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Article

History in Points, Lines and Polygons: Time Depth in the Landscape of Guangdong Province, Southern China

by
Ying Pan
1,2,3,
Jiayu Bai
1 and
Sam Turner
4,*
1
School of Architecture, South China University of Technology, Guangzhou 510641, China
2
State Key Laboratory of Subtropical Building Science, Guangzhou 510640, China
3
Guangzhou Municipal Key Laboratory of Landscape Architecture, Guangzhou 510640, China
4
School of History, Classics and Archaeology, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
*
Author to whom correspondence should be addressed.
Land 2023, 12(11), 1979; https://doi.org/10.3390/land12111979
Submission received: 21 September 2023 / Revised: 14 October 2023 / Accepted: 23 October 2023 / Published: 26 October 2023
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Abstract

:
Change and persistence are often richly entangled facets of landscapes. While many studies use land use/land cover (depicted as polygons) to illustrate landscape evolution, this paper draws on approaches from landscape archaeology to investigate how lines and points can also be used to examine landscape morphologies. The study uses three distinct spatial elements: points (graves), lines (field boundaries), and polygons (land use) to represent landscape transformations and reflect time depth in the landscape. The paper aims to identify the most enduring landscape elements within the region and uncover the underlying mechanisms of persistence. It is suggested that the time depth exhibited in field boundaries surpasses that of land use in this case. Field boundaries provide a useful way to examine agricultural intensification, whereas land use is more sensitive to agricultural commercialization and urbanization. In addition, the Chinese Feng Shui funeral culture emerges as a stabilizing force that encourages landscape persistence. This cultural driver ensures the persistence of field patterns surrounding graves, making these fields the most ancient plots within the study area. In conclusion, representing the time depth of landscapes through linear features and points can serve as an important supplement to the study of landscape change based on land use.

1. Introduction

Landscapes always change because they are the expression of the dynamic interaction between natural and cultural forces in the environment [1]. A changing landscape is very much a function of historical conditions, and any landscape that exists today results from earlier conditions and events in that locale [2]. However, some elements of the landscape change little; in other words, the time depth of these plots is quite deep. Considering the elements of both change and persistence at the same time helps us to develop a more holistic understanding of the landscape.
There are many methods for reflecting landscape change, among which one of the most commonly used is to measure the amount of land use conversion by constructing a land use transfer matrix within a certain period [3]. Landscape indices such as fractal dimension, dominance, and diversity are often used to reveal changes in landscape patterns and spatial structure [4,5]. However, these landscape indices can be criticized on the grounds that their analysis relies upon limited aspects of the landscape, such as land cover. They do not necessarily reflect the historical trajectory of the landscape [6] or the landscape’s overall character [7]. Abstract indices need to be combined with spatial visualization to display the geographical features of landscape changes more clearly. Landscape change trajectory analysis is a common approach to describe landscape change [8], which is used to find the dominant pathway in various transfer paths through statistics [9]. Mapping is also used to reveal the intensity or the spatial localization of landscape change [10]. In order to depict such changes, indices like the coincidence index [11], conservation and degradation indexes [12], or entropy [13,14] need to be constructed to measure the degree to which the landscape deviates from its baseline state. In addition, the rate of landscape change can be plotted in combination with the time scale of change [15].
The characteristics of landscape change mentioned above can be explained using many driving factors, including geography [16,17], population [6], economy [18], politics [19], social structure [20], technology [21], and culture [22]. The research methods used include simple two-factor correlation analysis and complex multi-factor logistic regression [23,24]. In addition, qualitative research methods such as questionnaires or interviews can also be used to obtain perspectives on the local population’s perception and motivational narratives of landscape change [25,26,27].
On the other hand, compared with the abundant research into landscape change, there is little research about landscape persistence. The persistence of landscapes is closely linked to questions of landscape identity and cultural landscape values [1,28]. It is an important criterion for the identification of so-called ‘traditional’ cultural landscapes [29] or landscape archetypes [30]. In order to measure and visualize landscape persistence, Van Eetvelde proposed the use of time depth maps, which indicate the age of current landscape types [31], accompanied by maps of the frequency of changes to search for the most persistent type in the landscape. In this sense, ‘time depth’ represents the extent to which features in the landscape are persistent over time. Other scholars created indicators such as the persistence index [32,33] or the history index [34] to evaluate the persistence of land use based on spatiotemporal variables. In general, settlements or woodlands are considered a relatively persistent element, while arable land is easily changed [35]. In a review of the mechanisms of landscape persistence in traditional agricultural landscapes [36], three aspects have been determined as preconditions for their preservation: (a) isolation (in geographic, economic, infrastructural, political, and cultural terms), (b) a geographical setting which is difficult for intensive agriculture, and (c) inhabitants who are ethnically and/or socially different from the national mainstream. Moreover, legal constraints are also regarded as drivers of landscape persistence [37]. This paper proposes a new perspective relating to the persistence mechanism of certain landscape elements.
A great deal of scientific literature has dealt with the study of landscape changes by analyzing land-use/land-cover data (typically represented in GIS as polygons). However, linear elements of the landscape can also reflect the history of landscape evolution. In this respect, Historic Landscape Characterization (HLC) developed in the UK provides some useful insights. HLC is adapted and used to characterize and display the diachronic evolution of the complete landscape [38], presenting today’s landscape character in the light of history’s ‘long chain’ of events [39]. Areas are categorized (as polygons) according to different types of historic character, which is identified based on the morphology of boundaries among other attributes, since particular groupings of components can reflect similar patterns of development in the past [40]. Examples of common HLC types in Europe and the Mediterranean include different kinds of open (i.e., unenclosed) arable fields, agricultural enclosures bounded by hedges, earth banks, walls or water channels, and several types of mountainside terraces [41,42]. In each area, different types of field boundaries may reflect different stages in the history of landscape development.
In this paper, graves were chosen as a type of monument that can be represented as ‘points’. As a type of sacred landscape feature, graves may carry collective memories of communities [43], strengthen local ethnic or other identities [44], and often are regarded as local heritage [45]. The case-study area has a very high density of graves, which also tend to possess long time depth. Incorporating them together with polygon elements (land use) and line elements (field boundaries) into the study of landscape persistence can enrich our understanding of how the landscape has developed.
The paper addresses three research questions. Firstly, it examines whether points and linear landscape elements can express something of the time depth of the landscape in the case-study area. Secondly, it considers whether elements that can be defined as lines or points in GIS reflect the time depth of landscape in a different way to polygon elements and whether these methods are complementary. Finally, it examines what drivers might enhance the persistence of certain elements in the landscape.

2. Materials and Methods

2.1. Study Area

The study area is located in Guangdong province in southern China. In recent years, rural Guangdong has witnessed rapid urbanization and population growth. As the most economically developed province of China, land use in Guangdong province has changed significantly over the last 30 years in relation to the drastic expansion of the built-up area, which grew by 93.7% between 1990 and 2018 [46].
The study area lies in a peninsula of 4.52 km2, comprising six villages within Jiadong Town, Lufeng City (Figure 1). The terrain predominantly consists of hills and terraces, with elevations ranging from 6 to 30 m. The soil type is latosol, and the climate exhibits subtropical monsoon characteristics, with abundant rainfall during the rainy season. The average annual temperature stands at 21.8 °C. At the end of 2020, Jiadong Town’s population was 60,893 [47]. According to local records, the earliest village in Jiadong was established in 1264, when the economy was mainly based on fishing supplemented using agriculture [48]. In the following few hundred years, staple crops such as rice and sweet potatoes were cultivated, along with cash crops like sugarcane and peanuts [49]. Following the establishment of the People’s Republic of China in 1949, private land ownership was abolished, and collective agricultural production was enforced via people’s communes. During this period, under the leadership of the communist regime, there was a nationwide agricultural infrastructure movement, ‘in Agriculture, Learn from Dazhai’, which caused dramatic changes in farmland [50]. After 1980, the implementation of the reform and opening-up policy in China made the family unit retake charge of agricultural production, which caused families to shift from single-crop farming to diverse cash crops as the market economy developed. Post-2000, the process of urbanization accelerated with small-scale industries appearing in the countryside. In summary, the rural landscape changed dramatically during the late 20th and early 21st centuries, with significant re-organization of agricultural land succeeded by increasingly rapid urbanization (Figure 2 and Figure 3). The historic landscape of the area has not been studied previously. It was chosen because it is representative of the wider region and because a good range of historical and current spatial data are available for study.

2.2. Data Source and Materials

The study’s quantitative analyses were conducted using aerial photographs and satellite images spanning five periods over the past 80 years (Table 1). The 1943 image, a military aerial photograph captured during World War II, provides insights into the rural landscape of a traditional agricultural society. Images from 1973 and 1980 were obtained through American reconnaissance satellites. The impact of commercialization and urbanization can be observed vividly through the satellite imagery provided by Google Earth for the years 2006 and 2022.
Owing to the scarcity of surveying and mapping traditions in China compared to Western countries after the Renaissance, the use of historical maps to study landscape evolution proves challenging. While accurate survey maps from the 18th and 19th centuries were commonly used in studies of landscape history in Europe [14,37], the earliest survey map available in this study area dates back to 1930, a 1:50,000 topographic map completed by the Guangdong Army Survey Bureau [51]. However, this map lacks information about field shapes and boundaries due to its large scale, rendering it unsuitable for this study.
Given the absence of extensive historical maps, the time depth analysis in this paper was restricted to the past 80 years. Fortunately, China had previously been an agricultural economy under family ownership for a long time, and its social structure was relatively stable [52]. As the landscape is easily influenced by social structure [53], we can assume that the landscape evolution had been relatively gradual in the decades before the founding of the Republic in 1949. The 1943 aerial photograph may, therefore, represent the landscape whose history spans centuries. The establishment of the communist regime generated drastic rural societal changes, accelerating landscape evolution. Hence, the 80 years of historical images comprehensively depict the landscape’s transformation from a traditional and historical one to the modern era. Additionally, Digital Elevation Model (DEM) data served as auxiliary data in the GIS layer, contributing to the examination of landscape differences.

2.3. Methods

The paper’s workflow is depicted in Figure 4. Aerial photographs and satellite images from various periods were integrated into a geodatabase using georeferencing using ArcGIS Pro 3.0 (ESRI). Three spatial elements—graves, field boundaries, and land use—were extracted from these historical images using artificial recognition to discern landscape details in high-resolution images.
To map land use, the most recent image (2022) served as the reference layer with previous land uses interpreted based on earlier raster data [54]. This approach allows the re-drawing of boundaries only for real changes, avoiding sliver polygons resulting from changes due to minor misplacement of images in different periods. Conversely, a chronological approach was used for field boundary extraction [55]. The earliest image (1943) was initially vectorized, followed by the amendment of changed portions in a newer layer corresponding to subsequent images, thus circumventing minor misplacement issues.
Graves were identified by interpreting images of different periods. Whilst an AI-based method could be used to identify such features [56], the lack of existing training data meant a manual method was more time-efficient for this relatively small case-study area. Graves, considered a subcategory of land use, are represented as small polygon elements in aerial photographs but could be converted into points based on the centroid position during spatial relationship analysis between graves and other landscape elements. This study used either polygon or point representations of graves depending on the technical requirements of the spatial analysis in GIS.
The time depth map was generated after assembling basic data. For the time depth of land use, the intersection of land use layers from five periods was initiated. The process sequentially compared whether land use on a specific plot remains consistent between two consecutive periods (T(n) and T(n − 1)). The time depth of land use at that plot corresponded to T(n) when differences arose. By iteratively reducing intersecting layers and repeating the process, landscape depth maps at five different periods were obtained. There was no need to draw time depth maps further because time information had been assigned to all the lines in field boundaries maps.
The study did not focus on the lifespans of individual graves, which obviated the need for a landscape depth map. Instead, the research examined the collective distribution of graves over time via kernel density analysis. Moreover, a continuity diagram of graves across periods was generated using statistical analysis of the transformation modes between graves and other land use types. Ultimately, graves were tentatively identified as highly durable landscape elements. This helped to explain the difference in the time depth maps based on land use and field boundaries.
Spatial correlation analysis between grave distributions and the other two elements was performed. For polyline elements (field boundaries), two methods assessed the relationship between points and polylines across different periods. Method 1: distances between graves and field boundaries in distinct periods were measured using the proximity analysis in GIS. This method identified the time-depth polyline type most pertinent to grave distribution, repeated across all five-period layers, and presented in a clustered column chart based on different periods. Method 2: buffer zones equidistant to boundaries in different periods were established, converting polylines into polygons. The proportion of grave points contained within these buffer zones determined the field boundary period most relevant to grave distribution. This operation was replicated across five-period layers, visualized as a clustered column chart based on periods.
In order to assess the relationships between land use and grave distributions, graves were treated as small polygons (rather than points) so that the time depth of polygons on their perimeter could be evaluated. The analysis was repeated for each of the five period layers, yielding a clustered column chart by period, which shows the relationship between graves and the time depth of adjacent land uses.

3. Results

3.1. Time Depth Based on Land Use

Manual interpretation of land use maps for five periods employing a backdating approach revealed the evolution of the landscape (Figure 5). As a peninsula in the bay of a river estuary with low hills, most of the land was used as farmland until 1943, while the higher areas remained uncultivated, covered by rough vegetation. Six settlements surrounded this higher ground, often accompanied by small woodlands which acted as protection against coastal sandstorms and served local faith as sacred forests. Graves dotted these elevated regions, while the northern bay retained its natural state.
By 1973, most land use elements had remained consistent since 1943, with modern road systems under development. The original small woodlands diminished, and the northern bay was transformed into salt plants. Following the “In Agriculture, Learn from Dazhai” movement, 1980 saw a significant expansion of farmland, especially in previously uncultivated land and shallow bays. This phase also entailed the development of irrigation canals. Few woodlands remained after clearance for agriculture, but the expansion of settlements was very limited. In the next stage, there was a dramatic change in land use along with the commercialization of agriculture and the family-owned production model. By 2006, high-profit fruit planting replaced grain production, and orchards replaced farmland. Large areas of farmland were also abandoned to be replaced by uncultivated lands such as grassland. The direct reason for the abandonment was that more and more families gave up low-income agricultural production and turned to work in nearby big cities [57]. Since the plots owned by the families are scattered in space, the abandonment fragmented the landscape. Along with urbanization, settlements underwent substantial expansion, accompanied by the increase in scattered graves. Simultaneously, factories and commercial spaces emerged, all of which were indicative of the rapid population growth during that period. In addition, almost all of the natural bays had been reclaimed into ponds for aquaculture. The land use in 2022 continued the previous trend, showing extreme fragmentation. The abandonment of farmland and orchards persisted, succeeded by the cultivation of economic woodland (eucalyptus) with better profits. Along with the fragmented expansion of settlements, the entire district has become a mosaic-like landscape.
Time-depth maps of land use across five periods were generated by intersecting the land use maps (Figure 6). In 1973, the majority of land use persisted from 1943. By 1980, only the bays on both sides and the central highlands exhibited relatively new land use. By 2006, a large portion of the peninsula’s land use had changed. The distribution of these young fields appeared relatively fragmented, but in general, the fields dating back to before 1943 still encompassed around half of the district’s area. The trend of fragmentation continued until 2022, with newer uses dominating the peninsula and older plots exhibiting fragmentation.

3.2. Time Depth Based on Field Boundaries

Interpretation of field boundaries in five periods, from old to new, revealed changes in boundary patterns (Figure 7). In 1943, a fine cobweb-like pattern of field boundaries prevailed, with small field sizes. By 1973, only minor modifications were observed in the basic boundary structure, excluding new boundaries added for salt plants on the north side. After that, the “In Agriculture, Learn from Dazhai” movement led to mechanized rectangular gridded farmland in 1980, replacing the previous organic form. Since it was required to level the terrain and build irrigation canals, these projects were primarily conducted in relatively low regions of the peninsula. Meanwhile, the traditional field pattern was often preserved in the relatively high areas. Under the policy of reform and opening up around 1980, it was difficult for family farming to execute the large-scale adjustments to farmland structure that were achievable during the collectivization period. Gradual changes characterized field boundaries between 2006 and 2022, with no significant geographic clustering. By 2022, many boundaries dating back to before 1943 persisted on the peninsula’s higher terrain, indicating that these boundaries and nearby lands were less disturbed by agricultural modernization.

3.3. The Continuity of Graves

The distribution of graves appeared to display a consistent pattern, and graves appear to be persistent elements in landscape development. This hypothesis was assessed using two approaches. When the graves are regarded as points, the distribution pattern of graves in the five periods can be analyzed using the kernel density on GIS (Figure 8). As depicted in the figure, the spatial distribution pattern of graves remained stable over the 80-year landscape evolution. Notably, the absolute density value exhibited an increase due to the growing number of graves. Furthermore, several distribution hotspots displayed minimal alterations, reinforcing the enduring nature of this distribution pattern.
When treating graves as polygons as a category of land use, a statistic was conducted regarding the conversion between graves and other land use types. The continuity of graves was represented by categorizing them across different periods and calculating the sum area of graves (Figure 9). Obviously, the periods of 2006 and 2022 showed the largest proportion of graves in terms of area, implying that many graves had relatively short histories. However, when we focus on the continuity of these strips, it becomes evident that the majority of graves have persisted since their initial appearance, with only a few interrupted strips in their historical continuity. This illustrates the remarkable persistence of the graves as a group. The steady spatial pattern of graves and the increase in density suggest that newly added graves were likely to be located in proximity to existing ones. The phenomenon indicates that there was somehow spatial attraction around the site of the graves, where the land can be regarded as the area with the deepest time depth on the peninsula.

3.4. The Geographical Correlation between Land Use, Field Boundaries and Graves

When we calculated the distance between the grave points and the field boundaries in different periods on the GIS, the result can be plotted in Figure 10. It is easy to find that no matter which period the graves belong to, they are closest to the earliest field boundaries (1943), which proves that graves tend to be positioned in close proximity to older boundaries.
There is another piece of evidence provided by analyzing the buffer zone of field boundaries. Via testing, it was determined that buffer zones with a radius of 20 m could approximately cover the entire study area. This finding is illustrated in Figure 11, where the proportion of graves contained within these buffer zones is depicted. Similar to the previous method, there is always the highest proportion in the buffer zones based on boundaries in 1943. Even though, as time went by, the types of boundaries became more and more, which diluted the proportion of graves contained in the 1943 buffer, the graves contained in the 1943 buffer still accounted for 60% in 2022. This result reaffirms the close relationship between the graves and the oldest boundaries.
By contrast, the result is very different when we focus on the relationship between graves and the polygon element, time depth of land use. Figure 12 is plotted by counting the perimeter of the graves contained in polygons of different periods. A higher proportion of graves were situated on old fields before 1973, and after that, the proportion of graves contained the land earlier than 1943 dropped sharply. On the contrary, by 2022, most of the graves were located in the fields developed after 1980. Obviously, this result is contradictory to the previous one that suggested a stronger connection between graves and the oldest boundaries. In the following discussion, the reasons for these divergent results will be explained.

4. Discussion

4.1. Differences in the Representation of History through Two Approaches

The underlying reason for the divergent trends in the time depth of land use and field boundaries can be attributed to the distinct historical events they reflect. In general, the 80 years involved in this study can be divided into three stages. In the first stage, before 1973, even though Chinese rural society underwent a transition from private ownership of land to agricultural collectivization, the impact on the rural landscape was slight, and neither field boundaries nor land use showed significant changes. The second stage, spanning 1973 to 1980, witnessed a dramatic transformation in the field pattern. This transformation was propelled by a nationwide farmland construction movement in the late 1970s, changing more than half of the field boundaries on this peninsula. On the contrary, this movement had little impact on the land use. Since it was under the collectivization of agriculture until that point, rice fields kept serving as the predominant land use category. The third stage is from 1980 to the present. There was a huge change in land use due to the commercialization of agriculture and the family-owned production model caused by the reform and opening up policy. In contrast, the field boundaries modified were scattered and slight because of the lack of social collectivization mechanism within family-based farming units.
It can be seen that the time depth of land use and field boundaries has different sensitivities to different historical events. In terms of the time depth of land use, agricultural commercialization and abandonment of farmland since 1980 resulted in the time depth of most fields in the district being later than 1980. Conversely, when examining the time depth map of field boundaries, we can find not only changes in field structure in the late 1970s but also a large amount of field boundaries tracing back to before 1943. Relatively speaking, the time depth of field boundaries suggests a deeper historical context. This study helps us to enhance our comprehension of landscape history by using research methods from landscape archaeology.
Notably, field boundaries are often altered when farming cultures are transformed. This phenomenon is observable in various contexts, from the establishment of imperial systems [58] to enclosure in post-medieval Europe [59]. In contemporary China, this represents the form of collectivist agricultural production brought about by the communist government and matched with modern mechanization. While this study did not discuss the reasons for the formation of the farmland texture pre-1943 due to the lack of research data, it nevertheless highlighted the complex relations between historical processes and the evolution of the landscape.
In addition, although the time depth of land use presents a short history, this relative brevity does not diminish its significance. On the contrary, the landscape evolution since 1980 has profound implications, marking one of the most significant transformations in the southern Chinese landscape in millennia. Many historic landscapes have been changed profoundly during this period, but such transformations should not be hastily considered episodes of erasure. In this case study, the data show that historic field boundaries have been preserved to a considerable extent, transmitting traces of the former landscape. Field boundaries reflect the morphology of the landscape, while land use reflects the function of the landscape. Each one is indispensable for landscape analysis. Consequently, adopting a holistic approach that integrates the data from both land use and field boundaries becomes crucial and enables a deeper understanding of the formation of the present landscape, which can provide valuable insights to guide future efforts to shape the landscape.

4.2. Historical Value of the Feng Shui Funeral Culture

Agricultural practices change quickly as social structure and economic systems are transformed. In contrast, it appears that graves maintain a strong continuity in the evolution of the landscape. This is likely to be related to the Feng Shui tradition of Chinese funeral culture. The Chinese funeral tradition requires a careful process for the selection of ancestral burial sites because the location of graves is related not only to the dignity of the deceased but also to the future prosperity of descendants [60]. Feng Shui constitutes a comprehensive system of theories and tools to assess the geographical configuration of burial grounds and residences alike. Central to its framework is the emphasis on an auspicious configuration of landscape. The ideal situation for a grave encompasses specific features, including a protective mountain behind, a flowing river in front, and flanking mountains to either side. The orientation of the grave is carefully determined, taking into account the precise dates of the deceased person’s birth and death.
The relatively high hills overlooking the bay emerged as optimal burial sites for ancestors based on the principles of Feng Shui. Given the absence of mountains and rivers in this district, these elevated locations were gradually endowed with sacredness and as sites of commemoration for the villages. As the local population grew, an increasing number of individuals chose to follow in the footsteps of their forebears by selecting these revered hills for their final resting places, which resulted in a consistent distribution pattern of graves with rising density (Figure 8).
Although some consider Feng Shui an outdated and superstitious belief system, it is still widely followed by millions of Chinese people at the grassroots level. The study area lies nearly 2000 km away from the political center of China in Beijing, and changes in the political system have not weakened the inheritance of this folk custom. On the contrary, Feng Shui has flourished over the past four decades after the reform and opening up. Over a millennium since its beginnings [61], the theory and practice of Feng Shui persist as a significant cornerstone of Chinese folk culture.

4.3. Cultural Factors as a Constraint on Landscape Change

When we understand the underlying reasons for the continuity of graves and consider the historical context of regional development, we can offer a more nuanced explanation for the apparent contrast in the relationship between the distribution of graves and older field boundaries compared to newer plots. These differences probably relate to variances in Feng Shui conditions across this little peninsula, influenced by the lie of the land. Consequently, a concentration of graves can be observed on the hillsides, where the old field boundaries were not affected by the farmland gridding in the late 1970s. In the process of agricultural commercialization after the 1980s, these areas were abandoned first to be replaced by fruit trees or timber that did not require expensive irrigation. Conversely, woodland or uncultivated land was less affected by people’s daily activities compared with farmland. These places with good Feng Shui conditions attracted new graves, resulting in the formation of persistent and sacred sites within the rural landscape.
There is a punctuated equilibrium paradigm proposed in some research about landscape change [62], which suggests a discontinuous evolution of landscape structure: abrupt phases of human-driven transformations alternating with longer phases of stability or gradual development. This theory can explain the episodic impact of agricultural and economic development on the landscape reflected in land use and field boundaries in this study. However, in contrast to the episodic impacts of those changes, folk cultures like Feng Shui exercise a more enduring influence on the landscape. Even in the context of strong political movements or rapid economic development, the inheritance of such cultural norms serves to guarantee the persistence of landscape form, with the effects extending beyond the graves themselves into the surrounding field pattern. It can be observed that protecting the continuity and diversity of local culture can also play a positive role in the protection of the persistence and diversity of landscapes.

4.4. Limitations and Prospect

This study has relied on the manual interpretation of remote sensing data to interpret time depth based on the morphology of fields and other landscape features. The accuracy of such interpretations is limited by issues, including the resolution of the data and the presence of vegetation or other obstructions. There is a level of subjectivity and uncertainty in the interpretation of field boundaries. Moreover, the situation in earlier historical periods is very poorly understood and would remain difficult to correct using rapid field surveys. Such problems need to be addressed by follow-up research, which might include methods such as Object-Based Image Analysis in automatic interpretation [63] or field-based analyses to examine the time-depth of boundary features [64].
Furthermore, although the paper discussed the impact of Feng Shui culture on the landscape, which probably relates closely to issues of landscape memory and landscape perception, the research focused heavily on morphological characteristics of the landscape. We did not interview local inhabitants to understand their attitudes towards the landscape or burial places. Our knowledge of this cultural mechanism is insufficiently detailed and should be supplemented in future research.
Finally, we can observe that the method of studying the time depth of landscape based on field boundaries could also be applied in other regions with varying development levels. The relationship between field boundaries and land use may be significantly different in other places, and the comparison between different regions would be helpful to draw more insightful conclusions.

5. Conclusions

Inspired by landscape archaeology, this study emphasizes the importance of linear and point elements in studying landscape evolution, which has been overlooked by many previous studies. This paper utilized two distinct spatial elements, polylines and polygons, to convey the time depth of the study area. The contrast between these elements was compared with a persistent point element. In this case study, it was found that the time depth of field boundaries was longer than that of land use, signifying that there is older historical information about landscape organization preserved in field boundaries. In addition, in the 80 years covered by this study, field boundaries reflected a clear process of agricultural intensification, which changed field patterns, while land use was more sensitive to agricultural commercialization and urbanization. Finally, it is concluded that cultural factors constrain landscape change, as reflected using the Feng Shui funeral culture of the study area. This culture not only fixes the location of graves in the area, but also leads to the retention of other nearby landscape features around the burials, in this case, the field patterns around the graves.
By analyzing individual monuments, field boundaries, and land use data, it is possible to provide a more holistic view of the landscape evolution of a place. Compared to land use data alone, linear and point data can provide indicators of more mechanisms of landscape change, such as the agricultural intensification and Feng Shui funeral culture, which have been identified as potentially important factors in this paper. Similar methods could be used in other parts of China and beyond to explore the time-depth of landscapes facing rapid urbanization.

Author Contributions

Conceptualization, J.B.; methodology, J.B.; software, J.B.; validation, S.T.; formal analysis, J.B.; investigation, J.B.; resources, Y.P.; data curation, J.B.; writing—original draft preparation, J.B.; writing—review and editing, Y.P. and S.T.; visualization, J.B.; supervision, S.T.; project administration, Y.P.; funding acquisition, Y.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China, grant number 51978275; China Scholarship Council under grant number 202206150068.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Acknowledgments

The aerial photos were provided by local photographer, Bingxu Fang. We thank him for his support.

Conflicts of Interest

The authors declare no conflict of interest.

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Land 12 01979 g001
Figure 1. Location of study area.
Figure 1. Location of study area.
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Figure 2. An aerial view of the study area (Houhong village, looking south-west). Photo: Bingxu Fang, September 2015.
Figure 2. An aerial view of the study area (Houhong village, looking south-west). Photo: Bingxu Fang, September 2015.
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Figure 3. Mixed land use pattern (The white patches in the picture are graves in Donglin village, looking southwest). Photo: Bingxu Fang, September 2015.
Figure 3. Mixed land use pattern (The white patches in the picture are graves in Donglin village, looking southwest). Photo: Bingxu Fang, September 2015.
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Figure 4. Workflow of the study.
Figure 4. Workflow of the study.
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Figure 5. The maps of land use in 5 periods.
Figure 5. The maps of land use in 5 periods.
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Figure 6. The time depth is based on land use in 5 periods.
Figure 6. The time depth is based on land use in 5 periods.
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Figure 7. The field boundaries in five periods.
Figure 7. The field boundaries in five periods.
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Figure 8. Kernel density of graves distribution.
Figure 8. Kernel density of graves distribution.
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Figure 9. Continuity of graves based on statistics of their area. (1. The height of the bar represents the area of the graves in this category. 2. Due to poor management, some graves may appear as grassland or bare land in aerial photos. When calculating the grave area, these have been included as ‘uncertain’ graves in the figure).
Figure 9. Continuity of graves based on statistics of their area. (1. The height of the bar represents the area of the graves in this category. 2. Due to poor management, some graves may appear as grassland or bare land in aerial photos. When calculating the grave area, these have been included as ‘uncertain’ graves in the figure).
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Figure 10. The average distance between graves and field boundaries in each period.
Figure 10. The average distance between graves and field boundaries in each period.
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Figure 11. The proportion of tombs contained in the buffer of field boundaries in different periods.
Figure 11. The proportion of tombs contained in the buffer of field boundaries in different periods.
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Figure 12. Perimeter of graves in different periods.
Figure 12. Perimeter of graves in different periods.
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Table 1. Data Source.
Table 1. Data Source.
Source and MaterialsPeriodsScale/ResolutionComments
Foreign Aerial Photography Record Group (RG) 373 in the National Archives of USA, Can number: ON064289, Spot number: TV362 October 19431:55,200Black and white negatives recorded on rolls of film, scanned through a scanner box provided by the archives with 1200 dpi resolution.
KeyHole Satellite Images in USGS, Entity ID: D3C1207-200158F0802 December 1973Around 1 mBlack and white images purchased via the USGS website.
KeyHole Satellite Images in USGS, Entity ID: D3C1216-200290A02426 July 1980Around 1 mBlack and white images purchased via the USGS website.
Google Earth Satellite Images12 April 2006Less than 0.5 mRGB images available in Google Earth.
Google Earth Satellite ImagesJanuary 2022Less than 0.2 mRGB images available in Google Earth.
ASTER GDEM v3 Dataset201930 m DEM data downloaded from NASA EARTH DATA website.
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Pan, Y.; Bai, J.; Turner, S. History in Points, Lines and Polygons: Time Depth in the Landscape of Guangdong Province, Southern China. Land 2023, 12, 1979. https://doi.org/10.3390/land12111979

AMA Style

Pan Y, Bai J, Turner S. History in Points, Lines and Polygons: Time Depth in the Landscape of Guangdong Province, Southern China. Land. 2023; 12(11):1979. https://doi.org/10.3390/land12111979

Chicago/Turabian Style

Pan, Ying, Jiayu Bai, and Sam Turner. 2023. "History in Points, Lines and Polygons: Time Depth in the Landscape of Guangdong Province, Southern China" Land 12, no. 11: 1979. https://doi.org/10.3390/land12111979

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