Ancient Stone Tidal Weirs in Penghu Archipelago: Distribution, Category, Structure and Function, a Google Earth and GIS Approach
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:...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-08-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-5-W7/311/2015/isprsarchives-XL-5-W7-311-2015.pdf |
| Summary: | 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. |
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| ISSN: | 1682-1750 2194-9034 |