Joint GFOI/GOFC-GOLD Expert Workshop 2: Approaches to monitoring forest degradation for REDD+

Transcription

1 Joint GFOI/GOFC-GOLD Expert Workshop 2: Approaches to monitoring forest degradation for REDD+ Forest carbon monitoring for REDD MRV with satellite 3D SAR Svein Solberg Norwegian Forest and Landscape Institute Wageningen, The Netherlands 1-3 October, 2014

2 Interferometric X-band SAR Orinoco, Colombia 2

3 Project background: Context, geographical location, type of degradation 1. Operational forest management, REDD 2. Norway, Tanzania, Indonesia 3. Storm damage and thinning, forest degradation, reduced impact logging, forest growth InSAR height 3

4 Relevant science papers published 1. Solberg, S., Astrup, R., Gobakken, T., Næsset, E., & Weydahl, D.J EsDmaDng spruce and pine biomass with interferometric X- band SAR. Remote sensing of environment. 114: Solberg, S., Weydahl, D.J. & Næsset, E SimulaDng X- band interferometric height in a spruce forest from airborne laser scanning. IEEE transacdons on geoscience and remote sensing. 48(9): Solberg, S., Astrup, R., Bollandsås, O.M., Næsset, E., & Weydahl, D.J Deriving forest monitoring variables from X- band InSAR SRTM height. Canadian Journal of remote sensing. 36(1): Næsset, E., Gobakken, T., Solberg, S., Gregoire, T.G., Nelson, R., Ståhl, G., Weydahl, D Model- assisted regional forest biomass esdmadon using LiDAR and InSAR as auxiliary data: A case study from a boreal forest area. Remote Sensing of Environment 115: Morrison, Keith, John Benne` & Svein Solberg, Ground- based C- band tomographic profiling of a conifer forest stand, InternaDonal Journal of Remote Sensing, 34:21, Solberg, S.; Astrup, R.; Breidenbach, J.; Nilsen, B.; Weydahl, D Monitoring spruce volume and biomass with InSAR data from TanDEM- X. Remote Sens. Environ. 139, Solberg, Svein; Astrup, Rasmus; Weydahl, Dan J "DetecDon of Forest Clear- Cuts with Shu`le Radar Topography Mission (SRTM) and Tandem- X InSAR Data." Remote Sens. 5, no. 11: Solberg, Svein, Gertrud Riegler, Philippe Nonin, EsDmaDng forest biomass from TerraSAR- X stripmap radargrammetry. IEEE transacdons on geoscience and remote sensing, 53(1): Solberg, S., Næsset, E., Gobakken, T. & Bollandsås, O.- M Forest biomass change esdmated from height change in interferometric SAR height models. Carbon Balance and Management. 9:5: Solberg, S., Weydahl, D.J. & Astrup, R Temporal stability of X- band single- pass InSAR heights in a spruce forest: Effects of acquisidon properdes and season. IEEE transacdons on geoscience and remote sensing. In press. 4

5 Availability of programs or tools and possibility for sharing Alt 1: working with DEM data: No problem, however; DEM correcdon Alt 2: InSAR processing: Soiware and tools available (ENVI Sarscape, Gamma, Erdas, ) 5

6 Methodology: Approach to mapping / monitoring degradation / enhancement of Carbon stocks Tanzania 6

7 Tanzania Methodology: Change categories Height change Coherence Deforestation Degradation Forest gain / growth Forest no-change 7

8 Methodology: satellite data requirements Data types/sensors: Bi- stadc, InSAR: Tandem- X, SAOCOM- CS / TangoSAT, Tandem- L Repeat- pass radargrammetry: TerraSAR- X, Cosmo Skymed Coverage: (regional/sub- /nadonal/global) Global Any SpaDal and Temporal resoludon ~10 m 1 year 8

9 Methodology: Calibration and validation EsDmates of biomass change , t/ha Norway InSAR Field inventory Solberg, S., Næsset, E., Gobakken, T. & Bollandsås, O.-M Forest biomass change estimated from height change in interferometric SAR height models. Carbon Balance and Management. 9:5: 1-12.

10 Methodology: Calibration and validation Stable and linear reladonship, except winter Norway Field measured AGB InSAR height Solberg, S.; Astrup, R.; Breidenbach, J.; Nilsen, B.; Weydahl, D Monitoring spruce volume and biomass with InSAR data from TanDEM-X. Remote Sens. Environ. 139,

11 Methodology: Calibration and validation EsDmates of biomass change , t/ha Norway InSAR Airborne laser scanning Solberg, S., Næsset, E., Gobakken, T. & Bollandsås, O.-M Forest biomass change estimated from height change in interferometric SAR height models. Carbon Balance and Management. 9:5: 1-12.

12 Methodology: Calibration and validation InSAR height change vs forest management records Norway Clearcut Thinning Storm damage and clearing 12

13 Methodology: Calibration and validation InSAR height change vs forest management records Indonesia Reduced impact logging 13

14 Methodology: Calibration and validation InSAR vs Global Forest Watch Tanzania Loss Gain

15 Methodology OperaDonal status of the exisdng technology: - R&D Does your approach provide a cost- effecdve soludon? - Commercial data <- > accurate data 15

16 Technical Challenges 1. Describe the obstacles to operadonal (widespread) use 1. SRTM DEM errors 2. SAR / GIS processing 2. Is ongoing access to data a concern? 1. Satellite data condnuity 2. Data cost Large- scale differences between X- and C- band SRTM 3. Are the methods limited by a lack of automadon or simplicity? 1. No (?) 4. Are your IT/infrastructure needs met? 1. Yes

17 R&D requirements 1. Indicate the nature of the R&D required to advance the methods to operadonal use 1. CorrecDon C- to X- band DEM 2. Model reladonship with field measured AGB 3. Seasonality, leaf- on / leaf- off 2. What are the Dmelines for compledng the development? 1. Autumn 2014 for BAU baseline 2. Summer 2015 for monitoring 3. Describe your satellite data set requirements 1. Bi- stadc X-, C- or L- band SAR 2. AlternaDvely repeat- pass P- band SAR 3. AlternaDvely repeat- pass X- or C- band SAR for radargrammetry 4. Is your approach transferable in a tropical/redd+ monitoring context? 1. Yes

18 Rate the importance of the following with respect to your R&D ac7vity Access to free satellite data and archives for R&D Provide input to SDCG/space agencies to ensure systemadc acquisidons of consistent satellite data New research partnerships and coordinated response to open calls for funding Assist in capacity building and technology transfer in REDD countries Discussions at polidcal level to encourage support of the science Future contribudon to GFOI Methods and Guidance DocumentaDon and GOFC- GOLD Sourcebook ParDcipaDon in future targeted workshops such as this one ParDcipaDon in an Annual Science MeeDng with open invitadon to government/industry/academia/research partners Others? Funding High- Med- Low High Low Low Low Med High High Med High

19 AddiDonal slides in case of quesdons 19

20 InSAR height stability in tropical rainforest Kapuas, Indonesia Acquisi7on H, m Temp, C Rain, mm Dry Wet Wet Wet Wet

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22 Clear cuts Recorded clear cuts InSAR height changes

23 A profile of height changes, Tanzania

24 Kapuas, Indonesia Forest heights 0-40 m Feb Aug Jun km 28 km

25 Kapuas, Indonesia Forest height changes m

26 Clear- cuts miombo forest, Tanzania Optical satellite image InSAR height change km Value High : 10 Low : -10