By Ger Devlin
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Fuzzy Sets. M. & Fabbri A. G. (2008). Application of spatial multi-criteria analysis to site selection for local park: A case study in the Bergamo Province, Italy. Journal of Environmental Management, 88, 752-769 Development of an Open Source GIS Based Decision Support System for Locating Wind Farms in Wallonia (Southern Belgium) 41 Appendix 1a – list of the selected ‘environmental’ constraint criteria Category ID 1 2 3 4 5 6 7 8 9 Environmental 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Criteria Alias Special Protection SPA Area Natura 2000 sites N2000 Site of ornithological BIRDS value Nature Reserve RES Underground cavity CSIS of scientific interest Central zones of Local CZLPND Plan for Nature Development zhib ZHIB Site of high biological SHBV value Airports AIRP Airplane landing ALR runway Microlight landing MLR runway Acoustic effect ACOU Zone of potential FLICK flicker effect High voltage lines HVL Proximity to roads ROAD Proximity to railroad RAIL “Green” parks GREEN Area devoted to NAT nature Parks PARK Close protection of CPWPZ water producing zone Remote protection of RPWPZ water producing zone Landslide risk LSL Area with important IKR karstic risks Area with karstic risks KR Risk of interference ANT with radio antenna Reference Constra Geo features int level processing Buffer zone (m) Polygon EX feature Polygon SE feature Polygon HS buffer Polygon EX feature Point EX buffer Polygon EX feature Polygon EX feature Polygon SE feature Polygon HS buffer Point HS feature Point SE buffer 2000 Polygon EX buffer 350 Polygon SE buffer 700 Line Line Line Polygon HS EX EX EX buffer buffer buffer feature 150 40 40 Polygon EX buffer 200 Polygon EX feature Polygon EX feature Polygon SE feature Polygon EX feature Polygon EX feature Polygon SE feature Polygon HS buffer 150 100 5000 600 42 Decision Support Systems, Advances in Appendix 1b – list of the selected ‘landscape’ constraint criteria Category ID 26 27 28 29 Alias Heritage landscapes Highly sensitive landscapes & territories Small wood lots PL Polygon EX feature HSLT Polygon HS feature SWL Polygon HS feature Buffer zone (m) Hilly forests Forest with recreational value Nature parks HF Polygon HS feature FRV Polygon HS feature NP Polygon SE feature 32 Large common rural landscapes LCRL Polygon HS feature 33 Proto-industrial landscape units PILU Polygon EX feature 34 Industrial landscape units with heritage value ILPV Point SE buffer 35 Urban landscape units with heritage value ULPV Point EX feature 36 Rural landscape units with heritage value RLPV Polygon SE buffer 2000 37 Linear features with heritage value LFPV Line HS buffer 1250 38 Viewshed of classified monuments VCM Polygon HS feature ZLV Polygon SE feature PLV Polygon SE feature 30 31 Landscape Reference Constra Geo features int level processing Criteria 39 40 Zones of landscape value Perimeter of landscape value 2000 3 Forecasting Rubber Production using Intelligent Time Series Analysis to Support Decision Makers Panida Subsorn, Dr.
For this reason, several tools used in the DSS for producing decision supports are common to those used by the PPO. Providing criteria for justifying actions. ). For example, the Directive on Sustainable Use of Pesticides requires the use of IPM in all the EC Member States by 2014, and asks governments to establish and apply methods for determining whether farmers apply IPM principles in practical crop management. In this context, site-specific data, scouting reports, and recommendations from the DSS will serve as acceptable criteria for justifying (to regulatory authorities, wholesalers, or processors) the application of chemicals.
207-238, ISSN 0032-0862 Rabbinge, R. T. (1989). H. ), pp. 3-15, Pudoc, Wageningen, The Netherlands A Web-based Decision Support System for Managing Durum Wheat Crops 25 Rabboni, T. (2009). Rinnovato l’Accordo di filiera Grano duro di alta qualità. Filiera Grano Duro News, Vol. 10, No. R. A. (1997). Input Optimization and Crop Management Using Decision-support System GLYCIM/GUICS, In: Proceedings of the International Congress on Modeling and Simulation, A. ), Vol. 3, pp. ; Pancaldi, D. & Alberti, I.