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G4INDO project Satellite Monitoring Component
G4INDO project Satellite Monitoring Component Niels Wielaard Dirk Hoekman Eric van Valkengoed G4AW all-partner Meeting Lor Interntional Hotel Bogor 09.10.2014 Introduction PusAir Radar and optical satellite-based monitoring of crops, core datasets: - Sentinel 1A,1B = SAR – 20-30 m resolution - Sentinel 2A, 2B = optical – 10 m resolution @ LAPAN @ Protata (NDI) Crop insurance system separate database (incl. information of clients) Monitoring of current conditions (TRMM, station data, status water levels rivers and reservoirs) + Seasonal climate forecasts (ECMWF, station-based) Hydrological models + Crop growth models DEWS @ BMKG Dynamic cropping calendar (KATAM) @ Balitbangtan Advice to farmers Introduction Cooperation LAPAN - SarVision - Wageningen University – TerraSphere Background NL partners: • Large crop monitoring projects e.g. Indonesia and Bangladesh since 1998 • Extending successful radar cooperation with LAPAN on forest and land cover monitoring to agriculture with new European satellites (Sentinel-1/2) Objective: • build new semi-automated satellite image processing system together, • building on and complementing ongoing programs of LAPAN and others, • fully based on requirements of Indonesia (insurance system, hardware) • operated in Indonesia at LAPAN Enabling cost-effective insurance and support to agricultural crop statistics, early warning and crop advice by improving dynamic crop calendar New era in satellite monitoring New era in agricultural crop monitoring using (radar) satellites: • Better information : new satellites with improved information content • More frequent information : new radar satellites that can see through clouds and haze enabling reliable very frequent ‘time-series’ observations at high detail every 2-6 days • Larger area coverage at higher detail : new semi-automated processing techniques area available for analysis and efficient large datasets • More affordable : 10-30m data available for free, 5m at low cost 10 - 30m spatial resolution Radar : ASAR, Sentinel-1A/B Optical: Landsat 8, Sentinel-2A/B, SPOT-4/5/6/7 1 - 5m spatial resolution Radar : TerraSAR-X/PAZ/CosmoSkymed New era in satellite monitoring What can be monitored using (radar) satellites: • Which land use / crop types, crop varieties are planted where, how many hectares? • When and where is soil prepared, planted when is the start of season? • What are different growth stages and biomass increase or decrease at different times? Support estimation of expected and actual yield. • Which areas are flooded, at what times and for how long? What risk past 10 years? What is the timing and extent of crop damages and losses such as caused by floods, droughts, pests and disease? Satellite monitoring can reduce (or replace) costly and time-consuming ground data collection. It can improve statistics. Provides historical data to assess risk trends and performance over time! New possibilities: radar and time-series Big problems with Vegetation Index normal satellites: clouds, haze and smoke Radar ‘sees’ through it New possibilities: radar and time-series New possibilities: radar and time-series Now becomes possible to cover very large area, at high detail, more frequent: -> From 6.25ha detail to 0.1ha detail, from every 16 days to every 5 days Powerful method for semi-automated analysis of hundreds of satellite images. New possibilities: radar and time-series Now becomes possible to cover very large area, at high detail, more frequent: -> From 6.25ha detail to 0.1ha detail, from every 16 days to every 5 days Powerful method for semi-automated analysis of hundreds of satellite images. Radar time-series monitoring Different crop growth stages detected by change of satellite signal over time, example Rice time-series monitoring at 10-30m Courtesy European Space Agency Colour picture made from 3 different dates of Envisat ASAR images, West Java Temporal signatures rice growing areas: green-red, urban areas: white Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 10-30m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice time-series monitoring at 5m 1 Nov 13 15 Nov 13 29 Nov 13 13 Dec 13 27 Dec 13 10 Jan 14 24 Jan 14 7 Feb 14 21 Feb 14 7 Mar 14 21 Mar 14 4 Apr 14 18 Apr 14 1 May 14 Rice at 5m resolution every 5-11 days Sharp results: Multi-temporal filtering 5m can solve marginal size (0.3 hectares) and scattered Rice time-series monitoring at 5m Floods time-series monitoring at 10-100m Time series of PALSAR Wide images animation Good visual impression of the flooding dynamics in the areas of focus Black: open water Bright white: flooded areas covered by tree canopy) Example from East Java Courtesy JAXA Example of multi-temporal ALOS radar, Nganjuk, Jombang, Kediri, East Java Colours: e.g. different times of planting and harvesting, number of crops Example from East Java Courtesy JAXA Example of multi-temporal ALOS PALSAR, Nganjuk, Jombang, Kediri, East Java Blue colour: where is the water and when?? Information for irrigation and forecast Toward near realtime flood monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: flooding detected, Jan 2007 Toward near realtime flood monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Apr 2007 Toward near realtime flood monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Jun 2007 Toward near realtime flood monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Jul 2007 Toward near realtime flood monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Sep 2007 Toward near realtime flood risk monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Oct 2007 Toward near realtime flood risk monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Dec 2007 Toward near realtime flood risk monitoring How much urban and crop area and how many people affected? Use PALSAR L-band: flooding under vegetation Use Sentinel C-band: flooding open areas Every 5 days 25m resolution PALSAR less frequent BLUE: Flooding detected, Dec 2007 To conclude Cooperation LAPAN - SarVision - Wageningen University – TerraSphere • Build new semi-automated satellite image processing system together, fully based on requirements of Indonesia and operated in Indonesia at LAPAN • Use new radar satellites building on and complement existing programmes • • • • Results can help enable safe farming: access to insurance and finance Results can help improve crop yield forecast using actual data Results can help improve flood risk history and forecast using actual data Results can help improve accuracy of crop statistics Next steps November – March: 1. Select area and discuss technical specifications needed (for insurance) 2. Start first satellite observations and collect field photos of crop growth Suggestions? New era in satellite monitoring New era in agricultural crop monitoring using (radar) satellites: • Better information : new satellites with improved information content • More frequent information : new radar satellites that can see through clouds and haze enabling reliable very frequent ‘time-series’ observations at high detail (every 2-6 days) • Larger area coverage at high detail : new semi-automated processing techniques area available for analysis and efficient large datasets • More affordable : 20-30m data available for free Reliable radar observations can be made every 2-6 days: • 1- 5m spatial resolution radar : TerraSAR-X/PAZ/CosmoSkymed • 20-30m spatial resolution radar : ASAR, Sentinel-1 Optical: Landsat 8, Sentinel-2 New era in satellite monitoring Type Sensor Resolution Update frequency Available Good for Radar ALOS-1, ALOS-2 PALSAR Fine/Scan 20-100m 10-60m Every 45 days Every 14-40 days 2006-2011 As of November 2014 Land cover, biomass wetlands, crop growth Radar ERS, ASAR, Sentinel1A 20-30m Every 35 days Every 12 days 2002-2012 As of July 2014 Cover change, floods, crop growth Radar Sentinel-1A+1B 20-30m Every 5 days As of Dec 2015 Cover change, floods Optical Landsat+Sentinel-2 20-30m Every 5 days 2015 Land cover, cover change, floods, crop growth Radar TerraSAR-X+PAZ 3-5m Every 11 (5/6 ) days Daily Since 2008 As of January 2015 Cover change, crop growth Optical MODIS 250m Daily 2000-now Land cover, cover change, floods, crop growth Optical RapidEye 5m Frequent 2009-now Land cover, cover change Optical Planet Labs 3m Daily 2014-2015 Cover change, floods Optical UAV (drone) 5-50cm now Land cover, biomass, yield etc. small areas Rice at 5m resolution every 5-11 days Sharp results: Multi-temporal filtering 5m detail suitable for monitoring of small farms Rice at 5m resolution every 5-11 days 26 June 2012 12 July 2012 13 Aug 2012 21 Sep 2012 28 July 2012 30 Sep 2012 Results courtesy of:
