Research in Earth ObservationProf. Mike Barnsley,

Department of Geography,

University of Wales Swansea.

Outline of Presentation

• Inferring land surface biophysical and biochemical properties from space;

• Universities and industry in partnership: CHRIS/PROBA — a “SmallSat” mission;

• Identifying the ‘brown field’ sites — mapping and monitoring land use within urban areas.

Global Environmental Monitoring

• Involved in several international satellite sensor missions (NASA-MODIS, CNES-SPOT4, CNES/NASDA-POLDER).

Inferring Surface Biochemistry

Reflectance spectrum for a Reflectance spectrum for a single green leaf showing single green leaf showing absorption by chlorophyll absorption by chlorophyll at 0.5at 0.5m and 0.65m and 0.65mm

First derivative spectrum First derivative spectrum showing “red edge” posit-showing “red edge” posit-ion (REP) at ~0.69ion (REP) at ~0.69m. REP m. REP highly correlated with highly correlated with chlorophyll content.chlorophyll content.

Scaling-up — Leaf to Canopy

In radiative terms, In radiative terms, vegetation canopies vegetation canopies do not behave do not behave simply as ‘big simply as ‘big leaves’. Errors will leaves’. Errors will be introduced if we be introduced if we assume leaf-scale assume leaf-scale relationships hold relationships hold at the canopy scale. at the canopy scale. The magnitude of The magnitude of these errors will be these errors will be a function of the a function of the canopy geometry.canopy geometry.

Determining SurfaceBiophysical Properties

Forward Forward scatterscatter

NadirNadir

BackscatterBackscatter

Surface Biophysical Properties

NIR,Red, NIR,Red, GreenGreen

MVA MVA (Green)(Green)

MVA MVA (Red)(Red)

MVA MVA (SWIR)(SWIR)

Surface Biophysical Properties

Isotropic Isotropic scatteringscattering

Geometrical-Geometrical-optical effectsoptical effects

Volume Volume scatteringscattering

Surface Biophysical PropertiesIsotropic Isotropic reflectance reflectance parameter parameter (spectral albedo (spectral albedo at 865nm) at 865nm) derived from derived from POLDER on POLDER on ADEOS data.ADEOS data.

University/Industry Partnership• MVA approach is being exploited for

agricultural monitoring through ESA Small-Sat project in partnership with Sira Electro-Optics Ltd, plus NRSC, Logica and Zeneca.

CHRIS (Compact High CHRIS (Compact High Resolution Imaging Resolution Imaging Spectrometer) will be Spectrometer) will be mounted on the PROBA mounted on the PROBA satellite (PROject for On-satellite (PROject for On-Board Autonomy).Board Autonomy).

University/Industry Partnership

• First test of the new breed of “smaller, faster, cheaper” satellites.

• Good example of U.K. science budget leveraging large ESA spend.

• Transforming scientific research into economically-viable, commercial applications of Earth Observation

Urban ‘Brown Field’ Sites

• Need to identify urban ‘brown field’ sites suitable for re-development for the projected 4 million new homes required by 2016.

• Exploit new generation of ultra-high spatial resolution, commercially-operated satellite sensors…

• …BUT…we need to develop new data-processing techniques appropriate to the scale/resolution of the data sets that these sensors will produce.

Urban ‘Brown Field’ Sites• Working jointly

with OS, Cardiff and Bristol C&CC;

• Infer land use from automated structural pattern analysis of land cover parcels identified in digital images. 25cm image for part of Bristol.25cm image for part of Bristol.

Urban ‘Brown Field’ Sites• Developing graph-theoretic, structural

pattern-recognition system to infer land use from the morphological properties of, and spatial/structural relations between, discrete land cover parcels.

Land Land cover cover parcelsparcels

Adjacency Adjacency graphgraph

Urban ‘Brown Field’ Sites• OS interested in potential of system to assist in

identification of new developments and in automated map updating.

OS-derived buildingsOS-derived buildings Image-derived buildingsImage-derived buildings

Other EO Research at Swansea

• Biodiversity of coastal dune systems using imaging spectrometers and LiDAR;

• Momentum and mass budgets of ‘surging’ glaciers using interferometric SAR;

• The carbon cycle of boreal forests using SAR;

• Scaling and generalization in the production of global land cover maps from EO.