|Abstract||In this paper, we describe a new system for the construction of both land use and land use intensity (within agricultural regions) called LUCIA (land use and cover with intensity of agriculture). Our
methodology combines the highly detailed Canadian Census of Agriculture and recent growing season composites derived from the SPOT4/VEGETATION sensor. Census data are of much coarser resolution than the remotely sensed data, but, by removing
non-agricultural pixels from each census sampling area, we were able to spatially refine the census data sufficiently to allow it to be used as ground truth data in some areas. The refinedcensus data were then used in the final step of an
unsupervised classification of the remotely sensed data. |
The results of the land use classification are generally consistent with the input census data, indicating that the LUCIA output reflects actual land use trends as determined by national
census information. Land use intensity, defined as the principal component of census variables that relate to agricultural inputs and outputs (e.g. chemical inputs, fertilizer inputs, and manure outputs), is highest in the periphery of the great
plains region of central Canada but is also very high in southern Ontario and Québec.