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EG2211 Earth Observation

EG2211 Earth Observation. Applications of Remote sensing. TOPICS. Quantitative remote sensing Rainfall estimation Land surface temperature Proxy air temperature NDVI, albedo, wind-speed and others Disaster Management Human Health Hydrodynamics. Quantitative remote sensing?.

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EG2211 Earth Observation

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  1. EG2211Earth Observation Applications of Remote sensing

  2. TOPICS • Quantitative remote sensing • Rainfall estimation • Land surface temperature • Proxy air temperature • NDVI, albedo, wind-speed and others • Disaster Management • Human Health • Hydrodynamics

  3. Quantitative remote sensing? • Estimation of a physical quantity • Proxy environmental variables • Application driven • Less science and more operational • Makes use of algorithms • Interfaces with environmental models

  4. Applications that use quantitative RS • Agriculture • NDVI, temperature, rainfall • Health • NDVI, temperature, rainfall, dust, wind • Hydrology • Rainfall • Climate change • NDVI, temperature, rainfall • Weather forecasting • Winds, rainfall

  5. Rainfall estimation • Cold Cloud Duration (CCD) using Meteosat • Tropical Rainfall Measuring Mission using radar (TRMM) • Special Sensor Microwave Imager (SSM/I) rainfall measurement using microwave instruments

  6. Rainfall estimation Cold Cloud Duration (CCD): • Pioneered by work of Lethbridge, 1967 • Became an operational system thanks to Milford and Dugdale at TAMSAT (University of Reading) • Based on relationship between period during which convective cloud tops are below a specific threshold and rainfall measured beneath them

  7. Rainfall estimation Tropical Rainfall Measuring Mission (TRMM): • TRMM mission is a joint US/Japan effort coordinated by NASDA (National Space Development Agency of Japan) • TRMM was launched in 1997 – with an initial mission life of 3 years • TRMM data is relayed to NASA Goddard Space Flight Center (GSFC)

  8. Rainfall estimation Tropical Rainfall Measuring Mission (TRMM): • Precipitation Radar (PR) • TRMM Microwave Imager (TMI) • Visible and Infrared Scanner (VIRS) • Clouds and the Earth’s Radiant Energy System (CERES) • Lightning Image Sensor (LIS)

  9. Rainfall estimation Special Sensor Microwave Imager (SSM/I): • System coordinated by NOAA • Became operational in 1987 • Uses a 7-channel passive microwave radiometer

  10. Rainfall estimation Special Sensor Microwave Imager (SSM/I): Data collected from the SSM/I are used to estimate severalgeophysical parameters including: • Rainfall Rate • Rainfall Frequency • Cloud Liquid Water • Cloudiness Frequency • Total Precipitable Water • Snow Cover • Sea-Ice • Sampling Frequency • Ocean Surface Wind Speed (1.0 degree only!)

  11. Land Surface Temperature • Thermal infrared images provide an estimate of the magnitude of radiant energy • Radiance (usually expressed as watts per square metre) can be converted to temperature via an instrument-specific algorithm • Energy (and hence temperature) is of the land surface (LST) • LST may be converted to a proxy air temperature by means of a solar correction algorithm

  12. Other quantitative measurements • NDVI • Albedo • Wind speed • Potential Evapotranspiration (PET) • Soil moisture • Tropospheric humidity

  13. NDVI • Monitoring • Habitat modelling • Hydrology

  14. VISIBLE • Albedo • Weather Fcst.

  15. WATER VAPOUR • Cloud motion • Troposphere

  16. Disaster Management • Wildfires Volcanic eruptions • Avalanche Tsunami • Earthquake Landslides • Flooding Extreme weather • Drought Disease • Refugees Military Uses of RS for Disaster Management

  17. Disaster Management PLANNING Disaster Management LEARNING MITIGATION

  18. Disaster Management PLANNING MITIGATION Monitoring situations Deployment of resources Decision-making Public relations Modelling Assessment Prediction Contingency COST EFFECTIVENESS !!!

  19. QuickBird used extensively throughout Asian Tsunami Disaster

  20. Human Health • Health and disease often has a spatial component • Climatic, environmental and socio-economic variables affect health • Epidemics and outbreaks spread across a region – either as a function of movement of people or environmental factors

  21. Human Health • Many countries are vulnerable to diseases directly influenced by the environment • Vector-borne diseases (like malaria) • Respiratory illnesses (like meningitis) • Water-borne diseases (like cholera) • Stress illnesses (heat-stroke or hypothermia) • Illnesses caused by “mechanical” effects of extreme weather events

  22. Hydrodynamics stream stream stream river river river stream estuary THE SEA

  23. Hydrodynamics From DeMers, 2002

  24. Hydrodynamics From DeMers, 2002

  25. Case Studies • Until mid-February we will be examining specific case studies where RS is used • Case studies will be: • Agriculture • Weather Forecasting • Human Health • Disaster Management and Emergencies

  26. Case Studies • Lecture session will provide basic material related to topic – but groups will have to prepare their own material and presentations for the workshop • Everybody will be assigned to a case-study group and will have to turn up to one workshop session following the lecture

  27. Case Studies – Timetable

  28. Case Studies – Timetable • You will ALL have to attend the second hour (workshop) covering each topic. You will have to take notes from the other groups presenting and record their literature references • Workshops will be based around Q&A sessions (questions from YOU) and a short group presentation

  29. Further Reading Cresswell MP, Morse AP, Thomson MC and Connor SJ. (1999). Estimating surface air temperatures from Meteosat land surface temperatures using an empirical solar zenith angle model. International Journal of Remote Sensing, Vol 20 (6), 1125-1132. Lethbridge M. (1967). Precipitation probability and satellite radiation data. Monthly Weather Review, Vol 95 (7), 487-490 Milford J and Dugdale G. (1990). Estimation of rainfall using geostationary satellite data. In Applications of Remote Sensing in Agriculture. Edited by Steven M and Clark J. Published by Butterworths, London Dugdale G, Hardy S and Milford J. (1991). Daily catchment rainfall estimated from Meteosat. Hydrological Processes, Vol 5, 261-270

  30. Further Reading TRMM Website: http://www.eorc.nasda.go.jp/TRMM/index_e.htm SSM/I Website: http://orbit-net.nesdis.noaa.gov/arad2/ TAMSAT (CCD Rainfall) Website: http://www.met.reading.ac.uk/tamsat/

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