Urban Land Use and Spatial Analysis

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Geomatics geomatics	-	-	2021	22.1 Days	CHF 1000
Land land	3.2	4.9	2012	16.9 Days	CHF 2600
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700
Urban Science urbansci	2.1	4.3	2017	20.7 Days	CHF 1600
Water water	3.0	5.8	2009	17.5 Days	CHF 2600

22 pages, 19346 KiB

Open AccessArticle

A Two-Layer SD-ANN-CA Model Framework for Multi-Typed Land Use and Land Cover Change Prediction under Constraints: Case Study of Ya’an City Area, Western China

by Jingyao Zhao, Xiaofan Zhu, Fan Zhang and Lei Gao

Land 2024, 13(5), 714; https://doi.org/10.3390/land13050714 - 19 May 2024

Viewed by 1786

Abstract

Land use and land cover change (LUCC) prediction of cities in Western China requires higher accuracy in quantitative demand and spatial layout because of complex challenges in balancing relationships between urban constructions and ecological developments. Considering city-level areas and various types of land [...] Read more.

Land use and land cover change (LUCC) prediction of cities in Western China requires higher accuracy in quantitative demand and spatial layout because of complex challenges in balancing relationships between urban constructions and ecological developments. Considering city-level areas and various types of land use and land cover, existing LUCC models without constraint or with only loose demand constraints were impractical in providing evidence of high accuracy and high-resolution predictions in areas facing fierce land competition. In this study, we proposed a two-layer SD-ANN-CA model to simulate and explore the LUCC trend and layout predictions for 2018, 2028, and 2038 in Ya’an City, Western China. The two-layer structure with an upper layer of the SD model and a lower layer of the ANN-CA model, as well as the advantages of all three methods of system dynamics (SD), artificial neural network (ANN), and cellular automata (CA), have allowed us to consider the macro-level demand constraints, meso-level driving factors constraints, and the micro-level spatial constraints into a unified model framework. The simulation results of the year 2018 have shown significant improvement in the accuracy of the ANN-CA model constructed in our earlier work, especially in types of forest land (error-accuracy: 0.08%), grassland (error-accuracy: 0.23%), and construction land (error-accuracy: 0.18%). The layout predictions of all six types of land use in 2028 and 2038 are then carried out to provide visual evidence support, which may improve the efficiency of planning and policy-making processes. Our work may also provide insights into new ways to combine quantitative methods into spatial methods in constructing city-level or even regional-level LUCC models with high resolution. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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24 pages, 9159 KiB

Open AccessArticle

Unsupervised Image Segmentation Parameters Evaluation for Urban Land Use/Land Cover Applications

by Guy Blanchard Ikokou and Kate Miranda Malale

Geomatics 2024, 4(2), 149-172; https://doi.org/10.3390/geomatics4020009 - 12 May 2024

Viewed by 1432

Abstract

Image segmentation plays an important role in object-based classification. An optimal image segmentation should result in objects being internally homogeneous and, at the same time, distinct from one another. Strategies that assess the quality of image segmentation through intra- and inter-segment homogeneity metrics [...] Read more.

Image segmentation plays an important role in object-based classification. An optimal image segmentation should result in objects being internally homogeneous and, at the same time, distinct from one another. Strategies that assess the quality of image segmentation through intra- and inter-segment homogeneity metrics cannot always predict possible under- and over-segmentations of the image. Although the segmentation scale parameter determines the size of the image segments, it cannot synchronously guarantee that the produced image segments are internally homogeneous and spatially distinct from their neighbors. The majority of image segmentation assessment methods largely rely on a spatial autocorrelation measure that makes the global objective function fluctuate irregularly, resulting in the image variance increasing drastically toward the end of the segmentation. This paper relied on a series of image segmentations to test a more stable image variance measure based on the standard deviation model as well as a more robust hybrid spatial autocorrelation measure based on the current Moran’s index and the spatial autocorrelation coefficient models. The results show that there is a positive and inversely proportional correlation between the inter-segment heterogeneity and the intra-segment homogeneity since the global heterogeneity measure increases with a decrease in the image variance measure. It was also found that medium-scale parameters produced better quality image segments when used with small color weights, while large-scale parameters produced good quality segments when used with large color factor weights. Moreover, with optimal segmentation parameters, the image autocorrelation measure stabilizes and follows a near horizontal fluctuation while the image variance drops to values very close to zero, preventing the heterogeneity function from fluctuating irregularly towards the end of the image segmentation process. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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19 pages, 8020 KiB

Open AccessArticle

Driving Domain Classification Based on Kernel Density Estimation of Urban Land Use and Road Network Scaling Models

by Gerrit Brandes, Christian Sieg, Marcel Sander and Roman Henze

Urban Sci. 2024, 8(2), 48; https://doi.org/10.3390/urbansci8020048 - 9 May 2024

Cited by 3 | Viewed by 1800

Abstract

Current research on automated driving systems focuses on Level 4 automated driving (AD) in specific operational design Domains (ODD). Measurement data from customer fleet operation are commonly used to extract scenarios and ODD features (road infrastructure, etc.) for the testing of AD functions. [...] Read more.

Current research on automated driving systems focuses on Level 4 automated driving (AD) in specific operational design Domains (ODD). Measurement data from customer fleet operation are commonly used to extract scenarios and ODD features (road infrastructure, etc.) for the testing of AD functions. To ensure data relevance for the vehicle use case, driving domain classification of the data is required. Generally, classification into urban, extra-urban and highway domains provides data with similar ODD features. Highway classification can be implemented using global navigation satellite system coordinates of the driving route, map-matching algorithms, and road classes stored in digital maps. However, the distinction between urban and extra-urban driving domains is more complex, as settlement taxonomies and administrative-level hierarchies are not globally consistent. Therefore, this paper presents a map-based method for driving domain classification. First, potential urban areas (PUA) are identified based on urban land-use density, which is determined based on land-use categories from OpenStreetMap (OSM) and then spatially smoothed by kernel density estimation. Subsequently, two road network scaling models are used to distinguish between urban and extra-urban domains for the PUA. Finally, statistics of ODD feature distribution are analysed for the classified urban and extra-urban areas. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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18 pages, 2875 KiB

Open AccessArticle

Spatio–Temporal Dynamic Characteristics and Driving Mechanisms of Urban Compactness in Central China

by Wenqin Ren, Linggui Wei, Xinhai Lu, Jinlong Xu and Yun Qin

Urban Sci. 2024, 8(2), 40; https://doi.org/10.3390/urbansci8020040 - 24 Apr 2024

Cited by 1 | Viewed by 1449

Abstract

As a result of rapid urbanization in China, the spatial restructuring of towns and cities has significantly impacted urban compactness. The study of the spatio–temporal characteristics and driving mechanisms of urban compactness in central China is a strategic imperative and conducive to promoting [...] Read more.

As a result of rapid urbanization in China, the spatial restructuring of towns and cities has significantly impacted urban compactness. The study of the spatio–temporal characteristics and driving mechanisms of urban compactness in central China is a strategic imperative and conducive to promoting regional sustainable development that is based on easing the contradiction between land resource supply and demand and reducing energy consumption. Therefore, this study focused on 80 prefecture-level cities in central China, utilizing barycenter model and GTWR model, among others, to analyze the spatio–temporal evolution pattern of urban compactness from 2006 to 2020 and its driving factors, with the aim of uncovering the intrinsic mechanisms behind enhancing urban compactness in the area. The results show the follows: (1) The urban compactness in central China has generally shown an upward trend, with a pronounced spatial clustering around provincial capital cities and the spatial changes in compactness predominantly concentrated in the north–south direction. (2) Various factors have influenced urban compactness, where government intervention and population aggregation present as bi-directional driving factors, while the effective use of land resources and high-quality industrial development, among others, present as positive driving factors. The spatio–temporal heterogeneity and agglomeration features of each driving factor are significant. (3) Further analysis indicates that the effective use of land resources is the primary factor in enhancing urban compactness, followed by technology. Therefore, we should adhere to the concept of compact cities and gradually promote the compactness of cities in central China based on the impact of the driving factors. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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20 pages, 5301 KiB

Open AccessReview

Urban Sustainability Development in Morocco, a Review

by Lahouari Bounoua, Mohamed Amine Lachkham, Noura Ed-Dahmany, Souad Lagmiri, Hicham Bahi, Mohammed Messouli, Mohammed Yacoubi Khebiza, Joseph Nigro and Kurtis J. Thome

Urban Sci. 2024, 8(2), 28; https://doi.org/10.3390/urbansci8020028 - 1 Apr 2024

Cited by 4 | Viewed by 4958

Abstract

During the last decades, Morocco has recorded substantial urbanization and faced challenges related to urban sprawl and encroachment on fertile lands. This paper reviews several studies assessing urban sustainability development in 27 Moroccan urban areas using the UN’s Sustainable Development Goal (SDG) indicator [...] Read more.

During the last decades, Morocco has recorded substantial urbanization and faced challenges related to urban sprawl and encroachment on fertile lands. This paper reviews several studies assessing urban sustainability development in 27 Moroccan urban areas using the UN’s Sustainable Development Goal (SDG) indicator 11.3.1, i.e., the ratio of Land Consumption Rate (LCR) to Population Growth Rate (PGR). Among the 27 urban areas reviewed, analysis of SDG 11.3.1 data revealed that only 7 exhibited trends towards sustainable urban development, while the remaining 20 showed a divergence from the sustainability objectives. We analyze the studies, conducted between 2020 and 2023, describing in depth the relationship between LCRs and PGRs, and provide a comprehensive summary of the SDG 11.3.1 outcome, discussing along the way methodological variations, and introducing a new concept for the evaluation of urban land consumption. The review reveals disparate regional urban development trends, emphasizing the need for local land tenure rules. Additionally, the study discusses how the SDG 11.3.1 reacts under the influence of several parameters such as land characteristics, climate, and geographic location. While the study acknowledges the limitations of SDG 11.3.1, it found that the indicator provides valuable insights into trends and comparisons, and should offer assistance to stakeholders, urban planners, and decision makers in their pursuit of sustainable development. However, these identified limitations underscore the need for a more comprehensive and multidimensional urban sustainability development indicator, capable of better addressing the complexities of the urban environment. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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16 pages, 642 KiB

Open AccessArticle

Urbanization Impacts on Rice Farming Technical Efficiency: A Comparison of Irrigated and Non-Irrigated Areas in Indonesia

by Mohammad Rondhi, Stefani Jessica Herlyana Suherman, Clement Billy Hensie, Shohibul Ulum, Anik Suwandari, Rokhani, Yasuhiro Mori and Takumi Kondo

Water 2024, 16(5), 651; https://doi.org/10.3390/w16050651 - 22 Feb 2024

Viewed by 2522

Abstract

By 2050, the world population is expected to double, with the majority living in urban areas. Urbanization is a result of population pressure, often emphasized in developing countries. It has various impacts on all economic sectors, among which is agriculture through irrigation, which [...] Read more.

By 2050, the world population is expected to double, with the majority living in urban areas. Urbanization is a result of population pressure, often emphasized in developing countries. It has various impacts on all economic sectors, among which is agriculture through irrigation, which plays an important role in the production and sustainability of farming. This paper aimed to analyze the effect of urbanization on farm performance using a sequential mixed method. The data of approximately 80,053 farmers were extracted from the Indonesian Rice Farm Household Survey (SPD) dataset. A stochastic frontier was employed to analyze technical efficiency (TE) and its determinants, which consist of farmers’ age, education level, climate change, land ownership, membership status, and pest infestation. The estimation results showed that the mean technical efficiency in both irrigation and non-irrigation rice farming was 64.7% and 66.2%, respectively. Although TE’s achievement in non-irrigated rice farming areas was greater than in irrigated ones, rice productivity in irrigated areas was greater than in non-irrigated. All technical efficiency determinants have significant effects on technical efficiency. The estimation results also showed that rice farming in urban areas tends to decrease technical efficiency. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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15 pages, 2556 KiB

Open AccessArticle

Analysis of Urban Congestion Traceability: The Role of the Built Environment

by Chenguang Li, Duo Wang, Hong Chen and Enze Liu

Land 2024, 13(2), 255; https://doi.org/10.3390/land13020255 - 19 Feb 2024

Cited by 2 | Viewed by 4707

Abstract

Analyzing the factors influencing traffic congestion is essential for urban planning and coordinated development. Previous research frequently focuses on the internal aspects of traffic systems, often overlooking the impact of external factors on congestion sources. Therefore, this study utilizes a geospatial dataset and [...] Read more.

Analyzing the factors influencing traffic congestion is essential for urban planning and coordinated development. Previous research frequently focuses on the internal aspects of traffic systems, often overlooking the impact of external factors on congestion sources. Therefore, this study utilizes a geospatial dataset and mobile signaling data, firstly applying the Fuzzy C-Means (FCM) algorithm to identify congested roads of different levels and trace the localization of travelers’ origins on regional congested roads. Furthermore, it employs the LightGBM method to study the influence of the built environment of various congestion sources on network-level congestion. The findings are as follows: (1) There is a positive correlation between traffic congestion and geographical location, with congestion predominantly caused by a few specific plots and demonstrating a concentrated trend in city centers. (2) Residential population density is the most critical factor, accounting for over 12% of the congestion contribution, followed by road density and working population density. (3) Both residential and working population densities show a non-linear positive correlation with congestion contribution, while the mixture of land use displays a non-linear V-shaped influence. Additionally, when residential population density is between 8000 and 11,000, it notably exacerbates congestion contribution. Significantly, by emphasizing land use considerations in traffic system analysis, these findings illuminate the intricate linkages between urban planning and traffic congestion, advocating for a more comprehensive approach to urban development strategies. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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19 pages, 4170 KiB

Open AccessArticle

The Impact of Commercial-Industry Development of Urban Vitality: A Study on the Central Urban Area of Guangzhou Using Multisource Data

by Lixin Liu, Yanjun Dong, Wei Lang, Huiyu Yang and Bin Wang

Land 2024, 13(2), 250; https://doi.org/10.3390/land13020250 - 18 Feb 2024

Cited by 6 | Viewed by 3336

Abstract

Urban commercial centers play a critical role in the development of cities, and it is of significant relevance to research the influencing variables of the urban vitality of commercial centers to improve the quality of urban commercial centers. This study employs big data [...] Read more.

Urban commercial centers play a critical role in the development of cities, and it is of significant relevance to research the influencing variables of the urban vitality of commercial centers to improve the quality of urban commercial centers. This study employs big data to construct a multiple linear regression model in order to uncover the spatial-distribution characteristics of urban vitality and commercial sectors in commercial centers within the primary urban region of Guangzhou. The findings indicate that the commercial sectors of life, business, finance, and leisure have a substantial influence on the fluctuation of pedestrian flow in commercial centers throughout the day. Conversely, public service commercial sectors do not have a significant impact on pedestrian flow. Furthermore, the effect of various commercial sectors on the vibrancy of urban commercial centers varies, and their performance differs on weekdays and holidays. Additionally, the level of integration among commercial sectors affects the vitality of the city’s commercial space. This research presents empirical facts that can be used to optimize the logical allocation of urban commercial resources in urban planning. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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18 pages, 3511 KiB

Open AccessArticle

Comparison of Random Forest and XGBoost Classifiers Using Integrated Optical and SAR Features for Mapping Urban Impervious Surface

by Zhenfeng Shao, Muhammad Nasar Ahmad and Akib Javed

Remote Sens. 2024, 16(4), 665; https://doi.org/10.3390/rs16040665 - 13 Feb 2024

Cited by 47 | Viewed by 8981

Abstract

The integration of optical and SAR datasets through ensemble machine learning models shows promising results in urban remote sensing applications. The integration of multi-sensor datasets enhances the accuracy of information extraction. This research presents a comparison of two ensemble machine learning classifiers (random [...] Read more.

The integration of optical and SAR datasets through ensemble machine learning models shows promising results in urban remote sensing applications. The integration of multi-sensor datasets enhances the accuracy of information extraction. This research presents a comparison of two ensemble machine learning classifiers (random forest and extreme gradient boost (XGBoost)) classifiers using an integration of optical and SAR features and simple layer stacking (SLS) techniques. Therefore, Sentinel-1 (SAR) and Landsat 8 (optical) datasets were used with SAR textures and enhanced modified indices to extract features for the year 2023. The classification process utilized two machine learning algorithms, random forest and XGBoost, for urban impervious surface extraction. The study focused on three significant East Asian cities with diverse urban dynamics: Jakarta, Manila, and Seoul. This research proposed a novel index called the Normalized Blue Water Index (NBWI), which distinguishes water from other features and was utilized as an optical feature. Results showed an overall accuracy of 81% for UIS classification using XGBoost and 77% with RF while classifying land use land cover into four major classes (water, vegetation, bare soil, and urban impervious). However, the proposed framework with the XGBoost classifier outperformed the RF algorithm and Dynamic World (DW) data product and comparatively showed higher classification accuracy. Still, all three results show poor separability with bare soil class compared to ground truth data. XGBoost outperformed random forest and Dynamic World in classification accuracy, highlighting its potential use in urban remote sensing applications. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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16 pages, 6783 KiB

Open AccessArticle

Hemeroby Mapping of the Belém Landscape in Eastern Amazon and Impact Study of Urbanization on the Local Climate

by Leonardo Seabra Furtado, Raimundo Vitor Santos Pereira and Everaldo Barreiros de Souza

Urban Sci. 2024, 8(1), 15; https://doi.org/10.3390/urbansci8010015 - 9 Feb 2024

Cited by 2 | Viewed by 2760

Abstract

This work contributes to the studies on landscape mapping induced by human pressure directly related to the urbanization process, whose approach is based on the concept of hemeroby adapted to the metropolitan area of Belém in the eastern Amazon. The mapping results using [...] Read more.

This work contributes to the studies on landscape mapping induced by human pressure directly related to the urbanization process, whose approach is based on the concept of hemeroby adapted to the metropolitan area of Belém in the eastern Amazon. The mapping results using 1985 and 2021 Landsat satellite data indicated that the artificial coverage characterized as medium to the high urban system (polyhemerobic and metahemerobic degrees) has increased by almost 17% toward northern districts and Outeiro/Mosqueiro islands, while the natural vegetation cover suppression (ahemerobic degree) was around 11%. In addition, we investigated the impacts of urban expansion on seasonal (WET from January to April and DRY from July to November) surface air temperature (minimum TN and maximum TX) patterns. From statistical comparisons between 18-year samples (2004/2021 to 1985/2002), we find evidence of a current significantly warmer climate, with a notable indication of higher surface temperature over densely urbanized areas compared to lower values over natural areas. In the TX climatology, particularly for the DRY regime, we identified a pattern similar to the classic heat island model with concentric isotherms reaching a maximum center over the more urbanized continental region of Belém and a thermal decrease at the edges. Therefore, the findings of this work are convincing that Belém already faces the direct impacts of urbanization on the local climate, so it is crucial to develop government strategies aimed at taking action to mitigate socioenvironmental risks and threats to the well-being of urban populations. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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25 pages, 17544 KiB

Open AccessArticle

Evaluate Human Perception of the Built Environment in the Metro Station Area

by Wei Gao, Xiaoli Sun, Mei Zhao, Yong Gao and Haoran Ding

Land 2024, 13(1), 90; https://doi.org/10.3390/land13010090 - 12 Jan 2024

Cited by 5 | Viewed by 2581

Abstract

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based [...] Read more.

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based on the “5D” index and Node-Place theory in the metro station area, current research on the built environment in metro station areas focuses on improving the economic and transportation efficiency while neglecting public perception of the construction of station space. Sentiments, as an important part of the individual’s perception, are closely related to the built environment. Therefore, this study takes 187 metro stations within the fifth ring road of Beijing, China, as an example and extracts public sentiment information from social media data using a wide range of natural language processing techniques to quantitatively analyze the distribution of the public’s sentiment characteristics (including intensity, polarity, and category) in the metro station area and deeply explores the spatial correlation with the distribution of the objective built environment elements. The study shows that influenced by the spatial design of the metro station, density, land use functions, etc., the sentiment intensity of the station area within the Fifth Ring Road of Beijing is “strong in the east and weak in the west, strong in the north and weak in the south”, and the sentiment polarity has the characteristic of gradually negative from inside to outside in a circular pattern. Synthesizing the sentiment perception in the metro station area, our study further divided the Beijing metro station area into four major categories and eight specific subtypes. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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21 pages, 13260 KiB

Open AccessArticle

Spatiotemporal Variation and Driving Factors Analysis of Habitat Quality: A Case Study in Harbin, China

by Yuxin Qi and Yuandong Hu

Land 2024, 13(1), 67; https://doi.org/10.3390/land13010067 - 6 Jan 2024

Cited by 7 | Viewed by 2182

Abstract

Biodiversity is profoundly influenced by habitat quality, and Harbin, a provincial capital situated in a cold climate zone, stands out as one of China’s regions most susceptible to the repercussions of climate change. To ensure the city’s continued sustainable growth, a thorough assessment [...] Read more.

Biodiversity is profoundly influenced by habitat quality, and Harbin, a provincial capital situated in a cold climate zone, stands out as one of China’s regions most susceptible to the repercussions of climate change. To ensure the city’s continued sustainable growth, a thorough assessment of habitat quality must be conducted. This study employs a comprehensive approach integrating the InVEST model, the PLUS model, a landscape pattern analysis, geographic detector, and a geographically weighted regression model. The goal is to assess how land use and habitat quality have changed in Harbin City, investigate factors contributing to spatial heterogeneity in habitat quality, thoroughly examine evolutionary patterns under the inertial development scenario from 2030 to 2050, and propose spatial optimization strategies. There are four key findings. First, from 2000 to 2020, agricultural land and forest were Harbin City’s two most prevalent land use types. The most notable transition occurred from forest to grassland, and the expansion of construction land primarily resulted from its encroachment into agricultural areas. Second, within the area of study, the landscape heterogeneity increased while simultaneously experiencing a decrease in connectivity, and the landscape had a tendency toward a more fragmented spatial distribution. Third, overall habitat quality rose between 2000 and 2020 but declined between 2030 and 2050. There was a “weak in the west and high in the east” distribution pattern in the spatial heterogeneity of habitat quality. Fourth, population density has the most impact on habitat quality, with the NDVI and GDP close behind. Conversely, precipitation and slope had comparatively smaller influences on habitat quality. Natural factors combined had a primarily favorable influence on habitat quality across the research region in terms of spatial distribution. Conversely, population density had a discernibly detrimental impact. Given these findings, this study suggests targeted strategies to optimize habitat quality. These recommendations are relevant not only for biodiversity conservation but also for the development of an ecologically sustainable community, particularly in a cold climate region. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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15 pages, 2987 KiB

Open AccessArticle

Spatiotemporal Pattern of Urban Sprawl Based on the Weighted Urban Proliferation Model: A Case Study of the Bohai Rim Region in China

by Yang Yang, Yang Liu, Huanbi Yue and Zhe Dong

Land 2024, 13(1), 55; https://doi.org/10.3390/land13010055 - 2 Jan 2024

Cited by 3 | Viewed by 2087

Abstract

Since the reform and opening up, China’s urbanization level has increased rapidly, with the urbanization rate rising from 17.92% in 1978 to 63.89% in 2020. At the same time, the extreme expansion of urban space has gradually become a common phenomenon, and the [...] Read more.

Since the reform and opening up, China’s urbanization level has increased rapidly, with the urbanization rate rising from 17.92% in 1978 to 63.89% in 2020. At the same time, the extreme expansion of urban space has gradually become a common phenomenon, and the problem of urban sprawl has become a stumbling block to the high-quality development of Chinese cities. The traditional single-indicator method and multi-indicator method have obvious shortcomings in the richness of index dimension and the subjectivity of indicator selection, respectively, when measuring urban sprawl quantitatively. In this study, based on the weighted urban proliferation (WUP) model, we integrated the three independent dimensions of urban permeation (UP), dispersion of built-up areas (DIS), and utilization density (UD) to verify the applicability and feasibility of the model for quantifying the spatiotemporal pattern of urban sprawl, taking the Bohai Rim region in China as an example. There were four main results. Most cities in the Bohai Rim region had a moderate-to-high level of urban sprawl, with obvious spatial heterogeneity by province. The average WUP of cities in the Bohai Rim region increased by 61.83% from 2000 to 2020, and cities with moderate urban sprawl became cities with high sprawl. The urban sprawl process in the Bohai Rim region accelerated during 2010−2015 and stabilized thereafter. The increase in WUP caused by the growth of built-up areas is the main driver of urban sprawl in the Bohai Rim region. This study found that the WUP model can be effectively applied to the Bohai Rim region of China, where it reflects the multidimensional features of urban sprawl and provides new insight into its spatiotemporal pattern. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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22 pages, 13336 KiB

Open AccessArticle

Integrating System Spatial Archetypes and Archetypical Evolutionary Patterns of Human Settlements: Towards Place-Based Sustainable Development

by Wenlin Gao, Wanyue Lyu and Binyi Liu

Land 2023, 12(12), 2164; https://doi.org/10.3390/land12122164 - 14 Dec 2023

Cited by 1 | Viewed by 2099

Abstract

Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach [...] Read more.

Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach to understanding sustainability challenges within specific spatio-temporal contexts. This study introduced a novel approach to assessing and characterizing human settlements using a spatio-temporal two-tier structure archetype analysis for human settlement systems. Applying inductive clustering to an integrated dataset, we identified five typical human settlement systems for 2019 and eight change patterns (2001–2019) in the Yangtze River Delta region. By linking inductively recognized human settlement systems into deductive categories of human-nature connectedness and associating inductive change patterns with deduced phases within the adaptive cycle, we defined five system spatial archetypes and three archetypical evolutionary patterns, revealing the typical interaction between them. This enabled us to understand sustainability challenges for each interaction, formulating seven tailored solutions to promote place-based development in human settlements. Generally, our approach showcases considerable potential in uncovering human settlement challenges, ultimately contributing to addressing these challenges at the local level within the broader context of global sustainability issues. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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22 pages, 26108 KiB

Open AccessArticle

Assessing the Urban Vacant Land Potential for Infill Housing: A Case Study in Oklahoma City, USA

by Francesco Cianfarani, Mohamed Abdelkarim, Deborah Richards and Rajith Kumar Kedarisetty

Urban Sci. 2023, 7(4), 101; https://doi.org/10.3390/urbansci7040101 - 26 Sep 2023

Cited by 1 | Viewed by 4163

Abstract

Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA [...] Read more.

Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study’s social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC’s urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC’s housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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20 pages, 9845 KiB

Open AccessArticle

A CA–Markov-Based Simulation and Prediction of LULC Changes over the Nyabarongo River Basin, Rwanda

by Aboubakar Gasirabo, Chen Xi, Baligira R. Hamad and Umwali Dufatanye Edovia

Land 2023, 12(9), 1788; https://doi.org/10.3390/land12091788 - 15 Sep 2023

Cited by 12 | Viewed by 2414

Abstract

Over the past few decades, the growth of population and the development of the economy have had a significant impact on the way land is used and covered (LULC) in the Nile Nyabarongo River basin. However, there is limited knowledge about the patterns [...] Read more.

Over the past few decades, the growth of population and the development of the economy have had a significant impact on the way land is used and covered (LULC) in the Nile Nyabarongo River basin. However, there is limited knowledge about the patterns of land use and the mechanisms that drive changes in these patterns because of human activities. Therefore, it is crucial to examine how land use and cover are shifting in this area, identify the factors responsible for these changes, and forecast future patterns. This study sought (1) to evaluate the changes in LULC from 1990 to 2020 and (2) to predict future fluctuations until 2060. By analyzing the LULC data for the years 1990, 2000, 2010, and 2020, this study simulated the future LULC patterns of the area for the next 30 years using the LULC transition matrix and the Markov chain model. The study classified the LULC into five categories: forestland, grassland, cropland, settlement, and water. The results revealed that there will be significant changes in the LULC of the study area from 2030 to 2060. The forest area is projected to decrease by 801.7 km, 771.6 km, and 508.2 km, while the cropland area will expand by 6307.2 km, 6249.2 km, and 6420.6 km during this period. The grassland area will experience a small increase of 761.1 km, 802.4 km, and 859.1 km, and the settlement area will also grow by 355.2 km, 407.4 km, and 453.2 km. In contrast, the water area will decrease by 55.9 km, 50.5 km, and 40 km. The ongoing pattern of LULCC is expected to persist over the next three decades, with an increase in cropland area and grassland. This study’s findings can provide valuable insights for land use planners and water resource managers in developing fair land use and water resource management policies for the entire region, enabling them to make well-informed decisions. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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18 pages, 5448 KiB

Open AccessArticle

Land Use and Land Cover Changes in Kabul, Afghanistan Focusing on the Drivers Impacting Urban Dynamics during Five Decades 1973–2020

by Hayatullah Hekmat, Tauseef Ahmad, Suraj Kumar Singh, Shruti Kanga, Gowhar Meraj and Pankaj Kumar

Geomatics 2023, 3(3), 447-464; https://doi.org/10.3390/geomatics3030024 - 9 Sep 2023

Cited by 6 | Viewed by 3628

Abstract

This study delves into the patterns of urban expansion in Kabul, using Landsat and Sentinel satellite imagery as primary tools for analysis. We classified land use and land cover (LULC) into five distinct categories: water bodies, vegetation, barren land, barren rocky terrain, and [...] Read more.

This study delves into the patterns of urban expansion in Kabul, using Landsat and Sentinel satellite imagery as primary tools for analysis. We classified land use and land cover (LULC) into five distinct categories: water bodies, vegetation, barren land, barren rocky terrain, and buildings. The necessary data processing and analysis was conducted using ERDAS Imagine v.2015 and ArcGIS 10.8 software. Our main objective was to scrutinize changes in LULC across five discrete decades. Additionally, we traced the long-term evolution of built-up areas in Kabul from 1973 to 2020. The classified satellite images revealed significant changes across all categories. For instance, the area of built-up land reduced from 29.91% in 2013 to 23.84% in 2020, while barren land saw a decrease from 33.3% to 28.4% over the same period. Conversely, the proportion of barren rocky terrain exhibited an increase from 22.89% in 2013 to 29.97% in 2020. Minor yet notable shifts were observed in the categories of water bodies and vegetated land use. The percentage of water bodies shrank from 2.51% in 2003 to 1.30% in 2013, and the extent of vegetated land use showed a decline from 13.61% in 2003 to 12.6% in 2013. Our study unveiled evolving land use patterns over time, with specific periods recording an increase in barren land and a slight rise in vegetated areas. These findings underscored the dynamic transformation of Kabul’s urban landscape over the years, with significant implications for urban planning and sustainability. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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16 pages, 3420 KiB

Open AccessArticle

Optimization Method for Land Use of the Xi’an Rail Transit Station Area Based on a Multi-Objective Model

by Haiyan Tong, Xiao Dong and Jiaping Liu

Land 2023, 12(9), 1705; https://doi.org/10.3390/land12091705 - 31 Aug 2023

Cited by 2 | Viewed by 1353

Abstract

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective [...] Read more.

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective function, constraint conditions, and the solution process. In response to this, a new multi-objective optimization model for rail transit station land use was built. With station space efficiency as the starting point, the three objectives of the model optimization were the traffic volume, environment quality, and land balance of the rail transit station, and the constraint conditions were the plot ratio, environment quality, and efficiency level. Lingo was used to solve the optimal plot ratio of different types of land use intensity. Compared with the non-inferior solution of the rail transit station area multi-objective original model, the ideal plot ratio of various land uses obtained by the optimized new model was more reasonable. There was a relatively large gap between the non-inferior solutions of some original models and the actual conditions. In contrast, the optimized new model had stronger maneuverability. The deviation ranges of the two models were −0.4% to 0.9% on the residential land plot ratio adjustment index, −3.2% to 4.8% on the public land plot ratio adjustment index, and 1.1% to 1.9% on the commercial land plot ratio adjustment index. This research aimed to provide a basis and reference for the land use and planning of Xi’an rail transit station. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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28 pages, 10752 KiB

Open AccessArticle

The Role of the Master Plan in City Development, Latakia Master Plan in an International Context

by Nebras Khadour, Albert Fekete and Máté Sárospataki

Land 2023, 12(8), 1634; https://doi.org/10.3390/land12081634 - 20 Aug 2023

Cited by 2 | Viewed by 8814

Abstract

The master plan has been a critical instrument for shaping the development of cities worldwide. This article delves into the impact of a well-designed master plan on shaping and transforming the structure of a city, while also exploring the various aspects that can [...] Read more.

The master plan has been a critical instrument for shaping the development of cities worldwide. This article delves into the impact of a well-designed master plan on shaping and transforming the structure of a city, while also exploring the various aspects that can be adapted in different contexts and conditions. The article aims to highlight how an effective master plan can drive development, guide urban growth, and offer a comprehensive framework for decision-making. Specifically, this study analyses the Latakia (SY) master plan, which was proposed in 2008, and compares it with the master plans of Barcelona (ES) and Montpellier (FR), two cities with significant experience in master planning. The analysis was conducted using several key criteria, such as general vision, housing policies, urban mobility, and green network. The results showed that urban development strategies in the Latakia master plan were of limited efficiency range compared to the other case studies, as it focused on tourism and economic development rather than providing an approach for sustainable city development. Therefore, this study recommends revising the development strategies of the Latakia master plan and addressing its limitations to improve the city’s structure, increase its sustainability, and quality of life. This article contributes to the existing body of knowledge on master planning by providing a critical evaluation of urban development strategies and offering a roadmap for future master plans. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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28 pages, 6689 KiB

Open AccessArticle

Assessment of Land Ecological Security from 2000 to 2020 in the Chengdu Plain Region of China

by Lindan Zhang, Wenfu Peng and Ji Zhang

Land 2023, 12(7), 1448; https://doi.org/10.3390/land12071448 - 20 Jul 2023

Cited by 18 | Viewed by 1907

Abstract

The purpose of land ecological security (LES) assessment is to evaluate the influence of land use and human activities on the land ecosystem. Its ultimate objective is to offer decision-making assistance and direction for safeguarding and rejuvenating the well-being and effectiveness of the [...] Read more.

The purpose of land ecological security (LES) assessment is to evaluate the influence of land use and human activities on the land ecosystem. Its ultimate objective is to offer decision-making assistance and direction for safeguarding and rejuvenating the well-being and effectiveness of the land ecosystem. However, it is important to note that there are still significant uncertainties associated with current land ecological safety assessments. This paper presents a comprehensive evaluation model that combines the strengths of subjective and objective weighting methods. The model is built upon an index system developed using the Pressure-State-Response (PSR) framework. To verify the level of LES, theThe results of classifying the total ecosystem service valueTotal Ecosystem Service Value are utilized to verify the level of LES. Furthermore, spatial distribution patterns of regional land ecological safety levels are analyzed using statistical techniques, such as Moran’s I, Mann–Whitney U-test, and Kruskal–Wallis H-test. The findings indicate that: (1) theThe evaluation model developed in this paper achieves a validation accuracy of 75.55%, indicating that it provides a more accurate reflection of the level of land ecological safety in the region; (2) The ecological security index is generally safe, with a mean value in the moderate safety range. It experienced a turning point in 2010, showing initial deterioration followed by improvement, mainly due to the transition between unsafe and relatively safe zones. (3) The level of economic development, topography, and urban-–rural structure are significant factors influencing the spatial concentration of LES in the region, ultimately shaping the spatial pattern of LES in the Chengdu Plain region. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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16 pages, 6519 KiB

Open AccessReview

Urban Land Use Survey Methods: A Discussion on Their Evolution

by Ioannis A. Pissourios

Urban Sci. 2023, 7(3), 76; https://doi.org/10.3390/urbansci7030076 - 18 Jul 2023

Cited by 2 | Viewed by 5412

Abstract

Although the tradition of surveying and analyzing urban land uses for town planning purposes dates back to the 19th century, the evolution of survey methods has not been studied in detail. With the intention of filling this gap, the present article reviews the [...] Read more.

Although the tradition of surveying and analyzing urban land uses for town planning purposes dates back to the 19th century, the evolution of survey methods has not been studied in detail. With the intention of filling this gap, the present article reviews the pertinent Anglo-American literature on survey methods, published from the beginning of the 20th century to date, and highlights the key contributions. Additionally, it proposes a periodization of the methodological evolution in three phases and identifies the main discussions developed on survey methodology, so as to provide a basis for more structured research on the subject matter. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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16 pages, 6037 KiB

Open AccessArticle

Evolution Pattern of Blue–Green Space in New Urban Districts and Its Driving Factors: A Case Study of Zhengdong New District in China

by Yanhe Niu, Sheng Jiao, Shaozhen Tang, Xi Tang and Jingwen Yin

Water 2023, 15(13), 2417; https://doi.org/10.3390/w15132417 - 29 Jun 2023

Cited by 5 | Viewed by 2574

Abstract

Understanding the spatial–temporal evolution of the blue–green space (BGS) is crucial for urban planning and ecological security protection. However, the evolutionary patterns and driving factors of the BGS in new urban districts remain unclear. Based on the classical qualitative models, “patch–corridor–matrix” and “sustainability [...] Read more.

Understanding the spatial–temporal evolution of the blue–green space (BGS) is crucial for urban planning and ecological security protection. However, the evolutionary patterns and driving factors of the BGS in new urban districts remain unclear. Based on the classical qualitative models, “patch–corridor–matrix” and “sustainability prism”, this study adopted the land use transition matrix and landscape index to quantify evolution patterns, and Pearson correlation and geographical detector analysis methods to reveal the driving factors. Taking Zhengdong New District as a case study, the results indicated the following: (1) The BGS rate was reduced by 35% from 2003 to 2021, with the most significant decrease in cultivated lands. (2) The evolution pattern of BGS alternated sequentially among ecological, disorderly, and balanced states. Among them, urban green spaces tended towards a more stable and aggregated state. Other BGSs became more fragmented and discontinuous. (3) The “sustainability prism” model consists of four driving factors, including social economy, rainwater safety, ecological liveability, and physical geography. (4) Socioeconomic factors significantly decreased the BGS, as indicated by the correlation coefficients of −0.988 and −0.978 between built-up areas and population and gross domestic products, respectively. Physical geographic factors played weak roles in the evolution of the BGS. Meanwhile, rainwater safety and ecological liveability positively affected the BGS. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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22 pages, 10934 KiB

Open AccessArticle

Identification and Classification of Urban Shrinkage in Northeast China

by Xiaosong Ma, Qingwu Yan, Qinke Pan, Xingshan Chen and Guie Li

Land 2023, 12(6), 1245; https://doi.org/10.3390/land12061245 - 17 Jun 2023

Cited by 6 | Viewed by 2808

Abstract

The phenomenon of shrinking cities is a significant challenge faced by many cities today. To more accurately identify the leading factors driving urban shrinkage and develop rational recommendations, precise identification and classification of urban shrinkage has become an indispensable part of the process. [...] Read more.

The phenomenon of shrinking cities is a significant challenge faced by many cities today. To more accurately identify the leading factors driving urban shrinkage and develop rational recommendations, precise identification and classification of urban shrinkage has become an indispensable part of the process. This paper focuses on the typical population loss region of China’s three northeastern provinces, using 497 identified physical cities as the basic research unit. Based on multi-source geographical big data and utilizing the geographically weighted regression (GWR) model, spatial modeling of population in the three provinces of northeast China was conducted, resulting in spatialized population data, followed by identification and classification of shrinking cities among the physical cities. Cities with a total population change rate of less than 0 are defined as shrinking cities. In cities where the total population change rate is greater than 0, cities with both a city shrinking area ratio and a decreased population ratio greater than 5% are defined as locally shrinking cities. Based on this, 90 (18.1%) shrinking cities and 118 (23.7%) locally shrinking cities were identified within the three provinces of northeast China. The phenomenon of urban shrinkage is distributed throughout various regions, mainly in smaller cities located near larger cities. According to the standards of the urban shrinkage classification model, the spatial pattern of population loss regions was divided into four types, identifying 13 (6.3%) global type, 111 (53.4%) concentrated type, 64 (30.7%) perforated type, and 20 (9.6%) edge type. Analysis of shrinking cities based on their classification revealed that the main reasons for urban shrinkage are the decline and dissolution of large industrial enterprises, abandonment and neglect of buildings, and unreasonable design planning in cities. Economic development and inward population flow can be promoted in shrinking cities by creating job opportunities, improving living standards, developing transportation, adjusting urban planning or concentrating urban population, as well as vigorously developing urban center areas. These measures can provide support for the revival and development of shrinking cities. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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21 pages, 2598 KiB

Open AccessArticle

How Does New Energy Demonstration City Policy Promote Urban Land Use Efficiency in China? The Mediating Effect of Industrial Structure

by Mengcheng Wang, Nana Lin, Youming Dong and Yifeng Tang

Land 2023, 12(5), 1100; https://doi.org/10.3390/land12051100 - 20 May 2023

Cited by 5 | Viewed by 2052

Abstract

As an effective measure to solve the dilemma of urban energy consumption and economic development, the new energy demonstration city (NEDC) policy in China could greatly promote the development of the new energy industry and urban economy. This study aims to [...] Read more.

As an effective measure to solve the dilemma of urban energy consumption and economic development, the new energy demonstration city (NEDC) policy in China could greatly promote the development of the new energy industry and urban economy. This study aims to explore how the NEDC policy effectively promotes the growth of urban land use efficiency (ULUE), an essential indicator of economic development, through the urban industrial structure. Based on the panel data of 285 Chinese cities during 2003–2019, this study took the NEDC policy as a quasi-natural experiment and employed the PSM-DID method and the mediating effect model to objectively evaluate its policy effects. We found that the NEDC policy could significantly promote the growth of the ULUE. Specifically, the ULUE has been significantly improved by 17.0%. The NEDC policy could also promote the ULUE indirectly through the mediating effect of industrial structure advancement (ISA), but the mediating effect of industrial structure rationalization (ISR) was not significant. Furthermore, the promotional effect of the NEDC policy on the ULUE has regional heterogeneity. Compared with eastern cities and high-innovation cities, central and western cities and medium-innovation and low-innovation cities can obtain much higher promotion effects. This study may provide some policy inspiration for policymakers to support low-corban and sustainable economic development and urban land use. Full article

(This article belongs to the Topic Urban Land Use and Spatial Analysis)

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