Yuning Cheng

The characterization and mapping of urban landscape spatial form are critical for advancing sustainable planning and informed environmental management. From a morphometric perspective, this study introduces a novel, data-driven framework for typo-morphological analysis. First, morphological cells (MCs) are defined as objectively and universally applicable spatial units for morphometric investigation. Second, by integrating a multi-dimensional cognition of full-scale morphological and associated landscape elements, we construct a set of 48 spatial form indicators and attach them to morphological cells, enabling a precise description of each unit. Third, a Gaussian mixture model (GMM) is employed to cluster the metrical information within the spatially lagged context derived from the topological structure of the morphological cells, resulting in the delineation of distinct typo-morphological zones (TMZs). We then adopt Ward’s algorithm to establish a hierarchical relationship among identified urban landscape types. Using Wuxi City, China, as a case study, our results demonstrate the effectiveness of the proposed framework in capturing the heterogeneity and underlying connotation of urban landscape spatial characteristics. Building upon the unsupervised clustering results, we further apply the classification and regression tree (CART) to provide a supervised interpretation of the key spatial form conditions driving typological decisions. It facilitates the systematic identification of the components and formative mechanisms of spatial form. The findings contribute a scalable, reproducible, and interpretable typo-morphometric approach for analyzing urban landscape spatial characteristics, thereby providing a robust quantitative foundation for integrated decision-making in landscape planning, socio-ecological assessment, and urban design practices. More broadly, the study carries both applied and theoretical significance for advancing refined urban governance and fostering interdisciplinary research related to urban sustainable development.

Landscape spatial structure serves as the foundational framework for vegetation arrangement and spatial organization, playing a crucial role in assessing landscape morphology. Traditional 2D graph theory methods have provided insights into planar structural characteristics but fail to capture the complexity of three-dimensional spatial attributes and organizational processes inherent in landscape systems. To address these limitations, this study proposes a novel multidimensional framework for the quantitative analysis and evaluation of landscape spatial structure by integrating 3D point cloud technology with spatial network analysis. The methodology consists of three key components: (1) the formulation of multidimensional spatial organization theory, (2) spatial unit extraction and structure analysis through ArcGIS 10.5 and Cytoscape v3.6.1, and (3) the development of an indicator system for evaluating spatial structure organization. The framework was validated through the analysis of 30 urban parks, where the regularity and range of indicators are generalized to establish evaluation criteria and determine weights. The findings indicate that spatial structure indicators are moderation indicators with optimal value ranges. The evaluation system was subsequently applied across the 30 parks for comprehensive evaluation. A total of 6 of 30 parks have comprehensive scores over 0.95. In practical application, the design score of Shuyang Park improved from 0.692 to 0.826 after evaluation and optimization, demonstrating the method’s effectiveness. This study underscores the potential of digital methodologies in advancing landscape spatial structure modeling, enhancing the understanding of spatial organization, and transitioning subjective assessments toward evidence-based objective evaluations. The proposed methodology and findings offer valuable insights for diagnosing, assessing, optimizing, and managing urban green spaces.

Urban parks are important components of the urban green space system, providing residents with a variety of leisure options. The design’s focal point is the spatial layout of the different use scenarios within these parks. Previous studies have largely concentrated on the scene and macro layout of urban public spaces but have not thoroughly investigated the digital characteristics and corresponding parametric methods for the layout of different internal use scenes in urban green spaces. This research selected 18 urban parks from various global regions as case samples and categorized eight typical park scene space types based on common activity scene requirements in park design using AutoCAD to identify vector boundaries in each sample. To examine the digital characteristics of these scene space types, a quantitative index system was established, including spatial density and scale indicators, spatial connection relationship indicators, and spatial unit morphology indicators. The analysis of these indicators across the samples shows that the number of scene spaces is positively correlated with the total park area, while natural experience scenes constitute the largest proportion of urban parks. Different scene types exhibit distinct spatial layouts; for example, circulation spaces demonstrate high connectivity due to their role in directing visitor flow. Some spaces exhibit a more fixed scale and size, while others vary considerably. Finally, this research develops a parametric design framework using the Grasshopper platform. By taking a park in Nanjing as a case study, this paper illustrates how to utilize digital layout features to generate scene space layouts, offering insights into intelligent generative design. This approach provides a structured method to enhance urban park design through the application of digital and parametric tools, contributing to the broader field of urban park design.

(1) Background: Sequential landscape changes give people experiences of dynamic beauty, and the key to creating spatial sequences lies in the organization of spatial changes. The purpose of this study is to use a 3D point cloud model to achieve a refined description of spatial sequences’ organizational characteristics from information acquisition to description and explore the quantitative interpretation methods of typical sequence organizational characteristics. (2) Methods: The proposed model contains three main steps: data acquisition and extraction, characteristic index system construction and data processing, and quantitative characterization analysis. A typology research method that combines quantitative induction with qualitative statistical verification is proposed. (3) Results: Seventy-two spatial sequence point cloud models of study cases are obtained; 4 indicators are established; 3 typical organization types are summarized, namely fluctuating, reversal and moderate type; and the characterization factors and threshold intervals for each sequence organization type are analyzed to validate the type classification result. (4) Conclusions: This research improves the accuracy of spatial data, the comprehensiveness of sequence organization characterization factors, and the reliability of classification results. It supplements the existing spatial sequence theoretical knowledge system and provides parameters that can be referred to in practical design.

A sponge city is an established urban stormwater management approach that effectively reduces urban runoff and pollutant discharges. In order to plan and design, estimate costs, and evaluate the performance of urban sponge city systems, it is essential to calculate the storage scale. In this context, a sponge city storage scale and calculation method based on a multifactor spatial overlay was designed, utilising the starting area of the Dafeng Hi-tech Development Zone in Yancheng City, China, as an illustrative example. The indicators for assessing the impact of sponge city systems on river plain networks are constructed based on four aspects: land planning, building density, water surface rate and green space rate. The relative importance of each indicator was determined based on the necessity of controlling runoff from land parcels and the appropriateness of facility construction. The annual runoff control rate of the 39 low-impact development control units in the study area was calculated using ArcGIS through multifactor spatial overlay mapping and weighting. The results showed that (1) the Geographic Information System (GIS)overlay technology can effectively assist in the decomposition of LID scales; (2) data can be derived, including the design storage volume and other basic control scale indicators for each unit. The study results are expected to serve as a reference for the preparation of special low-impact development plans in the river plain network area of China and the promotion of the construction of a sustainable blue–green system in the city.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking the city of Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving tour routes, transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; and (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate the tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) the tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving the tour routes, the transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

Complex network theory proposes a structural network model that abstracts the elements in a complex system into nodes and the relationship between elements into ties, which proved to be a scientific method to study the structural system of complexities. This article aims to apply the complex network theory to interpret the organization of landscape spatial structure and propose a spatial structure network construction and quantitative analysis method suitable for landscape space. The following two questions are addressed in this research: (1) How to extract the structural elements from the landscape space and realize the construction of the structural network model based on the 3D spatial information? (2) How to quantitatively analyze the organization characteristics of a spatial structure according to the particularity of landscape space? The research content of this article includes the following five aspects, which are 3D spatial information acquisition, structural element extraction, structural element description, structural network model diagramming, and quantitative index selection. Taking Nanjing Lovers Park as an example, the feasibility of this method is verified. The results show that the method proposed can guarantee the accuracy of the landscape spatial structure model, visualize the attributes of structural elements, and achieve a refined analysis of the structure organization.

By predicting and analyzing regional land use conflicts (LUCs), the contradictory relationship between urban development and land resources can be revealed, which can assist in achieving the rational use of land resources. Taking Liyang as a case study, this paper simulated land use in 2030 under three scenarios, namely, the natural growth scenario (NGS), economic development scenario (EDS), and ecological protection scenario (EPS), using the CLUMondo model. The ecological risk assessment model was used to measure the LUCs under each scenario. Through the comprehensive analysis of land use conversion, spatial distribution, and the change characteristics of LUCs, optimization strategies for future land use are proposed. The results indicate that (1) the intensity of land conversion under the three scenarios is ranked as EDS > NGS > EPS; (2) there is little change in the LUCs under the EPS, while significant deterioration is observed under the NGS and EDS; (3) the intensity of LUCs is positively correlated with the degree of land use conversion; and (4) in the future, particular attention should be paid to areas around the city center, the Caoshan Development Zone in the northwest, and Nanshan Bamboo Sea in the south, where high-intensity land use conflicts may occur.