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www.julius-kuehn.dePlantekongres 2019, Herning, Denmark 15.-16. Januar 2019
Possibilities with satellite images
Examples from the research center for agrigultural remote sensing
(FLF), Germany
Holger Lilienthal & Heike Gerighausen
Julius Kühn-Institut
Research center for agricultural remote sensing
c/o Institut for crop and soil science
Bundesallee 69, 38116 Braunschweig, Germany
www.julius-kuehn.de
FLF - Forschungszentrum für landwirtschaftliche Fernerkundung /
research center for agricultural remote sensing
Introduction - FLF
✓ Connected to the Institute for crop and soil science of the Julius Kühn-Institut
(governmental research of the ministry of agriculture in Germany)
✓ Established in March 2017
✓ Center of competence for remote sensing and agriculture, contact point forgovernmental authorities and institutions and data hub for farmers
✓ Production of agricultural geoinformation for research questions of the JKI and theministry of agricultre
✓ Organization of workshops and conferences
✓ Operationalization of reseach results from third party funded projects(z.B.: RiflE, AGRO-DE, SatAgrarStat, Dryland, SOIL-DE, ...)
Website: https://flf.julius-kuehn.de/
www.julius-kuehn.de
✓ Establishment of semi-automatic processing chains to processL1C-raw data and production of calibrated, terrain-corrected Sentinel-1 (Gamma0) and atmospheric corrected Sentinel-2 L2A Daten
✓ Provision of data products by Web Service-technologies (WMS/WFS); Setup of a WebClient
R/G/B: May/ June / July 2018, Monthly composites VH R/G/B: Band 4/ Band 3/ Band 2, 7. May 2018
Sentinel-1 L1C GRD Gamma0 Sentinel-2 L2A
Copernicus-Data
Introduction - FLF
www.julius-kuehn.de
Web-Client: https://flf.julius-kuehn.de/webdienste/web-client.htmlWMS-services: https://flf.julius-kuehn.de/webdienste/webdienste-des-flf.html
Data access
WebApp and WMS-Services of FLF
www.julius-kuehn.de
S4A/B: Payload on geostationary Meteosat Third Generation (Monitoring of trace gases in atmosphere)
S5P: Precursor LEO Mission (Atmosphere)
S6A/B: Altimetry Mission
S5A/B/C: LEO Mission on MetOp Second Generation (Chemical composition of atmosphere)
S3A/B: Mid resolution optical Mission and Altimetry(Land and Ocean)
S2A/B: High resolution optical Mission (Land, Vegetation, Water)
S1A/B: Radar Mission (C-Band) (SAR, Interferometry and Polarimetry. )
23. June 2015/6. March 2017
16. February 2016/25. April 2018
2021/2027
13. Oktober 2017
2021/2027
2020/2025
3. April 2014/ 25. April 2016
Copernicus Programme: Sentinel Satellites
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-1
A
D
Observation tracks and ground coverageof Sentinel-1A and -1B over Germany.
• C-Band SAR (5cm, 5.4GHz),
• 2 Modi (VV+VH, HH+HV)
• Swath width: 250km
• Spatial Resolution: 5x20m (10m)
• Descending orbits at 6 am (left)
• Ascending orbits at 5 pm (right)
• Radar is capable to measure on the dark side of the earth
• Independent of cloud coverage (rain > 5mm affects signal)
• Every 1-2 days and overpass over every location in Germany
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-1
VH
(Jensen, 2000)
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-1
Monthly radar composites (VH): R/G/B = March 18/April 18/May 18
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-1
Crop types and Agricultural events
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-1
Crop types
www.julius-kuehn.de
2021/2027
2020/2025
Sentinel-2
Observation tracks and ground coverage ofSentinel-2A and -2B over Germany.
• Overpass time at 10.30 am.
• Every 2-3 days overpass over every location in Germany
• Spectral Resolution: 490-2190nm,
13 (10) Bands
• Swath width: 290km
• Spatial Resolution: 10 m (10, 20, 60m)
www.julius-kuehn.deSentinel-2 timeseries
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
2017-11-06
2018-04-20
2018-05-05
2018-05-07
2018-05-12
2018-05-15
2018-05-20
Sentinel-2
www.julius-kuehn.de
2017-11-06
Sentinel-2
www.julius-kuehn.de
✓ Close and long-time cooperation with crop consultants and numerous practical farmers (operating data, field campaigns, on-farm trials / practical relevance)
✓ Test sites with main agricultural crops as well as further field trials
Ground truth
Rye Oilseed rape
Barley Potatoe
Sugar beetTriticale
www.julius-kuehn.de
0.5x0.5m²Plots
• Reflectance
• LAI, Biomass, ...
• Main crops: WW, WRo,
WB, OR, Tri, SB, Po,
Maize
• BBCH
Fieldspectrometer: HR1024
SPAD
BBCH, Height, ...
Erhebung auf JKI-eigenen Versuchsflächen und während Feldkampagnen (bundesweit)
Winterweizen: N > 400 Winterweizen: N > 250
Spectral database with reference data as base for modelling
Field campagne 2017 Domäne Bahrdorf
LAI-2200
Ground truth
www.julius-kuehn.de
Example I
N-Fertilization in Oilseed rape
✓ N-Fertilization in autumn optional (only if needed)
✓ N-Fertilization in spring compulsiory: Computation of required N-amount based on N-uptake in autumn
N-amountspring
N-uptake autumn [kg ha-1] = Fresh biomass autumn [kg m-2] * 45
N-amount N-uptake, typical for region N-uptakeautumn= ̶
Weighing of 4-5 samples/field ( 1m² each) fresh biomass
Pointmeasurements with Yara App Image IT
Online Sensors like Yara N-Sensor, ISARIA-Sensor, Greenseeker, ...
Current methods
www.julius-kuehn.de
PLS-S2FM Quality measures
R²val: 0.81
RMSEval: 1.40 t ha-1
RPD: 2.29
RPIQ: 3.53
Ncal/val: 41/40;
nfac: 3, VV: UVN
Beispiel: 200kg N ha-1
N-amount spring [kg ha-1] = N-amount – ((N-uptake autumn - 50) * 0,7)
Source: Sieling & Kage (2010)
Value for average oilseed rape
before Winter
N-Fertilization in Oilseed rape
Example I
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N1 N2 N3
N-fertilization in winter wheat
On-site inspections to determine N-status
✓ N-Tester
✓ Determination by crop density (N1)
✓ Determination by crop stage (N2/3) e.g. Biomass
Online sensors e.g. N-Sensor , ISARIA-Sensor, Greenseeker, ...
✓ Starting in spring:
First dose N1: EC25
Shooting dose N2: EC29/30-32
late dose N3: EC39/49, EC51/61
crop
soilpreceding-crop
intercrop
Nmin
N-Amount
…
Current methods
Example II
www.julius-kuehn.de
PLS-S2FM Quality measures
R²val: 0.79
RMSEval: 8.39 t ha-1
RPD: 2.21
RPIQ: 3.72
Ncal/val: 145/146; nfac: 4, VV: UVN
✓ Monitoring of crop development to determine N-fertilizationExample: Frish biomass
[t ha-1]
Example II
N-fertilization in winter wheat
www.julius-kuehn.de
PLS-S2FM Quality measures
R²val: 0.78
RMSEval: 0.88 t ha-1
RPD: 2.15
RPIQ: 3.26
Ncal/val: 203/203; nfac: 3, VV: UVN
✓ Monitoring of crop development to determine N-fertilizationExample: Frish biomass
Example II
N-fertilization in winter wheat
www.julius-kuehn.de
✓ Estimation of N-uptake (NUR) in winter wheat
PLS-S2NU-R Quality measures
R²val: 0.85
RMSEval: 27.84 t ha-1
RPD: 2.55
RPIQ: 3.52
Ncal/val: 133/134; nfac: 4, VV: UVN
NUR = NR * TMR
Example II
N-fertilization in winter wheat
www.julius-kuehn.de
✓ Estimation of optimum N-supply (NUC) based on dry matter
Quelle: Houles et al., 2007
NUC = 5.35*TM-0.442 (TM > 1t ha-1)NUC = 5.35 (TM < 1t ha-1)
Example II
N-fertilization in winter wheat
www.julius-kuehn.de
✓ Estimation of N-deficit or N-surplus (NU ) by comparing NUC and NUR
Quelle: Houles et al., 2007; Justes et al., 1994
NUC = 5.35*TM-0.442 (TM > 1t ha-1)NUC = 5.35 (TM < 1t ha-1)
NU = NUR, S2 – NUC,TM-S2
So far no validation available!
Example II
N-fertilization in winter wheat
www.julius-kuehn.de
Maps of regional ripening
6.6.18 11.6.18 26.6.18 1.7.18 4.7.18 16.7.18 19.7.18
✓ Support of harvest logistics
Sen
esze
nz
S2 < 20% CC
✓ ✓ ✓ ✓
Example III
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Remote sensing
Crop growth-modelling
Yield [dt/ha]Winter wheat
Yield estimation for regions, counties and countries possible with remote sensing
Accuracy up to ca. 10% *
*compared to weighed yield from a field
Example IV
Yield estimation in winter wheat
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Example IV
Yield estimation in winter wheat
www.julius-kuehn.de
Example IV
Yield estimation in winter wheat
www.julius-kuehn.de
Conclusion
Satellites (Sentinel-1 and Sentinel-2) offer valuable information on the development
of crops. In combination with expert knowledge and modeling the nutritional status
of crops as well as yield estimates become possible.
On-site inspections as well as ground truth is important to understand remote
sensing images.
Analysis of economic/ecological benefits.
✓ Validation and comparison of new approaches with current practice
✓ On farm test with farmers to demonstrate the performance in “real life”
Sentinels offer potential for additional uses (e.g. Soil-mapping and zoning, harvest
logistics-
Despite high temporal resolution no guaranty for data availabilitySynergy with Radar/S-1
www.julius-kuehn.de
Thank you for your attention!
Contact:
Dr. Holger Lilienthal
Julius Kühn-InstitutInstitute for crop and soil science
Email: [email protected]; [email protected]
Plantekongres 2019, Herning, Denmark 15.-16. Januar 2019
