ulg - myeorganics where it comes from and where it goes

MyEorganics - Stakeholder workshop2nd July 2015 – Liège - Belgium

By Antoine DENIS – PhD student - University of Liège - Belgium

““MyEorganics ! Where it comes from and

where it goes !”” !

Part I : “MyEorganics ! Where it comes from?”Part II : “MyEorganics ! Where it goes!”

“Can satellites help organic crop certification ?” • Since 2010!• As ULg PhD student

• EOrganic project– 2010 - 2012– East Germany & France, corn & wheat

• Organic cotton in Burkina Faso– 2011

Why I am here today?

Some publications: https://orbi.ulg.ac.be/browse?type=author&value=Denis, Antoine p005248

MyEorganics - Stakeholder workshop2nd July 2015 – Liège - Belgium

Part I

“MyEorganics ! Where it comes from?”

Part I : “MyEorganics ! Where it comes from?”

EOrganic project

1st feasibility study to evaluate the ability of satellites to help organic crop certification bodies

“Is it possible to discriminate between organic and non-organic crops with satellites?”

Want organic food/products?

Human health Environmentally friendly

1. Context & Justification

Organic crop ? = NO chemical synthetic pesticide & fertilizer= NO GMO= Crop rotation= Organic fertilizer and pesticide= ...

Crop Control· Yearly farm inspection· Documentary accounts· + Unannounced inspection· + Laboratory analysis · Cost? Frequency? Remote areas?

Certification Rules & agencies Labels

Organic food onthe market

To trust or not to trust ?

The IDEA

BIO!

BIO!

BIO!BIO

!BIO

!

BIO!

BIO! BIO

!

BIO!

BIO!

BIO!

BIO!

BIO!

BIO!BIO

!BIO!

BIO!

BIO!

BIO!

BIO!

BIO!

Identification of area to control

Field declared as organic !

Indicator computation

Identification of suspect fields

Too high nitrogen!

Analysis with several indicators

Hypothesis

► Management differences between organic and conventional crops

► Crop biophysical characteristics and general field appearance

► Satellites and transformed into satellites derived indicators

Cotton management differences

Bio-chemico-physical differences

Indicators

Less fertilizer in organic fields Less biomassLess canopy cover

Field canopy cover Biomass estimation

Lower nitrogen content of the plants

Leaves chlorophyll content

Smaller plants Plant height

Less spatial homogeneous fertilizer application and less efficient pesticide in organic fields

Higher spatial heterogeneity

Standard deviation of other indicators by field

HypothesisIn particular :

Part I : “MyEorganics ! Where it comes from?”

EOrganic – Study sites

Germany & France

Conventional wheat Organic wheat

► Crop biophysical characteristics and general field appearance

ColourDensityTractor traces

Part I : “MyEorganics ! Where it comes from?”

► Crop biophysical characteristics and general field appearance

Conventional corn Organic corn

Flowers

(weeds)

Part I : “MyEorganics ! Where it comes from?”

Conventional corn: Herbicide for soil preparation

Weeds management (corn)

Organic corn: Mechanical weeding

Part I : “MyEorganics ! Where it comes from?”

… and laboratory analysis (nitrogen, biomass, dry matter nutrient,…)

Hyperspectral reflectance

Chlorophyll

Crop cover

Height Plant and soil samples Documentation

Picture: UCL-geomatics

GPS

Part I : “MyEorganics ! Where it comes from?”

In situ measurements

(RapidEye)

CHRIS(hyperspectral)

SPOT

KOMPSAT 2 WorldView 2

Landsat

Swath Spectral bands

Spatial resolution

14-185 km 4-62 1-34 m

Part I : “MyEorganics ! Where it comes from?”

Satellites measurementsExploratory study - use of a set of satellites:

A set of satellites with different features:

• Spatial and spectral resolution

• Spatial and temporal availability

• Price, …

WorldView 10/08/2010 CHRIS-PROBA 05/06/2010

Satellites measurements

Biomass estimation

Crop spatial heterogeneity

Tractor tracesRS Indicators

Satellites measurements

Part I : “MyEorganics ! Where it comes from?”

Results: insitu

KOMPSTAT2 29/06/2010 B5

Nitrogen

Results: satellites

Discrimination quality (%)Wheat Corn87-100 60-87

Results: satellitesTractors tracks

Corn Wheat

Conv.

Orga.

Orga.

Conv.

Crop spatial heterogeneity

Separability: 90 % Wheat; 90-100 % Corn

Results: satellites

Best hyperspectral 2 bands ratio

Separability: 100 % Wheat & Corn

Results: satellites

Results: satellites

In the limited context of this study (wheat and corn in East of Germany)

Satellite images proved to be an efficient tool to discriminate organic from conventional crops and could consequently support work of organic certification bodies.

More research to refine and validate the method in other areas and climatic conditions before its implementation in the organic crop certification process.

Conclusion

MyEorganics - Stakeholder workshop2nd July 2015 – Liège - Belgium

Part II

“MyEorganics ! Where it goes!”

The case of organic cotton in Burkina Faso

Context & Justification

The case of organic cotton in Burkina Faso

Why the Burkina Faso ?• Huge amount of organic products from developing countries ($)

• Remote areas and certification control more difficult

Why the cotton?• Crop in developing countries

• Certified as organic

• To be studiable by RS

• Field big enough

Economic Importance of cotton in Burkina Faso• Cotton accounts for 50 to 60% of the

country’s foreign currency earnings • Cotton is the first export product

contributing largely to the country’s economic development

Context & Justification

Development of Organic cotton in Burkina FasoSuccessful since 2004, bright example of sustainable development that contributes to:• Alleviation of poverty•Improved food security by enhancing producers’ income with less risk to run into debt

Context & Justification

• Healthy way to crop both for people and the environment resulting in improved human and animal health (absence of chemical pesticides), and improved soil fertility and environment (organic cropping technique).

Objectives

Is it possible, in the context of South-West Burkina Faso,

► To help organic cotton certification process with satellites?► To discriminate organic and conventional cotton fields with satellites?

► Need to assess the bio-chemico-physical difference between organic and non organic cotton with diverse field measurements

Objectives

Biblio

Cotton Yield in Burkina Faso:

•Organic = 675 kg/ha (std dev = 314 kg/ha)

•Conventional = 1 100 kg/ha (std dev = 391 kg/ha)(Centre for Development and Environment of the University of Berne (CDE), Pineau et al. 2009)

Method

Method

Study site

MethodStudy site

Method

Study site

The case of organic cotton in Burkina Faso

Methodology – field measurements

Crop cover

Chlorophyll Height Notes + GPS + Phenology

• SPOT 5 (via ISIS program / CNES)

• 2.5 m color• 3 BANDS: Green, Red, NIR• Tasking window between

16/08/2011 – 25/10/2011• Nearly permanent cloud cover• 1 image on 15/11/2011

only !!! Very late !• + 1 MODIS image: surface

temperature emissivity (Sept-Oct)

Method

Satellite image

• Several local varieties for organic and conventional

• Several varieties Bt GMO • Low intensive cultivation • Farming operations: manually or workanimals• Rainfed

Method

Cotton cropping method in Burkina Faso

Spectral indicators• Simple bands• 2 bands combination

Spatial heterogeneity indicators• Standard deviation of pixels by field• …

Method

Satellite indicators

Results

The case of organic cotton in Burkina Faso

Results: insitu

Less clear difference !Difference organic vs non organic

• Phenology stage

• Local rain

• Local seeding date

• Fertilizer availability

• …

ResultsSatellite indicators:

Red / NIR Heterogeneity Multivariate sat. Multivariate (sat.+insitu)

Discussion and conclusion

Differences are observed between cotton types•For both field and satellite indicators•Statistically significant•Not enough pronounced with values ranges that largely overlapThis prevents the use of these indicators alone to be the base of a robust discrimination

But the method enables to target for priority field control, organic fields who present indicator values getting closer to the one of conventional or GM cotton fields

Further research:•Timely satellite acquisition!•Identification of the ideal phenological stage for cotton monitoring

Discussion and conclusionGeneral conclusion

Satellite Indicators are questionable:•A single image was acquired very late in the crop cycle •No straight conclusion regarding the general relevance of the use of RS techniques in the study context

Use of satellite images seems to be quite compromised given the unfavourable atmospheric conditions which are most of the time cloudy. Need for daily image acquisition for cloud free image?

Trees in cotton fields can strongly influence the reflectance and the spatial heterogeneity (from no tree to a complete agroforestry system)

Discussion and conclusion

Relevance of the use of satellite images in this context

Difference between cotton parcel is also due to other factors, difficult to take into account:•The phenology stages that can strongly vary from one parcel, farmer or region to another due to varying seeding date, itself depending among other on the local climatic condition, with very localized rainfalls. •Varying soil natural fertility•Varying level of development of the farmers (fertilizer availability)

Discussion and conclusion

Remaining obstacles

Université de Liège - Belgique

Acknowledgement

The French “Centre National d’Etudes Spatiales” (CNES) through its « ISIS » program (« Incitation à l'utilisation Scientifique des Images SPOT ») that enabled to acquire a SPOT 5 image at low cost for this study. SPOT "© CNES (2012), distribution Spot Image S.A.", Http://www.isis-cnes.fr/IntroPage.do

The “SOciété Burkinabé des FIbres TEXtiles” (SOFITEX) that allowed the field survey in conventional and GMO cotton fields.

The National Union of Cotton Producers of Burkina Faso (UNPCB – Union Nationale des Producteurs de Coton du Burkina Faso) that enabled the field survey in organic cotton fields and accompanied the entire field survey.

Helvetas Swiss Intercooperation Burkina Faso, for their important documentation on organic cotton production in Burkina Faso and their advices for the field survey preparation.

Thank You !

Some publicationsAvailable on ORBI: (https://orbi.ulg.ac.be/browse?type=author&value=Denis, Antoine p005248)

• Remote sensing enables high discrimination between organic and non-organic cotton for organic cotton certification in West Africa (Paper)

• Remote sensing and GIS techniques for supporting organic cotton certification process in West Africa (Oral presentation)

• Can satellites help organic crop certification? (Poster)• More to come…

Contact information

Arlon Campus Environnement (ACE)Water, Environment, Development unitUniversity of Liège (ULg)185, Avenue de Longwy,6700 ArlonBelgium

Antoine DENIS Bernard TYCHON

TEL 0032 63 230 997 0032 63 230 829

Email Antoine.Denis@ulg.ac.be Bernard.Tychon@ulg.ac.be

Website http://www.eed.ulg.ac.be/