The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 623–629, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-623-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 623–629, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-623-2021

  29 Jun 2021

29 Jun 2021

DETERMINATION OF REGIONS SUITABLE FOR AGRICULTURE IN THE GORDON COSENS FOREST OF ONTARIO BY MEANS OF ANALYTICAL HIERARCHY PROCESS WITH FUZZY LOGIC INFERENCE

R. Pittman, B. Hu, and G. Sohn R. Pittman et al.
  • Dept. of Earth and Space Science and Engineering, York University, 4700 Keele Street, Toronto ON M3J 1P3, Canada

Keywords: Analytical Hierarchy Process, Fuzzy Logic Inference, Land Management, Soil Texture, ELC Moisture Regime

Abstract. Analytical Hierarchy Process (AHP) with fuzzy logic inference on attributes was employed to determine areas most suitable for agriculture in the Gordon Cosens Forest (GCF) region within the District of Cochrane in northern Ontario, Canada. Attribute layers considered were soil texture, ELC (Ecological Land Classification) moisture regime, slope, canopy height model (CHM), distance to existing road networks and distance to water bodies. Fuzzy logic inference was utilized to rescale the attributes to a normalized range, taking into account preferability, which was then subjected to pairwise comparisons via AHP to determine the attribute layers' weightings. For the study area, the localities identified as most compatible for agricultural development include the southeastern section of the GCF at approximately 30 km south of the community of Fauquier and the westernmost area of the GCF at about 10 km east of Mattice.