Skip to main content

Table 1 Variables, SDM, and species used in combination of both datasets of some researches

From: Integration of remote sensing and bioclimatic data for prediction of invasive species distribution in data-poor regions: a review on challenges and opportunities

Variables SDM References
Climate variables (mean annual rainfall, mean monthly temperature, monthly land surface temperature during day and night time)
Remote sensing variables (monthly land surface temperature during the day and nighttime, panchromatic reflectance, red reflectance, near-infrared reflectance, shortwave infrared band 6 reflectance, NDVI, elevation, slope, relief, landform, rugged, and distance to River)
Survey data (distance to road, distance to village)
Random Forest (RF) Shiferaw et al. (2019a)
Climate variables (temperature seasonality)
Remote sensing variables (elevation, landform, lithology, distance to water, distance to urban areas)
Survey data (distance to road)
RF, MaxEnt, logistic regression, Bayesian networks, Ensemble Ng et al. (2018)
Climate variables (19 WorldClim bioclimatic variables)
Remote sensing variables (bedrock, bulk density, cation exchange capacity, soil texture fraction clay, coarse fragments volumetric, soil organic carbon stock, soil organic carbon content, soil pH, soil texture fraction silt, soil texture fraction sand, land cover, gross primary productivity, coefficient of variation, gross primary productivity, elevation)
MaxEnt Truong et al. (2017)
Climate variables (WorldClim variables and MODIS land surface temperature)
Remote sensing variables (long term EVI, surface reflectance including blue, red, near-infrared, and middle infrared wavelengths and land cover data)
MaxEnt Cord et al. (2014a, b)
Climate variables (WorldClim bioclimatic variables)
Remote sensing variables (monthly NDVI and EVI), elevation and slope
MaxEnt Wakie et al. (2014)
Climatic variables (growing degree days, mean temperature of the coldest month, summer moisture index, summer sum of precipitations, winter sum of precipitations, yearly solar radiation, summer solar radiation, soil water balance, topographic wetness index, topographic position
Remote sensing variables (NDVI, Renormalized Difference Vegetation Index (RDVI), Modified Simple Ratio index (MSR), Modified Chlorophyll Absorption Ratio Index 1 (MCARI1), blue band, green band, red band, near-infrared band, slope and topographic position, distance to the nearest water body)
9 SDM including Generalized Linear Model (GLM), RF, Artificial Neural Network, and Ensemble model Engler et al. (2013)
Climatic variables (WorldClim bioclimatic variables)
Remote sensing variables (NDVI)
Partial Least Squares regression Feilhauer et al. (2012)
Climatic variables (WorldClim bioclimatic variables)
Remote sensing variables (LAI, vegetation density, seasonality, and net primary productivity, forest cover, and heterogeneity, surface moisture, and roughness (forest structure), seasonality, topography, and ruggedness)
MaxEnt Buermann et al. (2008)
Climatic variables (WorldClim bioclimatic variables)
Remote sensing variables (monthly NDVI, monthly LAI, percent tree cover, scatter meter backscatter monthly composites at 1 km, elevation)
MaxEnt Prates-Clark et al. (2008)
Climatic variables (Bioclimatic variables derived from DAYMET)
Remote sensing variables (NDVI)
GLM Zimmermann et al. (2007)