1. Remote sensing is up! Inventory & monitoring Inventory – To describe the current status of forest Landcover / landuse classification Forest structure / functionality estimation Monitoring – To trace temporal changes of forest Expectable changes: growths, management activities Unexpected changes: disasters, illegal activities

2. Landuse classification by Landsat TM 01020 km 01020 Plate 2

3. Clearcuts in Russian Far East 1980 1985 1980 1990 1985 1996 1990 1999 1996 1980 1985 1980 1990 1985 1996 1990 1999 1996 Plate 5

4. Modern sensors Optical (excl. thermal) – High spatial resolution – Hyperspectral – Aerial photo Radar (SAR; Synthetic Aperture Radar) LiDAR (Light Detection And Ranging) – Large footprint – Small footprint

5. Optical – High spatial resolution Able to identify individual tree crowns – Count trees – Measure sizes (from above!!!) – Interpret forest structure – Accurate locating by GPS

6. Stand density estimation by high resolution images LANDSAT TM IKONOS Cedar plantations white dots: tree tops Tree densities DenseSparse Courtesy: N. Furua, FFPRI 160m3km Stand densities

7. Optical – Hyperspectral Very large number of narrow wavelength bands Spectral Reflectance Band 1 Band 2Band 7Band 5 Band 4 Band 3 VISNIR Landsat TM/ETM+ 224 Bands AVIRIS

8. Optical – Hyperspectral Forest applications – Species identification – Accurate classification – Chemical contents of leaves – Stress detection (red edge shift) Water/Disease/etc. Available sensors – Space-borne Hyperion (EO-1) – Air-borne AVIRIS/CASI/AISA/etc.

9. Optical – Aerial photo Surface model from stereo pairs of aerial photo – Automatic calculation – Canopy height (change) detection Retrospectively monitor by old photos Cheaper than LiDAR Mori (2004) http://www.kri.sfc.keio.ac.jp/report/mori/2004/c-67/mori_h16_sawa.pdf

10. SAR Active sensor using microwaves Responses of objects depend on their permittivity, shapes and sizes Waves penetrate much smaller objects than their wavelengths – Waves can penetrate rain, clouds – Shorter waves cannot penetrate the surface of forest canopies X band: 3.24 cm C band: 5.66 cm L band: 24.0 cm P band: 68.1 cm For forests, – Canopy detection – Volume estimation

11. SAR http://www.radarsat2.info/application/for/for_rs2_hoekman_indo.pdf

12. SAR Available sensors – Space-borne ALOS PALSAR (L) JERS1 SAR (L) RADARSAT (C) TerraSARX (X) (to be launched)

13. LiDAR Light Detection and Ranging Distance and direction to object is measured by the traveling time and direction of laser pulses By scanning the pulses, the height distribution of the ground surface can be estimated in 3D Canopy height is derived by subtracting the ground height from the surface height – No other mean can directly measure the tree/canopy height – Strong correlations with tree dimensions, e.g. volume High accuracy and detailed data – ~10cm error

14. Courtesy: Y. Hirata, FFPRI LiDAR Small footprint 木木 One shot of laser GPS IMU Time First pulse last pulse LiDAR: Light Detection And Ranging Laser pulse density: 22.5pts/m 2 Detected tree tops: 551 trees out of 657 trees = 83.9 ％ The technology has been adopted to the National Forest Inventories in North European coutnries