Land Spatial Development Based on Carrying Capacity, Land Development Potential, and Efﬁciency of Urban Agglomerations in China

: The Chinese government is undergoing a major reform. The current core task of new Ministry of Natural Resources (MNR) is to establish a national territorial spatial planning system (NTSPS). Urban agglomeration has become a main body in NTSPS. China’s new urbanization strategy identiﬁed 19 key development areas of urban agglomerations (UA), but the land development path is not clear. Due to the lack of research on the land development intensity evaluation (LDIE) of urban agglomerations, this study applied a GIS-based, multi-criteria method for LDIE to the Shandong Peninsular urban agglomeration (SPUA). Evaluation indices were determined for three factors (development intensity, supporting capacity, and utilization efﬁciency) that comprise the discriminant model of the three-dimensional matrix method, which was used to establish the method for this topic and demonstrate the accuracy of the land spatial development intensity. This empirical study on the SPUA indicated that, overall, the average indices for development intensity, supporting capacity, and utilization efﬁciency in the study area are 0.40, 0.34, and 0.55, respectively. Using the three-dimensional matrix discrimination model, three zones of development intensity were identiﬁed: key, stable, and restricted development zones. The threshold values for construction land growth in the eight cities of the SPUA were obtained. The ﬁndings provide a theoretical reference and guide for the practical application of LDIE as well as a scientiﬁc basis for sustainable land development and utilization. This paper proposes development goals and paths based on the resource and environmental carrying capacity, land development potential, and efﬁciency of urban agglomeration. This method helps to break the balance of various spatial planning and can effectively link provincial and prefecture-level land space planning, realizing urban group space control from single-objective, rigid, static, to multi-objective, ﬂexible, and dynamic development. We hope that this study will provide a reference for China’s urban agglomeration strategy and ideas for urban agglomeration policy makers in developing countries.


Introduction
As more and more rural people choose to enter the city, many cities around the world are expanding rapidly. 2018 Revision of World Urbanization Prospects of United Nations [1] shows that the urban area has gathered more than half of the world's population and is also the core area for future population growth. It is estimated that by 2050, about 70% of the world's population will live in cities. Since the reform and opening up, China's urbanization process has been accelerating, and the urbanization rate has increased from 17.90% in 1978 to 58.52% in 2017 [2]. The urban agglomeration is the product of the industrialization and urbanization transformation to the advanced stage [3]. Since the beginning of the 21st century, the UA has become a new regional unit for countries around the world to participate in global competition and international division of labor, and also the main body of China's new urbanization process. China's rapid urbanization and industrialization have led to severe pressures on resources and ecological environment, resulting in urban agglomeration diseases such as environmental pollution, traffic congestion, and degraded energy shortages in ecosystems.
The land development intensity evaluation (LDIE) is conducive to optimizing land development and utilization. This complicated and systematic method has attracted attention from many scholars. Existing research is mainly focused on the current development scale, the identification of factors driving development [16], temporal-spatial differentiation and patterns of urban land expansion [17][18][19][20], the productivity and efficiency of construction land use [21,22], and the evaluation of development potential [23]. Three above conditions (i.e., scale, efficiency, and potential) should be simultaneously taken into consideration to achieve the goal of sustainable development. Development scale is described as the extent to which urban agglomeration land space is exploited, which means the mass of land development. Utilization efficiency reflects the efficiency of the developed urban agglomeration space, and potential reflects the area that could be further used for construction purposes. Although these three elements should be regarded as a unified whole, little research has considered all three elements. In a study on space exploitation and the division of a drainage basin, Wang (2012) established a three-dimensional distinguishing matrix model deals with the relationship of the spatial development constraint indexes, space development intensity indexes, and space development guidance indexes [24]. This method gives us a good idea, and we attempt to extend its research from the basin to the urban agglomeration in this paper.
The evaluation of technology and methodology is the core of research in this area. In 1969, the American landscape architect McHarg proposed an evaluation method for the ecological suitability of land use from the perspective of superposition [25]. This evaluation method has become the basis for initial studies on modern land use and development intensity. In the past 40 years, LDIE has gradually become a significant method in urban and regional planning along with ecological and environmental planning. The main methods used can be categorized into two types [26][27][28]: (1) the element superposition method, which is rooted in the hand-drawn overlay techniques created by McHarg, Steinitz, and others [29]; and (2) the multi-criteria evaluation method based on GIS (MCE-GIS), which is applied in this study [30][31][32]. MCE-GIS includes methods such as interval multi-objective linear programming model [17], technique for order preference by similarity to an ideal solution (TOPSIS) [33], concordance analysis [34], analytic hierarchy process [35], fuzzy evaluation method [36], and a new identification method of priority landscapes and spatial conflicts with new investment area [37]. The second method is artificial intelligence, for which the main applications include fuzzy mathematics methods [38][39][40], artificial neural networks [41], matter-element models [42], cellular automata [43], and genetic algorithms [44]. In addition to the two types of methods mentioned above, an ecological niche-based method for assessing the suitability of land [45] along with a comprehensive evaluation of land based on public participation [46] (Shearera & Xiang, 2003) have appeared in recent years. Although the assignment of weights to index elements involves uncertainty [26], weighting methods are still the most widely used within LDIE research due to their simplicity and compatibility with GIS [47]. Landscape capacity assessment method become more and more popular in land spatial planning intensity. The base for assessing the possibility of new investment areas is an evaluation of landscape features which influence on possibility to hide new building area in landscape. This method is useful for planning development of suburban areas, especially those parts with high-value landscape [48]. However, based on the relationships among mass, efficiency, and potential, regulating and controlling the path and object of LDIE is regarded as a three-dimensional supporting relationship, it cannot be simply expressed by a weighted stack. So, we learn from the three-dimensional distinguishing matrix model to deal with the relationship of scale, efficiency, and potential in LDIE.
Although LDIE has been frequently used in research and in practice, it has rarely been applied to urban agglomerations. The application of LDIE to urban agglomerations has important theoretical significance related to China's new urbanization development strategy, the sustainable development of urban agglomerations, and the development and utilization patterns of land in China. Using existing research findings, this study applied LDIE and MCE-GIS to study SPUA and obtain the zoning categories of land spatial development intensity. The purpose of this study was to provide a new method for LDIE in China's urban agglomerations and provide a basis for decision making regarding land spatial development.

Study Area and Data Sources
SPUA is located in the coastal area of eastern China, which contains eight cities (Jinan, Qingdao, Yantai, Zibo, Weihai, Weifang, Dongying, and Rizhao; Figure 1). The eastern and southern part of SPUA is a hilly landform, and the Yellow River delta plain in the middle. The rivers are densely, and the Yellow River, the second largest river in China, passes through the region and flows into the Bohai Sea from southwest to northeast. SPUA close to the Bohai and Huanghai seas, and has an area of 7.47 × 10 4 km 2 . To the south of the peninsula is the Yangtze River Delta UA, and to the north are the Beijing-Tianjin-Hebei UA and Liaodong Peninsula UA. The Korean Peninsula and Japan lie to the east of SPUA. As China's frontier area involved in regional cooperation in Northeast Asia, the SPUA has a relatively high level of economic development based on industrial development. In 2017, the study area had a total population of 41 million. Meanwhile, according to the spatial distribution of economic activity, the research area has formed three centers of economic growth: Qingdao, Jinan-Zibo, and Yantai. SPUA is the important urban agglomerations in National 13th Five-Year Plan. Thus, strong emphasis should be placed on its optimization and improvement. Faced with typical problems related to LDIE, including relatively high intensity and low efficiency, the SPUA is a representative study area for urban agglomerations in China. The research data include physical geography data and socioeconomic data. The data sources show in Table 1. The data were standardized using the range-standardized method, and the weights were determined using the Delphi method in the ArcGIS 10.2 platform. The Delphi method is a structured communication technique, originally developed as a systematic, interactive forecasting method which relies on a panel of experts [49]. Delphi is based on the principle that forecasts (or decisions) from a structured group of individuals are more accurate than those from unstructured groups. The protected lands and landscapes of SPUA include the nature conservation area and the basic farmland area, which were shown in the map of Main Functional Area Planning of Shandong Province. When evaluating the natural potential for land development, the influence of elevation could be ignored because the majority of the SPUA is occupied by plains.

Methods
In February 2017, the State Council issued the "National Land Planning Outline (2016-2030)", stating that many serious problems exist in the process of urbanization, including inconsistence between economy; population and resource distributions; structural contradictions in urban, agricultural, and ecological spaces; mismatch between land development intensities and resource and environmental carrying capacity; and low-quality urbanization. The planning requires significant improvement of land development quality and efficiency. By 2030, the land development rate should not exceed 4.62%. Thus, in this study, the index system for assessing the quality of land development is constructed, taking into account the requirements of the national land planning outline. Only when the comprehensive model of urban agglomeration LDIE is scientific, complete, and systematic can it accurately determine the zoning of land development and utilization, which could establish a foundation to decide upon a pattern of land utilization and development ( Figure 2).

Evaluation System for Land Development Intensity in the SPUA
This study built a concrete measurement index based on the evaluation extent index, development supporting ability index, and development and utilization efficiency index of land in the SPUA. A four-grade (target, standard, criterion, and index layers) evaluation system was thus developed ( Table 2). The LDI of land space could be comprehensively evaluated based on the percentage of construction land area in each administrative unit out of the total area of the units (%) and the average rate of increase in the percentage of construction land. Construction land consists of cities and towns, independent mines, rural residential area, transportation land, water conservation facilities (excluding reservoirs), and other construction space. The formula for LDI is LDI reflects the land development extent, where x 1 is the proportion of construction land out of the total administrative area with weight w 1 , and x 2 is the annual rate of increase in the proportion of construction land with weight w 2 . The weight is scored by a number of experts.

Method for Evaluating Land Use Efficiency in the SPUA
Land use efficiency (LUE) was determined based on the strength and output of construction land bearing strength, which represents the amount of development and utilization activities, directly determines the efficiency of urban development and is usually expressed by a single or composite index (e.g., population and economic input). In this study, we selected the permanent resident population and fixed investment in construction land per km 2 to illustrate bearing strength and the GDP of construction land per unit (100 million) to show the output efficiency of land development. These two elements comprehensively represent the urban development and utilization efficiency. The formula for LUE is LUE reflects the land use efficiency, where x 1 is the standardized index of permanent resident population density for construction land with weight w 1 ; x 2 is the standardized index of fixed-investment density for construction land with weight w 2 ; x 3 is the standardized index of GDP for construction land; W 12 is the weight of the bearing strength index; and W 3 is the weight of the output efficiency index. The weight is scored by a number of experts.

Method for Evaluating Land Development Supporting Ability in the SPUA
Land development support (LDS) is the basis for the development of land in urban agglomerations and includes natural potential, locational condition, and economic development. A greater supporting ability of land development corresponds to a larger bearing development intensity and persistence.
Natural potential comprehensively evaluates the effects that restrictive factors such as geologic disasters; slope, water, and soil losses; and the preservation of water resources and basic farmland have on the development and construction of lands. The spatial scale of lands adopted in this study was determined by the negative planning concept as where x is the suitability value of the spatial index, which represents the natural potential, and NP is the natural potential index. The lower the grade of the evaluation unit, the less appropriate it is for development and construction, and thus the smaller the natural potential. To maximize ecological benefit, the natural potential grade in the formula is calculated by the minimum-value method in GIS layers. Five constraint forces (geologic disasters; slope, water, and soil losses; and the preservation of water resources and basic farmland) were graded according to their significance in land development. The index weights were set by the Delphi method as follows: unrestricted area, −1; low restricted area, −3; medium restricted area, −5; relatively high restricted area, −7; and restricted area, −9. These weights further confirm the restricted areas (Ar) in spatial development, including those areas restricted by geologic conditions (Agr), slope and topographic conditions (Asr), water resources (Awr), water and soil loss (Apr), and basic farmland (Acr) Ar = Agr + Asr + Awr + Apr + Acr In Equation (4), Agr includes disaster areas related to geologic processes such as avalanches, landslides, debris flows, surface collapses, ground fractures, and surface subsidence. Based on the Geological Disaster Prevention and Control Program, the urban agglomeration in this study is divided into four areas, the key prevention area, second key prevention area, medium prevention area, and non-disaster area, with respective weights of 9, 5, 1, and 0. Asr belongs to the slope-restricted area. According to the urban land site engineering specification (CJJ8-99), the maximum slope should be no more than 25 • . Thus, areas with slopes exceeding 25 • are defined as non-construction areas and are weighted with 9, while areas with slopes less than 25 • defined as construction areas and weighted with 0. Awr is the water resources-restricted area. Based on the zoning of groundwater overexploitation (2006.12) as well as the extent of environmental deterioration of the overdraft division of shallow underground, Awr is categorized into three types, severe overdraft area, medium overdraft area, and dynamic monitoring area, with respective weights of 9, 5, and 3. Apr is the area restricted by water and soil loss. In accordance with the map of the key prevention area of water and soil loss in Shandong Province and the classification and gradation standards for soil erosion in China, the SPUA is divided into the extreme loss area, strong loss area, moderate loss area, slight loss area, and tiny loss area, with respective weights of 9, 7, 5, 3, and 1. Acr is the basic farmland preservation area and has a weight of 9 due to a policy that prohibits its exploitation.
Using the overlay analysis of GIS, this study overlayed the above types of layers based on the maximum method. Finally, Ar is divided into five types of restricted areas: Ar 1 , Ar 3 , Ar 5 , Ar 7 , and Ar 9 .
Construction potential varies from restricted area to area. A non-restricted area is suitable for construction, while no construction is allowed in a restricted area. After engineering and prevention measures in low-, moderate-, and high-restricted areas and non-restricted areas, these areas are multi-functional. For example, a low-restricted area could be developed with public facilities, a moderate-restricted area could be used as residential land, and a high-restricted area could be regarded as an ecological landscape. Therefore, a correlational study (Wang et al., 2015) set the utilization potential indices k for different types of areas. Ac, which represents land potential, is obtained by summing all land types as Ac = Ar 1 k 1 + Ar 3 k 3 + Ar 5 k 5 + Ar 7 k 7 + Ar 9 k 9 − Ae where Ac is the potential of construction land, Ae is the current construction land area, and k are the potential indices of land utilization for different types of restricted areas (k 1 = 1, k 3 = 0.8, k 5 = 0.6, k 7 = 0.4 and k 9 = 0), which means that land in non-restricted areas can be fully used. The utilization rates of available lands are 0.8 in low-restricted areas, 0.6 in moderate-restricted areas, 0.4 in high-restricted areas, and 0 in restricted areas.
The location condition is based on two factors, the distance to the city center and road density, and is given by summing the linear weights of these two factors. The urban development index (UD) is represented by GDP per capita. Hence, the development and supporting ability LDS is calculated as where W 1 is the weight of the natural potential index, W 2 is the weight of the location condition index, and W 4 is the weight of the UD. The weight of the indexes come from the Delphi method.

Zoning Method of Healthy Development in the SPUA
The three-dimensional discrimination method is widely applied in land development research. In this study, development and supporting ability was plotted on the x-axis, utilization efficiency was plotted on the y-axis, and development intensity was plotted on the z-axis. This results in a three-dimensional coordinate system for the evaluation of LDI. Three points at the same distance from the origin are selected to represent the levels of the three dimensions (high, moderate, and low). Vertical lines are created from these points to the three axes, forming a 3 × 3 × 3 isometric chart and 27 matrix units, among which each unit (x, y, z) stands for the combination of development intensity, guidance, and constraint ( Figure 3). According to the natural potential law in land development, when x = 1, the development and supporting ability is relatively low; thus, development is prohibited in this area. In other words, such an area is defined as a non-development area. When x = y = z = 5, the area is optimum for development and is called a priority development area. L is regarded as the development suitability degree and is given by where L is the development suitability degree index, x is the land development supporting capacity index, y is the land use efficiency index, and z is the land development. Geometric manipulation gives the Euclidean distance between the area A(x, y, z) and the optimum development area (3, 3, 3). The purpose illustrates the extent to which the area is suitable for development. Calculating the L values of all areas while temporarily ignoring vector direction, ordering the values, and dividing them into three groups, we divided the study area into three types of areas (key, stable, and restricted development area) according to the development intensity and propose a concrete project ( Table 3). The natural potential and environmental carrying capacity are the basic conditions for land development in an urban agglomeration. For this reason, in this paper, we define the areas with low development and supporting abilities as restricted development areas.

Functional Division Matrix Units
Key development area

Land Development Extent
In 2014, the area of urban construction land in the SPUA was approximately 14,255.08 km 2 , accounting for 19.08% of the urban agglomeration. From 2001 to 2017, the annual average rate of increase in the area of construction land was 3.41%. The current development extent index B1 is obtained by weighting and combining the proportion index and the annual average rate of increase in construction land area. In 2017, B1 of the study area was 0.4. From the perspective of space, the area along the Jiaoji Railway connecting Jinan and Qingdao as well as downtown Weifang showed the highest levels of development, followed by the Jiaozhou and Qingdao downtown areas. However, the extents of development in the south-central and northern coastal areas were relatively low.

Land Use Efficiency
The land use efficiency (LUE) index is obtained by weighting and combining the bearing strength index and output efficiency index. In 2017, the average LUE index was 0.55. From the perspective of location, the development and supporting abilities were relatively high in the southern and eastern parts of the study area, which is primarily attributed to the high LUE indices of the Qingdao-Rizhao coastal area, Jinan-Zibo connecting area, and Yantai-Weihai coastal area. The downtown areas of Qingdao, Jinan, and Zibo along the Jiaoji Railway had the highest LUE indices (>0.9). Meanwhile, the LUE index of downtown Dongying in the northern coastal part of the study area did not exceed 0.21.

Land Development Supporting Ability
The land development and supporting ability index (B2) of the SPUA is obtained by weighting and combining the natural potential index, locational conditions index, and UD of national land development. In 2017, the average B2 of national land was 0.34. In terms of location, the northern and eastern parts of the study area had relatively high values of B2, with that of Kenli County in the Yellow River Delta being the highest (0.60) followed by the downtown areas of Qingdao and Dongying (0.59 and 0.56, respectively). The indices of the south-central and west-central parts were relatively low, with that of downtown Weifang being the lowest (0.11). The B2 values of Changle, Juxian, and Shanghe counties were no more than 0.2.

Zoning Based on LDIE
According to the development extent index, development and supporting ability index, and development and utilization efficiency index, this study also used a three-dimensional matrix model ( Figure 3) and matrix table (Table 3) of LDIE to evaluate zoning in the SPUA. The land of Shandong Peninsula was partitioned into three types of areas: key development areas, stable development areas, and restricted development areas (Table 4 and Figure 4). Table 4. Zoning of SPUA based on land development intensity evaluation

LDIE Partition Name of Area
Based on the partitions, we compared the indices of development extent, development efficiency, and supporting ability of SPUA with those of other urban agglomerations. The maximum and minimum values were used to measure the threshold values of land development intensity for areas with different functions in the study area; thus, the results can be used to develop a regulation and control scheme.
In 2017, the average proportion of Shandong Province's administrative district occupied by construction land was approximately 19%. The maximum current development extent is 25%. Thus, the national space is classified according to the range of 19-25%. Taking the increase speed of different types area and proportion of construction land into consideration, the higher the proportion of construction land, the lower the average annual rate of increase (AARI) construction land in future. The AARI in the proportion of construction land in the SPUA was 3.4% from 2000 to 2017, while the supply increase rate of construction land in China from 2006 to 2017 was 4.30%. Since 2000, the AARI in construction land in the Pearl River Delta was 7.57%, while those for the Yangtze River Delta and Beijing-Tianjin-Hebei region were 6.25% and 5.82%, respectively. The maximum AARI in construction land in the SPUA could be based on the average value of 6.54%, ranking it second out of the three urban agglomerations in China. Therefore, the threshold values for the rate of increase in construction land in the study area were defined as 3.40% (key development area), 4.30% (stable development area), and 6.54% (restricted development area) ( Table 5). Based on the threshold values given in Table 5, the area types of the eight prefecture-level cities in the SPUA are provided in Table 6. These values provide a scientific basis for accurately regulating and controlling the development intensity. Taking Jinan City as an example, the key development area with construction land is no more than 19% of the total area. Meanwhile, as can be seen in Table 6, if the annual average rate of increase is less than 6.54%, the future increase in the area of construction land will be no more than 57.06 km 2 .

Conclusions and Discussion
As stated by Stieglitz, urbanization in China and the development of new technology in the United States will be the two engines driving human development in the 21st century [50]. For more than 30 years, urbanization in China has promoted the rapid development of the economy and society in China. Five major UAs (the Yangtze River Delta, Pearl River Delta, Beijing-Tianjin-Hebei, Chengdu-Chongqing, and Middle Reach of the Yangtze River UA) account for 9.06% of China's area, 45% of the urban population, 50% of its GDP, 60% of fixed-asset investment, and 65% of the foreign direct investment in China. Therefore, urban agglomerations represent the core of China's strategy for economic development. Meanwhile, China must deal with the pressures of a growing population, strain on resources, and environmental degradation, which are also faced by other developing counties. It is possible to formulate a scientific plan for the sustainable development of urban agglomerations if the environmental carrying capacity, the status quo, and the future development potential of urban agglomeration areas are considered. At the beginning of 2017, the State Council issued the "Several Opinions on Delineating and Strictly Protecting the Red Line of Ecological Protection" to upgrade ecological security to the institutional and legal levels. One of the key tasks of the newly MNR is to improve the quality of land use in urban agglomerations, that is, to optimize the land use structure and improve land use efficiency of urban agglomerations without reducing ecological security land.
The traditional LDIE technique methods [10,51] with MCE-GIS pay more attention to the evaluation of land use intensity and development potential, but insufficient research on the current development efficiency. Therefore, we utilize a discriminant model of a three-dimensional matrix method composed of development intensity, supporting capacity, and utilization efficiency. The purpose of this method is to more scientifically and precisely identify problems related to land spatial development in urban agglomerations in order propose specific plans to improve land use quality. Then, based on the three-dimensional model, we obtained the zoning of national spatial development strength in the SPUA, China. The zones include key zones, stable zones, and restricted zones for development. The precise value of available construction land was calculated for each city in the SPUA. This method and evaluation result are highly consistent with the development needs of SPUA, and have been highly recognized by the Ministry of Natural Resources and the land administration department of SPUA. The research team was invited to give an academic report to the first National Symposium on Land Space Optimization Theory, Methods, and Practice organized by the Wuhan University and MNR in 25 November 2018 [52].
Urban sprawl is a non-compact, low-density development urban form, often exhibiting scattered, leapfrog, strip, or ribbon structure, resulting in poor travel patterns and irreversible environmental threat. Spatial planning framework have important influence on leading the urban growth. Sprawl is acknowledged to have several negative impacts in European Unions' territory, and smart and compact growth will be the future direction of urbanization [53]. Tsilimigkas et al. considered that integrated spatial planning framework is very important for regulating the complex territorial issues raised in medium-sized cities [54]. The urbanization model of self-promoted housing strategies could exploit loopholes and/or only partial application of the spatial planning framework and the very strict building regulations [55]. This is also the case in China's urbanization process. In order to explore the reform of the spatial planning system and build a national spatial planning system that is unified, interconnected, and hierarchically managed, the Central Office of the CPC Central Committee and the General Office of the State Council issued the "Provincial Space Planning Pilot Program" in January 2017, selecting Hainan and Ningxia. Jilin, Zhejiang, Fujian, Jiangxi, Henan, Guangxi, and Guizhou carried out provincial spatial planning pilots, coordinated various spatial planning, and prepared a unified provincial spatial planning. In April 2017, the Ministry of Land and Resources initiated the preparation of provincial land planning at the national level.
The state has officially approved nine urban agglomerations in the middle reaches of the Yangtze River, Harbin-Changchun, Chengdu-Chongqing, Yangtze River Delta, Central Plains, Beibu Gulf, Guanzhong Plain, Huhhot-Baotou-Erdos, Lanzhou-Xining, etc. The planning of the other 10 urban groups is being reported to the State Council according to procedures, and are awaiting replies. Coordinating provincial land planning and urban agglomeration planning, scientifically evaluating the quality of land use in urban agglomerations, is the basis for establishing the spatial planning system of "master plan-special plan-action plan", and improving "national-provincial-urban-county-village". This paper proposes development goals and paths based on the resource and environmental carrying capacity, land development potential, and efficiency of urban agglomeration. This method helps to break the balance of various spatial planning and can effectively link provincial and prefecture-level land space planning, realizing urban group space control from single-objective, rigid, static, to multi-objective, flexible, and dynamic development. We hope that this study will provide a reference for China's urban agglomeration strategy and ideas for urban agglomeration policy makers in developing countries.
The article still has problems such as possible indicators for the multi-attribute evaluation system and uncertainty in the index weights is needed. In contrast, the identification method of spatial conflicts of new investment area [37] and the method of landscape capacity assessment [48] used in the same high-value landscape can better exploit the value of land. This method can complement our lack of research. Different UAs have different development foundations, characteristics, and directions. The research method only discusses the land use quality evaluation of a coastal economic development type SPUA, which provides a reference for the evaluation of UA land use. The selection of evaluation indicators and weights is uncertain and cannot be directly used. Although insufficiencies remain, this study represents an exploration of the theory, method, and application of LDIE for urban agglomerations. As research continues, the theory and method will be gradually improved, and this paper will serve as a guide for the comprehensive, balanced, and sustainable development of urban agglomerations.