Remote sensing as landscape inventory tool

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This technical presentation from World Agroforestry Centre (ICRAF) scientist Thomas Gumbricht demonstrates four elements of using remote sensing as a landscape inventory tool.

This presentation formed part of the CRP6 Sentinel Landscape planning workshop held on 30 September – 1 October 2011 at CIFOR’s headquarters in Bogor, Indonesia. Further information on CRP6 and Sentinel Landscapes can be accessed from http://www.cifor.org/crp6/ and http://www.cifor.org/fileadmin/subsites/crp/CRP6-Sentinel-Landscape-workplan_2011-2014.pdf respectively.

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Remote sensing as landscape inventory tool

  1. 1. Remote Sensing as landscape inventory tool Thomas Gumbricht (ICRAF) Thomas GumbrichtSentinel landscapes, CIFOR 2011
  2. 2. PART 1 – A hierarchical approach Ecotope Thomas GumbtichtSentinel landscapes, CIFOR 2011
  3. 3. PART 1 – A hierarchical approach Patch and hillslope Thomas GumbtichtSentinel landscapes, CIFOR 2011
  4. 4. PART 1 – A hierarchical approach Basin Thomas GumbtichtSentinel landscapes, CIFOR 2011
  5. 5. PART 1 – A hierarchical approach Continental Thomas GumbtichtSentinel landscapes, CIFOR 2011
  6. 6. PART 1 – A hierarchical approach Africa Soil Information Service (AfSIS) – sentinel sites Thomas GumbtichtSentinel landscapes, CIFOR 2011
  7. 7. PART 1 – A hierarchical approach Sentinel site designSentinel landscapes, CIFOR 2011
  8. 8. PART 2 – phenology monitoring Monitoring vegetation annual phenology from time series of satellite imagery Thomas GumbtichtSentinel landscapes, CIFOR 2011
  9. 9. PART 2 – phenology monitoringDeriving vegetation density data form satellite data – basic principles
  10. 10. PART 2 – phenology monitoring Method: Capturing the raw data To do phenology studies requires a large amount of input data. At HQ we are using an automated FTP engine (Expect) to search the MODIS Data Pool https://lpdaac.usgs.gov/get_data/data_pool For the data we need.Sentinel landscapes, CIFOR 2011
  11. 11. PART 2 – phenology monitoring Cleaning and smoothing the annual time-seriesSentinel landscapes, CIFOR 2011
  12. 12. PART 2 – phenology monitoring Extracting annual phenology For the annual vegetation phenology, we extract 11 indexes: 1. The annual average vegetation density 2. The annual maximum vegetation density 3. The annual minimum vegetation density 4. The annual limit for vegetation green up 5. The accumulated vegetation growth over the growing season(s) 6. The incremental vegetation growth over the growing seasons(s) 7. The length of the growing season(s) 8. The length of the green up phase of the growing season 9. The annual day of year for the start of the first growing season 10. The annual day of year for the peak of the vegetation density 11. The number of growing seasons The first three indexes are based on the total annual vegetation cycle. The limit for vegetation green up is calculated per annum, and based on a ratio definition: EVIratio = (EVI - EVImin)/(EVImax – EVImin),Sentinel landscapes, CIFOR 2011
  13. 13. PART 2 – phenology monitoring Method: Extracting annual phenology The annual average vegetation density The annual maximum vegetation density Annual average vegetation density Annual maximum vegetation densitySentinel landscapes, CIFOR 2011
  14. 14. PART 2 – phenology monitoring Method: Extracting annual phenology The annual day of year for the start of the first growing season The annual day of year for the peak of the vegetation density Length of growing season Length of greening up periodSentinel landscapes, CIFOR 2011
  15. 15. PART 2 – phenology monitoringMethod: Land use and land cover mappingThe phenology data generated from annual time series of satellite imagescan be used for mapping land cover and land use. The phenology curve canbe be used to differentiate vegetation types that can not be distinguished in asingle scene of multi-spectral image data. I.e. Forests of different types, aswell as grasslands and various agricultural crops have different phenology.To actual classify land use and land cover from phenology, we need todevelop a library of typical phenology patterns. For this we need to developfield surveys or use phenology patterns reported in the literature.
  16. 16. Other indexes that could be used for analyzing annual variations like phenology Rainfall (can be obtained from a combination of station data and Remote Sensing) Temperature (available from the MODIS sensor)  Surface wetness (index can be generated from MODIS reflectance and emissivity data) Sentinel landscapes, CIFOR 2011
  17. 17. PART 3 – biophysical indexing Method summarySentinel landscapes, CIFOR 2011
  18. 18. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  19. 19. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  20. 20. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  21. 21. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  22. 22. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  23. 23. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  24. 24. PART 3 – Biophysical indexing Lake Naivasha - KenyaSentinel landscapes, CIFOR 2011
  25. 25. Mount Kilimanjaro - Kenya
  26. 26. Mount Kilimanjaro - KenyaSentinel landscapes, CIFOR 2011
  27. 27. PART 4 – Databases and data sharing Web client 1: Google EarthSentinel landscapes, CIFOR 2011
  28. 28. PART 4 – Databases and data sharingWeb client 2:Openlayers Sentinel landscapes, CIFOR 2011
  29. 29. PART 4 – Databases and data sharing Desktop client QGISSentinel landscapes, CIFOR 2011

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