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Geofairtrade project - Geotraceability for fair trade

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    Fair Trade is characterised by a large number of small scale producers scattered around the world with limited access to resources. It is showing a very impressive sales growth rate and increasing diversification of products across Europe. Fair Trade includes the three dimensions of sustainable development: economic, social & environmental. To improve their management skills and their access to new markets, Fair Trade actors need to conduct dedicated actions to demonstrate that Fair Trade products have a positive impact with regards to traditional trade by developing standardised sustainability development indicators.

    European consumers/citizens are now more and more concerned about animal welfare, food chain safety and the protection of the environment. They clearly want more transparency: in other words, they want more information about the products they buy, the products they eat. Different information are already provided to end-users by the way of the certifications. The success of these certifications has demonstrated that end-users, not only want to have the guarantee that a given product comes from a specific region but also to have more information on the environmental context of this region or on the modes of production. In other words, the geographical aspect should be integrated in classical traceability schemes.

    Information on Fair Trade is often difficult to understand for people not directly involved in data processing ( e.g. consumers…) An other important drawback is the declaratory nature of the collected information on a mandatory or voluntary basis. Conventional traceability systems does not transmit along the agri-food chain any specific information about the environment (direct or indirect) of the field production. Environmental context is “invisible” to agri-food chain operators and to consumers. For producers there is no or limited valorisation of farm level traceability information. No management tools to calculate sustainability indicators.

    Many of the activities involved in Fair Trade rely on geography. One of the main pillars of Fair Trade is the ability to identify the origin of the food produced and to be able to identify where the food comes from. Geographic information technologies and data are becoming increasingly accessible, thanks to public spatial data infrastructures and geoportals (e.g. Google earth). Geographical information could play a special role, because of its potential to present information in a lively and understandable way to consumers and stakeholders.

    The main objective of the GEO FAIR TRADE project is to bring together Fair Trade CSOs and RTD performers. Discussions with the principle Fair Trade stakeholders and actors have shown that their basic needs to win new markets and new consumers are Transparency and Traceability. Taking advantage of the results obtained in two FP5 and FP6 research projects, the CCI Gers and its partners CRA-W and CIRAD, together with six Fair Trade CSOs, have defined the main objectives of the project which are: For Fair Trade producers and certification bodies: to propose a management tool based on sustainable development indicators . For Fair Trade actors and consumers: to develop an information system that gives an objective and clear image of the producers involved in fair trade focusing on their commitment to improve the social, economic and environmental situation in their region. For Civil Society Organizations (CSOs): to be involved in case studies on Fair Trade and to disseminate results achieved on geotraceability and on sustainable development issues through dedicated indicators .

    Geo-Traceability has been defined in the GeoTraceAgri (IST, 2001), GTIS-CAP (FP6, 2004) and PETER (FP7, 2007) research projects as the ability to trace, with the aid of specific management systems, geographical information linked to traceability information all along agro-food chains. Geo-Traceability combines the functionalities of conventional traceability systems with the functionalities of geographical information systems (GIS) in order to enhance the traceability information by placing it in its agri-environmental context (soil, regional characteristics, agricultural management at the farm level, etc.). These spatial and temporal data can also be used to define Geo-Traceability indicators. Geo-Indicators may relate to several themes, such as food safety, product quality (organoleptic quality and technological quality), quality of the environment and also social issues (sustainable production methods). In a sense Geotraceability Indicators also include Geo-SDIs that this project intends to propose in the frame of Fair Trade. Within a traceability system, a physical flow (product lot) is linked to a data flow (lot of product characteristics). In order to link both flows, Geo-Traceability needs a specific identifier, to enables a lot of products to be identified and located at any time in the supply chain.

    Geotraceability represents 3 different stakes and objectives The stakes are linked to Food quality and safety, Sustainable development issues and Globalisation of markets. The main objectives are : generate an added value products, reinforce communication and exchange of information and develop good professional practices between FT operators. Consumers are becoming increasingly concerned/attentive by product with origin authenticity discerning and would like to have more detailed information about what they buy, in particular the origin of the product or the production method used. This growing consumer demand is represented by an increasing marketing, branding or labelling of food that indicate where the product is originated and how it is produced (specific production methods illustrated with a specific food quality). Finally, a third part is the fact that geographic information (maps…) can help to understand product specifications and the fact that these specifications are often linked with sustainable and rural development objectives which have a spatial dimension. These assets explain the development of Gegraphical Indication (GI) label/certification in the international markets, where we can notice a trend from mass produced and standardized food towards origin-linked differentiated products .

    The concept of geotraceability can illustrated in the following example . The principle is to scan the matrix code (two-dimensional bar code) which is present on a coffee packet using a Camera Phones + Mobile code reader or or introduce the code number through the web portal. This identifier can make the link with different geographical information on the area of production (here landuse map and soil map). The general data infrastructure behind this process also allows to calculate, in an independent way, sustainable development indicators which can be used to gives an objective and clear image of the producers involved in fair trade focusing on their commitment to improve the social, economic and environmental situation in their region. The identifier can also be used visualise specific information on product

    To achieve all the functionalities of the previous example, it is necessary to build a dedicated spatial data infrastructure. A SDI is a framework of spatial data, metadata, specific identifiers users and tools that are interactively connected through the internet in order to provide a basis for spatial information discovery and evaluation. This infrastructure must meet some of the FT characteristics : It must be related to various field of activity (management, products certification…) It must be designed for multiple actors (producers, industry, consumers…) It must be able to manage various types of data (geographic and non geographic) It must be made up of various data sources (traceability, remote sensing imagery…) It must be made up of cross-cutting functionalities (indicator calculation) It enables a fast, easy access to data and services (through the internet)

    Data will come from a variety of sources To ensure that the system developed is applicable elsewhere, emphasis will be put on existing data sources. Moreover, it is likely that many of the data sources will be in the form of or derived from satellite imagery. Satellite imagery provides a synoptic view of a study area and a consistency of coverage across different areas difficult to match with other data sources. However, raw satellite imagery is not directly exploitable and needs to be interpreted to derive indicators. Some data sources that are directly exploitable and available at a regional and/or global level on a range of topics or themes: Globcover and Africover: information on land cover SRTM: eleva tion data Climatic data sources Nevertheless, these data will not necessarily be available at a sufficient level of detail both from a spatial and information content level. Therefore, there will be cases were the necessary information for deriving indicators need to be extracted directly from satellite imagery. In this context satellite imagery can be used at wo levels: To provide context for other data, e.g. visualise producers location on Google Earth Satellite imagery is processed using a variety of techniques/algorthms to extract relevant information, e.g. land cover, elevation, biomass, … There are a range of publically available data archives that can be accessed for this purpose

    Other sources of data will be available at national level or for specific projects and will concern the types of data mentioned in the previous slide at a more detailed level, but also data on the population (e.g. Census) and on the economic activity. Although, when available these data will be potentially very useful, there will to be acquired from a variety of format and harmonised. Problems in terms of heterogeneity, completeness and varying degrees of precision will need to be addressed, e.g. when possible by using bringing data to common standards, complete with satellite image derived products. Data collected directly by fair trade actors will also play a central role in the development of indicators. Part of the work involved will be to link the data available to the geographical area they correspond to. This process is known as geo-referencing, e.g. People related data connected to settlements locations Some data will be collected directly in the field using GPS.

    This shows a time series of satellite imagery illustrating the evolution of land cover around the Kilimanjaro with satellite images from the 70s 90s and 2000. Bright red on the image indicates green healthy vegetation. As the red becomes more pale, the density of vegetation decreases potentially indicating land degradation if the changes occur through time. The disappearance of the snow cover is very noticeable as well as the intensification of land use in the unprotected area around Kilimanjaro. In particular, more large scale plantations are present and small scale farming has also increased. Satellite images can be used simply to put other data in context as shown in this example as the location of a number of producer is shown on the image. Each point can then be linked to a database describing information on each point, e.g. FT products, level of production, ...

    Satellite imagery can be interpreted to provide information that can be used in the derivation of Sustainable Development Indicators (SDI). The image on the left is analoguous to a photo where the colours can be understood by a trained user, but cannot directly be used in a computer to make calculations. The image on the right is a derived product from the satellite imagery where each colour corresponds to a land cover that can be further combined with other data to derive indicators.

    The data integration in the GeoFairTrade Integrated Information System will enable us to provide a common platform to fair trade actors giving them the tools to perform analysis for a range of scale and indicators whilst maintaining data integrity and the necessary level of confidentiality. FT actors with no system in place will benefit form the GFT tools, but also FT actors who will have already developed their own system by making compatible with others. The characteristics of the GFT IIS will be defined as part of the project and specific project resources/activities will be devoted to give FT actors the opportunity to be fully involved in this process. The architecture/infrastructure developed as part of the previous projects will be used, e.g. database structure, as a skeleton for the GFT IIS. However, the interface and analytical tools will be developed specifically for the FT sector. An open architecture approach will be adopted making it possible to further expand and enhance the system developed The common architecture will make it possible to define common indicators. For example, it will be possible for a FT actor to derive indicators and make comparisons across continents for the same FT products or for a given region across several FT products. The level and type of functionality including the interface, will be defined with and for FT actors.

    Sustainable development is a development that meets the needs of the present without compromising the ability of the future generations to meet their own needs (Bruntland report, 1987). Sustainable development is focusing on improving the quality of life for all the earth’s citizens without increasing the use of natural resources beyond the capacity of the environment to supply them indefinitely. The field of sustainable development can be conceptually broken into three constituent parts: environmental sustainability, economic sustainability and sociopolitical sustainability. An indicator is defined as a quantitative or qualitative parameter that provides an overall description of the state of the environment or of a society. In order to be usable, it must meet a number of criteria, such as the scientific and statistical quality of the data used in calculating it, the availability and accessibility of those data and its relevance to the subject concerned and the needs of the potential users. An indicator can be used for the purposes of inspection (e.g., allowing to sort out products that do not match a certain quality level) and also for management of the farm or the agricultural environment, notably when integrated into a performance indicator relating, for instance, to compliance with agri-environmental measures. Geo Fair Trade indicators will selected with the aim to provide information on the essence of sustainable development (Social, Economic and Environmental pillars) Indicators will varying in nature according to the scale at which sustainability and multifunctionality are examined. In Geo Fair Trade, indicators will always present a geographic dimension. Example of socio-economic indicator: HDI (human development index) Aggregated from different indicators or index: life expectancy, adult literacy rate, gross enrollment ratio, Gross domestic product at parity , purchasing power party

    The exact type of environmental indicators will depend on the selection of case studies, but an example of a simple indicators that can be derived could be the proportion of degraded land that requires land cover data to be derived. More complex indicators such as erosion risk level will involve the combination of several data sources.

    Indicators for social and economic aspects will be more difficult to derive as the data available to calculate them are often avaialble at coarse administrative level. Statistical techniques exist whereby land cover information can be used to disaggregate socio-economic data based on the fact that land cover data provides information on settlements and a simple rule could be to assign population level data proportionally to the area covered by settlements. A more complex disaggregation model would be to develop a matrix covering the area of interest where each cell is given a value based on the combination of land use present.

    To ensure that confidentiality of data is preserved, data can be aggregated to retain a more general level of information, whilst preserving the information content required for the production of indicators. For example, individual producer data can be interpolated for the purpose of deriving indicators at an aggregated level. This is best shown with the soil sample example where data are collected at point location but represented for one or more soil characteristic (e.g. pH) over a 2D surface.

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    Geofairtrade project - Geotraceability for fair trade - Presentation Transcript

    1. Geotraceability for Fair Trade
    2. General background
      • Fair Trade is characterized by a large number of small scale producers scattered around the world.
      • It is showing a very impressive sales growth rate and increasing diversification of products across Europe.
      • Although Fair Trade originally focused on the social and economic dimension of sustainable development, it now also includes the environmental dimension.
      •  More standardized information is required to better describe the complexity of Fair Trade
    3. New consumer expectations
      • Consumers are now more concerned with :
        • Sustainable development issues.
        • Ethical issues.
        • Information on product characteristics.
        • Differentiation of products in a global market scheme.
        • Geographical and environmental information on production areas.
    4. More transparency for Fair Trade
        • For consumers, the information on Fair Trade products and specifically the certification process are difficult to understand.
        • The declaratory nature of the information collected on a mandatory or voluntary basis (no reliable information) may hamper consumer confidence.
        • Conventional traceability systems do not allow to retrieve specific information about the environment of the production area . (Environmental context is “invisible” to Fair Trade operators and to consumers).
        • For producers organizations, the valorisation of traceability information at production level is limited.
    5. The use of geographic information
      • Many of the activities involved in Fair Trade rely on geography:
          • - Product origin
          • - Environment and product interactions
          • - Socio-economical context
      • Geographic information technologies and data are becoming increasingly accessible, thanks to public spatial data infrastructures and geoportals (e.g. Google earth).
      • Geographical information could play a special role, because of its potential to present information in a lively and understandable way to consumers and stakeholders.
      Google Earth Geo browser - WMS SMARTPHONE & PDA
    6. Project objectives
      • For Fair Trade producer organizations:
        • to propose a user friendly self evaluation tool based on sustainable development indicators .
      • For certification bodies:
        • to facilitate FT certification process
      • For Fair Trade actors and consumers:
        • to develop an information system that gives an objective and clear image of the producers involved in fair trade focusing on their commitment to improve the social, economic and environmental situation in their region
      • For Civil Society Organizations (CSOs):
        • to be involved in case studies on Fair Trade and to disseminate results achieved on geotraceability and on sustainable development issues through dedicated indicators .
    7. The GeoTraceability concept
      • GeoTraceability also implies :
        • Linking traditional traceability data with geographical information related to production areas.
        • The use of geo-indicators related to food safety, product quality, quality of the environment and also social issues these include GeoSDIs to be developed as part of the project.
        • The use identifiers to enables a lot of products to be identified and located at any time in the supply chain.
        • GeoTraceability means the ability to retrieve
        • geographical information about the origin and
        • the territorial identity of an agricultural product.
        • => UPSTREAM of the agro-food chain
      A capitalization of existing knowledge and experiences of three European research projects (GeoTraceAgri, GTIS-CAP and PETER)
    8. Why GeoTraceability for Fair Trade ? Generate added value products GeoTraceability Reinforce communication and exchange of information Stake 1: Food quality and safety Stake 3 : Globalisation Stake 2 : Sustainable development in the context of climate change Consumers are becoming increasingly attentive on certification & authenticity of product origin Proof the geographical origin of products and of all the transformation steps Indisputable and understandable geographical information facilitate management of production systems while complying to standards Develop good professional practices between all the FT operators
    9. Geotraceability in practice: a tool to easily visualise the product origin and characteristics
    10. Geotraceability in practice: based on dedicated spatial data infrastructures
      • S patial data infrastructures is a framework of spatial data , metadata , specific identifiers users and tools that are interactively connected through the internet in order to provide a basis for spatial information discovery and evaluation.
      • An infrastructure which :
      • Is related to various field of activity (management, products certification…)
      • Is designed for multiple actors (producers, industry, consumers…)
      • Is able to manage various types of data (geographic and non geographic)
      • Is made up of various data sources (traceability, remote sensing imagery…)
      • Is made up of cross-cutting functionalities (indicator calculation)
      • Enables a fast, easy access to data and services (through the internet)
    11. Data Sources for Geotraceability (I)
      • Regional or international thematic data:
        • Directly exploitable:
          • ESA GlobCover
          • FAO Africover
          • Shuttle Radar Topographic mission
          • Climatic: CGIAR/FAO/EuMetSat
      • Satellite image archives:
        • Used as a backdrop to provide context for other data: e.g. Google Earth
        • Or require processing to extract relevant information
        • GLCF, Landsat, Aster, SPOT, …
    12. Data Sources for Geotraceability(II)
      • National data sources or specific to a project
        • Land cover/use
        • Infrastructure
        • Socio-economic data
          • Geo-referencing requirements
          • Potential use of land cover/use data
        • Characteristics: Heterogeneous, Incomplete, Varying levels of precision
      • Data collected by fair trade actors
        • Production data
        • Socio-economic data
        • Field data
          • Use of GPS
    13. Use of Google Maps or Google Earth and role of cartographic data Ville de Moshi 144.000 habitants
    14. Producteur 1 Producteur 2 Producteur 3 Producteur 4
    15. Use of land cover/use data sources
    16. GeoFairTrade Integrated Information System: a horizontal approach
      • Integration of existing and new data to bring them to a harmonised level
      • Builds on the architecture/infrastructure developed as part of the previous FP projects
      • Generic tool that can potentially be further developed expanded
      • Online/offline web portal providing a common analytical framework
    17. Sustainable Development Indicators
        • An indicator is defined as a quantitative or qualitative parameter that provides an overall description of the state of environment or society.
        • Geo Fair Trade indicators will be selected with the aim to provide information on sustainable development (Social, Economic and Environmental pillars)
        • Indicators will vary in nature according to the scale at which sustainability and multifunctionality are examined.
      Sustainable development is a development that meets the needs of the present without compromising the ability of the future generations to meet their own needs (Bruntland report, 1987).
        • GEO SDIs  Geographical dimension must be associated to SDIs
    18. Example of environmental indicators to be potentially developed
      • Proportion of degraded area
        • Land cover
      • Erosion risk level
        • Topography
        • Land cover
        • Soil types
        • rainfall
    19. Cartographic analytical tools: Socio-economic data disaggregation
      • Social or economic data sources are often only available at coarse administrative level
      • A more precise geo-referencing can be obtained by overlaying them with land cover data
      • Land cover data makes it possible to identify settlement areas and thus disaggregate socio-economic data based on the area covered by individual settlements
      • Data can be aggregated to preserve confidentiality
      • Use of interpolation algorithms to create surface layers from point data, e.g. soil samples example
      Confidentiality issues: Aggregation of data Soil Sample locations Interpolated data, e.g. Soil pH
    21. Expected Benefits for GFT producers
      • Facilitate certification
      • Management tool (self-evaluation)
      • Marketing tool
      • Downstream traceability tool (from producer to consumer)
      • Common Spatial Data Infrastructure definition
      • Facilitate the integration of sustainable development constraints as part of Fair Trade and increase Fair Trade visibility to consumers
      • Possibility for producer organisations to give access to independent information

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