By Antoine Denis, Thesis defended
Organic Agriculture, in order to be differentiated from conventional one and to get the confidence of the consumers needs to be certified. In some European regions the certification control is also one of the conditions that organic farmers have to fulfil in order to benefit from the economic help targeting organic agriculture. Currently, certifications controls because of lack of time and money (expensive laboratory analysis) are mainly based on the verification of farmer’s accounting records (looking for prohibited input purchase) and very few parcels are actually controlled. Reliability of accounting control becomes more questionable when a farmer practices both organic and conventional agriculture on his land.
Earth Observation (EO) technologies present an important potential for providing an efficient, cheap, rapid and actual organic parcels control.
The main objectives of this PhD thesis is to develop a methodology based on Remote Sensing (RS) techniques that enables to discriminate organic fields from conventional ones, and in particular to assess the ability of the different current RS techniques (Multi-/hyper-spectral in high and very high spatial resolution) to identify the biophysical characteristics of the two type of parcels that enables to differentiate them. If successful the elaborated methodology could help organic certification bodies in the field certification process.
Because of specific management method, including exclusively organic fertilization and the exclusion of pesticide, organic farming fields differ from traditional ones by several aspects, among which lower plant nitrogen and chlorophyll concentration, higher intrafield heterogeneity of the canopy (crop’s height and biomass, disease extent) and a higher soil organic matter content.
The methodology used to identify biophysical differences between organic and conventional crops will consist of two main parts:
Field measurements: plant and soil samplings, hyperspectral crop measurements, chlorophyll content measurements, Plant Area Index derivation from hemispherical pictures, etc.
Various remote sensing data (high and very high resolution, multi and hyper spectral images) and spatial analysis techniques (spatial heterogeneity computation, biophysical indices derivation) will be used.
This research focuses in a first time on two crops, maize and wheat because they are quantitatively important (in terms of area covered), represent an important economic role and they have been the subject of numerous researches.
This PhD is conducted in parallel to a one year scientific research projects called “EOrganic”, a project from the European Space Agency (ESA).
- Can satellites help organic crop certification?
- Remote sensing and GIS techniques for supporting organic cotton certification process in West Africa.
- Remote sensing enables high discrimination between organic and non-organic cotton for organic cotton certification in West Africa