OpenNEX: Characterization of the Water, Carbon and Energy Cycles using Remote Sensing Observations скачать в хорошем качестве

OpenNEX: Characterization of the Water, Carbon and Energy Cycles using Remote Sensing Observations

Dr. S. Hamed Alemohammad (February 16, 2017) The main drivers of biodiversity on the Earth are the water, carbon and energy cycles and their interconnections, which govern the exchange of moisture, energy and mass between the land surface and the atmospheric boundary layer. These cycles are inter-linked through complex and nonlinear processes with large spatial and temporal variability. Therefore, turbulent fluxes from the land surface to the atmosphere and soil moisture, as a state variable at the boundary of the land and the atmosphere, are key to understanding ecosystem response to climate. Moreover, knowledge of these fluxes are necessary for constraining the global carbon, water and energy cycles. In this talk, first I will review recent studies on characterizing the feedbacks between biosphere and atmosphere using remote sensing observations and the role of soil moisture as a memory. Next, I present results from a set of airborne field campaigns on using a low frequency (P-band) Synthetic Aperture Radar (SAR) instrument to estimate surface and vegetation properties across different biomes. P-band SAR observations can be used to estimate root zone soil moisture and provide a better constraint on estimating water and carbon fluxes from the land surface to the atmosphere. Finally, I will introduce a new neural network based retrieval algorithm to estimate global gross primary productivity, and latent and sensible heat fluxes using remotely sensed Solar Induced Fluorescence (SIF) and other radiative and meteorological variables. Neural networks have high capability in characterizing non-linear relationships, and I will discuss how they can be applied to remote sensing observations to better monitor different variables of the water, carbon and energy cycles.