Hydroweight: inverse distance-weighted rasters and landscape attributes

Abstract

Environmental scientists often want to understand how upland features like forest cover affect receiving waterbodies (eg, water quality). Upland areas are characterized by deriving various landscape attributes (eg,% forest cover in catchment). However, this approach often assumes that the influence of upland features on receiving waterbodies is independent of their proximity to the waterbodies. This may not adequately describe important spatial patterns within the upland area, for example, if there was higher forest cover near the waterbody and lower forest cover farther away. The R statistical software package hydroweight helps to account for these patterns. hydroweight calculates landscape attributes based on distances to waterbodies—areas nearby have more influence than those farther away (ie, inverse distance-weighting). We implement various scenarios described by Peterson et al.(2011) that include …