment of surface integrity (SII) • Inventory (surface type, width, bridges) • Digital photos of the start of links • GPS record of the road centreline • Contract Sum US$208,000
Used Garmin - Appropriate Accuracy for Project • Two hour 100% within ±22m, 85% within ±10m withoutdifferential correction • Extreme terrain impaired satellite availability (PDOP) for < 5-10% of survey • No gyroscope or differential correction obtained maps for 100% of network • 95% spatial to ±20m • 5% spatial to ±20-300m
Appropriate Accuracy 0m 100m • System recorded point every second. • Post-processed to one point approximately every 10m Same Road surveyed by different teams 3 weeks apart
The Survey Teams • Four locally staffed survey teams • Completed 14,000 km in 8 weeks • Ex-pat training • 3 staff per vehicle • Driver • Computer Operator • Condition Assessor • (plus up to 4 observers) • “Support” vehicles in Special Zones
Not all Plain Sailing Roads often became impassable with rain Time-out on one of the “support” vehicles used through the Special Zones
Unexpected Delays: the Photo that Carried a 2-day Sentence... Vietnam Border Post
Outcomes of Project • Using low-cost technology a centreline was established for the entire country • Additional data on pavement type and condition collected at the same time • Local teams used for data collection - successful transfer of technology • Data now in use by consultants, Ministry and World Bank.
Samoa • South Pacific • 5,000 sq km • Pop. ~ 80,000 • ~ 850 km of roads
The Project • Part of Samoa Asset Management System project • Funded by World Bank • Centreline survey conducted to: • establish the extent of the network • identify nodes and location reference points • create videolog of roads • Contract $USD 20,000
Equipment • Used Trimble Pro-XRS • Differentially corrected using base station established for project • Data overlaid onto aerial photographs
The Problem • Aerial photos and centreline data didn’t match!
Systematic Difference • Data shifted 13 m E/W; 4 m N/S
Possible Sources of Error • ROMDAS Data Processing: • There was an error in the processing of the ROMDAS data. • Eliminated by testing process against data collected and aerial photos for city in NZ • Position of Base Station: • There was an error in the position of the base station. • Took average position over 12 days, measurements within 1 m
Likely Source of Error... • Projections: • The two sets of data were prepared using different projection parameters when converting to WSIG. • Aerial Photograph Rectification: • There was an error in the rectification of the aerial photographs.
Impact of Projections and Software for Base Station Location
Implications • Trimble Pathfinder Office gave closest results for projections • Appears that aerial photos were incorrectly projected or rectified • Subsequent investigations showed that the national grid has errors up to +100 m • Solution (temporary!): processed data using Trimble, moving position of base station by 4/13 m.
Conclusions • Centreline surveys are an important management tool for road agencies in developing countries • Low cost technology makes it possible for any country to collect the data • Need to come up with improved procedures for projections and reconciling with existing data sources