A flagship CTO event, this has grown into a platform for knowledge-sharing among peer groups steering ICT projects in e-delivery of health care, education and governance. This Forum echoes the Commonwealth's 2013 theme: The Road Ahead for Africa.

1. 7th Annual E-GOV Africa
Kampala, Uganda
7th Annual E-GOV Africa
Kampala, Uganda
GEOGRAPHIC INFORMATION SYSTEMS FOR
FOOD SECURITY AND LAND MANAGEMENT IN AFRICA
GEOGRAPHIC INFORMATION SYSTEMS FOR
FOOD SECURITY AND LAND MANAGEMENT IN AFRICAFOOD SECURITY AND LAND MANAGEMENT IN AFRICAFOOD SECURITY AND LAND MANAGEMENT IN AFRICA
Foster Mensah
Centre for Remote Sensing and Geographic Information Services
University of Ghana
Legon-Accra
1

2. OutlineOutline
• Introduction• Introduction
• GIS
GIS C St di• GIS Case Studies
• GPS
• Remote Sensing
• SLM
• A Panacea for Drylands – 15min Video

3. About CERSGISAbout CERSGIS
• Established by EPA and University of Ghana
• Geographic Information Services and Research
Support CentreSupport Centre
• It is a non-profit, self sustaining organization
• Provide Remote Sensing and Geographic Information
Systems (GIS) services in the application of GIS and
Remote Sensing.
• Provides services to government agencies, non-
governmental organizations, research institutions
d th i t tand the private sector

4. IntroductionIntroduction
• We live in an information age
• Geospatial information is one of the most critical
elements underpinning decision-making for manyp g g y
disciplines
• Geospatial information is an essential building blockp g
for sustainable development.
• Increasing the availability, access and interoperabilityIncreasing the availability, access and interoperability
of Geospatial information will stimulate innovation,
contribute to economic transformation and facilitate
national developmentnational development

5. Geographic Information System (GIS)Geographic Information System (GIS)
5

6. What is GIS ?What is GIS ? Reality
• Geographical Information System (GIS)
• Software and hardware that allows creation, visualization,
query and analysis of spatial data.q y y p
• Spatial data refers to information about the geographic
location of an entityy
6

7. 7

8. RasterRaster--Vector Data ModelVector Data Model
8

9. Applications of spatial dataApplications of spatial data::
• Modeling
f– Developing “where is” and “what if” scenarios
• Decision making support
– communicating processes and information that help
solve or avoid problems.
• Monitoring
relating to environmental management and support– relating to environmental management and support
for programme management services.
M P d ti• Map Production

10. Applications of spatial dataApplications of spatial data::
Spatial data analysis
1. distances between geographic locations
2. The amount of area within a certain geographic region
3. What geographic features overlap other features
4. The amount of overlap between features
5. The number of locations within a certain distance of another
10

11. thanksthanks toto geospatialgeospatial technology!technology!

12. LandLand suitabilitysuitability analysisanalysis
Land suitability analysis involves the application of
criteria to the landscape to assess where land is mostp
and least suitable
Land use
Rainfall
12

13. Site suitability analysisSite suitability analysis
Why do site suitability assessment?
– It greatly reduces the time and effort which might otherwiseg y g
be spent manually searching records
– It is a key factor and critical initial step in the design of
many projects
– It produces a detailed display of the most-suitable to least-
suitable areas for consideration, while filtering out unusable
or less desirable sites.

14. suitability modelingsuitability modeling
R litReality Spatial data layers Suitable areas
Model criteria:
- Land use
- Elevation
- Climate
14

15. LandLand suitabilitysuitability modelingmodeling processprocess
1. Determine the question to be studied
2. Define the criteria for the analysis
3. Determine the data needed to answer the question
4. Determine the GIS procedures needed
5. Create the model
6. Analyze the results and improve the model
7. Make a decision
15

16. ProcessProcess flowflow (Modeling)(Modeling)
Land use
Rainfall
16

17. Sample suitability and weighting
Criteria:
landscape restoration will be
necessary in certain areas
Weighting:
Open access areas more important
than reserved areas
Bare areas more important than
closeness to towns
Annual rainfall greater than 1200mmAnnual rainfall greater than 1200mm
is highly suitable
Slopes less than 10% is highly
suitable
17
suitable

18. Case Study:Case Study:Case Study:Case Study:
Suitability ModelingSuitability Modeling forfor LandscapeLandscape
RestorationRestoration
18

19. MethodologyMethodology
Landuse
Mapping
Terrain
Analysis
Climatic
Analysis
Landuse &
Accessibility
Rainfall
Suitable Slope
and Elevation
GIS Analysis to Generate
Overall Suitability
19

20. Inputs and CriteriaInputs and Criteria
1. Preliminary criteria categories were decided and weights assigned based on
the level of importance
2. Less suitable sites were given low values/weights (0 been the lowest) and the
most suitable areas assigned a higher weight (4 been the highest)
3 Layers added to each other and values for each data layer carried through and3. Layers added to each other and values for each data layer carried through and
applied to output
4. Rank as suitable the closer an area matches the optimum
5. The result is a suitability map which shows a range of values that reflect a
area’s suitability based on the user define criteria
20

21. Criteria ScoringCriteria Scoring
Input
Layer
Criteria
Potential Score
Low (0) High (1)
Terrain
Elevation <500m asl >500m asl
Slope >10 degree <10 degreeSlope >10 degree <10 degree
Low (0) Moderate (2) High (3)
Climatic
Rainfall
Distribution <1000mm 1000-1200mm >1200mm
Low (0) Moderate Low (1) Moderate (2) Moderate High (3) High (4)Low (0) Moderate Low (1) Moderate (2) Moderate High (3) High (4)
Land Use
Land Use
Types Reserved
Long Fallow Short Fallow Grassland
21

22. Elevation Criterion
2 Classes :
Altitude 0 - 500 msl = 0 (Low Suitability)
Altitude >500 msl = 1 (High Suitability)
22

23. Slope CriterionSlope Criterion
2 Classes:
Slope >10 degrees = 0 (Low Suitability)
Slope <10 degrees = 1 (High Suitability)
23

24. Annual Rainfall Criterion
3 Classes:
1000 0 (L S it bilit )<1000mm = 0 (Low Suitability)
1001 – 1200mm = 2 (Moderate Suitability)
>1200mm = 3 (High Suitability)
24

25. Land Use CriterionLand Use Criterion
4 Classes:
Reserved Area = 0
Closed Forest = 1Closed Forest = 1
Long Fallow = 2
Short Fallow = 3
Grassland = 4
25

26. ResultsResultsResultsResults
26

27. Slope & Elevation
Elevation layer is overlaid with Slope layer:
Suitability score ranges from 0, for areas that
meet no criteria to 2, for areas that meet both
criteria
27

28. Slope, Elevation & Rainfall
Slope layer is overlaid with the rainfall
and elevation layerand elevation layer
28

29. AreasAreas suitablesuitable forfor landscapelandscape restorationrestoration

30. Ranking Suitability Area % Area (ha) Class Total(ha)
0
Low
0.0 629
103,617
1 1.0 100,664
2 0.0 2,324
3
Medium
2 190,190
4 8 836,712
5 20 1,975,211
5,788,8896 28 2,786,776
7
High
30 3,030,098
4 050 585
8 8 762,548
9 3 257 939 4,050,5859 3 257,939
Total 100 9,943,091 9,943,091
30

31. Case Study:Case Study:Case Study:Case Study:
Desertification Hazard MappingDesertification Hazard Mapping
31

32. Desertification HazardDesertification Hazard
It is a process that can be as much man-caused as
natural and therefore is one of the natural hazards best
suited for mitigation by those who plan, implement, and
manage national development efforts.
Why create Hazard maps?Why create Hazard maps?
– Visual information better than tables of numbers
– Easier to convince peopleEasier to convince people
– Can be updated and disseminated easily
– Useful for mitigation planning

34. Geospatial PortalGeospatial Portal
demand for geospatial data
access to quality geospatial data Metadata serviceMetadata service
minimize duplication
efficient data maintenance Map serviceMap service
platform for partnerships
efficient data maintenance Map serviceMap service
DD--support servicesupport service

35. ONLINE GIS PLATFORMONLINE GIS PLATFORMONLINE GIS PLATFORM
FOR
AGRICULTURAL DEVELOPMENT IN GHANA
ONLINE GIS PLATFORM
FOR
AGRICULTURAL DEVELOPMENT IN GHANA

36. http://www.gis4ghagric.nethttp://www.gis4ghagric.net

38. Land coverLand cover MetadataMetadata
ElevationElevation

39. CropsCrops

40. SoilsSoils

41. ClimateClimate
MEAN ANNUAL RAINFALL
EVAPOTRANSPIRATION

42. Land SuitabilityLand Suitability
Cowpea
Millet

43. Sample MapSample Map

45. Global Positioning System (GPS)Global Positioning System (GPS)

46. GPS Requires 4 Satellites To
Obtain A “Position”

47. Longitude / LatitudeLongitude / Latitude
(North / West)(North / West) (North / East)(North / East)
9O9Ooo
OOoo
3O3Ooo
6O6Ooo
Equator ( 0 NS)
OOoo6O6Ooo18O18Ooo 120120oo
Equator ( 0 NS)
(South / West)(South / West) (South / East)(South / East)
Prime Meridian
(0 )(0 EW)

48. Getting your location/position on
the earth’s surfacethe earth s surface
+

49. FarmerFarmer--level GPS Mappinglevel GPS Mapping
1
2
5
1
2
5
2
3
4
3
4
HandHand--held GPS Receiverheld GPS Receiver
PT. NO LATITUDE LONGITUDE
1 05.68771 001.62076
2 05.52341 001.60019
3 05.33322 001.59332
49
4 05.44572 001.59902
5 05.68331 001.62045
1 05.52341 001.60019

50. GPSGPS DataData CollectionCollection
This is becoming extremely important collecting data on locations of
i t tinterest.
50

51. Remote SensingRemote Sensing

52. Why remote sensing?Why remote sensing?y gy g
• Access large areas
• Map inaccessible areas
• Timely repeats for monitoring• Timely repeats for monitoring

53. Types of remote sensing dataTypes of remote sensing data
Optical Lidar
Radar

54. Optical dataOptical dataOptical dataOptical data

55. SpaceSpace--basedbased applicationsapplications

56. OpticalOptical –– high resolutionhigh resolution
e.g. Worldview, Aerial photographs
1961 2007 Change

57. OpticalOptical –– medium resolutionmedium resolution
e g Landsat ASTER SPOT DMC (incl NigeriaSAT) CBERSe.g. Landsat, ASTER, SPOT, DMC (incl. NigeriaSAT), CBERS…
10 km

58. OpticalOptical –– coarse resolutioncoarse resolution
e g MODIS SPOT-VGT AVHRR MERISe.g. MODIS, SPOT VGT, AVHRR, MERIS…
MODIS
(500 m)
ASTER
(15 m)
QuickBir
d (1 m)
Landsat
(30 m)(500 m) (15 m) d (1 m)(30 m)
Daily ~40 days ~60 days on demandDaily ~40 days ~60 days on demand
FreeFree FreeFree Low costLow cost ProhibitivelyProhibitively
ExpensiveExpensiveExpensiveExpensive

59. Vegetation IndexVegetation Index –– ‘greenness’‘greenness’
• Reflection: leaves ≠ soil
• Normalised Difference
V t ti I d (NDVI)
e (%)
Vegetation Index (NDVI)
lectanceRefl
Wave Length (nm)
High NDVIHigh NDVI

60. Satellite Scenes – same season
0 k
ASTER
27th Nov
Landsat
ETM+ 12th
Landsat TM
30th Dec
10 km
27th Nov
2006
ETM+ 12th
Dec 2000
30th Dec
1986

61. > 4 S D
ChangeChange--detectiondetection
+1 to +2 S.D.s
+2 to +3 S.D.s
> +4 S.D.s
No Change (± 1 S.D)
Water / no data
< -3 S.D.s
-2 to -3 S.D.s
-1 to -2 S.D.s
∆ NDVI 1986 ∆ NDVI 2000ETM+ ∆ NDVI 1986
2000
∆ NDVI 2000
2006
ETM
2000

62. Example use of optical dataExample use of optical data
Land cover mapping
• Global Land cover Mapping Project 2000
• Classification based on SPOT VGT data and• Classification based on SPOT VGT data and
expert opinion/fieldwork - 1 km resolution
Mayaux, P., et al. 2004. A new land-cover map of Africa for the year 2000. Journal of
Biogeography, 31, 861-877

63. Dense forest
Mosaic forest
GLC 2000 Africa map
Mosaic forest
Woodlands
ShrublandsShrublands
Grasslands
AgricultureAgriculture
Bare soil
WaterbodiesWaterbodies

64. LandLand cover mapcover map -- GhanaGhana

65. Problem 1: Cloud

66. Problem 2: These look the same in optical
1. Pristine
2. Degraded
Budongo Forest, Uganda

67. RadarRadarRadarRadar

68. RadarRadarRadarRadar
• Side-looking
Active
radar Return
signalpulse signal
(backscatter)

70. Optical vs. Radar

71. Radar satellitesRadar satellites
Band Wavelength
Typical maximum
resolution Satellitesg
from orbit
X-band 2.5-3.75 cm ~1 m
TerraSAR-X (2007-)
TanDEM-X (2010-)
COSMO-SkyMed (2007-COSMO-SkyMed (2007-
)
C-band 3 75 7 5 cm ~3 m
ERS-1 (1991-2000)
ERS-2 (1995-2011)
ASAR (2002 2012)C-band 3.75-7.5 cm ~3 m ASAR (2002-2012)
RADARSAT 1 (1995-)
RADARSAT 2 (2007-)
S b d 1 6 N SAR (201 )S-band 7.5-15 cm ~6 m NovaSAR (2015-)
JERS-1 (1992-1998)
ALOS PALSAR (2007-
L-band 15-30 cm ~20 m
(
2011)
ALOS-2 PALSAR-2
(2013-)
SAOCOM (2015)( )
?DESDynI (2019)
P-band 70-130 cm ~50 m ?BIOMASS (2019)

72. ConclusionsConclusions -- RadarRadar
• Sees through clouds• Sees through clouds
• Penetrates vegetation
• Data not free

73. LidarLidar –– light detection and ranginglight detection and ranging
L• Laser
• Vertical looking
• Detects returns with high accuracy

74. 33--DD LidarLidar ImageryImagery

75. ConclusionsConclusions -- LiDARLiDARConclusionsConclusions LiDARLiDAR
Gi t i & t ti h i ht• Gives terrain & vegetation height
• Potential for very high resolution
• Sampling tool
• Cloud problems
• 1 satellite ever (ICESat GLAS)
• Mostly aircrafty

76. Risk and damage assessment
– with climate change it is likely that Earth observation and
weather monitoring satellites will become increasingly
i t t t i i ti i k timportant to improve existing risk assessment processes,
especially for damage evaluation.
Land cover monitoringLand cover monitoring
– given the effect agricultural expansion have on biodiversity
and climate change assessing the condition of land coverand climate change, assessing the condition of land cover
can be achieved by EO

77. Disaster monitoringDisaster monitoring
When you are on the ground, it is hard to grasp the size of these
events.

78. Land cover mappingLand cover mapping

79. Rural development
– Earth observation satellites allow objective assessments of
remote rural areas to help design, plan and monitor the
i t f l d d i lt l j timpact of land use and agricultural projects
Change DetectionChange Detection
– An important concept in monitoring is change...
B t llit j t k i d th l b th– Because satellites just keep on going round the globe, they
take repeat images which can be very helpful in explaining
change over timechange over time.

80. Change DetectionChange Detection

81. Useful websitesUseful websites
81

82. Famine Early Warning Systems Network (FEWS NET)
http://www.fews.net
82
http://www.fews.net

83. 83

84. 84

85. 85
http://www.foodsecurityportal.org/africa-food-security-vulnerability-indices

86. 86
http://www.fao.org/docrep/008/J6398e/maps/afr.htm

87. Land Use Planning :Land Use Planning :SustainableSustainable Land ManagementLand Management
• An iterative process
• Based on the dialogue amongst all stakeholders
• Negotiation and decision for sustainable land use
• Monitoring implementation.
Provides the prerequisites for achieving a sustainable
form of land use which is acceptable as far as the
social and environmental contexts are concerned andsocial and environmental contexts are concerned and
is desired by the society while making sound economic
sense.

88. MAIN PRINCIPLES:MAIN PRINCIPLES:
• Active community participation
• Consistent with national/local planning schemes
• Environmentally friendlyEnvironmentally friendly
• Community validation and approval
Approval by local authority• Approval by local authority
• Implementation and monitoring
88

89. VIDEOVIDEO
89

90. THANKTHANK YOUYOU !!
fmensah@ug.edu.gh