Monitoring Seasonality in Phenology of Amazonian Rainforests Using MISR and MODIS Data

Yuri Knyazikhin1, Jian Bi2, Sungho CHOI2, Taejin Park3,4 and Ranga B Myneni1, (1)Boston University, Earth and Environment, Boston, MA, United States, (2)Boston University, Boston, MA, United States, (3)Korea University, Seoul, Korea, Republic of (South), (4)Boston University, Earth and Environment, Boston, United States
Abstract:
Monitoring of dense vegetation such as Amazonian rainforests represents the most complicated case in remote sensing because reflectances saturate and are weakly sensitive to changes in canopy properties. A new approach to interpret such data based on analyses of angular signatures of radiation reflected by dense vegetation is discussed in this poster. This approach was applied to monitor seasonality in phenology of Amazonian rainforests using data from Terra MODIS, MISR and Aqua MODIS sensors. These three independent satellite datasets consistently show higher greenness level during the dry season relative to the wet season. This result is consistent with the light limitation hypothesis, i.e., light is the limiting factor for productivity of well-hydrated equatorial Amazonian rainforests.