About Us

Chris Finch



Mustafa Erkan Şahin




Chris Finch is based in the UK. He has 30 years of experience of the collection, interpretation and analysis of agricultural and environmental data in the UK and internationally. He has a deep understanding of the use of Earth Observation (EO) data for agricultural and environmental evaluation and monitoring.

He has worked extensively with land use data and assessing land use change and in the quality assurance of land use inventories and land use change assessments, including identifying needs, gap analysis, key category analysis and uncertainty assessments

He has experience of using training workshops to inform and update stakeholders and key delivery staff on issues related to data collection, data analysis and policy implications of land use and land cover systems and inventories.

He has more than 20 years’ experience of implementing European agricultural statistical systems, working in the UK, Ireland, Slovak Republic and Turkey, with particular experience of Land Parcel Identification Systems (LPIS) and Integrated Agricultural Control Systems (IACS). He has extensive knowledge of Turkey and the South Caucasus, having recently worked as KE4 in the External Quality Control Team (EQC), based in Ankara, Turkey, March 2015 to October 2017, with responsibility for Quality Control issues in the project: External Quality Control under Digitisation of Land Parcel Identification System, Turkey: EuropeAid/132338/D/SER/TR. He has also worked on assessing rangeland condition in South Georgia.

Chris is a technical specialist in agricultural and countryside policy and assessment, particularly in agri-environment and sustainable development.

He has a strong understanding of agriculture statistics reform – acted as Quality Control Manager for the implementation in 2002 and 2009 of the Eurostat LUCAS survey in the UK and Ireland, and throughout his career has advised governments and relevant statistics institutions on new technologies and methodologies for data collection, analysis and interpretation.


Mustafa Erkan Şahin is based in Ankara, Turkey. He is a specialist in GIS and remote sensing. Currently completing his MSc in Remote Sensing and GIS at Anadolu University, he is researching the use of support vector machines to help improve the accuracy of the automated classification process for remotely derived earth observation imagery.

Erkan has worked for the over two years on the completion of the Turkish Land Parcel Identification System (LPIS), as Team Leader of a team carrying out IQC controls of digital data derived from imagery of Turkey flown in 2015 and 2016. He has good experience of LPIS systems, digital data production and structure following EU standards. He was involved in data quality control in LPIS systems included technical and visual checks of digitisation accuracy during and at the end of production for each area delivered.

He also has experience of digitization of agricultural blocks and cadastral parcels in land consolidation projects in Turkey, including the design of blocks used as outcome data and the area of new parcel plans taking account of results derived from irrigation and hydrology projects, DEM data, social reports of the environment, engineering results, etc. He has provided training to the various companies and institutes on the same topic.

Quality Control of block designs included short edge/long edge providing 1/3-1/7 rate minimum for the most efficient agricultural parcels by various spatial analysis. Topology controls were also included.

He has experience on digitization of a range of classification maps, utilising GIS analysis to create classification maps using a variety of algorithms including road, soil, settlement and commission maps.



Chris Finch and Erkan Şahin have worked closely together on an EU-funded project to create a Land Parcel Identification System (LPIS) for Turkey, helping to ensure high quality and consistency of delivered digital data.

Chris was one of four key experts for the external quality control team (EQC). Erkan was a Team Leader in the internal quality control team (IQC) for the digitising contractor in Lot 1. A complete set of orthophotos was provided for the whole of Turkey, forming a huge dataset of over 50,000 individual images and almost 1 petabyte of data. A team of over 200 digitisers worked with the orthoimagery in a huge exercise to create a seamless geodatabase of reference parcels (agricultural blocks) covering the whole of Turkey’s agricultural surface and non-agricultural areas, in total almost 784K sq km. It is the single largest land cover digitising exercise in the whole of Europe.

Working through Environment Systems Ltd (www.envsys.co.uk) the role of Chris Finch, in a small External Quality Control team (EQC), was to ensure that the data provided meets EU JRC criteria for the quality requirements for an LPIS. The work involved evaluating a sample of all reference parcels digitised across the whole of Turkey, including automatic, thematic and visual controls.

As Team Manager, Erkan Şahin was responsible for internal IQC controls of digital data within Lot 1, devising and implementing technical and visual checks of digitisation accuracy during and at the end of production for each area delivered.

Turkey is a huge and agriculturally diverse country. There is a large arable and cereal sector (including rice and tobacco), major citrus fruit, wine and olive production, and with large areas of nut (hazelnut, walnut, almond and pistachio) and tea production. There are also extensive high biodiversity grasslands and forests.

Mapping and classifying this diversity presented many challenges, but the project was successfully completed in October 2017, after three years of intense activity.


Chris Finch provided technical expertise to an Environment Systems project for Mercy Corps in Georgia in 2011 (www.envsys.co.uk) to undertake an assessment of rangeland condition across the regions of Kvemo Kartli and Samtskhe-Javakheti. The study was undertaken under the Alliances Programme, a market development programme working in the beef, sheep and dairy sectors, run by Mercy Corps and funded by the Swiss Agency for Development and Cooperation (SDC).

Rangeland condition is a key concern underpinning the traditional pastoral system. It has often been assumed that where livestock are present they cause rangeland degradation through overgrazing. This project assessed current rangeland condition, looked at historical trends and identified factors contributing to condition. The study provided a baseline from which to inform and guide programme policy and future interventions surrounding access to pasture and improved nutrition for small scale livestock producers. The overall aim is to help ensure the future sustainability of the livelihoods of the local rural population.

The study utilised earth observation (EO) data, derived from Landsat satellites, using multispectral scanner analysis techniques to map rangeland condition into three classes of good, moderate and poor, supported and confirmed by limited ground truthing and discussions with local officials, farmers and graziers. The project found significant climatic effects on rangeland condition, with an increasingly early snow melt leading to faster drying out and burn-off of the grassland pastures later in the year.


Chris Finch was appointed as a Non-Key Expert tasked to advise and recommend on how research can support the improvement of the Turkish Greenhouse Gas (GHG) inventory for the LULUCF sector.

Key tasks included:

  • Identification of the main needs and research gaps of the Turkish National GHG Inventory
  • Attendance and facilitation of a 2 day workshop in Ankara, with all key LULUCF stakeholders from academia, Ministry of Forestry and Water Affairs (MoFWA) and Ministry of Food, Agriculture and Livestock (MoFAL)
  • Facilitation of a SWOT analysis by all Workshop attendees
  • Assessment of results of SWOT analysis and existing research projects and new research ideas that may support the LULUCF inventory
  • Preparation of a report on “How research can support the improvement of the Turkish GHG inventory for the LULUCF sector” based on the findings from activity A 1.1 (The review of existing information related to LULUCF sector AD and EF) and assessment of existing research projects and new research ideas that may support the LULUCF inventory.

He also provided advice on monitoring land use and land cover change in Turkey to the main contractor tasked with developing a Turkish national land use change monitoring system for use in GHG calculations (Geoville).


Erkan Şahin was commissioned by DSI to design irrigation lines feeding agricultural parcels in Şanlıurfa Suruç and Aydın Bozdoğan as part of continuing agricultural reform programme. Work involved;

  • Designing and Digitisation of parcel irrigations in Turkey using GIS software and databases also engineering parameters. The project is the first model in Turkey on the idea “in farm irrigation”. More than 15.000 irrigation lines designed until now.
  • The design required that each parcel had to be accessible for irrigation from local water hydrants.
  • Each irrigation line needed an optimal design balancing length of pipeline, distance from hydrant (to maximize water pressure) and cost.
  • Projects were carried out in ESRI products using spatial databases instead of CAD software which is more efficient and produces more rapid output.
  • The designs will be used to construct irrigation lines in the field before it starts, local farmers will be consulted to agree the irrigation layout.

Chris Finch produced a short report for Environment Systems Ltd in 2017 (www.envsys.co.uk) on the agricultural trade between Turkey and the UK as an input to a wider project on the potential for the use of EO data in improving agricultural productivity and sustainability. It assessed current levels of trade, as well as challenges and opportunities in the future for sustainable agriculture, rural development and food security in Turkey. Key interest in EO data was likely to be in:

  • Assessing and monitoring land use and land cover change, particularly changes in grassland and forestry cover as productive agriculture develops
  • Developing indicators of soil water availability, to better target and focus irrigation needs and requirements
  • Developing indicators of crop health and early estimates of yield, especially in the key fruit, nut and vegetable sector, so important to the Turkish export trade
  • The regular availability of data in the key spring and early summer growing season will make assessments of agricultural productivity more effective and useful for planning and monitoring purposes

Erkan Şahin is currently finishing his MA researching on Improving Classification Methods using support vector machines. SVM is very popular to use in statistical calculations in different areas. Research’s aim is to adopt this algorithm into remote sensing classifications to get a better classification from the imagery. Research is continuing.



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