Pacific island gis rs conference 2012 27 30 november 2012 suva
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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. Outline.

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Pacific Island GIS&RS conference 2012, 27 – 30 November 2012, Suva

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Pacific island gis rs conference 2012 27 30 november 2012 suva

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


Outline

Outline

  • ReCover project objective

  • ALOS PALSAR change detection and time-series analysis

  • MODIS time-series analysis for forest change detection

  • ICESat/GLAS space borne laser ranging for forest height & biomass

  • ReCover workshop and field work (October 2012)


1 eu recover project objective

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


2 alos palsar change detection and time series analysis

2. ALOS PALSAR change detection and time-series analysis

  • 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


Alos palsar dual temporal 2007 2010 coverage of west viti levu

ALOS PALSAR: Dual-temporal (2007,2010) coverage of west VitiLevu

2. ALOS PALSAR change detection and time-series analysis

2010-08/09

2007-08/09


Forest land cover change detection viti levu west 2007 2010 first results need to be evaluated

Forest land cover change detection (VitiLevu west) 2007 - 2010 (first results, need to be evaluated)

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

Water mask

Positive change (e.g. reforestation)

Positive change (e.g. reforestation)

Negative change

Negative change

Forest/dense vegetation -> non-forest

Forest/dense vegetation -> non-forest

Other vegetation decrease

6

Other vegetation decrease


Time series examples

Time-series examples

2. ALOS PALSAR change detection and time-series analysis

Stable forest


Time series examples1

Time-series examples

2. ALOS PALSAR change detection and time-series analysis

Deforestation of pine plantagen


Time series examples2

Time-series examples

2. ALOS PALSAR change detection and time-series analysis

Regrowth


3 modis ndvi time series for forest change detection using bfast algorithm verbesselt et al

3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.)

  • 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/)


3 modis ndvi time series for forest change detection using bfast algorithm verbesselt et al1

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

  • Stable tropical forest pixel

    NDVI


    3 modis ndvi time series for forest change detection using bfast algorithm verbesselt et al2

    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

  • Deforestation pixel

    NDVI


    3 modis ndvi time series for forest change detection using bfast algorithm verbesselt et al3

    3. MODIS NDVI time-series for forest change detection using BFAST algorithm (Verbesselt et al.)

    • If break detected -> Output:

      • Date of change

      • Magnitude of Change (compared to historical period)

    Deforestation pixel


    Modis ndvi analysis analysis fiji results

    MODIS NDVI analysis analysis Fiji – Results

    Year of change


    Apply modis ndvi time series algorithm at landsat time series 30m pixel resolution

    Apply MODIS NDVI time-series algorithm at Landsat time-series (30m pixel resolution)

    2000-2012, Intensive cloud cover


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

    • Developed by NASA

    • Mission life time 2003-2009

    • Ice sheets; vegetation

    • One scientific instrument

    http://earthobservatory.nasa.gov/Features/ICESat/

    • Geoscience Laser Altimeter System (GLAS)

      • 1 precisionsurfacelidar (1064nm)

      • 1 cloudandaerosollidar (523nm)


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

    • 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


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

    • 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..)


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

    signal begin

    ground

    signal end

    GLAS derived canopy height


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    4. ICESat/GLAS: space borne laser ranging for vegetation height and biomass mapping

    ICESat’sheights (pink & green ellipses = footprint)

    Airborne Laser Scanning (ALS) point cloud (blue)

    Digital terrain model by ALS data


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    Vegetation height map


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    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


    Pacific island gis rs conference 2012 27 30 november 2012 suva

    Vinaka vaka levu!

    http://www.vtt.fi/sites/recover/?lang=en


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