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JECAM | Joint Experiment for Crop Assessment and Monitoring

Argentina

Project Overview

Centered in San Antonio de Areco (Buenos Aires, Argentina), a small area (20 x 20 Km) was selected where high frequency crop and environmental monitoring is being performed. An extended area (70 x 70 Km) is being surveyed with lower frequency for crop mapping and identification of phenological events.

  1. Crop identification and Crop Area Estimation: Crop identification. We are testing several classification methods using optical images and RADAR images and its combination. During last campaign we continued obtaining data from the original JECAM/ SIGMA area as well as over a minimum dataset (MDS) area of 20 x 20 km with higher density collection. This small area matches with RADARSAT-2 Fine Quad Pol acquisitions during this campaign that we are collecting for the SAR intercomparrison experiment. We developed an intercomparisson of methodologies for cropland identification together with other JECAM/ SIGMA sites (China, Russiz, Ukraine, Brazil, and Belgium). We are moving from local to regional estimation of crop land and crop type. We are testing different sampling methodologies and different data sources together with other JECAM sites.
     
  2. Crop Rotations: Crop rotations in the last 6 campaigns are described and analized. We expect to write a manuscript during 2017. 
     
  3. Soil Moisture: Analysis of its effects on RADAR signal.
     
  4. Yield Prediction and Forecasting: We are working in an intercomparisson study for yield estimation at coutry level with SIGMA/ JECAM partners from Russia, China, Ukraine, and Africa leaded by Alterra (Wageningen, The Netherlands). We are also working in the estimation of biophysical parameters at field level using optical and RADAR images.

Project Reports

2017 Site Progress Report

2016 Site Progress Report

2015 Site Progress Report

2014 Site Progress Report


Peer Reviewed Papers:

Waldner, F., de Abelleyra D, Verón S. R., Zhang M., Wu B., Plotnikov D., Bartalev S., Lavreniuk M., Skakun S., Kussul N., Le Maire G., Dupuy S., Jarvis I. and Defourny P. (2016). Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity. International Journal of Remote Sensing. 37: 3196-3231.

de Abelleyra D., Verón SR (2016). Optical and RADAR remote sensing for characterization of agricultural systems in the Argentinean Pampas. The role of site-based measurements in agricultural monitoring: A workshop to promote collaborations between the USDA (NASS and LTAR) and GEOGLAM (JECAM, RAPP). May 24-26,  2016. Ames, Iowa, United States of America.

de Abelleyra D., Verón S. 2016. Caracterización, patrón espacial y controles de las rotaciones agrícolas en la Pampa Ondulada. 1ra reunión científica PNNAT-INTA. August 30-September 1, 2016. Buenos Aires, Argentina.

Verón, S.R. de Abelleyra, D. 2016. Estimación satelital del rendimiento de cultivos extensivos.  1ra reunión científica PNNAT-INTA. August 30-September 1, 2016. Buenos Aires, Argentina.

Verón S. R., de Abelleyra D., Lobell D. 2016. Impacto de la precipitación y la temperatura en el rendimiento de los cultivos de la región pampeana. 1ra reunión científica PNNAT-INTA. August 30-September 1, 2016. Buenos Aires, Argentina.

Verón S. R., de Abelleyra D,  Lobell DL. 2015.  Impacts of recent precipitation and temperature changes on crop yields in the Pampas. Climatic Change, 130: 235-245.

Bontemps S, M Arias, C Cara, G Dedieu, E Guzzonato, O Hagolle, J Inglada, N Matton, D Morin,  R Popescu, T Rabaute, M Savinaud, G Sepulcre Canto,  S Valero, I  Ahmad Bhutta , A Begué, B Wu, D de  Abelleyra, A  Diarra , S Dupuis, A French, I Hassan Akhtar , Kussul, V Lebourgeois, M Lepage, T Newby, I Savin, S  R Verón , B Koetz, P  Defourny. 2015. Building a Sentinel-2 like data set specifically dedicated to agriculture monitoring over 12 sites globally distributed. Remote Sensing, 7(12), 16062-16090; doi:10.3390/rs71215815

Waldner F, Diego De Abeyllera, Dmitry Plotnikov, Guerric Le Maire, Sergey Bartalev,  Stéphane Dupuy, Santiago R. Verón, Mykola Lavreniuk, Ian Jarvis, Pierre Defourny, Miao Zhang, Sergii Skakun, Nataliia Kussul. 2016. Cropland mapping in five contrasted agrosystems dominated by large sized fields (sent).

De Abelleyra D, Verón S. 2014. Comparison of different BRDF correction methods to generate daily normalized MODIS 250m time series. Remote Sensing of Environment, 140: 46-59.

Verón SR, de Abelleyra D. 2014. Comparison of X and C band satellite RADAR images to characterize irrigated agricultural fields. Proceedings of the International Geoscience and Remote Sensing Symposium IGARSS 2014. Quebec, Canadá. pp: 2106-2109.


Presentations:

De Abelleyra D, Verón SR, 2015. JECAM Argentina. JECAM/GEOGLAM Science Meeting Brussels, Belgium, 16-17 November, 2015.

De Abelleyra D, Verón S. 2013. JECAM Argentina. Preliminary results of two years of field data. 35º International Symposium in Remote Sensing of Environment. Beijing, China. April 22-25, 2013. 

De Abelleyra D, Verón S. 2013. Optical and Radar remote sensing for crop monitoring in the Argentine JECAM site. 2013 International Workshop on Using Remote Sensing for Crop Area Monitoring and Yield Estimation. September 11, 2013, Taichung, Taiwan.


Implementation Plans

Plans for Next Growing Season:

  1. We are moving from local (JECAM area) to regional level (province/ country) for crop area and yield estimations. We are testing our classification methodology in different regions of Argentina during different agricultural campaigns.
     
  2. Following the fitst intercomparisson study for cropland mapping finished this year, we are working this year in other two intercomparisson experiements: comparison of different sampling methods, and comparison of different data sources: in situ data, crowdsourcing and reference cropland maps.
     
  3. We are going to participate in the two JECAM SAR experiments for crop type mapping and Biomass/ LAI estimation.
     
  4. Improve estimation of actual evapotranspiration (as water stress index)

Site Description

Locations

Topography:

Gently slopes (lower than 3%)

Soils:

Mostly Mollisols. Silt loam / Silty clay loam textured.

Drainage class/irrigation:

Well drained soils / Mostly rainfed fields

Crop calendar:

Main grain crops are soybean, maize and wheat. Early wheat is planted in June/July while late wheat is planted at the end of July and August. Wheat heading occurs in mid October and its harvest is produced at the beginning of December. After a wheat crop, commonly it is planted a late soybean crop (in December) which is harvested in April. Also a late maize crop can be planted after a winter crop. Soybean and maize are mostly planted as one season crop. In these cases, soybean is planted in November and harvested in March/April and maize planted in October and harvested in March. Recently late maize crop is planted since December after a fallow.

Field size:

Average field size is ca. 20 ha. However plot size is very variable.

Climate:

The climatic type is humid temperate with an isohygro precipitation regime, with annual mean of about 1000mm.

Agricultural methods used:

Mostly no till agriculture. Main rotation (three years): Maize, Soybean, Wheat/Soybean.

 

Field Campaign photos. Left: Mature wheat field in San Antonio de Areco, Argentina. Right: wheat field in Shandong, during our visit to China JECAM site.

Topography:

Gently slopes (lower than 3%)

Soils:

Mostly Mollisols. Silt loam / Silty clay loam textured.

Drainage class/irrigation:

Well drained soils / Mostly rainfed fields

Crop calendar:

Main grain crops are soybean, maize and wheat. Early wheat is planted in June/July while late wheat is planted at the end of July and August. Wheat heading occurs in mid October and its harvest is produced at the beginning of December. After a wheat crop, commonly it is planted a late soybean crop (in December) which is harvested in April. Also a late maize crop can be planted after a winter crop. Soybean and maize are mostly planted as one season crop. In these cases, soybean is planted in November and harvested in March/April and maize planted in October and harvested in March. Recently late maize crop is planted since December after a fallow.

Field size:

Average field size is ca. 20 ha. However plot size is very variable.

Climate:

The climatic type is humid temperate with an isohygro precipitation regime, with annual mean of about 1000mm.

Agricultural methods used:

Mostly no till agriculture. Main rotation (three years): Maize, Soybean, Wheat/Soybean.

 

Field Campaign photos. Left: Mature wheat field in San Antonio de Areco, Argentina. Right: wheat field in Shandong, during our visit to China JECAM site.


Specific Project Objectives & Deliverables

Intercomparisson of Methodologies for cropland Mapping (Waldner et al, 2016)

Five methodologies developed for different JECAM sites (Argentina, Belgium, China, Russia and Ukraine) were tested over 5 locations (Argentina, Brazil, China, Russia and Ukraine). In situ (in field collected) data was collected by JECAM site partners and used for training and validation of classifiers.  

Results showed quite high overall accuracy for all methods (in general more than 90%). Higher variability was observed among sites than among methods. Russia and Ukraine showed the highest accuracy values, while Brazil the lowers. Some problems were observed to classify no cropland areas due to similarity with cropland fileds and spatial distribution of land uses. 

A test was performing reducing the sample size for training up to 10 % and showed low reduction in overall accuracy when reduction was higher than 40 %.


In Situ Observations

  1. Parameter: Road Surveys
    Data Collection Protocol:

    On road surveys were performed at least twice a year to identify winter and summer crops as well as fallows, pastures and grasslands. Surveys are performed over the JECAM/SIGMA area (100x100 Km) and with a higher collection density over MDS area (20x20 Km). Other in situ data sources are being collected in other areas of Argentina to expand the classification methodologies to other areas and get regional maps.

    Frequency: Biannually

EO Data Requirements

Approximate Start Date of Acquisition: August 1 (min), July 1 (preferred)
Approximate End Date of Acquisition: May 15 (min), Apr 30 (preferred)
Spatial Resolution: 60 m (min), 30 m (preferred)
Temporal Frequency: Every 15 days (min), Weekly (preferred), For Extensive data collection area, lower frequency of acquisition is required (October, December, February)
Latency of Data Delivery: Every 15 days (min), Weekly (preferred)
Wavelengths Required: R, NIR (min), R, G, B, NIR, Hyperspectral (preferred)
Across Swath: 20 Km (min), 70 Km (preferred), Intensive data collection area is 20 x 20 Km Extensive data collection area is 70 x 70 Km
Along Track: 20 Km (min), 70 Km (min), Intensive data collection area is 20 x 20 Km Extensive data collection area is 70 x 70 Km

SAR Data Requirements

Approximate Start Date of Acquisition: August 1 (min), July 1 (preferred)
Approximate End Date of Acquisition: May 15 (min), April 30 (preferred)
Spatial Resolution: 30 (min), 10 (preferred)
Temporal Frequency: 20 days (min), 15 days (preferred), For Extensive data collection area, lower frequency of acquisition is required (October, December, February)
Latency of Data Delivery: 15 days (min), Weekly (preferred)
Wavelengths Required: L, C, X
Polarization Quad Pol (min), Dual (HH/VV) or Single (HH) (preferred)
Incidence Angle Restrictions: 20-45° (min), 35-45° (Preferred)
Across Track: 20 (min), 70 (preferred), Intensive data collection area is 20 x 20 Km Extensive data collection area is 70 x 70 Km
Along Track: 20 (min), 70 (preferred), Intensive data collection area is 20 x 20 Km Extensive data collection area is 70 x 70 Km

Locations


Optical Sensors

DMCii
Imaging Mode:
Spatial Resolution:
Acquisition Frequency: 8 times (2014), 7 times (2013)
Pre-Processing Level:
Application: Images were very useful to supplement other optical images that were not available because of cloudiness. If we have the possibility to obtain orthorectified images, it will improve significantly the time required for image processing that in general requires manual georreferencing.

Proba-V
Imaging Mode:
Spatial Resolution: 100m
Acquisition Frequency: all available from March 2014
Pre-Processing Level:
Application:

Deimos
Imaging Mode:
Spatial Resolution:
Acquisition Frequency: 4 times
Pre-Processing Level:
Application: Images were very useful to supplement other optical images that were not available because of cloudiness.

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)