1. Introduction
Cultural heritage is the accumulation and essence of the development of human civilization; it is a rare and irreplaceable wealth endowed by history [
1,
2,
3]. Recording and protecting cultural heritage is a common responsibility and obligation of all people. With the development of society and the deterioration of natural environments, natural and artificial risk factors that pose serious threats to cultural heritage are increasing [
4,
5,
6,
7,
8]. When natural disasters such as earthquakes, floods and landslides occur, they can catastrophically impact cultural heritage [
9]. For this reason, research on cultural heritage protection has received considerable attention in recent years [
10,
11,
12,
13].
Spatial information technology developed in the mid-to-late 20th century brought an opportunity to improve cultural heritage monitoring. Remote sensing techniques have shown advantages over traditional manual work in monitoring cultural heritage. For example, detection using remote sensing techniques are non-destructive, and remote sensing data are easier to obtain and much lower in cost than data collected by manual work. Remote sensing can realize rapid multiscale exploration and mapping, rapid multisource data analysis, and the dynamic monitoring of cultural relics and their surrounding environments [
14]. Remote sensing has, therefore, been favoured by researchers in recent years and has become a new tool for cultural heritage protection [
15] and management [
16,
17,
18,
19,
20].
Immovable cultural relics refer to specific historical and cultural sites, architecture and art [
21], including ancient buildings, ancient sites, and historical and cultural artefacts. The observation of immovable cultural relics, as an important part of cultural heritage, using remote sensing techniques has become possible with the enhancement of the spatial and temporal resolution of satellite images [
22]. Commonly, dynamic monitoring of environmental factors at the macroscale is performed and the change information of protected cultural sites at the microscale are analysed to provide useful information to guide the protection of immovable cultural relics.
Researchers have monitored different environmental factors, such as vegetation indices, topography, climate variables, and land cover maps, to analyse the surrounding environments of immovable cultural relics [
23]. For example, Banerjee and Srivastava evaluated land cover and land use changes around cultural sites in central India using Landsat series images [
24]. Bai et al. analysed spatial and temporal changes in land cover classes in one of the World Heritage sites on Mount Wutai and its environment, based on multi-source remote sensing images, including moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) products, Landsat series images and advanced spaceborne thermal emission and reflection radiometer (ASTER) digital elevation model (DEM) data [
25]. Assassi and Mebarki analysed the spatial configuration of the ancient town of Timgad for urban and architectural planning [
26]. According to the derived environmental factors, some researchers focused on studying the impact of natural disasters and human activity on immovable cultural relics. Diwan extracted six environmental factors to produce predictive maps for Iron Age sites in Bekaa, Lebanon [
27]. Based on the Corine Land Cover dataset and GlobCover data of cultural sites and the nearby areas in Cyprus, Hadjimitsis et al. applied spatial analysis to monitor the impact of disasters on cultural sites and their surrounding environment and conducted risk assessments [
28]. In 2015, Agapiou et al. used Landsat series images to classify the environment surrounding the Paphos area in Cyprus, revealing the impact of urban expansion on immovable cultural relics [
29]. Environmental monitoring usually requires a large area to be observed so that low or moderate spatial resolution images are used. To process these images, professional software is necessary to implement data pre-processing [
30,
31] (e.g., radiation calibration and atmospheric correction) and information extraction (e.g., principal component analysis, filtering, and classification). Traditional software, such as ENVI and ArcGIS, takes a long time and is relatively inefficient in the processing of massive data, thus limiting the application of remote sensing. Google Earth Engine (GEE) is a non-profit platform that has powerful capabilities for image processing and massive computing. For example, Chen et al. used GEE to calculate an ecological index that can reflect the quality of the ecological environment based on thousands of Landsat TM images, and then assessed the eco-environment quality in the Three Rivers Source Region [
32]. Generally, however, GEE has not been fully utilized for cultural preservation. Therefore, it is necessary to explore the potential of GEE to efficiently handle a large amount of remote sensing data in the field of cultural preservation.
In terms of protected cultural site monitoring, researchers used various remote sensing images to extract the boundaries of cultural heritage sites. In earlier times, the most commonly used images were Landsat series images. Aminzadeh and Samani used Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images to identify the boundaries of historical sites in Persepolis [
33]. Themistocleous et al. conducted a multi-temporal analysis of historical sites in Cyprus and showed the feasibility of using remote sensing to monitor historical sites [
34]. Then, high spatial resolution images have shown advantages in fine monitoring of cultural heritage sites. In 2014, Figorito and Tarantino detected and extracted historical sites from time series aerial images and achieved good results [
35]. In the same year, Luo et al. extracted the relics of the Dunhuang imperial road in the Hexi Corridor based on remote sensing image interpretation, geographic information system (GIS) analysis and field surveys [
36]. In recent years, unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) have become increasingly common methods for researchers to investigate historical sites [
37,
38,
39]. LiDAR data include height and structure information of ground objects and can be used to reconstruct cultural sites [
40]. Trier used a faster region-convolutional neural network (R-CNN) and airborne LiDAR data to draw a map of Norwegian cultural heritage [
41]. Cultural heritages can be recorded, visualized and reconstructed based on 3D modelling by using a digital camera and LiDAR scanner [
42]. In 2017, Hatzopoulos et al. performed 3D digital modelling of the Tholos monument in Greece [
43]. In the same year, the historical masonry arch, Dokuzunhan Bridge, was measured for 3D modelling by Altuntas et al. [
44]. However, LiDAR is costly, and the available data are limited. Alternatively, UAVs can capture high spatial resolution images at a low cost [
45]. In 2019, Su et al. used UAV images to monitor the Huangwei site in Jinmen, Taiwan, China. Through the analysis of weather, topography and other factors using GIS, the environmental risks were evaluated, and an environmental risk map was created to reveal the potential environmental risks of the study site [
46]. In general, most existing studies on monitoring protected cultural sites can only reach the scale at large buildings, such as ancient buildings and cave temples [
33,
34,
36,
46]. It is rare to monitor cultural sites at a finer scale, such as bridges. In addition, superior to UAV images, Google Earth images not only have a high spatial resolution but also the historical images can be obtained without any cost. Currently, however, Google Earth historical images have not been fully used in monitoring cultural heritage sites. Therefore, it is possible to explore the potential of Google Earth images to monitor the cultural relics of small areas.
In the current research on cultural heritage protection, most research has focused on a single scale. For example, Zhen et al. evaluated the impact of climate change and human disturbance on giant panda habitat in the core area of a heritage site in Ya’an, China [
47]. Roy et al. assessed the geographical environment of Majuli Island in Assam and sought effective measures to protect the island from further erosion by the Brahmaputra and its tributaries [
48]. These studies either analysed the environment scale or the protected site scale, while the effects at both the macro- and microscales are important. In addition, most of the research focuses on risk assessment and risk map production [
49,
50,
51]. There is a lack of research on tracking the impacts of disasters on cultural relics.
In summary, in terms of the dynamic monitoring of immovable cultural relics using remote sensing, the current research mainly faces the following shortcomings. First, sub-meter spatial resolution remote sensing images are not fully used, especially Google Earth historical images. The utilization of sub-meter-resolution images has the potential to observe small cultural sites. Second, when monitoring environmental factors surrounding the cultural site, the images are often processed by some popular remote sensing software, which is time-consuming and laborious. Most non-remote-sensing researchers are unfamiliar with some advanced data processing tools, such as the GEE platform. Third, most of the current research focuses on spatial archaeology and environmental risk assessment. There is a lack of research on the whole process of disaster monitoring, such as tracing the source of the disaster or tracking the situation after the disaster.
Therefore, this study carried out environmental factor monitoring and immovable cultural relic detection at both the macro- and microscales. In terms of environmental factor monitoring, remote sensing images with moderate spatial resolution were used to extract various environmental factors by the GEE platform. In terms of cultural relic monitoring, Google Earth time series images with a sub-meter spatial resolution were used to extract the attribute information to reflect the changes before and after destruction. A ruined immovable cultural relic, the Shunji Bridge, was studied in this paper. Quantitative assessment of the Shunji Bridge ranging from environmental factors at the macroscale to the protected cultural site at the microscale was performed. The whole process of the destruction of the bridge was traced, and the causes of its destruction were analysed. The findings can provide technical support for the risk assessment of and emergency response to natural disasters.
4. Discussion
4.1. Evaluation of Impact Factors
To evaluate the impact degree of each factor on immovable cultural relics, this study uses the analytic hierarchy process (AHP) to establish an index evaluation system. The AHP was proposed by Saaty in the 1970s. The idea of this method is to sort index according to its importance and decide the weight of each index [
59].
The steps for AHP include (1) defining the problem and determining the goal; (2) developing the hierarchy structure and establishing an index evaluation system; (3) applying a comparison matrix for each index; (4) conducting the consistency check; (5) determining the relative weight of each index [
60]. It is generally agreed that the consistency ratio (CR) < 0.1 leads to a satisfactory consistency.
In this study, the impact factors include land cover, vegetation cover, topography, soil erosion and the Shunji New Bridge. Therefore, an index evaluation system was established according to these five impact factors, experts were invited to score these factors, and the comparison matrix U was derived as follows.
The five elements from left to right and from top to bottom represent land cover, vegetation cover, topography, soil erosion and the Shunji New Bridge, respectively. The number “1” means two factors contribute equally to the objective, “2” means one factor is slightly favour over another, “3” means one factor is strongly favour over another, and “4” means one factor is very strongly favour over another.
The weight of each index was calculated by obtaining the eigenvector of the comparison matrix. The derived eigenvector is , and the CR = 0.016. Since the CR is less than 0.1, it indicates a good consistency. Therefore, the Shunji New Bridge has the greatest impact, followed by land cover and soil erosion. The impacts of vegetation cover and topography on the Shunji Bridge are relatively small, mainly because vegetation cover is directly affected by land cover, and topography is an attribute that does not constantly change.
This study monitored the impact factors related to the damage of the Shunji Bridge, including the environmental factors and the bridge’s attribute. However, some other impact factors cannot be obtained by remote sensing techniques, such as rainfall, wind direction, sunshine time, and the materials and structure of the bridge. These factors also have important impacts on the damage of the bridge and can be obtained by other technical means and data sources. Since we did not monitor all of the impact factors, the extracted five factors partly contributed to the bridge’s destruction. Nevertheless, this study has demonstrated a fair example of some impact factors that can be derived from remote sensing techniques.
4.2. Efficiency in GEE
The experiment was performed on the GEE to extract environmental factors from Landsat 7 ETM+ and Sentinel-2 images. To demonstrate the high efficiency of the GEE platform, the computational costs and random-access memory (RAM) of the process were implemented in the GEE platform and the traditional software (i.e., ENVI and SNAP), respectively, for comparison. All procedures were performed on a Lenovo laptop with an Intel (R) Core (TM) i5-7300HQ CPU processor and a Windows 10 64-bit operating system. The computational costs and RAM are shown in
Table 5 and
Table 6.
From the efficiency comparison of the different software, it can be seen that data processing on the GEE platform can save considerable time and RAM. It is therefore suggested that GEE is worthy of promotion in many applications.
5. Findings
In this paper, the Shunji Bridge, from environmental factors at the macroscale to the protected cultural site at the microscale, was studied using remote sensing techniques. The causes related to the damage of the Shunji Bridge were analysed from multiple aspects. At the macroscale, Landsat series and Sentinel-2 images were processed in the GEE platform to extract multiple environmental factors. According to the dynamic monitoring results derived from environmental factors, the urbanization process in the Jinjiang River Basin has accelerated. The vegetation coverage in this area also increased. At the microscale, Google Earth time series images were used to extract attribute information of the cultural relic, and the spatial and temporal changes in the Shunji Bridge before and after the destruction were detected. The causes of its destruction were analysed quantitatively. The results show that construction activities greatly affected the Shunji Bridge. Although some other factors may also contribute to the destruction of the bridge, this study has shown the practicability of monitoring the changes of cultural relics in the hazard and tracing the causes of the bridge’s destruction using remote sensing. The findings of this study are as follows.
In terms of the source of the destruction of the Shunji Bridge, the rainstorm caused by typhoons in July 2006 was the initial trigger for this disaster. However, both the surrounding environment and the construction of the Shunji New Bridge contributed to the destruction of this cultural relic. On the one hand, there was a large area of barren land in the upper reaches of the Jinjiang River because of the deforestation and farmland degradation, causing serious water loss and soil erosion. On the other hand, the Shunji New Bridge, located 80 m upriver, blocked water to some degree, leading to sedimentation near the Shunji Bridge. The inhospitable surrounding environment and long-term sedimentation in the river were potential threats to the Shunji Bridge. When the rainstorms occurred, the river water rose rapidly, and the flood water could not drain downstream in time due to sedimentation. The rainstorms brought branches and silt that hit the Shunji Bridge. Finally, the Shunji Bridge collapsed, and the damage was irreversible.
By tracking the situation after destruction, urbanization and greening in the Jinjiang River Basin have continued. Since urbanization has a great impact on immovable cultural relics, urban construction should be avoided as much as possible in the areas surrounding immovable cultural relics. Moreover, urban construction should be reasonably planned before implementation, and urban greening should be further improved.
6. Conclusions
“Strengthening efforts to protect and safeguard the world’s cultural and natural heritage” is one of the targets (Target 11.4) of the United Nations Sustainable Development Goals (SDGs). This study has shown the advantages of remote sensing and GIS techniques for cultural heritage monitoring and protection planning. According to this case study of the Shunji Bridge, the findings can provide guidance and suggestions for the protection of immovable cultural relics in regional urban planning and construction, as well as technical support for regional natural disaster risk assessment. The emergency response and preventive protection of immovable cultural relics can be enhanced by environmental change and early warning monitoring. Moreover, it is important to publicize this information and provide a better perspective to all people. For example, a special day, such as the “Cultural and Natural Heritage Day”, could be established, and educational activities could be held to raise public awareness of cultural heritage protection.
The methods used in this study are also applicable to other types of cultural heritage. Due to the small scale of the Shunji Bridge, only the area property of the cultural site was extracted. However, when studying ancient buildings and ancient sites with large areas, other information of cultural heritages can be extracted and analysed, such as vegetation and buildings around the cultural landscapes. Dynamic remote sensing-based monitoring can be performed on the surrounding environments of protected cultural sites to extract change information, so that the impacts of natural and human factors on cultural heritage can be obtained.
In the future, observed satellite data and remote sensing techniques are expected to be further improved to better serve the cultural heritage protection. In terms of data, for example, the Planet satellite provides images with a spatial resolution of 3–5 m and can achieve daily coverage at the global scale. The recently launched satellite, SuperDove, obtains the images with a spatial resolution of 3 m and 8 multispectral bands. The Planet and SuperDove images can be used to monitor large-scale cultural sites, such as ancient buildings and ancient sites. The rich spectral information lies in images with eight multispectral bands and has the potential to monitor different types of tree species in natural heritage sites. However, to monitor small relics, such as bridges and towers, the images with a sub-meter spatial resolution are required. The current available sub-meter images, such as Pleiades and WorldView, do not have a very high temporal resolution. Therefore, cultural heritage protection can be promoted with the development of remote sensing satellites.
In terms of techniques, information extraction is the core of the dynamic monitoring process. Either in traditional software or the GEE platform, the selection of samples is required for land cover classification. This procedure is time consuming and laborious. More importantly, the experts’ knowledge included in the sample and feature selections could be the biggest obstacle for the non-remote-sensing researchers. The deep learning technique provides an automatic approach for extracting information. However, this type of approach is easily affected by many factors, such as weather conditions, acquisition time, solar azimuth, etc. For atypical buildings, such as heritage sites, the accuracy derived by the automatic information extraction approach has not reached the requirements for practical use. Therefore, the development of information extraction techniques is also important to accurately monitor cultural relics.
In summary, the research development trends in the protection of cultural heritages using remote sensing technology have the following aspects. First, with the development of unmanned aerial remote sensing systems (UARSSs), LiDAR technology and hyperspectral remote sensing, more data will be available for monitoring cultural heritage, and these data should be comprehensively utilized. Accordingly, the data processing techniques should be further improved. Some tools that can deal with massive amounts of data, such as the GEE platform, should be popularized among non-remote-sensing experts. Second, it is suggested that change detection should be updated annually within the core and buffer zones of each protected cultural site. The changes in some key factors, such as vegetation and buildings, can be monitored so that experts can evaluate whether these changes pose threats to the cultural relics. Finally, we traced the source of a relic’s destruction and tracked the situation after its destruction. With the improvement in the spatial and temporal resolution of satellite images, it will be possible to conduct the long-term monitoring of important cultural relics with potential safety hazards. By doing so, disasters may be detected in advance, and emergency responses can be taken to prevent damage. These measures are important for reducing the disaster risks of cultural relics and strengthening preventative protection.