一个支持谷歌地球引擎的Python方法,用于识别人为的古老景观特征
Filippo Brandolini1, Guillem Domingo-Ribas1, Andrea Zerboni2
1McCord Centre for Landscape - School of History, Classics and Archaeology, Newcastle University, UK, Newcastle upon Tyne, NE4 5HP, UK.
Open research Europe
|August 30, 2023
概括
本研究介绍了一个新的,免费的,开源的云协议,使用谷歌地球引擎和Sentinel-2卫星数据来绘制历史景观特征. 该方法有效地识别了波平原埋藏的水文和人为元素.
科学领域:
- 环境科学 环境科学
- 考古学的考古学
- 地理空间分析的研究.
背景情况:
- 可持续的景观发展至关重要,需要整体的遗产管理和跨学科对话.
- 遥感,特别是卫星图像,对于记录和管理自然和文化景观遗产越来越重要.
- 像谷歌地球引擎 (GEE) 这样的免费云计算平台增强了景观研究能力.
研究的目的:
- 介绍一个新的,免费的,开源软件 (FOSS) 云协议用于历史景观分析.
- 展示谷歌地球引擎 (GEE) Python API在历史景观研究中的应用.
- 调查"卫星卫星-2"卫星图像在探测埋藏的景观特征方面的潜力.
主要方法:
- 在Google Colab中开发一个Python脚本,使用FOSS云协议.
- 使用Sentinel-2卫星图像应用多时态方法.
- 使用光谱指数和光谱分解分析来识别景观特征.
主要成果:
- 该协议成功地确定了意大利北部波平原的古河景观特征.
- 证明了Sentinel-2数据和GEE在检测埋藏的水文和人为特征方面的有效性.
- 验证了拟议的FOSS云协议用于历史景观研究.
结论:
- 开发的FOSS云协议为全球历史景观研究提供了可复制和适应的方法.
- 谷歌地球引擎和Sentinel-2图像提供了强大的工具,用于发现隐藏的风景遗产元素.
- 这种方法通过提高对景观遗产的理解和管理来支持可持续发展.
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