ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprsarchives-XL-5-W7-311-2015 Ancient Stone Tidal Weirs in Penghu Archipelago: Distribution, Category, Structure and Function, a Google Earth and GIS Approach Luo L. 1 2 Wang X. Y. 1 2 Liu J. 1 2 Guo H. D. 1 2 International Centre on Space Technologies for Natural and Cultural Heritage under the Auspices of UNESCO, Beijing, China Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 12 08 2015 XL-5/W7 311 314 Copyright: © 2015 L. Luo et al. 2015 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://isprs-archives.copernicus.org/articles/XL-5-W7/311/2015/isprs-archives-XL-5-W7-311-2015.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-5-W7/311/2015/isprs-archives-XL-5-W7-311-2015.pdf

The aim of this study was to give a comprehensive archaeological investigation for Penghu’s stone tidal weirs (STWs) based on both Google Earth and GIS. Firstly, this study uses GoogleEarth Pro tools to clip a GeoEye-1 image (acquisition date: 22/07/2013) and a WorldView-2 image (acquisition date: 25/01/2014) for Chipei Island and Husi Island, respectively, and save them at a “premium resolution” of 4800 dpi. More, using 15 m panchromatic orthorectified Landsat images as a base, two clips were geo-referenced in ENVI 5.1 with minimal root mean square error. Furthermore, the STWs were manual extracted from the two GoogleEarth images in ArcGIS 10.1. Category and size statistics are presented; construction structure and weir function are discussed. Lastly, by using GIS analyses, STWs characteristics of intertidal flats across Penghu archipelago have been mapped and related to key geographical environmental variables. From spring to summer of 2015 our research team conducted investigations into Penghu’s STWs based on different seasons and time periods of GoogleEarth historic images. Our results showed that, distributed amongst Penghu’s coastline, there are 503 STWs. Compared with the official survey results (around 592 STWs), the counts are similar but the GoogleEarth-based method is more time-saving and efficient.