Mapping agriculture's impact by combining farm management handbooks, life-cycle assessment and search engine science. (June 2016)

• Record Type: Journal Article
• Authors: Navarro, Javier; Bryan, Brett A.; Marinoni, Oswald; Eady, Sandra; Halog, Anthony
• Is Part Of: Environmental modelling & software. Volume 80(2016:Jun.)
• Page Start: 54
• Page End: 65
• Publication Date: 2016-06
• Subjects: Sustainable intensification -- Life-cycle inventories -- Agricultural knowledge systems -- Spatial modelling -- Information retrieval -- Farm management handbooks; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.02.020
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Despite great advancements in recent years, the availability of detailed and regionalised farm practice data at national scale remains an obstacle for spatially-detailed research on sustainable intensification. Parsing and information retrieval techniques were applied to 385 farm management handbooks to estimate farm practices (use of fertilisers, pesticides, water, fuel) of 72 commodities grown in 42 regions. Life-cycle inventories were used to derive GHG emissions and energy use from farm practice data. Practices and impacts were mapped at 1.1 km 2 resolution using agricultural census data and a remote-sensing-based land use map. Existing data was linearly extrapolated using a rule-based approach to fill spatial gaps. Estimates were, in aggregate, comparable to the best available data at national and local scales. Our method contributes to the push to create more spatially-detailed assessments of agricultural impacts at a national scale by focusing on the production of basic data at the farm level. Highlights: Our method estimates farm practices from a large number of farm management handbooks. It extracts handbook knowledge with natural language processing and query expansion. Practices are mapped to 1.1 km 2 resolution and linearly extrapolated to fill gaps. The practices mapped are use of fertilisers, pesticides, water and fuel. GHG emissions and energy use are derived from practices with life-cycle inventories.