Quantifying Spatial and Environmental Effects in Spatial Autoregressive Model with the spatialreg.hp R package Abstract. Ecological data frequently exhibit spatial autocorrelation, whereby geographically proximate sampling units are more similar in species distribut

【🎉Latest accepted article】
Quantifying Spatial and Environmental Effects in Spatial Autoregressive Model with the spatialreg.hp #RPackage

#AverageSharedVariance | #HierarchicalPortioning | #SpatialAutocorrelation | #VariationPartitioning

@mapjournals.bsky.social

doi.org/10.1093/jpe/...

The biogeography of soil- and airborne fungi in the southwestern U.S. in relation to climate and vegetation Abstract. To assess how fungal dispersal might respond to climate change, we examined how climate and geography influence the regional distribution of fung

The biogeography of soil- and airborne fungi in the southwestern U.S. in relation to climate and vegetation

#dispersal
#distance-basedredundancyanalysis
#distance-decayrelationships
#fungalcommunitycomposition
#precipitation
#spatialautocorrelation

academic.oup.com/ismecommun/a...

Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing Machine Learning - Spatial autocorrelation is inherent to remotely sensed data. Nearby pixels are more similar than distant ones. This property can help to improve the classification performance,...

NEW PAPER about the impact of #spatialAutocorrelation between training and test sets on classification performance in remote sensing.A brief story ⬇️

bit.ly/3ezbbfy