| Title | Land use and cover with intensity of agriculture for Canada from satellite and census data |
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| Author | Kerr, J T; Cihlar, J |
| Source | Global Ecology and Biogeography; vol. 12, no. 2, 2003 p. 161-172, https://doi.org/10.1046/j.1466-822X.2003.00017.x |
| Year | 2003 |
| Alt Series | Natural Resources Canada, Contribution Series 20181250 |
| Publisher | Wiley-Blackwell |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Canada Centre for Remote Sensing Divsion |
| Released | 2003 03 07 |
| Abstract | To develop the first national databases on land use and agricultural land use intensity in Canada for a wide variety of environmental monitoring applications. Canada. 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 refine the census
data sufficiently to allow their use as ground truth data in some areas. The 'refined' census 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. |
| GEOSCAN ID | 311604 |
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