Metrics for quantifying anthropogenic impacts on geomorphology: road networks

摘要

This work tests the capability of a recently published topographic index, the Slope Local Length of Auto-correlation (SLLAC), to portrait and delineate anthropogenic geomorphologies. The patterns of the anthropogenic pressure are defined considering the road network density and the Urban Complexity Index (UCI). First, the research investigates the changes in the SLLAC in two derived parameters (average SLLAC and the SLLAC surface peak curvature - Spc - per km(2)) connected to the increasing of the anthropogenic structures. Next, natural and anthropogenic landscapes are clustered and classified. The results show that there is a direct correlation between the road network density and the UCI, and the mean SLLAC per km(2). However, the Spc is inversely correlated with the anthropogenic pressure (network density and urban complexity). This shows that the surface morphology (slope) of regions presenting anthropogenic structures tends to be well organized (low Spc) and, in general, self-similar at a long distance (higher average SLLAC). The results of the clustering approach show that the procedure can correctly depict anthropogenic landscapes having a road network density greater than about 3 km/km(2), also in areas covered by vegetation. This latter result is promising for the use of such a procedure in regions that cannot be seen directly from orthophotos or satellite images. The proposed method can actively capture the alteration produced by road networks on surface morphology identifying different signatures of urban development: exploration and densification networks that are responsible for increasing the local density of the network and expanding the network into new areas, respectively. The effects of this alteration on surface processes could be significant for future research, creating new questions about differences due to human or landscape forcing on Earth surface processes. Copyright (c) 2015 John Wiley & Sons, Ltd.