ESA STSE

Earth Observation Land Data Assimilation Scheme

EO-LDAS Final Presentation Workshop

Frascati, 25th March 2011

EO-LDAS field campaign Gebesee 2010

measurement concept, satellite data and first results

Matthias Forkel1,2, Hans-Jörg Fischer1, Hannes Tünschel1, Sören Hese1 & Christiane Schmullius1

1 Friedrich Schiller University of Jena, Department for Earth Observation 2 now at Max Planck Institute for Biogeochemistry Jena

1 Scope of the field campaign

- Collection of in-situ and satellite data for validation of

the EO-LDAS prototype

- Plan overall field campaigns and data collection

- Generate schedule of expected overpasses

- Liaise with EO suppliers - Undertake fieldwork according to EO data

collection schedule

- Package field data with metadata

2 Gebesee test site

Fig.: Location of the Gebesee test site in the Thuringian basin near Erfurt

2 Gebesee test site

Advantages of the site large fields (~ 1 km²), small villages relatively homogenous topography and soils → appropriate for medium resolution remote sensing applications presence of an eddy flux tower (51.1001°N, 10.9143°E, 162 m a.s.l.)

good contacts to an open-minded farmer's cooperative

2 Gebesee test site

Soil types

relatively homogenous

topography

and soils: mostly loess soils

and in the south clay

clay

loess

3 Measurement concept

Fields and crop types

- winter wheat: field A, E

- rape: fields B, F

- winter barley: fields C, G

- maize: fields D, H

- primary fields A-D: nearly

weekly measurements

- secondary fields E-H:

additional measurements

Fig.: Sample fields

3 Measurement concept

Sampling Units (SU)

up to 4 SUs per field with 5 points to

capture pixel-scale variability

requirements for SU location:

- >100 m distance to field border

- represent different soil types

Fig.: Design of a sampling unit

Fig.: Location of sampling units

3 Measurement concept

4/20 4/23 4/29 5/12 5/14 5/21 6/4 6/8 6/10 6/16 6/24 7/1 7/2 7/7 7/16 7/22 7/30 8/4 8/10

A 3 4 4 2 3 4 3 3 3 3 4 3 3 3 3

B 4 4 2 2 3 3 3 3 3 4

C 4 4 4 1 4 4 3 3 3 3

D 3 3 3 3 3 3 2 2 2 2

E 4 4 4 3 3 2 3 3

F 4 4 3 3

G 4 4 4 3

H 1 3 3 1 3 3

Tab.: Measurement days and SUs per day and field

- 19 measurement days

3 Measurement concept

Variables

Spectra: 1 per point + 1 as transect across SU = 6 per SU

Leaf area index: 4 values per SU

Canopy cover: 1 value per SU

Vegetation height: 1 value per SU

Surface soil moisture: 3 per point = 15 per SU

Atmosphere Optical Thickness: 1 per SU

Spectrometer measurements

- ASD field spec 3

- spectral range 350 – 2500 nm

- 3 detectors

- spectral resolution:

3 nm @ 350-1000 nm

10 nm @ 1000-2500 nm

- resampled to 1 nm channels

- Raw data as ASD binary files

Field measurements:

- optimization and white reference with spectralon

- 30 measurements at each sampling point

- 30 measurements during a transect through the SU

= 180 single measurements for each SU

3 Measurement concept

3 Measurement concept

Leaf Area Index

- Licor LAI 2000

- fisheye lens

- five detectors for different angles

- 4 LAI values for each SU

- at each corner point of the SU

Canopy cover measurements

- Scalebar 60 cm x 200 cm

-- 10 cm raster

- Photographs taken about 1 m above

vegetation

Estimation of Canopy cover:

- Definiens developer algorithm

- Classification of vegetation and soil

- Ratio calculation

- Canopy cover in percentage

3 Measurement concept

Vegetation height

- photograph of a scalebar in

front of the crops

- 3 m distance between

camera and scale

- estimating average height

manually by interpreting the

photographs

3 Measurement concept

Soil moisure measurements

- ThetaProbe ML2X Soil Moisture Sensor

with 1% accuracy

- 3 measurements at each sampling point

3 Measurement concept 3 Measurement concept

Aerosol optical thickness

Microtops 2 sun photometer

- 5 channels (440, 500, 675, 870, 1020 nm)

- 1 measurement at each SU

3 Measurement concept

Soil laboratory test

- soil sample of each SU

- dried to 0% moisture

- spectrometer measurements of each

sample at 5% steps of moisture increase to

saturation

- analysis of each sample according to the

moisture increase steps with ASD view

spec pro software

4 Soil spectra

4 Soil spectra

4 Soil spectra

Fig.: Soil spectra (loess chernozem) depending on moisture contents

Increasing wetness

0%

40%

Landsat 5 08/05/2010

Formosat-2 25/07/2010

Spot 22/05/2010

Rapideye 09/07/2010

10 km

5 Satellite data

Acquired EO data

6 Results

Leaf Area Index

Fig.: Maps of SU-averaged LAI

6 Results

Leaf Area Index

Fig.: Field-averaged cycles of LAI and standard deviation

loess

clay

6 Results

Leaf Area Index – Spatial variability inside SU, field and crop type

Fig.: Coefficient of variation of LAI in wheat, rape, barley and maize

6 Results

Spectra A) winter wheat B) rape

C) winter barley D) maize

Fig.: Spectra 2010-06-16

6 Results

Spectral indices

Fig.: Field-averaged NDVI, NDMI and PRI and standard deviation

NDVI

Win

ter

wh

ea

t

NDMI PRI

Ra

pe

W

inte

r b

arl

ey

Ma

ize

Many thanks to the EO-LDAS team!

Many thanks to the EO-LDAS team!

Andrius Ramanauskas Caroline Baumgart

Eric Thomas Falko Stier

Franziska Behnsen Hannes Tünschel

Hannes Werner Jana Peukert Kerstin Traut

Lisa Hagedorn Lisa Wedekind

Marius Bockwinkel Martin Faber

Martin Lindner

Participiation grouped by study: 8 students from M. Sc. Geoinformatics = 43% 2 M. Sc. Geography 16 B. Sc. Geography = 52% 1 art history 1 political science 1 nutrition science

Martin Thurner Mathias Müller

Max Tobaschuss Miguel Kohling Peggy Bierbaß Peter Schmider Rene Michaelis

Robert Wolff Sebastian Willi Oehmke

Susann Förster Thomas Brockmann Thomas Schiemann

Tillmann Lösche Tino Wunderlich – B.Sc. thesis

Thanks to UCL for providing measurement instruments!

6 Results

Canopy cover

Fig.: Field-averaged cycles of canopy cover and standard deviation

6 Results

Vegetation height

Fig.: Field-averaged cycles of vegetation height and standard deviation

6 Results

Soil moisture

Fig.: Field-averaged cycles of soil moisture and standard deviation

6 Results

AOT

Fig.: Aerosol optical thickness