4.7 Article

Quantitative Analysis of Anthropogenic Morphologies Based on Multi-Temporal High-Resolution Topography

Journal

REMOTE SENSING
Volume 11, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/rs11121493

Keywords

Geomorphology; LiDAR DTM; Anthropogenic signatures; SLLAC; DoD

Funding

  1. National Key Research and Development Program of China [2017YFC0601501, 2017YFC0601502]
  2. China National Mineral Resources Assessment Initiative [1212010733806, 1212011120140]
  3. University of Padova [60A08-5455/15]

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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.

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