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Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable...
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Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Innovations – Data and Machine Learning".

Deadline for manuscript submissions: 24 November 2025 | Viewed by 2440

Special Issue Editors

Dr. Wenwu Tang

E-Mail Website
Guest Editor
Department of Geography, University of North Carolina at Charlotte, Charlotte, NC 28223-0001, USA
Interests: geographic information science; spatial cyberinfrastructure; agent-based modeling; land use and land cover change; complex adaptive spatial systems
Special Issues, Collections and Topics in MDPI journals
Dr. Jianxin Yang

E-Mail Website
Guest Editor
Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China
Interests: spatial analysis; environment; environmental impact assessment; land use planning; natural resource management; mapping; spatial statistics; sustainability; geoinformation; geographical analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Minrui Zheng

E-Mail Website
Guest Editor
School of Public Administration and Policy, Renmin University of China, Beijing 100872, China
Interests: big data for spatial governance; GIScience; spatial analysis and modeling; machine learning; land use and land cover change
Special Issues, Collections and Topics in MDPI journals
Dr. Jingye Li

E-Mail Website
Guest Editor
Land Resource Management, School of Public Administration, Hohai University, No. 8 West Focheng Road, Jiangning, Nanjing, China
Interests: land use change; land use planning; spatial analysis; remote sensing and gis; ecosystem services; landscape ecology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to introduce our 2nd edition of this special issue in the Land journal, entitled "Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition". This special issue aims to explore complex dynamics of land systems (urban, rural or coupled) and their sustainability through the lens of spatiotemporal data analytics and modeling. We invite contributions that delve into the multifaceted aspects of land use, land cover, spatio-temporal analysis of landscape patterns and land resources management, emphasizing the critical role of spatiotemporal data analytics and modeling methods as well as geocomputing capabilities from advanced cyberinfrastructure, artificial intelligence, and high-performance or cloud computing.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights into spatiotemporal analysis and modeling in face of a number of challenges when applied to the study of land systems, including, but not limited by, handling large datasets, problems with data quality, spatiotemporal scale and complexity, and the necessity for specific computing methods represented by cyberinfrastructure and artificial intelligence technologies. Geography, urban studies, landscape ecology, environmental science, sustainability science, archaeology and anthropology, and earth science are just a few examples of the research fields that spatial-temporal data analytics and modeling are applied. We encourage researchers to examine the intricate interplay of natural and human factors shaping landscapes, with a particular focus on fostering sustainability, resilience, and adaptive management within spatiotemporal context. Submissions may encompass a wide range of topics, including land change dynamics, spatial modeling (including simulation, optimization, and statistics), remote sensing (including close range, e.g., using unmanned vehicles), geospatial and cyberinfrastructure technologies, artificial intelligence, digital twins, and policy interventions that contribute to our understanding of land system for sustainable and resilient landscape. By bringing together cutting-edge research, this special issue aspires to provide insights and strategies for better-informed decision-making, ultimately fostering the sustainable development and management of our precious landscapes.

This Special Issue welcomes manuscripts that link the following themes:

  • Land change dynamics;
  • Spatio-temporal analysis of landscape pattern;
  • Spatial simulation, spatial optimization, and spatial statistics;
  • Shaping sustainable landscapes;
  • Land development;
  • Land resources management;
  • Geocomputing and cyberinfrastructure technologies;
  • Modern artificial intelligence applications in the study of land systems;

We look forward to receiving your original research articles and reviews. You may choose our Joint Special Issue in Land.

Dr. Wenwu Tang
Dr. Jianxin Yang
Dr. Minrui Zheng
Dr. Jingye Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spatiotemporal modeling spatial-temporal
  • landscape patterns and processes landscape
  • sustainability and resilience
  • geospatial technologies
  • land use/land cover
  • land change
  • modeling landscape
  • assessment methods
  • landscape dynamic evolution

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

30 pages, 10749 KiB  
Article
Three-Dimensional Ecological Footprint Assessment of Cropland in Typical Grain-Producing Regions Based on Carbon Footprint Improvement
by Peipei Pan, Xiaowen Yuan, Yanan Jiang, Yuan Wang, Xinyun Wang and Yongqiang Cao
Land 2025, 14(4), 852; https://doi.org/10.3390/land14040852 - 14 Apr 2025
Viewed by 322
Abstract
The challenges of limited cropland resources and ecological degradation in grain-producing areas were addressed in this study within the broader context of China’s ecological civilization and dual carbon goals. An integrated framework was employed, applying the three-dimensional ecological footprint (EF3d) model, [...] Read more.
The challenges of limited cropland resources and ecological degradation in grain-producing areas were addressed in this study within the broader context of China’s ecological civilization and dual carbon goals. An integrated framework was employed, applying the three-dimensional ecological footprint (EF3d) model, enhanced by carbon footprint improvement, to assess cropland at the provincial, municipal, and county levels. The analysis indicated a rise in both carbon absorption and emissions, resulting in a carbon surplus. Since 1984, chemical fertilizers have been identified as the predominant source of carbon emissions. Carbon absorption was found to vary distinctly among the four crops. Additionally, carbon fluxes displayed notable spatial and temporal variability. The ecological deficit persisted, showing distinct spatial clustering. Moreover, the cropland ecological footprint breadth (EFsize) was found to exhibit a pattern of decrease–increase–decrease, while cropland occupation remained high. The ecological footprint depth (EFdepth) consistently surpassed the threshold of 1. Spatially, the distribution pattern of cropland EFsize was opposite to that of EFdepth; the centroid of per capita cropland EFdepth underwent a significant spatial shift. The cropland EF3d was observed to experience a downward trend, with considerable regional disparities. Furthermore, unsustainable use of cropland was observed across multiple scales. This research provides an empirical foundation for promoting advancing ecological agriculture and sustainable cropland use practices. Full article
(This article belongs to the Special Issue Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition)
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21 pages, 19423 KiB  
Article
Analysis of Landscape Fragmentation Evolution Characteristics and Driving Factors in the Wei River Basin, China
by Changzheng Gao, Qisen Dang, Chu Li and Yongming Fan
Land 2025, 14(3), 538; https://doi.org/10.3390/land14030538 - 4 Mar 2025
Viewed by 599
Abstract
Historically, the Wei River has served as part of the Yongji Canal section of the Grand Canal, playing a crucial role in connecting northern and southern China. However, with the acceleration of urbanization in China, issues such as excessive land development and ecological [...] Read more.
Historically, the Wei River has served as part of the Yongji Canal section of the Grand Canal, playing a crucial role in connecting northern and southern China. However, with the acceleration of urbanization in China, issues such as excessive land development and ecological landscape fragmentation have emerged. Exploring the mechanisms of landscape fragmentation evolution in the Wei River basin and proposing optimization strategies is of significant importance for land use and ecological stability within small- to medium-sized river basins. This study selected land use data from the Weihe River basin between 2000 and 2020, using landscape pattern indices to analyze the trend of landscape fragmentation. The principal component analysis (PCA) and geographical detector methods were employed to explore the distribution characteristics and driving factors of landscape fragmentation. The research results indicate that: (1) The degree of landscape fragmentation in the Wei River basin has progressively intensified over time. The edge density index (ED), the landscape division index (DIVISION), the landscape shape index (LSI), and the Shannon diversity index (SHDI) have increased annually, while the contagion index (CONTAG) and area-weighted mean patch size (Area_AM) have continuously decreased; (2) Landscape fragmentation in the Wei River basin is characterized by stable changes in the source and tributary fragmentation areas, a concentrated distribution of fragmentation in the tributaries, and a significant increase in fragmentation in the main stream; (3) The analysis using the geographic detector method indicates that vegetation coverage (FVC), human activity intensity (HAI), and land use/land cover change (LUCC) are the main driving factors of landscape fragmentation in the Wei River basin. The findings explore the mechanisms of landscape fragmentation in the basin and provide a reference for land use planning and ecological restoration in the region. Full article
(This article belongs to the Special Issue Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition)
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23 pages, 4504 KiB  
Article
A “Foundation-Function-Structure” Framework for Multiple Scenario Assessment of Land Change-Induced Dynamics in Regional Ecosystem Quality
by Yue Pan, Jing Gao and Jianxin Yang
Land 2025, 14(3), 515; https://doi.org/10.3390/land14030515 - 1 Mar 2025
Viewed by 435
Abstract
Understanding the changes in ecosystem quality caused by land use changes is critical for sustainable urban development and environmental management. This study investigates the spatial-temporal evolution of ecosystem quality in Wuhan from 2000 to 2020 and forecasts future trends under multiple land use [...] Read more.
Understanding the changes in ecosystem quality caused by land use changes is critical for sustainable urban development and environmental management. This study investigates the spatial-temporal evolution of ecosystem quality in Wuhan from 2000 to 2020 and forecasts future trends under multiple land use scenarios for 2030. Using a “foundation-function-structure” assessment framework, we integrate system dynamics (SD), the Patch-generating Land Use Simulation (PLUS) model, and a neural network-based ecosystem quality inversion model to analyze land use transitions and their ecological impacts. The results indicate that rapid urban expansion has significantly contributed to the decline of cropland and forest areas, while impervious surfaces have increased, leading to notable ecological degradation. Simulations for 2030 under three scenarios—ecological protection, natural development, and economic priority—demonstrate that the ecological protection scenario yields the highest ecosystem quality, preserving landscape connectivity and mitigating degradation risks. In contrast, the economic priority scenario results in extensive urban expansion, exacerbating ecological stress. Under the ecological protection scenario from 2020 to 2023, the decline in ecosystem quality was primarily due to the expansion of urban fringes and the erosion of forest and grassland areas. The increase in ecosystem quality was mainly attributed to the transformation of early urban edge conflict zones into stable urban edge interior areas and the integration of fragmented ecological land patches. These findings highlight the need for strategic land use planning to balance economic growth and environmental conservation. This study provides a robust methodological framework for assessing and predicting ecosystem quality changes, offering valuable insights for policymakers and urban planners striving for sustainable development. Full article
(This article belongs to the Special Issue Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition)
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27 pages, 13448 KiB  
Article
Spatial and Temporal Dynamics of Territorial Spatial Conflicts and Construction Land Expansion in Guizhou Province: A 40-Year Perspective
by Huaiyu Wang, Liu Yang and Hongzan Jiao
Land 2025, 14(3), 507; https://doi.org/10.3390/land14030507 - 28 Feb 2025
Viewed by 429
Abstract
Territorial spatial conflicts (TSCs) refer to a contradiction of utilization resulting from the inconsistency of the needs and objectives of different subjects of interest for spatial resources in planning, utilization, and management. This research aimed to unveil the TSCs, construction land expansion (CLE), [...] Read more.
Territorial spatial conflicts (TSCs) refer to a contradiction of utilization resulting from the inconsistency of the needs and objectives of different subjects of interest for spatial resources in planning, utilization, and management. This research aimed to unveil the TSCs, construction land expansion (CLE), and their relationship in Guizhou Province from 1980 to 2020, both temporally and spatially. This paper established indicators to assess CLE, including construction land expansion velocity, construction land expansion intensity, and construction land expansion pattern to analyze the expansion characteristics of construction land in Guizhou Province. At the same time, the territorial spatial conflict indicator (SCII) was constructed to study the TSCs in Guizhou Province, and its evolution pattern was explored through the cold hotspot analysis. On this basis, it investigated the relationship and linkage between TSCs and CLE through the ordinary least squares (OLS) regression model and geographically weighted (GWR) regression model. Furthermore, this paper also constructed an economic elasticity coefficient and a population elasticity coefficient to analyze the collaborative relationship between TSCs and GDP along with population volume. The research revealed that while the velocity and intensity of CLE in Guizhou Province have escalated over time, this expansion displayed considerable geographical variation across various locations. Simultaneously, the TSCs intensified, demonstrating a slight positive correlation with the expansion. The study of the spatial and temporal evolution characteristics and response relationship between the TSCs and CLE provided a reference for the optimization of regional territorial space. It is highly valuable and significant in fostering efficient utilization of land resources, adjusting to economic and social transformations, and improving the scientific rigor of spatial planning. Full article
(This article belongs to the Special Issue Spatiotemporal Data Analytics and Modeling of Land Systems: Shaping Sustainable Landscape, Second Edition)
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