EG2211Earth 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?

Estimation of a physical quantity Proxy environmental variables Application driven Less science and more operational Makes use of algorithms Interfaces with environmental models

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

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

Rainfall estimation

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

Cold Cloud Duration (CCD):

Rainfall estimation

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)

Tropical Rainfall Measuring Mission (TRMM):

Rainfall estimation

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)

Tropical Rainfall Measuring Mission (TRMM):

Rainfall estimation

System coordinated by NOAA Became operational in 1987 Uses a 7-channel passive microwave

radiometer

Special Sensor Microwave Imager (SSM/I):

Rainfall estimation

Data collected from the SSM/I are used to estimate several geophysical 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!)

Special Sensor Microwave Imager (SSM/I):

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

Other quantitative measurements

NDVI Albedo Wind speed Potential Evapotranspiration (PET) Soil moisture Tropospheric humidity

NDVI

•Monitoring•Habitat modelling•Hydrology

VISIBLE

•Albedo•Weather Fcst.

WATERVAPOUR

•Cloud motion•Troposphere

Disaster Management

Uses of RS for Disaster Management

Wildfires Volcanic eruptions Avalanche Tsunami Earthquake Landslides Flooding Extreme weather Drought Disease Refugees Military

Disaster Management

DisasterManagement

PLANNING

MITIGATIONLEARNING

Disaster Management

PLANNING MITIGATION

ModellingAssessmentPredictionContingency

Monitoring situationsDeployment of resourcesDecision-makingPublic relations

COST EFFECTIVENESS !!!

QuickBird used extensively throughout Asian Tsunami Disaster

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

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

Hydrodynamics

stream stream

stream

stream

riverriver river

estuary

THE SEA

Hydrodynamics

From DeMers, 2002

Hydrodynamics

From DeMers, 2002

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

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

Case Studies – Timetable

Topic Lecture/workshop

Week beginning

Agriculture 22/1/2007

Weather forecasting

29/1/2007

Human health 5/2/2007

Disasters 12/2/2007

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

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

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/