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Trend in Remote Sensing Technology for Forest Measurement & Monitoring

Trend in Remote Sensing Technology for Forest Measurement & Monitoring. Gen Takao CIFOR. Trees are …. It’s me!. big. Measurement is. a hard job. Visibility is. limited. Area is. vast. Changes occur. slowly & for long. Can be destroyed. instantly. Forest remote sensing.

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Trend in Remote Sensing Technology for Forest Measurement & Monitoring

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  1. Trend in Remote Sensing Technology for Forest Measurement & Monitoring Gen Takao CIFOR

  2. Trees are … It’s me! big

  3. Measurement is a hard job

  4. Visibility is limited

  5. Area is vast

  6. Changes occur slowly & for long

  7. Can be destroyed instantly

  8. Forest remote sensing • simultaneity • can observe remote area at once • periodicity • can observe repeatedly • recordability • can observe retrospectively

  9. Contents • How do we measure forests using RS? • Modern sensors and technique of RS • Do we actually tell you the truth by RS?

  10. 小樽 札幌 羊蹄山 支笏湖 Scales of forest and remote sensing MODIS 分解能 500m TM/ETM+ 分解能 30m IKONOS PS 分解能 1m x 2048 x 1024 x 4096 x 512 x 256 x 128 x 16 x 32 x 64 x 4 x 2 x 8 x 1 グリッド 50 m グリッド 500 m グリッド 5 km グリッド 50 km

  11. Temporal Operation lifetime Observation swath Spatial resolution (27.4yr) 10Kdays Sensor SPOT HRV-P 10yr (2.7yr) 1Kdays 1yr Observation frequency (3.3mt) 100days 1mt 10days 1day 1m 10m 100m 1km 10km 100km 1,000km Spatial Temporal & spatial scales ofthe sensors LANDSAT MSS/TM/ETM+ NOAA AVHRR large watershed small watershed ALOS PRISM IKONOS/QuickBird community Terra/Aqua MODIS individ. trees

  12. 時間 Operation lifetime Observation swath Spatial resolution (27.4年) 1万日 Sensor 10年 (2.7年) 1千日 1年 Observation frequency (3.3月) 100日 1月 10日 1日 1m 10m 100m 1km 10km 100km 1,000km 空間 Temporal & spatial scales ofthe sensors High Med Low Spatial resolution LANDSAT MSS/TM/ETM+ NOAA AVHRR SPOT HRV-P large watershed small watershed IKONOS/QuickBird ALOS PRISM community Terra/Aqua MODIS individ. trees

  13. Trade-offs to date ofspatial and temporal resolution • Low spatial resolution(≧ 100m) • Temporal: high globally • Rapid changes in a wide area, e.g. phenology, fires • Medium spatial resolution(≧ 10m) • Temporal: not so high globally • Current condition/temporal changes of vegetation • High spatial resolution (＜ 10m) • Temporal: can be very high at specific targets, but very low globally • Current condition of an area of interest

  14. Relative size of the spatial resolution to the objects • Resolution >> Object (L-resolution) • Averaged objects • Forest canopy • Resolution << Object (H-resolution) • A piece composing an object • Individual tree crown • Resolution ～ Object • Maximum variance Crown sizes are so variable that often you cannot choose the relative size!

  15. Why do we want to know forest? • Because we want to manage it for us! Aims / incentives Actions Conserve valuable ecosystems Off-limit See beautiful sceneries Connect pts by walkways Harvest, re- & afforestation Need timbers Raise profits Slash & burn, golf courses Study the ecophysiology Experiments

  16. Forest management, plan and measurement management A would-be forest A forest now Remote Sensing is Up! Inventory measurement Monitoring Planning Plan Implementation Do Evaluation See

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