Micro-topographic roughness analysis (MTRA) highlights minimally eroded terrain in a landscape severely impacted by historic agriculture

Journal Article (Journal Article)

The 190 km2 Calhoun Critical Zone Observatory in the Piedmont region of South Carolina, USA lies in an ancient, highly weathered landscape transformed by historic agricultural erosion. Following the conversion of largely hardwood forests to cultivated fields and pastures for ~200 years, excess runoff from fields led to extreme sheet, rill, and gully erosion across the landscape. Roads, terraces, and a variety of other human disturbances have increased the landscape's surface roughness. By the 1950s, cultivation-based agriculture was largely abandoned across most of the Southern Piedmont due to soil erosion, declining agricultural productivity, and shifting agricultural markets. Secondary forests, dominated by loblolly and shortleaf pines, have since regrown on much of the landscape, including the 1500 km2 Sumter National Forest, which was purchased from farmers and private land owners in the 1930s. Although this landscape was intensively farmed for approximately 150 years, there are a few hardwood forest stands and even entire small watersheds that have never been plowed and degraded by farming. Such relatively old hardwood stands and watersheds comprise relic landforms whose soils, regoliths, and vegetation are of interest to hydrologists, environmental historians, biogeochemists, geomorphologists, geologists, pedologists, and others interested in understanding the legacy of land-use history in this severely altered environment. In this work we champion the need for high-resolution terrain mapping and demonstrate how Light Detection And Ranging (LiDAR) digital elevation model (DEM) data and microtopographic terrain roughness analyses (MTRA) can be used to infer land use history and management. This is accomplished by analyzing fine scale variation in terrain slope across the 1190 km2 CCZO using data derived from three independent and overlapping LiDAR datasets at varying spatial resolutions. Terrain slope variability MTRA is further compared to three other methods of capturing and quantifying fine-scale surface roughness. We lastly demonstrate how these analyses can be employed in concert with historic aerial photography from the 1930's, contemporary Landsat remote sensing data, and ecological field data to identify reference relic landforms: hardwood stands, hillslopes, and small watersheds that have experienced minimal anthropogenic erosion for study and conservation.

Full Text

Duke Authors

Cited Authors

  • Brecheisen, ZS; Cook, CW; Heine, PR; Richter, DDB

Published Date

  • March 1, 2019

Published In

Volume / Issue

  • 222 /

Start / End Page

  • 78 - 89

International Standard Serial Number (ISSN)

  • 0034-4257

Digital Object Identifier (DOI)

  • 10.1016/j.rse.2018.12.025

Citation Source

  • Scopus