Digital Mapping and GIS-Driven Feeder Road Network Database Management System for Road Project Planning and Implementation Monitoring in the Feeder Road Sector THIS IS A DFR PROJECT FUNDED BY DFID

THE PURPOSE IS TO DEVELOP A GIS-DRIVEN NATIONAL Martin hMENSAH, Kwaku OPON TUTU, Eli SABLAH FEEDER ROAD DATABASE FOR PLANNING, DEVELOPMENT, Department of Feeder Roads AND MAINTENANACE OF FEEDER ROADS Ministry of Road Transport

Emmanuel AMAMOO-OTCHERE, Foster MENSAH Centre for Remote Sensing and Geographic Information Services University of Legon

PROJECT AREA – ZONE 1 The scope of the inventory and mapping covers all engineered and unengineered Feeder Roads in each district. B U R K I N A F A S O UPPE R E AST

UPPE R WEST The process starts with District Assembly Consultations.

NO RTHE RN (Pilot) The consultations involve the use of existing District REPUBLIC REPUBLIC OF

Feeder Roads Maps as reference for sketching in, all the OF TOGO missing roads that are not on the map with the COTE I'VOIRE

BR O N G AH A FO participation of all stakeholders in a “mass-mapping” VOLT A exercise

ASHAN TI The output from the consultation is an up-to-date sketch E ASTE RN map of all the engineered and unengineered roads in the GREATER WESTERN district. Legend FE EDER ROAD CENTRAL NE T WOR K A E I N U G ZONE 1

F O ZONE 2

F G U L ZONE 3

Survey Process

1. Desk 2. District Study/Consultation 3. Survey 4. Deliverables Consultation DISTRICT CONSULTATION

Structures Road Survey List Assemble list of roads Update lists Road Definition and maps Structures List Prepare Map Survey of Roads Node Definition List

GPS Survey Shape File

1 ASSEMBLY PERSONS FROM THE EXPLORING THE DISTRICT MAPS ASSEMBLY PERSONS FROM AND AREA COUNCILS VALIDATING SETTLEMENT NAMES AND LOCATION

GPS SURVEY & ROAD INVENTORY

ASSEMBLY PERSONS FROM AND ANYAMAM AREA COUNCILS VALIDATING SETTLEMENT NAMES AND LOCATION

Captured Features: Road segments, Culvert/Bridges Infrastructure Facilities settlement locations Data Capture Equipment: Trimble Pro XR GPS receiver with sub-metre accuracy.

Mode of Data Capture: Road segments - line mode Drainage structures - point mode Infrastructure facilities - point mode Settlement locations - point mode

2 GPS SURVEY

The feeder road network is mapped with a “mobile” GPS receiver, recording coordinates of:

Roads Settlements Bridges Culverts Schools Health Facilities Water Points

Public buildings OUTPUT OF GPS SURVEY OF LUHUESE TO OBANE ROAD SUPERIMPOSED ON A CLASSIFIED SATELLITE IMAGE

SPACE IMAGES FOR ROAD IDENTIFICATION ATTRIBUTES OF ROAD INVENTORY

1. Date 2. District No. 3. Road No. 4. Start Node Name 5. End Node Name 6. Start Chainage 7. End Chainage 8. Functional Class I/C/A 9. Engineering Class E/P/N 10. Road Width 11. Pavement P/U 12. Surface R/G/S/C 13. Side Drains L/U 14. Topography 15. Roughness G/F/P 16. Camber G/F/P 17. Drainage G/F/P 18. Traffic H/M/L

ATTRIBUTES OF DRAINAGE STRUCTURE INVENTORY

1. Date 2. District Code 3. Road No 4. Start Node Name DATABASE DEVELOPMENT 5. End Node Name 6. STRUCTURE No 7. River Name 8. GPS Northings 9. GPS Eastings/Westings 10. Chainage (km+m) 11. STRUC TYPE (eg BC,SB,CP) 12. SIZE (mm) n / dia, n / W x H 13. LENGTH (M) 14. Headwalls (0/1/2) 15. Structure Condition Rating (1-5) 16. Notes

3 ROA D N ETW ORK

D RAI NAG E S TRU CTU RES

SE TTL EME NTS FAC ILIT IES

OUTPUTS

FEEDER ROAD NETWORK ROAD DATABASE LINKED TO FIELD PHOTOS

DANG ME E AST DI ST RI C T

AMEDEKO&VR &V TEHE &VFORKPO BAKPA

ABLORDEKOPE TALIBANYA V& V& OKUDZETOKOPE KASANGBLEKPO &V &VDZITSEKOPE V& OBUABAKOPE V& KPONGUNOR V& V&ENGLENSE KENYA

ODORKOKOPE &V KENYA MANGOASE KUBIKOPE MADAVUNU &V V& V& R SALENYEKOVP&E V&AKPAYAKOPE I V&ADODOADZEKOPE DOGOBOM AYISAH V& V

&V E

AMUYAOKOPE R SOLIGATE &VAMAKITSEKOPE KPETUHOR &V OFIAKPONYA TODZE AKANKOPE &V V& AVEYAOKOPE SCHOOL CAESARKOPE &V &V DORMKOPE V& KAJA V &V &V V& DENDO V& AKPOKOPE &V O AGBANAWVE& V& GBAGORHE V& L TUGAKOP&VE V&KPENYAKOPE WONYV&I WAPEKE ADATSEKOPE T AFIADENYIGBA V& &V V&KV&AJADORNVYA &V A BONIKORPE TETEKPO YOMOEKOPE V& V&& ADITSREKORPE ALEMAWORV& &V V& KAJADORNYA KAJANYA &V V&V ZUERNOR &V &VSEGA V& V&V& DOESISE KWESITSEKOPE TWASAMKOPE SONGKUENY&VA &V &V V& V&&V BOSOEKOPE FANVT&IVIKOPE &V DRAKOPE EKPEKOPE V& &V KORPEDEKA/KPOTIKO&VPE &V V& V&DETSEKOPE &V ASIGBEKOPE AMATE-KONI V&TAMATOKU AGBADZAKOPE

NUHALENYA&V &V YAUKOPE V& ELAVANYO-KONI V&V& TOVE VIDZROKOPE TAGBORKOPE V& &V DUNUKOPE V& KASSEH V& TODJOKOPE V& ADDOKOPE TEYEKOPE V& V&HWAKPO JUNCTION FAITHKOPE ANGORSEKOPE&V KPOTSUNU KORLEKOPE &V MANAIKPO MATEKOPE KOLUEDOR V& V& V& &V AKLORBORME &VGBANTANA V& V& &V V& AKLIGBEKOPE V&HWAKPO DOGO TELAPEM DORDOEKOPE SEGE KESEVE &V V& &V &V &V N MATSEKOPE GBANAVE V& KYEMWOAKOPE V& DEKUKOPE &V 2 0 2 Kilometers V& ADORNOKOPE MANGV&OASE &V ABOSEKOPE LUKUTUKOPE &V GLOME KAKIETSEKOP&VE V& &V V& OSOYAA DORNGWAM GBORVENYA ANUKPENYA V& DIKANYA(DICV&AT&VO) V& &V AHLIHAKPOSISI KOPEHEMV& &VMADAGBER &V AMEVOTSEKOPE V& TAMKOPE TEKPEKOPE V&SENOKIKOPE V& V& LUFENYA MAKATAKOPE MATAHEKO &V V& &V &V WONORKOPE &V WASAKUSE DZETROKOPE AYORNUKOPE NO.2 DAMEKOPE &V NYAV&MANUKOPE/LAWERKOPE AJUMANIKOPE &V KOKUSI &V V& TOGBLOKU &V GORMV& OBONUKOPE V& AKYIAKPOYOM V& SALTPONDS V& V& AGAKPOKPANYA &V BIG ADA SOWUKOPE &V &V V&

KUBIKOPE SONGOR LAGOON V&

KPOSEM LEGEND AMINAPA OBANE V& &V &V KPOTSITSEKOPE &V SETTLEMENTS V& KWALAKPOYOM TANIFO ANYAMAN -TANINO KABLEVU GOI ABUANORKOPELOLOMYA V& TEGLEKOPE V& SOLIKOPE &V V& &V V& V& KOLIKPO &V ANYAMAM V& AZIZAKPONYA &V &V FUTUENYAADA FOAH &V PATUKOPE SURFACE TYPE AKPLABANYA PUTE ALAVANYO SONGUTSOKPA V& &V TOTIMEKOPE V& V& OCANSEYKOPE WOKUMAGBE V& V& &V AYIGBO PAVED V& V& LOLONYAKOPE &V V& &V GRAVEL SAND

CLAY

GPS SURVEYED ROADS CLASSIFIED BY SURFACE TYPE SUPERIMPOSED ON WATERBODY LAYER EXTRACTED FROM THE DIGITAL TOPOGRAPHIC MAP PRODUCED BY SURVEY DEPAARTMENT.

4 SUMMARY – Zone 1 CONCLUSIONS

At the end of the survey: GPS/GIS/RS are essential tools for capturing, updating and visualizing road network data for Engineered Roads 8,814 km, efficient road maintenance planning and management

Partially Engineered Roads 1011 km GIS provides the platform for the creation and manipulation of a spatial database for visualizing Non-Engineered Roads 1879 km road attributes such as, surface type, surface condition, traffic volume and any other road related TOTAL 11,703 km attributes

The participation of local people in the capture of road related data is essential for ensuring data integrity

“Confidence Builders in Resources Management Information Systems” Thank You.

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