1. ReCover for REDD and sustainable forest management EU ReCover project: Remote sensing services to support REDD and sustainable forest management in Fiji Pacific Island GIS&RS conference 2012, 27 – 30 November 2012, Suva Johannes Reiche, Martin Herold: Wageningen University Donata Pedrazzani: GMV Fabian Enßle: Freiburg University

2. ReCover for REDD and sustainable forest management Outline 1.ReCover project objective 2.ALOS PALSAR change detection and time-series analysis 3.MODIS time-series analysis for forest change detection 4.ICESat/GLAS space borne laser ranging for forest height & biomass 5.ReCover workshop and field work (October 2012) 2

3. ReCover for REDD and sustainable forest management 3 1. EU ReCover project objective To develop beyond state-of-the-art service capabilities to support reducing deforestation and forest degradation in the tropical regions: –Research project driven by REDD+ monitoring needs –Monitoring system of forest cover, forest cover changes and biomass mapping including accuracy assessment. –Capabilities are based on utilizing earth observation and in-situ data –Using multiple remote sensing data sources –Involvement of national and regional partners, and user organizations

4. ReCover for REDD and sustainable forest management 2. ALOS PALSAR change detection and time-series analysis 4 ALOS PALSAR –L-band SAR system (sensitive to biomass) –SAR is not affected by clouds –Fine Beam Dual data was ordered and processed to 25 m resolution Country-wide mosaic for 2010 (25 m) (will be completed) False colour image RGB R: HH polarisation G: HV polarisation B: HH/HV ratio

5. ReCover for REDD and sustainable forest management ALOS PALSAR: Dual-temporal (2007,2010) coverage of west Viti Levu 5 2007-08/09 2010-08/09 2. ALOS PALSAR change detection and time-series analysis

6. ReCover for REDD and sustainable forest management 6 Classification Step 1: water mask (HH-07&10) Step 2: Vegetation cover change (HV difference 2007-2010) Step 3: Differentiating deforestation and other vegetation decrease, such as agriculture (HH-HV difference 2007) Water mask Positive change (e.g. reforestation) Negative change Forest/dense vegetation -> non-forest Other vegetation decrease Forest land cover change detection (Viti Levu west) 2007 - 2010 (first results, need to be evaluated) 6 Water mask Positive change (e.g. reforestation) Negative change Forest/dense vegetation -> non-forest Other vegetation decrease

7. ReCover for REDD and sustainable forest management Time-series examples 7 Stable forest 2. ALOS PALSAR change detection and time-series analysis

8. ReCover for REDD and sustainable forest management 8 Deforestation of pine plantagen Time-series examples 2. ALOS PALSAR change detection and time-series analysis

9. ReCover for REDD and sustainable forest management 9 Regrowth Time-series examples 2. ALOS PALSAR change detection and time-series analysis

10. ReCover for REDD and sustainable forest management BFAST: –time-series analysis package that detects changes as breaks in the time-series –Developed by Dr. Jan Verbesselt, Wageningen University (Netherlands) –BFAST R package is open source and free of charge ('http://bfast.r-forge.r-project.org/)'http://bfast.r-forge.r-project.org/) 3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.)

11. ReCover for REDD and sustainable forest management Input: 16 day MODIS NDVI composites (250m) –Complete country-wide time-series for 2000 – 2012 –MODIS data is freely downloadable Settings: –Historical period: 01/2000-12/2004 –Monitoring period: 01/2005-01/2012 NDVI Stable tropical forest pixel 11 3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.)

12. ReCover for REDD and sustainable forest management NDVI 12 Deforestation pixel 3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.) Input: 16 day MODIS NDVI composites (250m) –Complete country-wide time-series for 2000 – 2012 –MODIS data is freely downloadable Settings: –Historical period: 01/2000-12/2004 –Monitoring period: 01/2005-01/2012

13. ReCover for REDD and sustainable forest management 13 Deforestation pixel If break detected -> Output: (1)Date of change (2)Magnitude of Change (compared to historical period) 3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.)

14. ReCover for REDD and sustainable forest management 14 MODIS NDVI analysis analysis Fiji – Results Year of change

15. ReCover for REDD and sustainable forest management Apply MODIS NDVI time-series algorithm at Landsat time- series (30m pixel resolution) 15 2000-2012, Intensive cloud cover

16. ReCover for REDD and sustainable forest management 16 4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping Geoscience Laser Altimeter System (GLAS) 1 precision surface lidar (1064nm) 1 cloud and aerosol lidar (523nm) http://earthobservatory.nasa.gov/Features/ICESat/ Mission life time 2003-2009 Developed by NASA One scientific instrument Ice sheets; vegetation

17. ReCover for REDD and sustainable forest management 17 3 Lasers of non-continuous 40 shots per second 33-day to 56-day campaigns, footprint ~52m to 148m (70m) Laser spot separation along track ~175m 4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

18. ReCover for REDD and sustainable forest management 18 Data distribution by National Snow and Ice Data Centre 15 standard GLAS products, binary file format GLA01 product Transmitted and received waveform parameters GLA14 product Global land surface altimetry data Up to 6 Gaussian peaks fitted to waveform Range increments Quality flags (cloud, saturation, range correction..) 4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

19. ReCover for REDD and sustainable forest management 19 signal begin signal end ground GLAS derived canopy height 4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

20. ReCover for REDD and sustainable forest management 20 ICESat’s heights (pink & green ellipses = footprint) Airborne Laser Scanning (ALS) point cloud (blue) Digital terrain model by ALS data 4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

21. ReCover for REDD and sustainable forest management 21 Vegetation height map

22. ReCover for REDD and sustainable forest management 22 5. ReCover workshop and field trip (October 2012) ReCover workshop –Participants: Forestry, GIZ, SOPAC and ReCover team –Presenting the ReCover project and status of remote sensing based products –Joint work & data exchange with Forestry and SOPAC Joint ReCover field trip (SOPAC & ReCover team) ReCover work will be continued –Product refinement and validation –Joint work and data exchange

23. ReCover for REDD and sustainable forest management 23 Vinaka vaka levu! http://www.vtt.fi/sites/recover/?lang=en