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

2. It’s me! big Trees are …

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

11. community 1day 10days (3.3mt) 100days (2.7yr) 1Kdays (27.4yr) 10Kdays 1mt 1yr 10yr 1m10m100m1km10km100km1,000km Spatial Temporal individ. trees small watershed large watershed Temporal & spatial scales of the sensors LANDSAT MSS/TM/ETM+ NOAA AVHRR ALOS PRISM Sensor Operation lifetime Observation frequency Spatial resolution Observation swath SPOT HRV-P Terra/Aqua MODIS IKONOS/QuickBird

12. 1日1日 10 日 (3.3 月 ) 100 日 (2.7 年 ) 1 千日 (27.4 年 ) 1 万日 1月1月 1年1年 10 年 1m10m100m1km10km100km1,000km 空間 時間 individ. trees community small watershed large watershed Temporal & spatial scales of the sensors LANDSAT MSS/TM/ETM+ NOAA AVHRR ALOS PRISM Sensor Operation lifetime Observation frequency Spatial resolution Observation swath SPOT HRV-P Terra/Aqua MODIS IKONOS/QuickBird LowMedHigh Spatial resolution

13. Trade-offs to date of spatial 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! Conserve valuable ecosystems See beautiful sceneries Need timbers Raise profits Off-limit Connect pts by walkways Harvest, re- & afforestation Slash & burn, golf courses Aims / incentivesActions Study the ecophysiologyExperiments

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