Reconstruction of Cropland for the Rikaze Area of China Since the Tubo Dynasty (AD 655)

Abstract

The reconstruction of cropland across historical periods offers valuable insights into the relationship between climate change and human–environment interactions. By extracting key demographic and tax revenue data from historical documents, we estimated cropland data during the Tubo, Yuan, Ming, and Qing dynasties for the Rikaze area in China. Subsequently, according to the characteristics of cropland fragmentation in the Rikaze area, we employed geographically weighted regression (GWR) to reconstruct the 1 km × 1 km cropland cover datasets across the four dynasties for the Rikaze area. The findings are as follows. The amount of cropland showed that the change in cropland in the Rikaze area in the four periods was extremely high, which reflects the great instability of cropland in the Rikaze area. Under the combined action of social unification, cropland production policies, and a suitable climate, the Tubo dynasty was the most significant period of cropland development in the Rikaze area, with the area of cropland reaching 591,927 mu. However, under the influence of the nomadic regime and harsh climate in the Yuan dynasty, the cropland area was sharply reduced, reaching only 18,338 mu. During the Ming and Qing dynasties, the cropland area increased steadily, reaching 200,000 mu and 547,000 mu, respectively. The spatial distribution of cropland shows that the cropland in the Rikaze area is mainly distributed in the middle reaches of the Yarlung Zangbo River, the middle and lower reaches of the Nianchu River, and the Pengqu River Valley. Counties and districts with better agricultural conditions, such as Jiangzi, Bailang, and Renbu, are the main concentration areas of cropland in the Rikaze area. The overall spatial distribution pattern of cropland shows fragmented distribution along rivers, highlighting the characteristics of valley cropland. The research in this paper represents the active exploration of the reconstruction of cropland distribution under complex terrain conditions.

1. Introduction

Cropland is an important basis for human survival and development and also an important means by which human beings change the land cover [1]. Cropland change in historical periods is an important part of global change research. It can not only provide data and a theoretical basis for the study of past climate change and climate formation mechanisms, but also provides a reference for the simulation and prediction of future climate scenarios [2,3,4]. Consequently, the reconstruction of historical cropland is increasingly receiving scholarly attention.

Recently, scholars have intensively pursued research on the reconstruction of cropland in historical periods. This work has greatly advanced our understanding of the interplay between human activities and environmental evolution throughout history. Representative datasets, such as HYDE [5,6,7] and SAGE [8], are currently extensively employed in global environmental change research. For instance, Peng et al. [9] utilized data from SAGE and HYDE to estimate the rise in atmospheric CO₂ attributable to land use changes between 1860 and 1990 and to assess the implications of these changes for the carbon cycle. Similarly, Fuchs et al. [10] employed the HYDE dataset to evaluate the effects of land use alterations on the global carbon cycle across various future scenarios. However, their uncertainties at the regional level render these datasets primarily suitable for large-scale analyses [11,12,13]. Consequently, many scholars have extensively utilized a wealth of historical documents to reconstruct historical cropland on a regional scale in areas including China [14,15,16,17], Europe [18,19,20], and South Asia [21,22]. These efforts contribute to enhancing the accuracy and reliability of global land use datasets. Liu et al. [23] employed the ANN-FLUS model to meticulously reconstruct the historical dynamics of the cropland distribution in Vietnam spanning the years 1885 to 2000. Utilizing an array of varied data sources, Yu et al. [24] developed an exhaustive spatial–temporal dataset that intricately details the progression of cultivated land distribution across China from 1900 to 2016. Although significant advances have been achieved in research on the spatial reconstruction of historical cropland in recent years, existing methodologies and the choice of study regions continue to exhibit notable limitations. In terms of research methods, the prevailing methods of reconstructing spatial patterns assume that the impacts of various factors on the distribution of cropland have remained constant over the past millennia [25,26]. This simplified approach may be useful for plains, but its suitability for areas with fragmented agricultural distribution, such as the Tibetan Plateau, still requires validation. In the realm of research area selection, current studies predominantly target the typical agricultural areas of the Tibetan Plateau [27,28]. Conversely, scholarly attention to the Rikaze area remains limited, and the outcomes of related reconstruction efforts are notably sparse.

Situated in the southern part of the Tibetan Plateau, the Rikaze area features a com-plex topography, with cropland predominantly dispersed along the river valleys, exhibiting a fragmented pattern. The area boasts a protracted history of agricultural cultivation; however, the scarcity of historical documents poses significant challenges in reconstructing the spatial distribution of historical cropland here. In view of this, based on a large number of historical data related to agricultural activities, we estimated the cropland areas during the Tubo, Yuan, Ming, and Qing dynasties in the Rikaze area. According to the characteristics of the complex topography and fragmented cropland distribution in the Rikaze area, the gridding reconstruction method of GWR was used to map historical cropland. This work not only provides a basis for the study of cropland pattern changes in Tibet’s historical periods but also serves as a methodological reference for land use research in other regions with fragmented distributions.

2. Study Area

The Rikaze area, situated in the Southern Tibetan Plateau and the southwestern part of the Tibet Autonomous Region, is bordered by Lhasa to the east and Ngari to the west and shares borders with India, Nepal, and Bhutan to the south (Figure 1). Situated between the Himalayas and the Kailas Range Mountains, the area features a rugged and complex terrain characterized by high mountains, expansive valleys, and lake basins. It boasts an average elevation exceeding 4000 m, abundant sunlight with over 3300 h of annual sunshine, and a mild climate with a frost-free period of approximately 120 days. The average annual temperature ranges from 7 to 9 °C, with most precipitation occurring between July and August. The area boasts a rich network of rivers, notably the Yarlung Zangbo River, Nianchu River, and Pengqu River, which are vital in supporting agricultural development. Dating back to the Paleolithic era, the Rikaze area has served as a vital area for agricultural activities [29]. The discovery of highland barley seeds approximately 3200 years ago marked the onset of primitive agriculture in the area [30]. Around 1400 years ago, the advent of new farming tools and techniques spurred the extensive development of cropland, reaching a historical zenith. Around 1200 years ago, the Tubo regime collapsed, leading to a prolonged era of subdued agricultural activity. Around 800 years ago, the Yuan dynasty’s unification of the Tibetan administration led to relative societal stability, catalyzing the restoration and development of agriculture. Around 600 years ago, this stability further facilitated the gradual recovery of agriculture and the expansion of cropland. Around 300 years ago, despite the impacts of war and exploitation, agriculture still developed to a certain extent, providing a basic guarantee for the survival of local residents. Thanks to its natural advantages, such as abundant sunlight and rivers, and its long history of agricultural development, the Rikaze area is often referred to as the ‘Granary of Tibet’. Agriculture has consistently been a cornerstone of local economic and social progress [31,32].

3. Data and Methods

The overall research framework of this study is shown in Figure 2. In this work, the cropland areas during the Tubo, Yuan, Ming, and Qing dynasties were estimated utilizing historical population and tax data. Subsequently, employing the gridding reconstruction method of GWR, the estimated cropland areas were spatially allocated to generate a spatial distribution map.

3.1. Estimation of Cropland Area

The Rikaze area was remote and closed during historical periods, with scant documentation of its cropland. Given the absence of direct records containing cropland data, the population serves as the primary determinant of cropland changes and represents a reasonable proxy for the estimation of cropland area. Therefore, the population and tax data of the Tubo, Yuan, Ming, and Qing dynasties (specifically, AD 655, 1287, 1368, and 1830) were extracted from a large number of historical documents, including A General History of Tibet [33], Ancient Architecture in Tibet [34], A Local Economic History of Tibet [35], and Population of China: Tibet Volume [36], to estimate the areas of cropland in the Rikaze area. For more historical documents, please see Supplementary Materials. Subsequently, we introduce the specific estimation methods for the cropland area during the four dynasties as follows.

3.1.1. Tubo Dynasty (AD 655)

During the Tubo dynasty, its rulers divided their territories into five ‘Ru’ (the basic unit of the Tubo local administration)—specifically, Wuru, Yueru, Yeru, Rula, and Subiru. It was also proposed to add Xiangxiong to the five ‘Ru’, resulting in the six ‘Ru’ of Tubo. The Rikaze area involved portions of the Rula, Yeru, and Xiangxiong areas [33] (Figure 3). Historical records indicate that Yeru had a population of approximately 700,000, Rula had around 720,000 (inclusive of present-day Nepal), and Xiangxiong was home to about 500,000 inhabitants [36]. We employed historical and geographic data to define the spatial extent of the Rikaze area. By analyzing the geographical range of Rula, the proportion of modern cropland was determined, and the population of Rula was calculated. Integrating these data with the modern population ratio and the per capita cropland area enabled the estimation of the population and cropland area in the Rikaze area during the Tubo dynasty. Firstly, based on records detailing the administrative scope of the six ‘Ru’ during the Tubo dynasty, we spatialized these regions within the contemporary administrative boundaries of Tibet. The results show that the administrative boundaries of the Rikaze area historically encompassed Rula (excluding Nepal), the majority of Yeru (excluding Nimu County), and the three counties of Saga, Zhongba, and Jilong, which were part of Xiangxiong at that time. Rula covered a vast territory that included the counties of Rikaze and what is now known as Nepal [37]. Given the extensive range of the Rula population statistics, the population estimates for the Rikaze area within Rula were derived based on the proportion of modern cropland. Secondly, based on the modern population ratio, the populations of the four counties of Nimu, Saga, Zhongba, and Jilong during the Tubo dynasty were converted. Thus, the population of the Tubo dynasty in the Rikaze area was 758,881 people. Finally, referring to the calculation of 0.78 mu per capita in the Tubo dynasty in the work of Luo [38], the cropland area during the Tubo dynasty in the Rikaze area was 591,927.18 mu.

3.1.2. Yuan Dynasty (AD 1287)

In 1271, Tibet was formally annexed into the territory of the Yuan dynasty. In 1287, Kublai Khan, the Emperor of the Yuan dynasty, conducted a comprehensive household census in Tibet, resulting in the division of thirteen ‘Wanhu’ (each ‘Wanhu’ was equivalent to a county-level administrative unit) [39]. According to historical records, the inventory utilized ‘Huoerdu’ as the statistical unit. The ‘Huoerdu’ is a composite statistical unit based on both land and the population. Each ‘Huoerdu’ encompasses six individuals and cropland capable of sowing 12 ‘Mongoliagrams’ (1 ‘Mongoliagram’ was equivalent to 1.50 kg) of seed [40]. Historical records indicate that, of the thirteen ‘Wanhu’, six ‘Wanhu’ were part of the Rikaze area, accounting for 13,545 ‘Huoerdu’. An additional 737 ‘Huoerdu’ were not included in this count. Consequently, the Rikaze area during the Yuan dynasty comprised a total of 14,282 ‘Huoerdu’, with a population of 85,692, and had the capacity to cultivate 171,384 ‘Mongoliagrams’ of seeds [36,41,42]. Based on the ‘Huoerdu’ standards and records, one ‘Mongoliagram’ was equivalent to 1.5 kg; furthermore, one ‘Mongoliagram’ equated to 0.11 ‘Zangke’ (‘Zangke’ is a traditional unit of weight in Tibet, equal to about 14 kg). The land area sown with 1 ‘Zangke’ seed is 1 ‘Zangke’ land, i.e., about 1 mu [34]. It can be obtained that the cropland in the Rikaze area during the Yuan dynasty amounted to 18,338.09 mu.

3.1.3. Ming Dynasty (AD 1368)

In 1368, the Ming dynasty established thirteen ‘Zong’ (equivalent to the modern administrative unit at the county level), four of which were located in the Rikaze area. According to historical records [43], during the Ming dynasty, Tibet had a population of approximately 1 million people over an area of 188.07 × 10⁴ km², so its population density was 0.50. The population data of the Ming dynasty were based on the population density data of Liu, and, combined with the size of the modern Rikaze area, the population of the Rikaze area in the Ming dynasty was obtained. The modern Rikaze area covers 179,240 km², and the estimated population of the Rikaze area in the Ming dynasty was 89,620. Historical records [44,45] indicate that, during the Qing dynasty, the population of Tibet remained at approximately 1 million, exhibiting minimal growth and maintaining similar levels of productivity. Accordingly, this study assumed that the per capita cropland area remained stable from the Ming to the Qing dynasties. According to the calculation of the per capita cropland area of the Qing dynasty, the cropland area of the Rikaze area during the Ming dynasty was 200,000 mu.

3.1.4. Qing Dynasty (AD 1830)

The cropland data for the Rikaze area in the Qing dynasty came from the Inventory of the Year of the Iron Tiger (the tax record of Tibetan areas in the Qing dynasty) [46]. The main content of the inventory is the tax data of various monasteries, nobles, and manors in the Tibetan areas during the Qing dynasty. The cropland area could be obtained after conversion. Wang et al. [47] reconstructed the spatial pattern of cropland in the Yarlung Zangbo River region in 1830 based on this inventory. In this study, the conversion relationship of the cropland area obtained in the above study was adopted:

1 Dun = 2 Gang = 80 standard mu

During the Qing dynasty, ‘Gang’ and ‘Dun’ served as the primary units of measurement employed by the local Tibetan government to levy differential taxes from various ‘Zong’.

Then, according to the different types of tax difference of each manor, the tax that could not be used to convert the cropland area was excluded, and the tax difference paid by serfs belonging to nobles, temples, and government manors was not counted twice. The taxes recorded in the inventory included cropland and abandoned land where serfs could not serve or pay taxes. Since the amount of tax difference was not counted, it was listed as the proportion of hidden fields and corrected in this work. The proportion of hidden fields was set at 20%, and the cropland area was 547,000 mu in 1830.

3.2. Gridding Reconstruction Model

As shown in Section 3.1, we estimated the cropland areas for the four historical periods; subsequently, we conducted the gridding reconstruction of cropland. Prior to the gridding reconstruction process, the maximum historical distribution range of cropland was identified (Section 3.2.1). The initial step in gridding reconstruction involves identifying the primary natural and human factors influencing the cropland distribution. Subsequently, the GWR method was employed to quantify the impacts of these factors on the cropland distribution, leading to the development of a grid model. Finally, data on the cropland areas from each historical period were integrated into the model, enabling the analysis of the spatial and temporal variations in cropland distribution across these periods in the Rikaze area.

3.2.1. Maximum Distribution Extent of Cropland

The Rikaze area features a complex geomorphology, with cropland interspersed across diverse landforms, including river valleys, river terraces, and platforms. The distribution of cropland is more fragmented compared with that of the plains. The distribution of modern cropland indicates that the maximum elevation of cropland is found in Jiru Village, Gangba County, at approximately 4750 m. Consequently, regions exceeding this elevation are deemed uncultivable. Regarding the slope, 65.75% of cropland has a gradient of less than 15 degrees, and almost 90% falls below a 30-degree incline [48]. Thus, the threshold for feasible cropland slopes is established at 30 degrees, with steeper gradients considered unsuitable for cultivation. Furthermore, lake areas were designated as limiting factors and thus excluded from regions suitable for cropland distribution [49]. Elevation and slope information was derived from DEM data with a 12.50 m resolution [50]. Each factor was binarized, with values of 0 indicating no cropland and 1 indicating the presence of cropland. The analysis of spatial overlays ultimately established the maximal extent of cropland distribution in the Rikaze area.

3.2.2. Selection of Dominant Factors Influencing Cropland Distribution

A factor determines the possibility of cropland distribution according to its value, which is an important basis for the allocation of cropland quantities. These factors primarily encompass the altitude, slope, rivers, and settlements. Given the unique natural conditions in the Rikaze area, its agriculture consists predominantly of facility agriculture, relying on rivers and irrigation infrastructure, thus diminishing the influence of precipitation on the cropland distribution. Consequently, river data are considered a crucial factor [51].

A settlement refers to a place where people live and work and is interdependent on cropland. Therefore, settlements are regarded as an important factor. Utilizing historical resources such as atlases of cultural relics, county annals, and literary sources, this study constructed a database of settlements spanning the four historical periods: the Tubo, Yuan, Ming, and Qing dynasties [52,53]. Furthermore, in order to verify the accuracy of the sources of the settlements, we randomly selected settlement sites and collected samples such as carbon chips/pottery chips and sent them to the Beta Laboratory in the United States for AMS¹⁴C dating (the AMS¹⁴C dating technique is an important radioisotope dating method that has the characteristics of high precision and rapid measurement). According to the OxCal v4.4 [54] radiocarbon isotope dating correction program and IntCal20 [55] tree ring curve correction data, the median of the 2σ corrected age error range was used as the calendar age to verify the accuracy of the settlement age. Finally, according to the relative orientation of each settlement, they were transferred from the map to the present location. The settlement distribution maps of the Tubo, Yuan, Ming, and Qing dynasties in the Rikaze area were obtained by spatialization (Figure 4).

3.2.3. Construction of Gridding Model Based on Geographical Weighted Regression

At present, the reconstruction of cropland patterns in the historical period of the Tibetan Plateau valley mainly relies on the gridding model designed by Luo [26]. The factors affecting the distribution of cropland in this model include natural factors and human factors. According to the influence degree, Luo calculated the land appropriability degree of the grid and assigned the cropland in the historical period to the corresponding grid. However, this method assumes that the relationship between the impact factors remains stable throughout the area and the weight of each impact factor remains unchanged over the past 300 years. The Rikaze area is located between the Himalayas and the Kailas Range Mountains, with an average elevation of more than 4000 m. The terrain is complex and diverse, consisting of high mountains, wide valleys, and lake basins [56]. The distribution of cropland is notably fragmented, and simple reconstruction using a uniform weight fails to capture the spatial heterogeneity inherent in the cropland distribution. However, GWR facilitates the creation of local relationship models tailored to specific regional characteristics, effectively capturing the spatial variations of each influencing factor and elucidating the local spatial relationships and heterogeneity among these factors. Therefore, on the basis of the previous cropland gridding reconstruction model, this study introduces the GWR method to improve the reconstruction model.

The specific process is as follows.

Firstly, the factors of elevation, slope, rivers, and settlements are standardized. Among them, for rivers and settlements, we need to use the ArcGIS 10.8 software to analyze the cost distance and then perform standardization. The standardization method is as follows:

$$NE={\displaystyle \frac{MaxE-E}{MaxE}}$$

(1)

$$NSL={\displaystyle \frac{MaxSL-SL}{MaxSL}}$$

(2)

$$NR={\displaystyle \frac{MaxR-R}{MaxR}}$$

(3)

$$NSE={\displaystyle \frac{MaxSE-SE}{MaxSE}}$$

(4)

In these equations, E, SL, R, and SE represent the elevation, slope, rivers, and settlements, respectively.

Then, the ArcGIS 10.8 software is used to generate a 1 km × 1 km regular grid and grid center in the research area. The center point of the grid is used to extract the standardized influence factors. After this, the GWR 4.0 software is used to calculate the weight coefficient of each influence factor. The land reclamation degree of each grid center point in each period is calculated. The calculation formula is

$$Y_{i,nx}={\mathsf{\beta }}_0+{\mathsf{\beta }}_{1}E+{\mathsf{\beta }}_{2}SL+{\mathsf{\beta }}_{3}R+{\mathsf{\beta }}_{4}SE$$

(5)

In the formula, Y_i,nx represents the land reclamation degree of grid i in the n_x year; β_x is the weight coefficient. The different distributions of settlements for the four periods (Figure 4) are input into the GWR 4.0 software to calculate the land reclamation degree of each period.

The land reclamation degree is assigned to the field of the located grid pixel to form a layer of the potential distribution range of cropland with a spatial resolution of 1 km. After this, we construct the cropland allocation model. The model is as follows:

$$G_{i,nx}={\displaystyle \frac{Y_{i,nx}\times A_{nx}}{{\displaystyle \sum _{i=1}^x{Y}_{i,nx}}}}$$

(6)

$$L_{i,nx}={\displaystyle \frac{G_{i,nx}}{{area}_i}}$$

(7)

In the formula, G_i,nx, L_i,nx represent the cropland area and reclamation rate of grid i, respectively. A_nx represents the area of cropland in the area in the n_x year; area_i represents the area of grid i.

4. Results

4.1. Cropland Area in the Tubo, Yuan, Ming, and Qing Dynasties

The total cropland area of the Rikaze region in the Tubo, Yuan, Ming, and Qing dynasties was 591,927.18 mu, 18,338.09 mu, 200,000 mu, and 547,000 mu, respectively (

Table 1. Population sizes and cropland areas in different dynasties in the Rikaze area, China.

Period	Tubo Dynasty	Yuan Dynasty	Ming Dynasty	Qing Dynasty
Population (×104)	75.90	8.60	9.00	24.40
Cropland area (mu)	591,927.18	18,338.09	200,000	547,000

). From the Tubo dynasty to the Qing dynasty, there was an initial decline followed by an increase in the extent of cropland. Notably, the Tubo dynasty featured the largest area of cropland, supporting the largest population. During the Yuan dynasty, both the population and the cropland area significantly decreased. In 655, Tibet unified the plateau, gradually annexing surrounding factions. Centered around the Yarlung Zangbo River and Lhasa Valley, Tubo’s territory expanded, and its population increased, culminating in the population peak of the Tubo dynasty. During this period, government policies promoting land reclamation and the construction of irrigation facilities, along with the warm and humid climate, created favorable conditions for agricultural development. Agricultural production primarily catered to local demands, with underdeveloped trade routes and minimal export demands fostering a self-sufficient economy that supported a substantial population. Furthermore, Tubo’s nomadic herding flourished, and the vast plateau pastures provided abundant resources for herdsmen, considerably easing the agricultural burden of population support.

However, in 842, the Tubo dynasty was destabilized by internal power struggles and political factions, ultimately leading to the assassination of the king. This event precipitated the collapse of the central authority, plunging society into profound turmoil and political chaos. With the collapse of the central authority and the fragmentation of the previously unified policy, various separatist forces emerged, and frequent conflicts broke out over territory and resources. The ongoing civil war was a serious drain on manpower and resources, with large numbers of workers forced to fight; agricultural work was interrupted or became difficult to maintain, leading to the abandonment of cropland. The war also caused a large population loss, which weakened the agricultural base. During the Yuan dynasty, Mongolian rulers prioritized nomadism and discouraged agriculture, significantly affecting agricultural development in Tibetan regions. To advance nomadic herding, the rulers established specialized departments to oversee the management of horses and other livestock, and they enacted policies such as ‘prohibiting the slaughter of cows and horses’ to further foster the growth of nomadism [57]. This policy resulted in the marginalization of agriculture and the abandonment of extensive tracts of cropland. Concurrently, the climatic conditions during the Yuan dynasty deteriorated, posing greater challenges to agricultural production and exacerbating the sharp decline in cropland areas. Under the combined pressure of environmental conditions and policy, the Yuan dynasty marked the most pronounced period of agricultural decline in Tibetan regions. With the stability of society in the Ming and Qing dynasties, various measures to promote the development of productive forces began to be taken. Vigorous efforts were made to reclaim cropland, and abandoned land was not allowed [58]. Especially in the Qing dynasty, the government attached great importance to the construction of cropland, water conservancy, artificially dug canals, and built levees. In addition, many preferential policies were implemented to encourage the military and civilians to cultivate cropland, and the amount of cropland increased.

4.2. Spatial Distribution of Cropland in the Tubo, Yuan, Ming, and Qing Dynasties

The spatial distribution of cropland in the study area during the Tubo, Yuan, Ming, and Qing dynasties is shown in Figure 5. The distribution of cropland was the widest in the Tubo dynasty. In the Yuan dynasty, it was only sporadically distributed across the study area and then expanded in the Ming and Qing dynasties.

During the Tubo dynasty, the cropland in the Rikaze area reached a certain spatial extent. The cropland grid accounted for 1.67% of the total grid number in the study area, and the average reclamation rate was 12.99%. Cropland is distributed sporadically along the two sides of major rivers, such as the Yarlung Zangbo River, Nianchu River, and Pengqu River. Limited by the natural conditions and agricultural production levels, the reclamation rate of the whole region is not high. Cropland grids with reclamation rates below 10% account for 0.16%; rates between 10% and 15% accounted for 1.41%; and rates between 15% and 20% accounted for 0.10%. Only 0.01% of cropland had a grid reclamation rate above 20% (

Table 2. The proportion of the cropland area in each reclamation rate interval during the Tubo, Yuan, Ming, and Qing dynasties in the Rikaze area based on cropland maps.

Dynasty	Cropland Area		Reclamation Rate Interval/%
	Proportion of Cropland Grid/%	Average Rate of Reclamation/%	≤10	10~15	15~20	≥20
Tubo	1.67	12.99	0.16	1.41	0.10	0.005
Yuan	0.30	2.27	0.30	-	-	-
Ming	0.63	11.57	0.05	0.58	0.003	0.003
Qing	1.17	17.05	0.03	0.25	0.79	0.09

). The highest reclamation rate of the cropland grid was 58.24%. The grid with a high reclamation rate was concentrated on the terrace near the Nianchu River Basin, where the settlement distribution was relatively concentrated. The valley was wide, the population was concentrated, and the basic agricultural conditions were good. This was the area where agriculture began in the Rikaze area.

The proportion of the cropland grid in the Yuan dynasty was 0.30%, decreasing by 1.903% compared with the Tubo dynasty. The scale of cropland decreased greatly, making this the period with the smallest cropland area during the study period. The average reclamation rate of the cropland grid was 2.27%, and the highest reclamation rate was 5.93%. Cropland was only scattered across the middle and lower reaches of the Nianchu River Basin, Jiangzi County, Bailang County, Renbu County, and other counties. The reclamation rate of the cropland grid in the whole region was below 10% (Table 2). The substantial decline in agriculture in Tibet before the Yuan dynasty can be primarily attributed to incessant warfare and a rapid economic downturn, leading to the widespread abandonment of cropland and a significant downturn in agricultural development.

The proportion of the cropland grid in the Ming dynasty was 0.63%, increasing by 0.34% compared with the Yuan dynasty. The average reclamation rate of the cropland grid was 11.57%. The highest reclamation rate was 23.35%; the grids with high reclamation rates were concentrated in important agricultural counties such as Lazi, Sangzhuzi, Bailang, Jiangzi, and Sajia; and the distribution was in the form of patches. In the Ming dynasty, the Tibetan people and the soldiers in the Rikaze area jointly cultivated and planted, and they successively reclaimed the abandoned cropland, which increased the cropland area. However, due to the decrease in the population after the war, agricultural development lagged, resulting in a slow increase in the cropland area during this period. In the cropland grid, reclamation rates of less than 10% accounted for 0.05%, rates between 10% and 15% accounted for 0.58%, rates between 15% and 20% accounted for 0.003%, and rates over 20% accounted for 0.003% (Table 2).

In the Qing dynasty, the proportion of the cropland grid was 1.17%, increasing by 0.54% compared with that in the Ming dynasty. The scale of cropland was further expanded and spread outwards from the relatively concentrated area of settlements. The average reclamation rate of the cropland grid was 17.05%. The highest reclamation rate was 43.59%. In the cropland grid, reclamation rates below 10% accounted for 0.03%, rates between 10% and 15% accounted for 0.25%, rates between 15% and 20% accounted for 0.79%, and only 0.09% of the cropland grid had reclamation rates above 20% (Table 2). The agricultural development level was improved during the Ming dynasty, and the cropland area expanded. The cropland area of Rikaze increased from the Ming dynasty to the Qing dynasty. However, due to the continuation of the feudal agricultural economy and the prolonged use of primitive farming methods in the Rikaze area during the Qing dynasty, the expansion in cropland was modest, and agriculture remained relatively undeveloped.

To ensure the reliability of the reconstruction results, we used the improved gridding model to reconstruct the modern cropland data for 2020. In the actual cropland grid consisting of 7886 points, 6837 were classified as cropland, with consistency of 86.70%. According to the above test results, the overall model is ideal, validating the reasonableness of the reconstruction model used in this study. Furthermore, based on prior research findings, in 1830, the distribution of cropland was notably concentrated in the Jiangzi, Bailang, and Renbu regions, whereas it was considerably less extensive in the Jilong and Nielamu areas [47]. This observation aligns with our reconstruction results and further corroborates the accuracy of our model. For more validation details, please see Supplementary Materials.

5. Discussion

5.1. Comparisons with Previous Studies

In previous studies, Wang et al. [47] employed a grid model to reconstruct the cropland patterns in the middle reaches of the Yarlung Zangbo River Valley for the year 1830. Chen et al. [59] utilized a similar model to reconstruct the cropland patterns in the Yellow River–Huangshui River Valley over the past 300 years. Li et al. [60] utilized population data as a proxy to reconstruct the cropland patterns in Qinghai and Tibet over the past century. These studies have laid a good foundation for the quantitative estimation and spatial reconstruction of the historical cropland area of the Tibetan Plateau. However, most of them focus on the agricultural zones of the Tibetan Plateau, with limited investigations targeting the Rikaze area, where historical agriculture-related data are relatively scarce. Furthermore, the temporal scope of historical cropland reconstruction typically spans only a few centuries, rendering the study period relatively brief. Finally, and most importantly, these studies have not sufficiently taken into account the spatial heterogeneity of the Tibetan Plateau. It has to be assumed that the natural and human factors that have affected the spatial distribution of cropland in the past few hundred years have remained unchanged.

Compared to existing research, this study spanned a more extended period, and, while it encountered more significant challenges in data acquisition, it effectively addresses the gap in historical cropland reconstruction in the Rikaze area. Specifically, this study investigated the historical changes in cropland in the Rikaze area from the Tubo dynasty to the Qing dynasty, covering more than a thousand years. We employed the gridding method of GWR to reconstruct its spatial distribution pattern, which fully considered the spatial heterogeneity of the Tibetan Plateau. The adoption of the GWR model allowed for the more effective consideration of the spatial heterogeneity of the factors impacting the distribution of cropland in the region. This enhancement not only improved the accuracy of the research but also rendered the results more region-specific, thereby facilitating the development of more targeted policy recommendations.

We also constructed a database of settlements spanning the four dynasties (Figure 4). Specifically, the human factors that affect the spatial distribution of cropland are no longer constant. As a result, the maps obtained are likely to be closer to the actual situation than the reconstruction results of previous studies. The findings of this study can complement and improve the global cropland datasets, e.g., HYDE, improving their resolution and accuracy at the regional level. Historical cropland data are crucial in supporting simulations and analyses of climate change, determining climatic mechanisms, and forecasting future climatic shifts. These data enable more precise simulations and an understanding of the impacts of cropland changes on the global environment, offering a valuable historical reference to address future environmental changes.

5.2. Uncertainties and Prospects

Firstly, this study faced limitations concerning the source of cropland data. Owing to the scarcity of direct historical records on cropland, this research primarily estimated cropland areas using indirect data such as population and tax revenue information. This approach is crucial when data are scarce. Nevertheless, potential deviations in historical tax records and population statistics can lead to inaccuracies in the indirectly derived cropland data. For instance, during the Tubo dynasty, the territory was much larger than it is today, with the population covering regions like present-day Tibet and Nepal. Consequently, the values might be overestimated. The scarcity of archaeological data constrains our direct understanding of the scale of cropland in historical periods, potentially leading studies to rely on less comprehensive data. To enhance the data accuracy, future research should consider integrating a broader array of data sources, including remote sensing imagery, archaeological data, and historical maps. This multi-source approach will allow for the more comprehensive verification and enrichment of historical cropland data.

Secondly, the model used to reconstruct the cropland distribution primarily selected natural and social factors such as the elevation, slope, rivers, and settlements. These factors impose significant constraints on agricultural activities in plateau regions. Nevertheless, the model does not adequately account for the impacts of nomadic activities and associated factors on the distribution of cropland, potentially resulting in deviations between the reconstructed results and the actual conditions. In future research, it would be beneficial to incorporate natural and social factors associated with nomadic activities into the modeling process, allowing for a comprehensive analysis of their interrelationships in terms of spatial distribution.

Finally, the uncertainty of historical administrative boundaries presents a challenge in cropland reconstruction. This study analyzed the correspondence between ancient administrative units and modern administrative divisions, employing modern conversion methods to estimate the cropland areas across various periods. Nevertheless, the scope for enhancement remains, constrained by the accuracy and completeness of the extant historical data. Consequently, future research should focus more on the precise reconstruction of historical administrative boundaries and integrate more accurate historical boundary data with GIS technology to refine the cropland reconstruction model, thereby enhancing the model’s spatial accuracy and historical consistency.

5.3. Marginal Characteristics

The utilization of historical cropland in the Rikaze area is constrained by a combination of natural and social factors, exhibiting pronounced marginal characteristics. The area’s complex topography and significant elevation variations result in a cropland distribution that is heavily reliant on the natural conditions. During the Tubo dynasty, the cli-mate was warm and humid, conducive to the cultivation of drought-tolerant crops like highland barley and wheat at high altitudes. The altitude for these crops reached 4100 m, with an upper limit of around 4700 m [61]. However, after entering the Yuan, Ming, and Qing dynasties, the climate gradually became colder, reducing the upper limit of cropland to 4000 m. The decline in temperature significantly affected crop growth at high altitudes, particularly during winter, when low temperatures restrict agricultural productivity. Consequently, the extent of cropland has substantially decreased. Additionally, the historical cropland changes in the Rikaze area strongly reflect the characteristics of social margins. During the Tubo dynasty, the rulers prioritized agricultural development, implementing measures such as wasteland reclamation, water diversion for irrigation, and the enhancement of production tools. Consequently, the cropland area during this period reached a flourishing stage within the study area. However, with the governmental transition, agriculture’s prominence sharply declined. The Mongolian rulers of the Yuan dynasty placed a significant emphasis on nomadic herding, establishing dedicated organizations to oversee and promote this sector. During this period of fragmentation, frequent warfare and pronounced internal conflicts led to a dramatic decrease in the population and a substantial reduction in the cropland area—from 591,927 mu to 18,338 mu. Consequently, the cropland changed greatly from the Tubo dynasty to the Yuan dynasty, showing strong social and marginal characteristics.

6. Conclusions

This study systematically collected and analyzed population and tax data covering four periods in the Rikaze area, drawing from a substantial body of historical documents, and subsequently converted this information into cropland data. Then, the gridding reconstruction method of GWR was used to spatially map historical cropland, and the results were verified, so that reasonable reconstruction results could be obtained. The main conclusions are as follows. The amount of cropland shows that the changes in cropland in the Rikaze area in the four periods were extremely large, reflecting the great instability of cropland in the Rikaze area. Under the combined action of social unification, cropland production policies, and a suitable climate, the Tubo dynasty was the most significant period of cropland development in the Rikaze area, with the cropland area reaching 591,927 mu. However, under the influence of the nomadic regime and harsh climate in the Yuan dynasty, the cropland area was sharply reduced, reaching only 18,338 mu. During the Ming and Qing dynasties, the cropland area increased steadily, reaching 200,000 mu and 547,000 mu, respectively. The spatial distribution of cropland shows that the cropland in the Rikaze area is mainly distributed in the middle reaches of the Yarlung Zangbo River, the middle and lower reaches of the Nianchu River, and the Pengqu River Valley. Counties and districts with better agricultural conditions, such as Jiangzi, Bailang, and Renbu, are the main areas in which cropland is concentrated in the Rikaze area. The overall spatial distribution pattern of cropland shows a fragmented distribution along rivers, highlighting the characteristics of valley cropland. The research presented in this paper represents an active exploration of the reconstruction of cropland distribution under complex terrain conditions.