PPT-Transferability of land surface model parameters using remote sensing and in situ observations

Author : sherrill-nordquist | Published Date : 2018-03-12

By Ben Livneh Overview Unified Land Model ULM was developed 1 Rigorous calibrations performed at 220 basins 2 Regionalizetransfer calibrated parameters Domain and

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Transferability of land surface model parameters using remote sensing and in situ observations: Transcript

By Ben Livneh Overview Unified Land Model ULM was developed 1 Rigorous calibrations performed at 220 basins 2 Regionalizetransfer calibrated parameters Domain and catchment attribute data sets. Francisco Chavez, M. Messie. Monterey Bay Aquarium Research Institute. F. Chai (U of Maine), Y. Chao (NASA/JPL), . David Foley (NOAA/NMFS), R. Guevara, M. Niquen (IMARPE) and R.T. Barber (Duke). Approach. Modelling. Research interests . Chris Brunsdon, Claire Jarvis, Lex Comber, Nick Tate, Jen Dickie, Pete Fisher, Kevin Tansey, Heiko Balzter, . Joerg Kaduk. www.le.ac.uk/geography. Research Areas. Spatial Analysis and . Sensing and Air Quality Applications. Richard Kleidman. Science Systems and Applications, Inc.. NASA . GSFC. ARSET - AQ. A. pplied. . R. emote. . S. E. nsing. . T. raining . –. . A. ir . Q. uality. By: Ben . Livneh. & Dennis . Lettenmaier. Overview. Unified Land Model (ULM) was developed. 1. Rigorous calibrations performed at 220 basins. 2. Regionalize/transfer calibrated parameters. Domain and catchment attribute data sets. Key RS contributions; timing and magnitude of disturbance; attribution (human/natural. ). Looks for TRENDS and EVENTS in the same . algorithm. Choice of spectral index matters (multi-proxy approach to improve certainty?). Bot/. Geog. 4111/5111. Ken Driese. Dept. of Botany . Group Activity: . Solving Remote Sensing Problems. How could you assess the effect of drought on plant biomass in California?. How could you map sage grouse habitat in Wyoming?. th . & 8. th. November 2013. Contents. Introduction. GMES .  Copernicus. Six thematic areas . Infrastructure. Space data. An introduction to Remote Sensing. In-situ data. Applications. Summary & Questions. Francisco Chavez, M. Messie. Monterey Bay Aquarium Research Institute. F. Chai (U of Maine), Y. Chao (NASA/JPL), . David Foley (NOAA/NMFS), R. Guevara, M. Niquen (IMARPE) and R.T. Barber (Duke). Approach. DeeDee Whitaker. SW Guilford High. EES & Chemistry. whitakd@gcsnc.com. Outline. What is remote sensing?. How does remote sensing work?. What role does the electromagnetic spectrum play in satellite imagery?. Principles, results, and challenges. Lecture at the ERCA . 2018. Grenoble, . January 18, 2018. Andreas Richter. Institute of Environmental Physics. University of Bremen. Bremen, Germany. ( . richter@iup.physik.uni-bremen.de. Co-Chairs: . . Part I - Kevin . Turpie. (UMBC GSFC), Cecile Rousseaux (USRA NASA). . Part II - Maria . Tzortiou. (CUNY), Emmanuel Boss (. Univ. of Maine). . Part III - Michelle . Gierach. (NASA JPL), Sherry Palacios (BAERI ARC). – . should be maximum three lines. . Olo. . que . liciumque. . porem. . harum. . hiliquidis. . ium. quo . doloreped. qui . aperum. . doluptia. . perumen. . ditatestia. qui . volupta. . spedipsusam. Corresponding author (phil.teillet@ccrs.nrcan.gc.ca). 1. INTRODUCTION Over the next few years, the nature of remote and in situsensing and their relationship with the Internet will change drastically Course Objectives. To expose students to a broad spectrum of satellite remote sensing methods to derive geophysical parameters of interest. To provide students with the understanding necessary to distinguish between algorithm fundamentals and nuanced implementation details.

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