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Table 7 Predicting water presence compared to random locations using GLM

From: Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia

Model Data Source Variable Odds Ratio P > |z| 95% CI Lower 95% CI Upper
SRTM-LandSat SRTM slope 0.40 <0.001 0.27 0.61
  SRTM TWI 1.29 0.02 1.04 1.59
  SRTM aspect 1.003 0.012 1.00 1.005
  SRTM TPI500 0.65 <0.001 0.55 0.75
LandSat -ASTER ASTER TPI2000 0.96 0.005 0.94 0.99
  LandSat 3:1 0.005 0.006 0.0001 0.22