The Land Suitability Rating System is a spatial planning tool to assess crop suitability in Canada

摘要

The Land Suitability Rating System (LSRS) is a rule-based set of algorithms that integrates soil, climate and landscape factors to calculate a classed suitability rating for a given landscape to support commercial field crop production. The attributes used to define each of the factors are based on their proven ability to affect crop growth, their ability to be measured (or estimated by proxy) and their availability in accessible databases. The LSRS was first published in 1995 by Agriculture and Agri-Food Canada as a site-specific, manual calculator for spring-seeded small grains that incorporated sets of attribute point deduction curves based on expert knowledge. Since that time the system has been expanded to include additional crop modules and all data handling and calculations are automated through a set of web-based applications. The current version of LSRS (version 5) is implemented in Ruby on Rails? software as a suite of web services. The system runs against any soil map with standardized Canadian Soil Information Service soil data tables to process soil attributes and calculate limitations to crop growth. A climate factor rating is based on crop-specific agro-climatic indices and thresholds. Climatic indices have historically beene calculated from 30 year climate normal periods using monthly data but LSRS can now also utilize daily data records which facilitate trend analyses within annual historic records. Outputs from Global Circulation Models can also be used to assess potential impacts of climate change on crop suitability. Gridded climate datasets enable direct overlay and extraction of climate attributes to the spatial extent of soil map polygons. Finally, the system incorporates a landscape factor related to land erodibility and constraints to management. Each of the three suitability factors is assigned a class rating between 1 (no limitations) and 7 (unsuitable) with the final overall rating being the most limiting of the three factors. Recent improvements in the ability of the system to process multiple climate datasets have resulted in LSRS used increasingly as a spatial research tool in assessing climate change impacts on agricultural crop distributions at both national and regional scales.