Elaborate Monitoring of Land-Cover Changes in Cultural Landscapes at Heritage Sites Using Very High-Resolution Remote-Sensing Images

Yunwei Tang, Fulong Chen, Wei Yang, Yanbin Ding, Haoming Wan, Zhongchang Sun and Linhai Jing
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Yunwei Tang: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Fulong Chen: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Wei Yang: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Yanbin Ding: College of Geography and Tourism, Hengyang Normal University, Hengyang 421002, China
Haoming Wan: Research Center of Big Data Technology, Nanhu Laboratory, Jiaxing 314002, China
Zhongchang Sun: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Linhai Jing: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

Sustainability, 2022, vol. 14, issue 3, 1-18

Abstract: Insufficient data and imperfect methods are the main obstacles to realize Target 11.4 of the Sustainable Development Goals (SDGs). Very high-resolution (VHR) remote sensing provides a useful tool to elaborate monitor land-cover changes in cultural landscapes so as to evaluate the authenticity and integrity of the cultural heritage sites (CHS). In this study, we developed a semi-automatic two-level workflow to efficiently extract delicate land-cover changes from bi-temporal VHR images (with spatial resolution ≤ 1 m), where most current studies can only manually interpret changes at this scale. Based on the monitoring result, we proposed an indicator named interference degree that can quantify the changes in cultural landscapes of the CHS as a complementary indicator to achieve Target 11.4 for SDGs. Three representative types of CHS with different landscapes were studied in 2015 and 2020 based on the VHR Google Earth images, including cave temples, ancient architectural buildings, and ancient sites. The proposed workflow was demonstrated to be effective in extracting delicate changes efficiently with the accuracy around 85%. The interference degree well reflects the preservation status of these CHS and can be periodically observed in a long term as an evaluation indicator. This study shows the potential to produce the first-hand global-monitoring data of CHS to support Target 11.4, thus serving for the sustainable development of the world’s cultural heritage.

Keywords: cultural-heritage site; very high-resolution; cultural landscape; interference degree; object-based image analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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