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JECAM | Joint Experiment for Crop Assessment and Monitoring

Canada CFIA - Ottawa

Project Overview

Goals of the site in terms of:

Crop Identification and Crop Area Estimation
Crop Condition/Stress
Soil Moisture
Yield Prediction and Forecasting
Crop Residue, Tillage and Crop Cover Mapping
Soil Properties

Project Reports

2017 Site Progress Report

2016 Site Progress Report

2015 Site Progress Report

2014 Site Progress Report



  1. Jégo, G., Pattey, E., Mesbah, M., Liu, J., Duchesne, I. 2015. Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model. Int. J. Appl. Earth. Obs. Geoinf. 41: 11-22.
  2. Shang, J., Liu, J., Huffman, T., Qian, B., Pattey, E., Wang, J., Zhao, T., Geng. X., Kroetsch, D., Dong, T., Lantz, N. 2014. Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images. J. Appl. Remote Sens. 8(1): 085196
  3. Pattey, E, Jégo, G., Liu, J., . Smith, W.N., VanderZaag, A.C., Desjardins, R.L., Tremblay, N., Geng, X., Qiu, B., Shang, J., McNairn, H., Jarvis, I. (2015).  "Field-scale research to quantify the impact of climate variations on crop production andto enhance the environmental performance.", ECORC/ACGEO Agri-Environmental Science Day. Invited Presentation, Ottawa, ON, Canada, February 10, 2015. (Presentation)
  4. Pattey, E., Jégo, G., Mesbah, S.M., Liu, J., and Duchesne, I. (2015). "Impact of spatial resolution of soil and climatic data on regional corn yield predictions using OptimiSTICS package.", STICS workshop 2015, Rennes, France, March 24-26, 2015, pp. 2 pages.
  5. Mesbah, S.M., Pattey, E., Jégo, G., Liu, J., Hagolle, O., Dedieu, G., Buis, S., and Lecharpentier, P. (2015). "Assimilation of Earth Observation biophysical descriptors into the STICS crop model using a formal Markov Chain Monte Carlo algorithm.", American Geophysical Union Annual Meeting, Montreal, QC, Canada, May 3-7, 2015. (Poster)
  6. Camacho, F., Lacaze, R., Latorre, C., Baret, F., De la Cruz, F., Pattey, E., and others (2015). "Collection of Ground Biophysical Measurements in support of Copernicus Global Land Product Validation: The ImagineS database.", 2015 EGU General Assembly, Vienna, Austria, April 2015, Oral presentations; Geophysical Research Abstracts Vol. 17, EGU2015-2209-1.​
  7. Liu, J., Pattey, E. and Admiral, S., 2013. Assessment of in situ crop LAI measurement using unidirectional view digital Photography. Agric. For. Meteorol. 169: 25-34.
  8. Sansoulet, J., Pattey, E., Kroebel, R., Grant, B., Smith, W.N., Jego, G., Desjardins, R.L., Tremblay, N., Tremblay, G. 2014. Comparing the performance of STICS, DNDC and DayCent models for predicting N uptake and biomass of spring wheat in Eastern Canada. Field Crops Res. 156(1): 135-150.
  9. Pattey, E., Liu, J., Admiral S., 2013. Performance of unidirectional view digital photography to retrieve crop LAI using GreenCropTracker software. American Society of Agronomy annual meeting, Tampa FL, Nov. 2013.
  10. Camacho F., Baret F., Weiss M., Lacaze R., Di Bella C., Demarez V., Merhez Z., Rudiger C., De la Cruz F., Pat G.M.., Tapela M., Pattey E., Mattar C., Rojas J., Erena M., Chirima G.J.., Barcza Z., Waldner F. 2014. FAPAR in situ measurements network of sites within the IMAGINES project. First Workshop CEOS LPV FAPAR sub-group. Ispra, Italy, 23-24 January 2014
  11. Pattey, E.; Jégo, G.; Mesbah, S. M.; Liu, J.; Hagolle, O. 2014. Impact of LAI Assimilation Approach on STICS Crop Model Performance to Predict Yield and Biomass of Field Crops. SENTINEL -2 for Science Workshop. ESRIN, Frascati, Italy, 20-22 May 2014.
  12. Pattey, E., Jégo, G., Vanderzaag, A., Liu, J., Qian, B., Smith, W., Geng, X., Baret, F., Beaudoin, N., Desjardins, R., Fernandes, R., Jarvis, I., Huffman, T., Lacaze, R., McNairn, H.,2014. JECAM CFIA-Ottawa. JECAM/GEOGLAM Science Meeting. Ottawa, Canada, 21-23 July 2014.
  13. Latorre, C., Camacho, F, Pattey, E., Jégo, G., Vanderzaag, A., Liu, J., Qian, B., Smith, W., Geng, X. 2015. Implementing multi-scale Agricultural Indicators exploiting Sentinel. Vegetation field data and production of ground-based maps: Ottawa site, Canada., May to August 2014. EC proposal Reference FP-7-311766.
  14. Liu, J. and Pattey, E. 2016. Preliminary assessment of the ImagineS products for CFIA experimental site, Ottawa, ON, Canada, 12pp.
  15. Pattey, E.,Jégo, G. ,A. Vanderzaag, J. Liu, B. Qian, X. Geng; Res. Team: S. Admiral, M. Mesbah, D. Dow, T. Hotte, F. Baret, M. Weiss, R. Lacaze, F. Camacho, N. Beaudoin, R. Desjardins, T. Huffman, H. McNairn 2016. 2016 Canadian JECAM Site Update: CFIA-Ottawa. JECAM Science Meeting Kyiv, 11-12 Oct 2016 (poster).

Implementation Plans

Plans for Next Growing Season: 

Similar approach, the main experimental site will be planted in corn; the second sites continue rotation of corn, soybean, and wheat. We do not anticipate destructive sampling in other fields because there is no more funding to support this activity. However, we will deploy available longbar fAPAR, PASTiS-PAR, and PASTiS-57 sites in representative fields as resources allow.

Site Description


Canada CFIA - Ottawa
Site Extent   Centroid: 45.3, -75.7666
Top left: 45.341, -75.8333 Bottom Right: 45.26667, -75.7

Site Description

Location: CFIA Ottawa Laboratory 3851 Fallowfield Road, Ottawa, Ontario, Canada
Topography: flat < 0.5% Gradient
Soils: Modified marine sediments with a fine texture and neutral composition. Layers of silty sediments interspersed in the upper 2 meters. Clay loam is the dominant texture.
Drainage class/irrigation: Tile Drainage and Precipitation Fed Field
Crop calendar: spring crops: corn soybean, wheat canola
Field size: 15-75 ha fields
Climate and weather: Average of 732 mm of rain yr-1 and 236 mm of snow yr-1 and  temperature averages from 13.4 °C- 20.9 °C from May-August (Environment Canada, Government of Canada 2014)
Agricultural methods used: Tillage, synthetic fertilizer, seeding, harvest when grains are dry enough

Figure 1. Eddy covariance instruments and flux gradient intakes.


CO2, H2O and sensible heat flux measured in two fields using 3 eddy covariance towers. Nitrous oxide fluxes measured using 2 flux gradient towers. Destructive biomass, LAI, soil sampling, yield mapping, non-destructive PAI, lChl (Dualex), crop cover (nadir photos), soil moisture & T, intercepted PAR, other data from weather station.

Figure 2. Photograph showing early planted soybean on the left, late planted on the right at the main research field on Sep 1, 2016.

Specific Project Objectives & Deliverables


Two crops were monitored: soybean (F14) and corn (F14N). Soybean and corn were planted by the private producers. April, May and July were drier than normal and June was near normal for rainfall.

Figure 8: Daily precipitation measured at field site (April 12 to October 26) or at the airport site (before April 12 and after October 26).

The delay in the seeding was seen in the biomass sampling data. The rainfall in mid-August resulted in some enhanced growth in the late seeded soybean but not the early seeded soybean.

Figure 9: Dry shoot biomass, plant area index and green leaf area index of soybean in 2016 (CFIA, field 14).

Fraction of absorbed PAR was measured using longbars in early and late seeded soybean as well as corn. PASTiS-PAR and PASTiS-57 measurements were attempted but difficulties with equipment prevented gaining meaningful data.

Figure 10: Fraction of absorbed PAR from longbar measurements.

The delay in seeding was also seen in the leaf chlorophyll measurements obtained with the Dualex.

Figure 11: Dualex leaf chlorophyll readings for the top leaves of soybean. Dualex units approximate µg m-2 leaf chlorophyll.

Soybean yield measurements showed values slightly smaller in the drier areas of the field (west) and slightly higher values in the wetter areas (east, water feature in the centre).

Figure 12: Yield map from soybean harvest, headlands and partial passes removed. Yield expressed as kg m-2


Yield from the corn field has not been finalized. Yield data from the corn and soybean fields have not been received from the private producers.

Eddy covariance measuring systems were recording fluxes during all the growing season. The cumulative evapotranspiration associated with the late seeded soybean (295 mm) was lower than that of the early seeded soybean (317 mm).

The cumulative dry biomass extracted from the CO2 flux data indicated that the late seeded soybean accumulated about 25% less biomass than the early seeded site. 

Biophysical products were derived by CNES from Landsat-8 and RapidEye data acquired over CFIA in 2013 and 2014, using the Sentinel-2 product processing stream.

For Landsat-8 data, top of canopy reflectance in the green, red, NIR and SWIR-1 bands were used; for RapidEye, all five bands (blue, green, red, red-edge and NIR) were used.

The products include the estimates of four biophysical parameters: LAI,  cover fraction (fCover), black and white sky fAPAR.

The accuracy of the products is satisfactory. The two attractive aspects of the S2 products are as follows:

1) the products result from an inversion approach based on radiative transfer modeling;

2) the products issued from the two satellite sensors are consistent, which shows the robustness of the approach knowing that the reflectance information used for the two sensors is quite different.

The performance of assimilation strategies using different optimization algorithms based on JECAM CFIA-Ottawa datasets is in progress.

In Situ Observations

  1. Parameter: APAR
    Data Collection Protocol:

    using 1-m long integrated PAR bars

  2. Parameter: Non-destructive Leaf chlorophyll
    Data Collection Protocol:

    SPAD, Dualex

  3. Parameter: Soil respiration
    Data Collection Protocol:

    discrete & automated chambers

  4. Parameter: Yield
    Data Collection Protocol:

    Yield mapping and manual harvest

    Frequency: Annually
  5. Parameter: Sensible, latent and CO², flux data and meteorological data
    Data Collection Protocol:
    • Eddy Flux
    • Automated weather stations
    • Tunable diode lasers
    Frequency: half-hourly, daily means and standard deviations
  6. Parameter: Soil moisture and temperature sensors
    Data Collection Protocol:
    • Several sites equipped with sensors and loggers
    Frequency: half-hourly averages
  7. Parameter: PAI
    Data Collection Protocol:

    DH photography, PASTIS-57 sensors


EO Data Requirements

Approximate Start Date of Acquisition: April 21
Approximate End Date of Acquisition: September 19
Spatial Resolution: 2.5m - 30m
Temporal Frequency: Monthly (approximately)
Latency of Data Delivery: Variable
Wavelengths Required: R, NIR (min)
Across Swath: Variable
Along Track: Variable

SAR Data Requirements

Approximate Start Date of Acquisition: N/A
Approximate End Date of Acquisition: N/A
Spatial Resolution: N/A
Temporal Frequency: N/A
Latency of Data Delivery: N/A
Wavelengths Required: N/A
Polarization N/A
Incidence Angle Restrictions: N/A
Across Track: N/A
Along Track: N/A


Canada CFIA - Ottawa

Latitude: 45.3
Longitude: -75.7666

Site Extent
Top left
Latitude: 45.341
Longitude: -75.7666
Bottom Right
Latitude: 45.26667
Longitude: -75.7

Optical Sensors

JECAM | Joint Experiment for Crop Assessment and Monitoring | Group on Earth Observation

©2013 Joint Experiment for Crop Assessment and Monitoring © HER MAJESTY THE QUEEN IN RIGHT OF CANADA SA MAJESTE LA REINE DU CHEF DU CANADA (2012)