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Assessing Neighbor and Population Growth Influences on Agricultural Land Conversion

Abstract

This study uses remote sensing data to assess the extent of agricultural land converted to developed (built-up) land in Alberta, Canada, from 2000 to 2012. Pairing aggregated conversion values with county-level census data, we further investigate the impacts of population growth and conversion activities in the neighboring areas on agricultural land conversion. To account for the omitted variable bias and spatial dependency, a first-differenced spatial regression model is used. The results show that spillover effects can be attributed to both neighbor conversion activities and neighboring population growth. Controlling for spatial dependence is important for producing estimates with minimized risk of bias. A policymaker who considers land use strategies in isolation from neighbors may make decisions with potentially adverse impacts. The dominant influences of population growth and spatial lag effects direct recommendations on regional planning mandates and mechanisms that promote densification in urban areas.

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Notes

  1. The Edmonton-Calgary Corridor (ECC) makes up just 6 % of the provincial land base, yet as of 2011 contains 74.2 % of the population (Statistics Canada 2011). The ECC includes Edmonton, Calgary, and 12 counties (Sturgeon, Parkland, Strathcona, Leduc, Brazeau, Wetaskawin, Ponoka, Lacombe, Red Deer, Mountain View, Rocky View, and Foothills) connecting these urban centers.

  2. The annual cropland category includes all AAFC categorized non-perennial crops, including grains, oilseeds, horticulture, fallowed land, and land too wet to be seeded. The forest category includes AAFC’s categories of coniferous, broadleaf, and mixed woodland .

  3. Population and agricultural data were not available for the years 2000 and 2012, so the nearest years for which Census of Population and Census of Agriculture data are collected were used instead.

  4. To determine the appropriate weights matrix, a first-order contiguity Queen weights matrix was compared to distance-based weights matrices. Distance-based weights were tested at 5-km intervals from a minimum distance of 20 km to a maximum of 180 km. The 35-km threshold was chosen on the basis of intensity of spatial correlation (the highest Z-score associated with Moran’s I test).

  5. Neighbor effects from agricultural land conversion and population density changes cause feedback loops as they affect each other simultaneously. To estimate an agricultural land conversion value, neighbor effects are calculated on one level only.

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Acknowledgments

This work was supported by the Alberta Land Institute.

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Correspondence to Feng Qiu.

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Haarsma, D., Qiu, F. Assessing Neighbor and Population Growth Influences on Agricultural Land Conversion. Appl. Spatial Analysis 10, 21–41 (2017). https://doi.org/10.1007/s12061-015-9172-0

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Keywords

  • Agricultural land conversion; population growth
  • Spatial regression model
  • Spillover effects
  • Alberta-Canada.