Share Email Print

Proceedings Paper

GIS and remote sensing based method to extract fluvial terraces for archaeological purposes
Author(s): L. Duarte; A. Gomes; A. Teodoro; S. Monteiro Rodrigues
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Fluvial terraces are significant geomorphological features justifying the presence of rivers at high altitudes and constitutes the remains of the old river along the valleys, qualifying their incision capacity. Fill terraces can preserve lithic artefacts of Paleolithic communities that used the terrace clasts as raw material to manufacture their stone tools. The identification of fluvial terraces from cartography (analogical or digital) is based on different techniques and methods. Geographical Information Systems (GIS) has been used for the detection and identification of these fluvial geomorphologic features. Digital Elevation Model (DEM) derived from airborne Light Detection And Ranging (LiDAR) and slope-derived are the most used in the literature. The use of Remote Sensing (RS) data provides detailed information about the surface features, so it can be very useful to help in the identification of fluvial terraces. Recently, along the fluvial terraces of Minho river (border between Spain and Portugal), a significant amount of Paleolithic artefacts was found. The objective of this work was to study different approaches combining GIS and RS data to identify fluvial terraces and define the staircase levels along the Minho river valley. An approach was tested on the Minho River based on DEM and several auxiliary parameters. The analysis was based on several maps, such as DEM, slope, Normalized Difference Vegetation Index (NDVI), Land Use Land Cover (LULC) and hydrological data. The data were in WGS84 UTM zone 29 (EPSG:32629) and the spatial resolution adopted was 10 meters. Different scenarios were tested and validated in order to find the best methodology.

Paper Details

Date Published: 9 October 2018
PDF: 11 pages
Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 1079006 (9 October 2018); doi: 10.1117/12.2325119
Show Author Affiliations
L. Duarte, Univ. do Porto (Portugal)
A. Gomes, Univ. do Porto (Portugal)
A. Teodoro, Univ. do Porto (Portugal)
S. Monteiro Rodrigues, Univ. do Porto (Portugal)

Published in SPIE Proceedings Vol. 10790:
Earth Resources and Environmental Remote Sensing/GIS Applications IX
Ulrich Michel; Karsten Schulz, Editor(s)

© SPIE. Terms of Use
Back to Top