Hefei’s Land Use Simulation and UDB Determination in Economic Development Scenario

doi:10.21203/rs.3.rs-3906266/v1

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Hefei’s Land Use Simulation and UDB Determination in Economic Development Scenario

https://doi.org/10.21203/rs.3.rs-3906266/v1

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Along with the scale development of the world's cities, large-scale urban development cannot be achieved without scientific urban planning, but the national spatial planning based on the current situation is far from being able to meet the needs of exponential scale growth of cities.Using a patch-generating land use simulation (PLUS) model, this study predicted Hefei’s land use change from 2020 to 2060 and determined its urban development boundaries based on ecological service value data. The main findings are summarised as follows: First, the PLUS model accurately simulated Hefei’s land use change. Second, the main trend of land use change was the transformation of nonconstruction land to construction land, with arable land to construction land accounting for by far the largest proportion. The comparison with ecological land showed that the government attaches more importance to ecological protection than grain security. Third, Hefei’s construction land development follows a typical extensive growth pattern, and human intervention (e.g., urban planning) and natural conditions (e.g., DEM-derived elevation) influence the development of urban construction land. By superimposing Hefei’s predicted construction land with eco-logical service value, this study verified the reasonability of Hefei’s territorial spatial planning and the pro-activeness of its urban development strategy. In conclusion, multi-scenario simulation results combined with ecological data can provide a decision-making reference and theoretical support for Hefei’s territorial spatial planning and urban development boundary determination.

Land Use

Economic Development Model

Urban Development Boundary

Hefei

In the context of rapid urbanisation, some Chinese cities are facing urban spatial over-expansion characterised by economic growth plus extensive expansion. Statistics show that from 2010 to 2020, China's urban population increased by 34.7%, while the ur-ban construction land area increased by 51.58%, almost double the population growth rate[1]. Such urban sprawl has heavily encroached on forestland, arable land, wetland, and other urban ecological land, resulting in various problems, such as ecological damage, land resource shortage, and chaos in urban spatial patterns[2]. The determination of urban development boundaries (UDBs) is considered to be among the most effective solutions against urban sprawl. Therefore, the determina-tion of UDBs is an important element of territorial spatial planning because it can effec-tively promote orderly development of urban space and curb unlimited and blind sprawl. To achieve urban sustainability and new-type urbanisation, General Secretary Xi Jinping stated in the report of the 19th National Congress of the Communist Party of China that China must specify three control lines, including the ecological protection red line, per-manent basic farmland protection red line, and UDBs. By specifying the three control lines, China can restrict land development in the delineated regions, thereby curbing urban sprawl and stimulating the redevelopment of urban space[3].

The Yangtze River Delta is among the regions of China with the greatest comprehensive strength, most rapid development, and highest innovation level, and is an important con-fluent point of the Belt and Road regions and the Yangtze River Economic Belt. Anhui Province has been officially included in the Yangtze River Delta since the State Council issued the Guidelines on Promoting the Development of the Yangtze River Economic Belt Backed by the Golden Waterway in 2014. As the capital of Anhui Province, Hefei City was incorporated in the Development Plan of the Yangtze River Delta City Clusters in 2016. As an important part of the Yangtze River Delta city clusters with "one core and five circles", Hefei has gradual-ly become a sub-centre of the Yangtze River Delta. While the integration of the Yangtze River Delta has become a national strategy, Hefei is facing increasingly high development requirements and more challenges in the process of development. This has led to an in-creasing conflict between the expansion of urban construction land and protection and governance of other urban land (e.g., Chaohu wetland, basic farmland, and ecological cor-ridors). Therefore, it is of practical significance to plan the UDBs of Hefei, build a coordi-nated urban-rural relationship, and coordinate urban construction with ecological protec-tion in Hefei.

In this study, Hefei’s land use was simulated. Based on Hefei’s existing land use data, we predicted its future land use, determined its future UDBs, superimposed the predicted construction land with ecological service value, and dynamically adjusted the planned UDBs in accordance with the Territorial Spatial Planning of Hefei City (2021−2035). This study aims to provide support and reference for determining Hefei’s urban development boundary in the future.

2.1 Definition of UDBs

The term “UDB” was first proposed in the Garden Cities of Tomorrow written by Ebenezer Howard. On this basis, The London Plan absorbed the idea of garden cities and developed the Green Belt theory, laying a theoretical foundation for UDBs. In 1973, the State of Oregon (US) proposed the UGBs concept (i.e., the boundaries between towns and villages in the state[4]) and stipulated that the development of urban construction land is only allowed within the specified boundaries. Subsequently, an increasing number of countries and cities attached importance to urban growth and implemented various polices to curb urban sprawl.

Despite the continuous study of UDBs in China and internationally, there is no consensus on the criteria for determining UDBs. In existing studies, UDBs are mainly determined based on three criteria: the scope of urban infrastructure supply[5], boundaries between urban and rural land[6], and boundaries and forms of urban space[7]. Today, the more common method for determining UDBs is based on urban spatial boundaries. Specifically, UDBs are considered as the expansion boundaries for the expected urban development in the future; UDBs are not only rigid control lines for protecting regional ecological resources and environment but are also flexible control lines for ensuring reasonable development and reuse of regional urban construction land[8]. On this basis, this study argues that the model prediction of land use change provides a new idea and approach for determining UDBs.

2.2 Research methodology

The methods for determining UDBs can be classified into positive thinking and reverse thinking. The positive thinking approach is to analyse the distribution of urban construction land, use different simulation models to simulate land use based on multi-source remote sensing data as well as various influencing mechanisms, in order to determine UDBs[9]. Using the remote sensing (RS) and GIS technologies, Zhuang et al. developed a suitable UDB model according to China’s arable land and ecological protection red lines and various land use policies[10]. To simulate urban sprawl, previous studies selected simulation models such as logistic regression models[11], artificial neural network (ANN) models[12], SLEUTH (slope, land use, exclusion, urban extent, traffic, and hill shading) models[13], Future Land use simulation (FLUS) models [14], ant colony optimisation models[15], and cellular automata (CA) models[16]. CA models are widely used due to their ability to present spatial interactions and local spatiotemporal causality, as well as ability to implement spatial interactions in adjacent hierarchies[17–18]. CA models have become the mainstream models for studying UDBs. The reverse thinking approach mainly includes the following methods: 1) doing subtraction in the urban planning according to the evaluation results for urban areas suitable for urban construction[19], 2) forcing the formation of prohibited-development boundaries based on the negative planning theory[20–21], and 3) specifying the UDBs using the overall ecological security pattern as a constraint and using a minimum cumulative resistance model[22].

2.3 UDB studies

Along with the wave of the world for urban planning, China, as a member of the global development, is gradually paying attention to the study of urban planning. In China, studies on UDBs started relatively late. The Urban Planning Preparation Measures (2006) promulgated by the Ministry of Housing and Urban-Rural Development was the first to consider UDBs as a management method. In China, UDBs were first implemented in 2014. In July 2014, the Ministry of Land and Resources and Ministry of Housing and Urban-Rural Development jointly convened the Kick-off Meeting on the Pilot Work of UDBs, designating 14 cities (including Beijing, Xiamen, and Wuhan) as pilot areas for determining UDBs. This was the first time that UDBs were clearly defined at the national level. The kick-off meeting also stipulated the requirements for determining UDBs.

Existing UDB studies in China are still at the initial stage. Taking specific regions of China as examples, most such studies tried to determine UDBs using a CA model (or its extended model) combined with other models. For example, CA models can be combined with digital mining technology[23]; a land expansion analysis strategy to generate a PLUS model[24–25]; dynamic weight trimming technology to modify the TradaBoost algorithm to generate a CAtrans model[26]; and with a Markov model, using the remote sensing based ecological index (RSEI) and ecological sensitivity as the basis for ecological constraints (ECs)[27]. These models can simulate future urban development, which can be used by policy makers to provide policy suggestions for sustainable land use. Luo et al. determined the importance of taxation and land use regulation by discussing the effectiveness of Hangzhou’s UDB policies[28]. Lin et al. analysed the effect of traffic planning on Guangzhou’s territorial spatial layout[29]. Through land use suitability evaluation combined with a CLUE-S model, land development evaluation can properly consider policy factors (e.g., ecological and farmland protection), making the simulation results more consistent with the actual status of urban development[30].

Located in the hinterland of central Anhui between the Yangtze River and Huai River (in East China), Hefei is a sub-centre of the Yangtze River Delta economic zone. With the rapidly increased urbanisation level in recent years, Hefei is facing an obvious contradiction between urban land expansion and ecological protection. However, few studies have investigated the UDBs of Hefei. Selecting Hefei city as the study area, this study tries to provide empirical support and theoretical basis for determining Hefei’s UDBs through model prediction.

3.1 Data sources

The data on land use GDP, spatial distribution of population, precipitation, and temperature were cited from the Resource and Environment Science and Data Centre of the Chinese Academy of Sciences (http://www.resdc.cn), elevation data were cited from the Geospatial Data Cloud (https://www.gscloud.cn), road data were cited from the OSM dataset (http://www.openstreetmap.org), soil type data were cited from the Soil Subcentre of the National Earth System Science Data Centre (http://soil.geodata.cn), and river and lake data were cited from the National Catalogue Service for Geographic Information (http://www.webmap.cn).

3.2 Model method

3.2.1 PLUS Model

A PLUS model integrates two modules, a rule mining method based on land expansion analysis and a CA model based on a multi-type random seeding mechanism, and is coupled with a multi-objective optimisation algorithm, making it able to better simulate specific development and constraint scenarios[25]. The rule mining method of the land expansion analysis strategy (LEAS) module extracts the data of land expansion from the data of two periods on land use change and uses the random forest algorithm to mine the driving factors for the expansion of different types of urban land. The objective is to ascertain the development probability of different types of urban land and the contribution of driving factors to the expansion of them. Using the multi-type random seeding mechanism combined with the diminishing threshold mechanism, the CA model can simulate the automatic generation of patches on a spatiotemporally-dynamic basis under the constraint of development probability.

The development probability is calculated as follows:

$${P}_{i,k\left(X\right)}^{d}=\frac{\sum _{n=1}^{M}I[{h}_{n}\left(X\right)=d]}{M}$$

where, X denotes the vector for a driving factor, M denotes the number of decision-making trees, d can be 0 or 1 (1: other types of land use can be transformed into land use type k, 0: other types of land use can be transformed into land use type k),h_n (X) denotes the predicted type of land use when the decision-making tree is n, I[h_n (X) = d denotes the exponential function of a decision-making tree, and P_(i,k(X))^d denotes the probability of the expansion of land use type k at the spatial unit i.

3.2.2 Accuracy test

The Kappa coefficient and figure of merit (FOM) coefficient were selected to evaluate the accuracy of simulation results [31]. The value range of the Kappa coefficient is 0 to 1; a value greater than 0.8 indicates a high consistency and high accuracy of the simulation results. The FOM coefficient is equal to the ratio of the intersection of the actual land use change and predicted land use change to the union of them. The value ranges from 0 to 1 and the larger the value of the FOM coefficient, the higher the accuracy of the simulation results.

3.2.3 Land use change

The land use transfer matrix can visually reflect the quantitative change, structural characteristics, and change direction for different types of land use between different time nodes from 2020 to 2060. Because this study involved many time nodes, the land use transfer matrix was visualised by creating a Sankey diagram of land use change. The land use transfer matrix is expressed as follows:

$${\text{P}}_{\text{i}\text{j}}=\left[\begin{array}{cccc}{\text{P}}_{11}& {\text{P}}_{12}& \cdots & {\text{P}}_{1\text{n}}\\ {\text{P}}_{21}& {\text{P}}_{22}& \cdots & {\text{P}}_{2\text{n}}\\ \cdots & \cdots & \cdots & \cdots \\ {\text{P}}_{\text{n}1}& {\text{P}}_{\text{n}2}& \cdots & {\text{P}}_{\text{n}\text{n}}\end{array}\right]$$

$${\text{S}}_{(\text{t}+1)}={\text{P}}_{\text{i}\text{j}}{\text{S}}_{\text{t}}$$

$${\text{P}}_{\text{i}\text{j}}\in \left[\text{0,1}\right),{\sum }_{\text{n}=1}^{\text{n}} {\text{P}}_{\text{i}\text{j}}=1(\text{i},\text{j}=\text{1,2},3,\cdots ,\text{n})$$

where, P_ij denotes the state transition matrix, n denotes the land use type, and S_(t+1) and S_t denote the land use state at the time t + 1 and t, respectively.

3.2.4 Ecological service value

Based on the findings of Cao et al.[32], we extracted Hefei’s ecological service value data. Due to the complexity of the calculation process of ecological service value, refer to the original article for its calculation equation.

4.1 Model accuracy

Based on Hefei’s land use data in 2010, we simulated its land use in 2020 and compared the simulation results with the actual ones in 2020. In this study, the Kappa coefficient and FOM coefficient were both used to verify the accuracy of the simulation results. The results show that the Kappa coefficient is 0.93 (the closer to 1 its value, the higher the accuracy of simulation; a value greater than 0.80 indicates that the model accuracy is high statistically), and that the FOM value is 0.54 (the value greater than 0.2 indicates high accuracy)[33]. Therefore, the PLUS model is reliable, and suitable to simulate Hefei’s future land use change.

4.2 Characteristic analysis of predicted land use change

Using the PLUS model, we quantitatively predicted Hefei’s different land use in 2030, 2040, 2050, and 2060 in the scenario of economic development, and spatially visualised the prediction results using ArcGIS10.8 (Fig. 1). With the ongoing integration of the Yangtze River Delta and implementation of Anhui’s strong provincial capital strategy, Hefei is experiencing rapid economic growth and accelerated urbanisation. The rapid development of its urban economy has dramatically stimulated the demand for construction land, resulting in the continuous expansion of its construction land. Quantitatively, the dominant type of land use in the next 40 years will still be arable land, followed by construction land, water, forestland, grassland, and other types of land.

In Anhui Province, grain supply has long been tight, and economic development has increased the demand for construction land, resulting in a quantitative reduction in arable land. Therefore, Anhui is facing an obvious contradiction between economic development and grain security. Land is an important factor for guaranteeing economic development and grain supply. From the perspective of land system change, the above contradiction is essentially a spatial conflict between construction land and arable land. In 2020, Hefei’s land use was dominated by arable land overall but by construction land in the core economic development areas. Northern Hefei is mainly covered by arable land, construction land, and a small water area, whereas southern and eastern Hefei is mainly covered by water area, forestland, and grassland. The new construction land in 2030, 2040, 2050, and 2060 is formed due to the outward expansion of construction land present in 2020 and construction land in northern Hefei continues to increase. This pattern is in line with the main directions of Hefei’s ongoing urban expansion. The expansion of Hefei’s construction land mainly follows an extensive growth pattern. In terms of spatial structure, the overall pattern of Hefei’s urban expansion is still centred on the original urban areas. Driven by economic development factors, the ongoing urban expansion trend is continued; hence, non-construction land in peripheral areas is constantly and rapidly occupied by the extensive urban expansion.

4.3 State transition analysis of predicted land use change

To visualise the transformation of different land types in different cross-section years, the land use layers between adjacent cross-section years were superimposed to determine the transformation of different land types in each cross-section year, and then the results were visualised using ArcGIS 10.8 and R language. As shown in Fig. 3, the main land use change in Hefei from 2020 to 2060 is the transformation from non-construction land to construction land. Arable land transformed into construction land overwhelmingly accounts for the largest proportion. Specifically, the arable land area decreases from 759,668.04 ha in 2020 to 620,871.84 ha in 2060, a decrease of 18.27%; the construction land area increases from 194,392.71 ha in 2020 to 336,840.93 ha in 2060, an increase of 73.28%. Meanwhile, a certain quantity of construction land is transformed into non-construction land, mainly into types of land with certain ecological service value (e.g., water, forestland, and grassland). Evidently, to address the negative impacts (e.g., pollution) of economic development, the government of China has gradually adopted the principle of “ecological priority and green first” instead of “economic development first and then pollution harnessing”.

From 2020 to 2060, the new construction land is mainly contiguously distributed in Shushan District, Baohe District, Yaohai District, and Luyang District. The urban development of the former Chaohu City is restricted by the surrounding ecological land, so its construction land is expanded to surrounding areas. As the two wings of Hefei City, Feixi County and Feidong County undertake some ecological service functions; its construction land is distributed in the form of dotted grids and is rarely derived from forestland or grassland. Compared with the other areas of Hefei, Lujiang County has a higher DEM-derived elevation. The development of construction land is most significantly affected by DEM-derived elevation and soil type, and forestland, grassland, shrub land, and bare land are significantly affected by DEM-derived elevation and slope. Due to the combined effect and DEM-derived elevation and Ecological Protection Red Line of Anhui Province, Lujiang County’s grassland, shrub land, and forestland are not remarkably impacted. Therefore, some forestland and grassland in their edge areas are transformed into construction land in Lujiang County. According to the 14th Five-year Plan of Hefei City on Ecological Environmental Protection, Hefei will systematically restore and protect the natural environment of the Chaohu Lake basin during the 14th Five-year period (2021−2025), specifically achieving the following objectives by 2020: 1) the ecological authenticity and integrity of the Chaohu Lake basin are significantly restored; 2) construction land around Chaohu Lake shows dotted growth; 3) the water area of Chaohu Lake basically remains unchanged; 4) very little forestland and grassland are transformed into construction land. Evidently, human intervention can dramatically affect land use change. Hefei’s land use change from 2020 to 2060 shows that DEM-derived elevation and urban planning can influence the process of land system change. Land is among the essential natural elements for human survival, and the utilisable types of land are scarce and limited. Therefore, the determination of UDBs under China's territorial spatial planning can provide a spatial guarantee for smart growth in Hefei's economic development, thereby promoting the reasonable, scientific and high-quality development of Hefei’s urban economy.

4.4 Determination of UDBs

4.4.1 Methods and criteria for the determination of UDBs

In China, UDBs are mainly determined using three methods: the positive method, reverse method, and integrated method. Focusing on urban development, the positive method is to determine UDBs by using a growth model or based on constraints and current construction land status combined with the needs of urban development. This method is suitable for cities with fewer resource constraints and large development space. The reverse method emphasises the principle of “bottom line first and then blueprint”, namely, excluding the areas unsuitable for urban development and construction first and then using the remaining areas to determine UDBs. This method is mainly suitable for cities with obvious resource constraints and limited development space. As the combination of the above two methods, the integrated method is suitable for cities that have developed to a certain stage and attach equal importance to the development of incremental space and stock space. In this study, we must ensure the availability, scientificity, and systematicness of related data and consider the fact that northern Hefei has a large development space but other spaces are obviously constrained by resource factors (e.g., natural conditions). Therefore, we adopted the reverse method to superimpose Hefei’s predicted construction land with ecological service value, compared the results with its current urban planning, and dynamically adjusted Hefei’s UDBs. This provides a new approach for determining UDBs in territorial spatial planning.

Hefei’s predicted urban construction land reflects its future land demand for urban development, and the current resource constraint is mainly manifested as the ecological service value of idle land from the perspective of ecological environment. Using the method specified by Cao et al. [32], we evaluated the ecological service value of Hefei. The accuracy of the predicted land use data is 30 × 30 m. To ensure the consistency of data accuracy, we re-sampled the raster data of Hefei’s ecological service value, performed accuracy matching between the data, and used the natural discontinuous point method to set four levels for ecological service value (low, fairly low, medium, fairly high, and high levels). Additionally, the predicted construction land from 2020 to 2060 was superimposed with ecological service value. Figure 5 shows that Hefei’s urban construction land is basically distributed in areas with a low level of ecological service value. Evidently, Hefei’s current urban development pattern follows China's development concept of "ecological priority and green first", proving the correctness of its current urban development strategy. Therefore, determining Hefei’s UDBs based on the current research data is operable, and such UDBs have a binding force on Hefei’s future urban development, thereby preventing its unlimited urban sprawl, optimising its urban spatial structure, beautifying its spatial morphology, and improving its overall spatial efficiency.

4.4.2 UDB pattern

The UDB pattern must be determined based on the ongoing urban development scale, basic resource conditions, and urban development strategy. Based on the requirements for determining UDBs under the Guidelines for Preparing City-level Territorial Spatial Master Planning (Trial), we consider the development of future urban construction land, to provide spatial guarantee for urban development. To ensure the scientificity, operability and effectiveness of the determination of Hefei’s UDBs, we developed the following principles for the determination of Hefei’s UDBs:

1) Respect the reality and keep the baseline

Land use regulation is a key tool for macro regulation of urban development. China's urban planning system and land reserves are powerful tools for the government to regulate land, and reasonable government intervention and regulation is beneficial to the scale growth and transformational development of cities[34]. The land within the determined UDBs should include contiguous urban construction land, and approved and allocated urban construction land, and must be in line with the approved urban planning (including overall urban planning, overall land use planning, and detailed control planning). The reality must be respected. Hefei’s urban development has both advantages and disadvantages, so it is necessary to determine its UDBs by taking appropriate measures at an appropriate time, keeping the baseline for its urban spatial development.

2) Optimise the urban morphology and ensure reasonableness and scientificity

The determined UDBs should be as complete as possible. Additionally, ecological and landscape corridors between city groups should be adequately reserved to prevent disorderly urban expansion, and a certain amount of flexible space should be reserved for subsequent urban construction and development. Moreover, it is not advisable to overemphasise the beautifulness of the determined UDBs but to determine UDBs scientifically and reasonably. It is necessary to ensure the feasibility and systematicness of urban development and project implementation within the determined UDBs. This requires paying attention to the correlation between urban compactness and economic efficiency in territorial spatial planning, taking into account the economic development of multiple sectors, coordinating the subjective demands of various interests, and giving benefits to the production, living and recreational needs of residents[35].

3) Strategic guidance, and planning first

Hefei’s UDB pattern should be in line with the urban development strategy determined by its overall territorial spatial planning, manifest Hefei’s urban development directions (eastward advancement and southward expansion), and prioritise the construction land for provincial-level and city-level major strategic areas (e.g., the cradle and industrial clustering areas of "Quantum Centre", “USTC (University of Science and Technology of China) Silicon Valley” around the USTC campus, Binhu Financial Area, fund clustering area of Hefei New & Hi-tech Industrial Park, and Binhu International Science Communication Centre). Additionally, Hefei’s overall territorial spatial planning (2021 to 2035) stipulates its new urban development pattern. In this pattern, based on the principles of intensive and efficient production space, liveable living space, and beautiful ecological space, Hefei will develop an overall territorial spatial pattern characterised by “guidance by centres, parallel development at two wings, multi-polar support, splendid Linghu, and synergy of six belts”. Provincial-level and city-level major strategies can guide territorial spatial development. At the same time, in the preparation and implementation of territorial spatial planning, there is a need to improve the professionalism and technical ability to predict future land use changes by considering the urban compactness paradigm, incorporating planning concepts that reflect inclusive and contextualized participatory development processes. This improves the transparency and comprehensibility of the adaptation between project results and stakeholder interests, and facilitates the supplementation of public participation in planning to promote broad and inclusive territorial spatial planning[36–37]. Therefore, UDBs should be manifested in Hefei’s territorial spatial planning to provide support for Hefei’s strategic development.

4) Improve efficiency and ensure quality

Hefei’s UDBs should be concentrated along current urban construction land, deployed in areas with good locational and traffic conditions, and embrace the existing low-efficiency and idle land as a matter of priority. In 2010, Hefei incorporated Chaohu City into its administrative jurisdiction. Urban development will never be achieved without sufficient water supply. Hence, Hefei’s UDBs should be determined on the principle of "determining urban areas, locations, population, and production by water supply". In other words, the scale and layout of population, industries, and land use should be reasonably distributed based on water resource constraints (including the lower and upper limits of water supply). Under the constraints of the water environment, an overly compact urban form, while beneficial to physical health and social relationships and synergistic with the social well-being of urban residents, is to some extent detrimental to the well-being of urban residents[38]. Therefore, while strictly adhering to the bottom line, the delineation of urban development boundaries needs to grasp the appropriate development boundary form and provide a more relaxed environment and spatial constraints for the development of urban form. The determination of Hefei’s UDBs is intended to improve the efficiency of urban land use and development, develop a high-quality spatial growth pattern, and achieve the ultimate goal of smart growth.

In the context of China's territorial spatial planning, the prediction of future land use patterns of cities can provide data support for the formulation and adjustment of urban development planning, and can be useful for urban development in other regions or countries in the world, thus helping to alleviate the contradiction between urban development planning and actual urban development and construction around the world and promoting the effective use of land resources worldwide. Using a land use prediction model, we predicted and analysed the land system evolution in Hefei (a core city with great potential for development in the Yangtze River Delta) from 2020 to 2060, and used the reverse method to determine Hefei’s UDBs based on ecological service value. The following conclusions are drawn:

First, the PLUS model is suitable to accurately simulate Hefei’s land use change. It is reasonable to simulate Hefei’s future land use pattern in the scenario of economic development scenario using a PLUS model (This conclusion needs to be analysed in conjunction with section 4.1 “Analysis of model accuracy”).

Second, Hefei’s main land use change from 2020 to 2060 is the transformation from non-construction land to construction land. The arable land transformed into construction land overwhelmingly accounts for the largest proportion (18.27%), and the newly-increased construction land accounts for 73.28%. Ecological land (e.g., water, forestland, and grassland) basically remains unchanged. Evidently, the government of China attaches great importance to and firmly carries out the development idea of “priority to ecology, and green first”.

Third, Hefei’s land use change from 2020 to 2060 spatially follows a typical extensive growth pattern, but the basic land use pattern is influenced by the DEM-derived elevation and man-made urban development planning, producing a significant implicit impact on the future urban land system evolution. Land is among the essential natural elements for human survival, and the utilisable types of land are scarce and limited. Therefore, the determination of UDBs under China's territorial spatial planning can provide a spatial guarantee for smart growth in Hefei's economic development.

Fourth, Hefei’s urban development is obviously constrained by resource factors (e.g., natural conditions). Hence, we used the reverse method to superimpose Hefei’s predicted construction land with ecological service value, compared the results with Hefei’s current urban development planning, and dynamically determining Hefei’s UDBs. By superimposing the predicted construction land with the low ecological service value, we analysed and verified the correctness and scientificity of Hefei’s current urban development strategy. The detailed criteria for the determination of UDBs provide a new approach for the determination of UDBs in territorial spatial planning.

5.1 Discussion

In this study, we predicted Hefei’s land use change process in the scenario of economic development, mainly because the patch change mechanism for multi-type land use in the PLUS model can simulate the patch-level evolution of diverse land use types, improving the accuracy of land use simulation and prediction. The PLUS model can predict urban land use change under diverse scenarios (e.g., free development and ecological protection).

This study focused on Hefei’s urban development in the scenario of economic development, but ignored the comprehensiveness and systematicness of land system development, and failed to make a horizontal comparison of Hefei’s land use change under different scenarios, making it difficult to provide adequate support for scientific and reasonable determination of "three zones and three lines" in territorial spatial planning.

The farmland and ecological land around urban core areas can serve as isolation belts between city groups and perform agricultural, ecological and landscaping functions. With rapid development of urban economy, there is an increasing probability that the arable land and forestland in the periphery of central urban areas are transformed into construction land, posing a certain threat to the grain security and ecological security of cities. Hence, this problem should be regulated and addressed properly. In this study, the newly-increased construction land is mainly sourced from arable land, but very little ecological land is transformed into construction. Evidently, ecological security is given enough attention, whereas the grain security pattern is severely impacted by economic development. Hence, Hefei needs to implement the national arable land protection system more effectively, improve arable land quality and grain yields, and develop an internal cycle for Hefei’s grain supply and demand.

This study has several limitations. In the simulation process, this study did not consider Hefei’s land use change in other scenarios, nor made a horizontal comparison of land use change between different scenarios. Owing to the unavailability of data on Hefei’s “three zones and three lines”, the UDBs of Hefei were not determined on a subdivision basis. Moreover, the basic farmland protection areas and ecologically-vulnerable areas were not identified to impose constraints on the spatial layout simulation of UDBs. This limitation needs to be further overcome in future studies. In future studies, socioeconomic variables (e.g., population and GDP) and ecological variables (e.g., ecological service value) predicted by other models can be introduced to the PLUS model, to conduct more comprehensive multi-factor simulation.

Author Contributions: Sheng Zhang: Conceptualization, Methodology, Formal analysis, Main Data Collection, Writing – original draft, Funding acquisition; Jie Tao: Conceptualization, Methodology, Formal analysis, Writing – original draft, Writing – review & editing, Supervision.All authors have read and agreed to the published version of the manuscript.

Funding: This research was funded by Key Projects of Hefei: Hefei North City Master Plan and Land Space Utilization Plan (2007 Edition)and Key Project of Yangtze River Delta Integration and Key Project of Anhui Province: Functional Zoning and Land Use Planning of Hefei Luogang Central Park (2022 Edition).

Acknowledgments: The authors sincerely appreciate the anonymous reviewer and editors’ valuable comments and suggestions to improve the manuscript.

Conflicts of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations

AUTHOR BIOGRAPHIES

Sheng Zhang is a doctor from Hefei University of Technology, His research mainly focuses on land use change and simulation of urban development boundaries.

Address: School of Management, Hefei University of Technology, Heifei, 230009, China

e-mail: [email protected]

Jie Tao(* )is a master from Anhui Normal University, His research mainly focuses on land use change, sustainable development of ecological economy.

Address: School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China

e-mail: [email protected]

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Hefei’s Land Use Simulation and UDB Determination in Economic Development Scenario

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Abstract

Figures

1. Introduction

2. Literature Review

2.1 Definition of UDBs

2.2 Research methodology

2.3 UDB studies

3. Materials and Methods

3.1 Data sources

3.2 Model method

3.2.1 PLUS Model

3.2.2 Accuracy test

3.2.3 Land use change

3.2.4 Ecological service value

4. Results and Discussion

4.1 Model accuracy

4.2 Characteristic analysis of predicted land use change

4.3 State transition analysis of predicted land use change

4.4 Determination of UDBs

4.4.1 Methods and criteria for the determination of UDBs

4.4.2 UDB pattern

1) Respect the reality and keep the baseline

2) Optimise the urban morphology and ensure reasonableness and scientificity

3) Strategic guidance, and planning first

4) Improve efficiency and ensure quality

5. Conclusions

5.1 Discussion

Declarations

References

Additional Declarations

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