Presentation on theme: "PhD remote sensing course, 2013 Lund University Understanding Vegetation indices PART 1 Understanding Vegetation indices PART 1 : General Introduction."— Presentation transcript:
PhD remote sensing course, 2013 Lund University Understanding Vegetation indices PART 1 Understanding Vegetation indices PART 1 : General Introduction Talk by Hongxiao Jin
Light interaction with canopy Transmittance and reflectance PART 1
Horizontal leaves Can be understood from optical path and cross-section area.
Leaf angle distribution probability density function: G( l ) Random leaves I I 0 i is the angle between sun beam and leaf normal Cross-section area Average ratio of shadow cast area onto horizontal surface to each single leaf area
The history of VIs NDVI Dr. John Rouse, the Director of the Remote Sensing Center of Texas A&M University where the Great Plains study was conducted with Landsat-1 PhD student Donald Deering and his advisor Dr. Robert Haas With the assistance of a resident mathematician (Dr. John Schell) To “normalize” the effects of the solar zenith angle
NDVI is simple, easy to use, by correlating with ground observation. and therefore, NDVI is over-used (abused) Use NDVI for LAI fAPAR fraction of vegetation cover water content preciptation Leaf nitrogen content chlorophyll concentration in leaf Biomass Plant productivity (GPP/NPP) Vegetation stress monitoring Vegetation disturbance Flowering phenology Rats activity Grazing monitoring …
NDVI~fAPAR Observed direct proportional relationship Attempt to prove it by prof. Knyazikhin The well-known fAPAR product only use this direct proportional relationship as backup algorithm to infer fAPAR from NDVI