EC/FAO Programme on Information Systems to Improve Food Security Decision-Making in the European Neighbourhood Policy (ENP) East Area Training on introduction of Geographic Information System (GIS) to improve cropforecasting system in Armenia 1. Background Armenian State Agrarian University, Yerevan, Armenia January 25 February 7, 2012 - REPORT - A two week training was jointly organized by the ARMSTATEHYDROMET (hereinafter: Hydromet) and FAO under the EC/FAO Programme on Information Systems to Improve Food Security Decision-Making in the European Neighbourhood Policy (ENP) East Area from January 25 to February 7, 2012. The Programme is financed by the European Commission and implemented by FAO. The Programme aims at improving food security by enhancing the national capacity to generate, analyse, communicate and mainstream more relevant and reliable information into policies and programmes. The training took place at the Armenian State Agrarian University. 2. Training objectives Objective of the training was to get participants acquainted with geographic information systems and their application in agriculture. The training provided both theoretical and practical knowledge and skills in data collection, database management and computer mapping in order to work independently with ArcGIS software, GIS project design and management. The knowledge and skills acquired will be immediately applied to used for the improvement of Agromet Bulletin. The training was conducted by a national consultant, Hovik Sayadyan (Professor, Lecturer of GIS at Yerevan State University). 3. Participation The training was attended by 15 participants. Training was organised for the stakeholders of the Programme concerned with crop forecasting, including mainly staff from Hydromet (Agrometeorological and Climatology Units, 13 participans), Ministry of Agriculture (Agricultural Planning Department, 2 participants). The training was also attended by some members of the Crop Forecasting Working Group, 2 members. The objective of Crop Forecasting Working group is to provide decision-makers with reliable information on crop forecasting through improving crop forecasting system in Armenia.
The list of participants is provided in Annex 1. Figure 1. Training session Figure 2. Group picture 4. Process Introductory speeches The participants were welcome by the Country Coordinator of the EC/FAO Food Security Information Systems to improve decision-making. The Country Coordinator noted the importance to improve crop-forecasting system in Armenia taking into account the problems related to climate change and the importance of producing the Agromet Bulletin to provide timely information to stakeholders, including farmers. The training itself was very technical. Course was composed of 10 lectures, which include theoretical part and exercises. Each lecture/exercise was composed of 4 hours-1 hour lecture and 3 hours of exercises, in total it made 10 hours of lecture and 30 hours of exercises. Before the initiation of the training Armstatehydromet provided the following information on: 2
- Data set of rainfall data on 38 stations for 1 month during the crop season. - Data set of crop yield on one cereal crop. Main topics of the training were: Fundamentals of GIS: Introduction, defining of GIS, Components of GIS; Displaying map data: navigating a map, looking at feature attributes; Symbolizing and classifying features and rasters, Labeling features; Database management: Database data models, creating a database, GIS database applications, developments in database; Spatial data analyses: Spatial data models and structures, modeling surfaces and networks; Data input and editing (Presenting data): Methods of data input, data editing, towards an integrated database; production and export of thematic maps including labeling and legend insertion into Agromet Bulletin, production of color tables to assign legend to the thematic maps; Data analysis: Measurements in GIS-lengths, perimeters and areas, queries, reclassification, calculations; performing interpolation of the main agrometeorological variables (rainfall, temperature, crop yield) using Inverse of Distance method, Overlay the DEM layers into maps; Analytical modeling in GIS: Process models, modeling physical and environmental processes, modeling human processes; starting a model, building a model, enhancing a model; Remote sensing and GIS: Fundamentals of remote sensing, satellite imagery, aero-photos, satellites for the study of natural resources, links between remote sensing and GIS; raster data, raster analysis, storing raster, import NDVI from METEOR-AVHRR (http://www.metops10.vito.be/metop-s10_pages/main.html#distribution), produce a mask to mask-out areas that are not interesting (e.g. non agricultural areas); Global positioning systems (GPS) and GIS: Principals of global positioning systems, different GPS systems, GPS link to GIS environment; GIS project design and management: Problem identification, designing a data model, project management, implementation problems, project evaluation. Each presentation was followed by practical exercises to strengthen the capacities of the trainees in using the new technique. The training was designed and organized in order to engage all participants in discussions and reflect on appropriate recommendations for all state institutions involved in crop forecasting in Armenia. The training agenda is provided in Annex 2. 3
The participants were very much interested in the materials provided by the Lecturer. They agreed that, the duration of the training was insufficient taking into account the complexity and volume of information provided More time was needed for practical exercises. The Lecturer confirmed his readiness to assist the trainees in further practical work upon a request. The manual on GIS was provided to Hydromet for reference. 5. Evaluation of the training Participants were asked to assess the relevance and effectiveness of the training at the end of the training. The evaluation forms and the results of the surveys are presented in Annex 3. 6. Conclusions and follow-up actions The training was successful in meeting its objectives. At the end of the two week training, participants were able to use the models and to perform analytical modelling of GIS independently, in particular: - Produce and export thematic maps including labeling and legend insertion into Agromet Bulletin. - Perform interpolation of the main agrometereological variables (rainfall, temperature, crop yield) using the Inverse of Distance method. - Extract area of statistics for specific shp. Files (Marz administrative division) - Overlay the Digital Evaluation Model layers into maps. - Produce a Mask to mask-out areas that are not interesting. (i.e. non agricultural areas) - Import data from Excel files. - Import NDVI from METOP-AVHRR (http://www.metops10.vito.be/metop- S10_pages/main.html#distribution) into GIS. - Produce colour table to assign legend to the thematic maps. The discussions during the training demonstrated that there is strong interest from the national institutions in improving crop forecasting in Armenia. The training was successful in gathering both users and producers of information. It is worthwhile noting that the Ministry of Agriculture (MoA) is both producer of information (providing operational data) and user of the Agromet Bulletin for policy-making. There was excellent collaboration between the institutions involved in crop forecasting, in particular Hydromet and MoA. The training clearly demonstrates that this collaboration is indispensable for improving crop forecasting and will need to be institutionalized for sustainable results. Follow up actions agreed by the participants are the following: Trainees, in particular Hydromet staff, will use the newly acquired capacity in GIS for compiling the Agromet Bulletin. The first draft of the updated Bulletin is planned to be issued and disseminated to Marz support centres end of March. The Programme will organize a number of other training sessions for improving crop forecasting 4
Annex 1. List of participants Two-week GIS training to improve crop forecasting, in particular to assist in development of Agromet Bulletin 1. Armine Sahakyan, Agrometeorological forecast division, leading specialistarminebob@gmail.com 2. Nelli Arakelyan, Agrometeorological forecast division, first class specialist nelliarakel@gmail.com 3. Susanna Shindyan, Climate research division, first class specialist -susshindyan@gmail.com 4. Ashkhen Iritsyan, Climatology division, first class specialist -ashkheniritsyan@gmail.com 5. Azat Safaryan, Climatology division, first class specialist azatsafaryan@mail.ru 6. Narine Saghoyan, Hydro meteorological information service division, senior specialist - narine.saghoyan@mail.ru 7. Lusine Yeritsyan, Hydro meteorological information service division, leading specialist - lusi.ya82@yandex.ru 8. Marine Beluyan, Meteorological forecast division, leading specialist - marine_beluyan@mail.ru 9. Andryusha Avagyan, Meteorological forecast division, leading specialist a_n_d_84@mail.ru 10. Mariam Mkhitaryan, Agrometeorological division, leading specialist sammar52@hotmail.com 11. Lilit Aghajanyan, Hydrography division, senior specialist lilithydro@mail.ru 12. Edgar Yeganyan Hydrography division, first class specialist eyeganyan@gmail.com 13. Diana Hovhanissyan, Applied Climatology Division - dianahovhannis@gmail.com 14. Heriknaz Lemberyan, MoA, Agricultural Planning Dpt. - erika5arm@yahoo.com 15. Artur Petrossyan, MoA, Agricultural Planning Dpt - artur5arm2003@yahoo.com 16. Valentina Grigoryan, Advisor to Director of Armstatehydromet Service - valent_g2000@yahoo.com 17. Zara Petrossyan, Head of Hydrometereological Operation Centre of Armstatehydromet Service - edittaron@gmail.com 5
Annex 2. Training agenda EC/FAO Food Security Information Systems to improve decision-making TRAINING TOPIC: GIS application in Agro-meteorology Instructor: E-mail: Dr.Hovik Sayadyan hovik_s@yahoo.com Phone: +374 91382978 Training objective The objective of the training is to provide assistance to Armstatehydromet in application of the GIS to improve crop forecasting system in Armenia. The application of GIS could bring all different aspects of agriculture and agro-meteorology together and enhance effective decision making through different analyses and data processing. Two week training on GIS basic course and its application in agro-meteorology, will assist the trainees: to understand GIS and its application for the analyses of agromet and phoenological data to have both theoretical and practical knowledge in data collection, database management and computer mapping to work independently with ArcGIS software, GIS project design and management Target group 15 staff of Armstatehydromet Service and other national stakeholders. The list and positions were provided by Armstatehydromet Service. Venue and resources Training will take place in the Armenian State Agrarian University (ASAU). The room is furnished with tables, whiteboard, 4 PCs with GIS software etc. The trainees will ensure the availability of personal computers. All this is provided by Armenian State Agrarian University free of charge. Some other technical staff, e.g. stationery, memory sticks are provided by the Programme. Training outline The course is offering an understanding of geographic information systems and their application for the study of agricultural issues. Course is composed of 10 lectures, which include theoretical part and exercises. Each lecture/exercise is composed of 4 hours-1 hour lecture and 3 hour of exercises, in total it makes 10 hour of lecture and 30 hours of exercises. Before the initiation of the training Armstatehydromet is supposed to provide the following information: 6
- Data set of rainfall data on 38 stations for 1 month during the crop season. - Data set of crop yield on one cereal crop. Lecture 1 (January 25): Fundamentals of GIS: Introduction, defining of GIS, Components of GIS Exercise 1: Displaying map data, navigating a map, looking at feature attributes Lecture 2 (January 26): Displaying data: Symbolizing and classifying features and rasters, Labeling features Exercise 2: Changing symbology, symbolizing features and rasters, classification by standard and manual methods, using graduated and chart symbols Lecture 3 (January 27): Database management: Database data models, creating a database, GIS database applications, developments in database Exercise 3: Overview of tables, database management systems, queries on tables, joining and relating tables, summarizing tables, import data from Excel files Lecture 4 (January 30): Spatial data analyses: Spatial data models and structures, modeling surfaces and networks. Exercise 4: Using location queries, preparing data for analyses (dissolve features, clipping layers, etc.), buffering features, overlaying data, calculating attribute values, extract area of statistics for specific shp. files (Marz administrative division) Lecture 5 (January 31): Data input and editing (Presenting data): Methods of data input, data editing, towards an integrated database Exercise 5: Basic elements of map design, choosing symbols, labels and titles, setting up scale bars, choosing coordinate system. Production and export of thematic maps including labeling and legend insertion into Agromet Bulletin. How to produce color table to assign legend to the thematic maps Lecture 6 (January 1): Data analysis: Measurements in GIS-lengths, perimeters and areas, queries, reclassification, calculations Exercise 6: Perform interpolation of the main agrometeorological variables (rainfall, temperature, crop yield) using Inverse of Distance method, Overlay the DEM layers into maps Lecture 7 (February 2): Analytical modeling in GIS: Process models, modeling physical and environmental processes, modeling human processes Exercise 7: Starting a model, building a model, enhancing a model Lecture 8 (February 3): Remote sensing and GIS: Fundamentals of remote sensing, satellite imagery, aero-photos, satellites for the study of natural resources, links between remote sensing and GIS Exercise 8: Raster data, raster analysis, storing raster, import NDVI from METEOR-AVHRR (http://www.metops10.vito.be/metop-s10_pages/main.html#distribution), produce a mask to maskout areas that are not interesting (e.g. non agricultural areas) 7
Lecture 9 (February 6): Global positioning systems (GPS) and GIS: Principals of global positioning systems, different GPS systems, GPS link to GIS environment Exercise 9: Obtaining GPS points, Input of GPS data into GIS environment, link GPS data with other GIS layers Lecture 10 (February 7): GIS project design and management: Problem identification, designing a data model, project management, implementation problems, project evaluation Exercise 10: Examples of GIS project design and management Note: Copies of lecture handouts and related materials, as well as copies of exercises that trainees did during the training will be distributed to the trainees on memory sticks. 8
Annex 3. Evaluation results Evaluation Form A. What is, according to you, the level of concordance between the training programme and the objectives of EC/FAO Programme on food security Information Systems? 1.Fundamentals of GIS: Introduction, Components of GIS, Displaying map data, navigating a map, looking at feature attributes 2:Displaying data: Symbolizing and classifying features and rasters, Labelling features classification by standard and manuall methods, using graduated and chart symbols 3.Database management: Database data modelsgis database applications, database, queries on tables, joining and relating tables developments in 4.Spatial data analyses: Spatial data models and structures, modeling surfaces and networks, using location queries, preparing data for analyses, buffering features, overlaying data, calculating atttribute values, extract area of statistics for specific shp. files (Marz administrative division) 5: Data input and editing: Methods of data input, data editing, towards an integrated database, choosing coordinate system. Production and export of thematic maps including labeling and legend insertation into Agromet Bulletin. 6: Data analysis: Measurements in GIS-lengths, perimeters and areas, queries, reclassification, calculations, perform interpolation of the main agrometeorological variables (rainfall, temperature, crop yield). 7: Analytical modeling in GIS: Process models, modeling physical and environmental processes, modeling human processes, building a model, enhancing a model 9
8: Remote sensing and GIS: Fundamentals of remote sensing, satellite imagery, aero-photos, links between remote sensing and GIS, raster analysis, import NDVI from METEOR-AVHRR (http://www.metops10.vito.be/metop-s10_pages/main.html#distribution) 9: Global positioning systems (GPS) and GIS: Principals of global positioning systems, different GPS systems, GPS link to GIS environment 10: GIS project design and management. Give your comments:.. B. Do you estimate that your training will be beneficial to the activities of your Service or Institution? Yes No C. Estimate how this training programme will serve in your activities in your country?. D. Evaluate the level of this training according to your own instruction level and your experience. appropriate level too high level too low If the level did not suit you, give explanations:. E. Do you estimate that the length of your training was sufficient? Yes No If no, what is according to you, the length that is the more suitable?. F. How do you estimate the organization of the training programme? good middle mediocre Comments:... G. Please indicate any comments that appear important and relevant on any non-didactical aspects that were not mentioned above.... 10
H. Do you have some recommendation for FAO and EC for the improvement of such kind of training session?... Date Results of the evaluation 17 participants have participated at the training and 15 of them filled out the questionnaire. The results of the survey among the respondents were as follows: The majority of the respondents (80%) acknowledged that the relevance of training and level of concordance between the training program and the objectives of EC/FAO Programme on Food Security Information Systems was very high (excellent and very good) and only three respondents considered that the level was good (Figure 1). Figure 2 illustrates the answers provided by the respondents regarding the relevance of the specific sections of the training. Figure 1. Level of concordance 11
Figure 2. Relevance of specific sections of the training All respondents considered that their service or institution will benefit from the training. Almost all respondents (14 out of 15) estimated that the level of the training was appropriate taking into account their knowledge and experience. However, as illustrated in Figure 3, about two-thirds of the respondents considered that the length of the training was insufficient. This issue was discussed during break-time discussions: a number of trainees estimated that more time was needed for practice as many aspects of the training were very technical. Figure 3. Duration of the training (sufficient or not) The organization of the training was appraised positively. As shown in Figure 4, all respondents found that it was very good or excellent. 12
Figure 4. Organization of the training In addition, all trainees were very satisfied with the Lecturer s training capacity and teaching methods. They highly appreciated the trainer s skill and experience. All trainees considered that it will be very useful to have the continuity of the training and as a recommendation they suggested to organize this kind of trainings more often. 13