Analysis of the Drivers of Landcover and Landuse Change in Western   Kenya over the Last 30 years       Mike Norton-Griffi...
Research Objectives• LBDA /ICRAF   – Develop statistically robust and useful measures of landuse and     landcover change ...
LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
FEWS NET/USGS RECENT CLIMATE VARIATION DATA   (http://earlywarning.usgs.gov/fews/reports.php)
FEWS NET/USGS RECENT CLIMATE VARIATION DATA   (http://earlywarning.usgs.gov/fews/reports.php)
FEWS NET/USGS RECENT CLIMATE VARIATION DATA   (http://earlywarning.usgs.gov/fews/reports.php)
FEWS NET/USGS RECENT CLIMATE VARIATION DATA   (http://earlywarning.usgs.gov/fews/reports.php)
LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
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LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
GEOREFERENCING THE 1983 AERIAL PHOTOS                                    UTM        UTM      ICRAF                        ...
KATUK ODEYO 1983, AERIAL PHOTO ID: 1521_0074S       KATUK ODEYO Flight Lines and Photos              Strong features for c...
10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
KATUK ODEYO 1983, AERIAL PHOTO ID: 2492_0035N     KATUK ODEYO Flight Lines and Photos            Strong features for contr...
10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
SOME DIFFICULT EXAMPLES:
ESTIMATING THE LOCATION OF OTHER (UN-GEOREFRENCED) SAMPLES                  ~ 17 sample sites, LOCATIONS???            KAT...
FLIGHT LINES CREATED FROM GEOREFERENCED SITES & ASSUMED FLIGHT PATH            KATUK ODEYO Flight Lines and Photos        ...
ESTIMATED SAMPLE SITESon the same flightON LOCATION RELATIVE TOeach other,  Estimated sample sites CREATED BASED path are ...
Success Rate and Implications:Of a total of 142 sample sites, 52 (47%) were exactly georeferenced, 90 wereestimated (63%)....
Fields with crops, harvested, bare fields, "patches"Active Cultivation         Woody Crops: tea, coffee, orchards         ...
Extensification of Agriculture
Changes to Active Cultivation and          Fallow Land
Changes to Natural Vegetation
Other Indices of Change                 1983     2010Field dividers& Hedgerows      38.6      50.1(km/ km-2)Ratio Modern: ...
Trees on Farms
Land Tenure as a Driver of Change
Comparison Between Remote Sensing            Platforms• Objectives:  – What is the most efficient remote sensing    platfo...
Which Platforms and Technology? – Compare quickbird visually generated data against   high resolution digital photography ...
2010 Land-use/Landcover mapping Western Kenya Integrated EcosystemManagement Project (WKIEMP)
Reporting and Databases• Report on Phase 1 will cover methodology,  preliminary results and the resource  requirements for...
LBDA / ICRAF Phase II• Yes, robust and useful descriptors of land cover and land  use change can be derived from the 1983 ...
Implications for ICRAF• While Quickbird imagery is appropriate for the survey and  monitoring of certain agro-forestry com...
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years
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Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years

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Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years

  1. 1. Analysis of the Drivers of Landcover and Landuse Change in Western Kenya over the Last 30 years Mike Norton-Griffiths & Harvey Herr (Jnr)
  2. 2. Research Objectives• LBDA /ICRAF – Develop statistically robust and useful measures of landuse and landcover change – Identify data on the potential drivers of change and their dynamics• ICRAF – Use of Quickbird imagery for inventory and monitoring of agro- forestry components in the smallholder landuse matrix – Procedures for efficient selection of Sentinel Landscapes and Sites – Quantify system dynamics for future monitoring
  3. 3. LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
  4. 4. FEWS NET/USGS RECENT CLIMATE VARIATION DATA (http://earlywarning.usgs.gov/fews/reports.php)
  5. 5. FEWS NET/USGS RECENT CLIMATE VARIATION DATA (http://earlywarning.usgs.gov/fews/reports.php)
  6. 6. FEWS NET/USGS RECENT CLIMATE VARIATION DATA (http://earlywarning.usgs.gov/fews/reports.php)
  7. 7. FEWS NET/USGS RECENT CLIMATE VARIATION DATA (http://earlywarning.usgs.gov/fews/reports.php)
  8. 8. LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
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  10. 10. 20
  11. 11. 21
  12. 12. LAKE BASINDEVELOPMENTAUTHORITY 1983 SURVEYGRID WITH ICRAFSENTINEL SITES, WESTERNKENYA
  13. 13. GEOREFERENCING THE 1983 AERIAL PHOTOS UTM UTM ICRAF Film OID Record # CODE XX YY Name Direction Scanned Control Georef Easting Northing BLOCK Photo 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1491-0061 S Y 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1491-0062 S Y 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1491-0063 S Y 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1491-0064 S N 3 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1491-0065 S N 3 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1491-0066 S Y 3 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1491-0067 S Y 3 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1502-0001 N Y 3 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1502-0002 N Y 1 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1502-0003 N Y Y 1 27 948 2627 26 27 722500 9967500 4 Katuk Odeyo 1502-0004 N Y 3 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1502-0005 N Y 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1502-0006 N Y 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1502-0007 N Y 28 949 2628 26 28 722500 9972500 4 Katuk Odeyo 1502-0008 N Y Y 30 1000 2727 27 27 727500 9967500 4 Katuk Odeyo 1511-0001 N Y 1 30 1000 2727 27 27 727500 9967500 4 Katuk Odeyo 1511-0002 N Y 1 31 1001 2728 27 28 727500 9972500 4 Katuk Odeyo 1511-0003 N Y KATUK ODEYO Flight Lines and Photos Strong features for control points XX --> 26 27 28 1491S 1502N 1511N 1521SLOCATION KNOWN WITHIN ~ 5km2 8 6 61 7 5 71 28 62 6 4 72 63 5 3 73 64 4 2 74 65 3 1 1 3 66 2 2 35 4 27 67 1 66 3 34 5 1 65 4 33 6 36 2 64 5 32 7 35 3 63 6 31 8 26 34 4 62 7 30 9 5 29 10 2492N 2501S 2511N 2521S 2531N 2541S
  14. 14. KATUK ODEYO 1983, AERIAL PHOTO ID: 1521_0074S KATUK ODEYO Flight Lines and Photos Strong features for control points XX --> 26 27 28 1491S 1502N 1511N 1521S 8 6 61 7 5 71 28 62 6 4 72 63 5 3 73 64 4 2 74 65 3 1 1 3 66 2 2 35 4 27 67 1 66 3 34 5 1 65 4 33 6 36 2 64 5 32 7 35 3 63 6 31 8 26 34 4 62 7 30 9 5 29 10 2492N 2501S 2511N 2521S 2531N 2541S
  15. 15. 10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
  16. 16. 10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
  17. 17. KATUK ODEYO 1983, AERIAL PHOTO ID: 2492_0035N KATUK ODEYO Flight Lines and Photos Strong features for control points XX --> 26 27 28 1491S 1502N 1511N 1521S 8 6 61 7 5 71 28 62 6 4 72 63 5 3 73 64 4 2 74 65 3 1 1 3 66 2 2 35 4 27 67 1 66 3 34 5 1 65 4 33 6 36 2 64 5 32 7 35 3 63 6 31 8 26 34 4 62 7 30 9 5 29 10 2492N 2501S 2511N 2521S 2531N 2541S
  18. 18. 10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
  19. 19. SOME DIFFICULT EXAMPLES:
  20. 20. ESTIMATING THE LOCATION OF OTHER (UN-GEOREFRENCED) SAMPLES ~ 17 sample sites, LOCATIONS??? KATUK ODEYO Flight Lines and Photos Strong features for control points XX --> 26 27 28 1491S 1502N 1511N 1521S 8 6 61 7 5 71 28 62 6 4 72 63 5 3 73 64 4 2 74 65 3 1 1 3 66 2 2 35 4 27 67 1 66 3 34 5 1 65 4 33 6 36 2 64 5 32 7 26 35 3 63 6 31 8 34 4 62 7 30 9 5 29 10 2492N 2501S 2511N 2521S 2531N 2541S
  21. 21. FLIGHT LINES CREATED FROM GEOREFERENCED SITES & ASSUMED FLIGHT PATH KATUK ODEYO Flight Lines and Photos Strong features for control points XX --> 26 27 28 1491S 1502N 1511N 1521S 8 6 61 7 5 71 28 62 6 4 72 63 5 3 73 64 4 2 74 65 3 1 1 3 66 2 2 35 4 27 67 1 66 3 34 5 1 65 4 33 6 36 2 64 5 32 7 26 35 3 63 6 31 8 34 4 62 7 30 9 5 29 10 2492N 2501S 2511N 2521S 2531N 2541S
  22. 22. ESTIMATED SAMPLE SITESon the same flightON LOCATION RELATIVE TOeach other, Estimated sample sites CREATED BASED path are equidistant from KNOWN SITES &GRID distance determined by the length of the flight line within the grid square or the from the grid to the edge of a block. Estimated sites that lie between a geo- referenced site and grid or block edge are spaced evenly along the distance of the flight line. 10x10 km 01/27/10 QUICKBIRD SATELLITE IMAGE, “LOWER NYANDO/KATUK ODEYO”
  23. 23. Success Rate and Implications:Of a total of 142 sample sites, 52 (47%) were exactly georeferenced, 90 wereestimated (63%).We have discovered automated georeferencing software which should speedthings up.
  24. 24. Fields with crops, harvested, bare fields, "patches"Active Cultivation Woody Crops: tea, coffee, orchards Ag. Overhead: tracks, pathways, field dividers Grass fallowFallow Bush fallowManaged Herbaceous Cover Managed pastures, grassy areas around compounds and fields Plantations, woodlotsManaged Woody Cover Scattered trees in crops, roads, homesteads, hedgerows Hedgerows: natural, planted, windrows, tree hedges Indigenous forest, riparian stripsNatural Woody Vegetation Scattered tress in bushland and grassland Bush cover (non-tree woody vegetation)Natural Herbaceous Cover Grass dominated areas (not managed pastures or fallow) Number of compounds Number of traditional roofsInfrastructure Number of modern roofs Compound area Roads, tracks and pathways (NOT in crops)Miscellaneous Bare areas, rock outcrops, rivers, lakesLandscape Managed (1), Mixed (2), Natural (3)Land Management Good (1), Medium (2), Poor (3)Infrastructure quality Good (1), Medium (2), Poor (3)
  25. 25. Extensification of Agriculture
  26. 26. Changes to Active Cultivation and Fallow Land
  27. 27. Changes to Natural Vegetation
  28. 28. Other Indices of Change 1983 2010Field dividers& Hedgerows 38.6 50.1(km/ km-2)Ratio Modern: Traditional 1:8.5 1:0.3Roofs
  29. 29. Trees on Farms
  30. 30. Land Tenure as a Driver of Change
  31. 31. Comparison Between Remote Sensing Platforms• Objectives: – What is the most efficient remote sensing platform for the Phase 2 activities – Can Quickbird be used for the inventory and monitoring of agro-forestry components within the ICRAF sentinel sites
  32. 32. Which Platforms and Technology? – Compare quickbird visually generated data against high resolution digital photography – Visual compared with computer classification of tree density, and “trees on farms” – Visual compared with computer classification of landcover and landuse
  33. 33. 2010 Land-use/Landcover mapping Western Kenya Integrated EcosystemManagement Project (WKIEMP)
  34. 34. Reporting and Databases• Report on Phase 1 will cover methodology, preliminary results and the resource requirements for the Phase 2 study of the entire LBDA area• Regional data are already on-line, more layers are being prepared• All bock, grid and point data will be available in Xcel format, with complete geo-referencing for use by LBDA and ICRAF researchers
  35. 35. LBDA / ICRAF Phase II• Yes, robust and useful descriptors of land cover and land use change can be derived from the 1983 and the 2010 Quickbird imagery.• Yes, regional data on potential drivers are readily quantifiable in both time and space• However, higher resolution imagery (digital aerial photography) will produce significantly better results than Quickbird imagery and will offer a much more flexible approach to re-sampling• Yes, it is possible to design a re-sampling programme (using either Quickbird or digital aerial photography) to analyse the drivers of landcover and landuse change over the last 30 years.
  36. 36. Implications for ICRAF• While Quickbird imagery is appropriate for the survey and monitoring of certain agro-forestry components within the complexity of the African smallholder production systems, the finer details of the agro-forestry components cannot be consistently identified.• Visual analysis of Quickbird sample sites is an essential component to the development and testing of computer models to monitor landcover and landuse• Appropriate methods are available for the efficient selection of sentinel landscapes and sites• To monitor internal (project) or external (climate) impacts, the dynamics and trajectory of the system must be understood

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