Abstract

Human activities have reshaped the geomorphology of landscapes and created vast anthropogenic geomorphic features, which have distinct characteristics compared with landforms produced by natural processes. High-resolution topography from LiDAR has opened avenues for the analysis of anthropogenic geomorphic signatures, providing new opportunities for a better understanding of Earth surface processes and landforms. However, quantitative identification and monitoring of such anthropogenic signature still represent a challenge for the Earth science community. The purpose of this contribution is to explore a method for monitoring geomorphic changes and identifying the driving forces of such changes. The study was carried out on the Eibar watershed in Spain. The proposed method is able to quantitatively detect anthropogenic geomorphic changes based on multi-temporal LiDAR topography, and it is based on a combination of two techniques: the DEM of Difference (DoD) and the Slope Local Length of Auto-correlation (SLLAC). First, we tested the capability of the SLLAC and derived parameters to distinguish different types of anthropogenic geomorphologies in 5 study case at a small scale. Second, we calculated the DoD to quantify the geomorphic changes between 2008 and 2016. Based on the proposed approach, we classified the whole basin into three categories of geomorphic changes (natural, urban or mosaic areas). The urban area had the most clustered and largest geomorphic changes, followed by the mosaic area and the natural area. This research might help to identify and monitoring anthropogenic geomorphic changes over large areas, to schedule sustainable environmental planning, and to mitigate the consequences of anthropogenic alteration.

Highlights

  • On a geological timescale, landscape morphologies are mainly created by natural driving forces such as tectonic movement, erosion, sediment transport and deposition and climate [1]

  • The proposed method is able to quantitatively detect anthropogenic geomorphic changes based on multi-temporal light detection and ranging (LiDAR) topography, and it is based on a combination of two techniques: the Digital Elevation Models (DEMs) of Difference (DoD) and the Slope Local Length of Auto-correlation (SLLAC)

  • The original SLLAC calculation begins with a slope map derived from the DTM, by computing the slope as a derivative of the quadratic-based polynomial models proposed by Evans et al [26]

Read more

Summary

Introduction

Landscape morphologies are mainly created by natural driving forces such as tectonic movement, erosion, sediment transport and deposition and climate [1]. Among the digital terrain analysis techniques presented in the literature, the DEMs of Difference (DoDs) was found as a very useful approach to quantify volumetric change between successive topographic surveys in a diverse set of environments at a range of spatial and temporal scales [13,14,15,16,17]. This method enables insight from morphological change to be coupled with the four fundamental geomorphic processes: erosion, transport, deposition, and storage of sediment [18]

Objectives
Methods
Findings
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call