Edge Expansion Research Articles

Mapping and evaluating spatiotemporal patterns of urban expansion in global earthquake-affected areas: a nighttime light remote sensing perspective

ABSTRACT Amidst the backdrop of frequent global earthquakes, assessing the spatiotemporal dynamics of urban expansion in earthquake-affected areas is imperative for sustainable development insights. The current analyses, however, are primarily focused on administrative units or some specific natural units. Here, we quantified spatiotemporal patterns of urban expansion from 2000 to 2020 in global earthquake-affected areas globally. Specifically, we delineated such areas using data from earthquakes of magnitude 5.5 and above since 1965. Then, employing nighttime light remote sensing data, we extracted urban entities and systematically evaluated the spatiotemporal patterns of urban expansion in earthquake-affected areas. The findings indicate a phase-based differential growth in urban expansion in earthquake-affected areas from 2000 to 2020. The average deceleration factor for urban areas in earthquake-affected areas over the past 20 years is 128.67%. Urban expansion in earthquake-affected areas is growing at a rapid pace, except for Europe and North America. In addition, 66.7% of urban expansion in global earthquake-affected areas presents low-density sprawl and solitary edge expansion trends, potentially affecting population density and land use efficiency. This study offers the most exhaustive analysis of urban expansion in earthquake-affected areas in recent decades and calls for administration beyond administrative boundaries to some extent.

Extraction of agricultural plastic greenhouses based on a U-Net Convolutional Neural Network Coupled with edge expansion and loss function improvement

ABSTRACT Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more effectively than traditional interpretation methods, which face challenges like high workloads and poor repeatability. In this study, we aim to enhance the inventorying of Agricultural Plastic Greenhouses (APGs) by improving the extraction accuracy of their locations and numbers through remote sensing techniques. Utilizing GF-7 satellite imagery, we propose an enhanced U-Net convolutional neural network (CNN) model that incorporates edge information expansion and a joint loss function to optimize performance. The primary objective is to provide a rapid and accurate method for mapping APGs, which is crucial for effective agricultural management and environmental monitoring. The U-Net network’s accuracy was enhanced by 1.1% after expanding 3 × 3sample edge information, and further by 1.9% by combining edge extension and loss function constraints. Our results demonstrate that the modified U-Net model significantly improves extraction accuracy compared to traditional methods, thereby facilitating better inventory management and planning for agricultural cash crops. This advancement not only supports farmers in optimizing resources but also contributes to sustainable agricultural practices by enabling precise monitoring of APG distribution. Implication Statement Compared to traditional interpretation methods, which suffer problems such as heavy workloads, small adaptation ranges and poor repeatability, deep learning network models can better extract target features from remote sensing images. In this study, we used GF-7 image data to improve the traditional U-Net convolutional neural network (CNN) model. The Canny operator and Gaussian kernel (GK) function were used for sample edge expansion, and the binary cross-entropy and GK functions were used to jointly constrain the loss. Finally, APGs were accurately extracted and compared to those obtained with the original model. The results indicated that the APG extraction accuracy of the U-Net network was improved through the expansion of sample edge information and adoption of joint loss function constraints.

Urban growth simulation guided by ecosystem service trade-offs in Wuhan metropolitan area: Methods and implications for spatial planning

The effective integration of ecosystem services (ESs) and urban growth simulation is crucial for spatial planning decisions that support sustainable and high-quality development. Interactions (i.e., trade-offs, synergies, and irrelevance) generally exist among ESs, however, few studies have been done on the methodology for simulating urban growth that optimizes the synergistic effect of ESs. In this study, the Wuhan metropolitan area was taken as the research area. Four key ESs in 2000, 2010, and 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil retention (SR) were evaluated by using the InVEST model. Then the ordered weighted averaging (OWA) method was applied to optimally allocate ESs trade-offs and identify ecological priority protection areas (EPPAs). Finally, the PLUS model was used to simulate urban growth scenarios under different levels of ESs protection constraints and propose spatial planning strategies. The results revealed the following. (1) From 2000 to 2020, the three ESs (i.e., WY, CS, and HQ) exhibited the spatial distribution pattern with high in the east and low in the west, and higher in the woodland than in built-up areas, except SR, which remained at a weak level throughout the region. (2) During the 20 years, SR and the other three ESs, HQ and CS showed a synergistic relationship; WY exhibited a very weak trade-off with HQ; and WY and CS changed from a very weak trade-off to a weak synergy. (3) Seven ecosystem service patterns (ESPs) were generated, and ESP 5 was compared as the ideal option. The weights of SR, WY, CS, and HQ in this pattern were 0.063, 0.187, 0.313, and 0.437, respectively. (4) By 2030, the built-up areas will exhibit edge expansion and interconnection development trends, with the high-constraint ecological protection scenario as the most compact mode, and the spatial structure of “two districts, one axis, four cities as one” is consistent with the development tendency. Our findings can help to enrich the method of urban growth management oriented by ecological protection, and provide a scientific basis for ecological environment restoration and land use spatial planning practices.

Can internal range structure predict range shifts?

Poleward and uphill range shifts are a common-but variable-response to climate change. We lack understanding regarding this interspecific variation; for example, functional traits show weak or mixed ability to predict range shifts. Characteristics of species' ranges may enhance prediction of range shifts. However, the explanatory power of many range characteristics-especially within-range abundance patterns-remains untested. Here, we introduce a hypothesis framework for predicting range-limit population trends and range shifts from the internal structure of the geographic range, specifically range edge hardness, defined as abundance within range edges relative to the whole range. The inertia hypothesis predicts that high edge abundance facilitates expansions along the leading range edge but creates inertia (either moreindividuals must disperse or perish) at the trailing range edge such that the trailing edge recedes slowly. In contrast, the limitation hypothesis suggests that hard range edges are the signature of strong limits (e.g. biotic interactions) that force faster contraction of the trailing edge but block expansions at the leading edge of the range. Using a long-term avian monitoring dataset from northern Minnesota, USA, we estimated population trends for 35 trailing-edge species and 18 leading-edge species and modelled their population trends as a function of range edge hardness derived from eBird data. We found limited evidence of associations between range edge hardness and range-limit population trends. Trailing-edge species with harder range edges were slightly more likely to be declining, demonstrating weak support for the limitation hypothesis. In contrast, leading-edge species with harder range edges were slightly more likely to be increasing, demonstrating weak support for the inertia hypothesis. These opposing results for the leading and trailing range edges might suggest that different mechanisms underpin range expansions and contractions, respectively. As data and state-of-the-art modelling efforts continue to proliferate, we will be ever better equipped to map abundance patterns within species' ranges, offering opportunities to anticipate range shifts through the lens of the geographic range.

Exploring the Spatiotemporal Evolution Patterns and Determinants of Construction Land in Mianning County on the Eastern Edge of the Qinghai–Tibet Plateau

Studying the spatiotemporal evolution and driving forces behind construction land amidst the intricate ecological and geological setting on the eastern edge of the Qinghai–Tibet Plateau offers invaluable insights for local sustainable development in a landscape transition zone and ecologically fragile area. Using construction land data from four phases, spanning 1990 to 2020, in Mianning County, this study employs methodologies like the Landscape Expansion Index (LEI) and land use transfer matrix to delineate the spatiotemporal evolution characteristics of construction land. A comprehensive set of 12 influencing factors across five categories—geomorphology, geological activity, climate, river and vegetation environment, and social economy—were examined. The Geographically Weighted Regression (GWR) model was then employed to decipher the spatial distribution pattern of construction land in 1990 and 2020, shedding light on the driving mechanisms behind its changes over the three decades. The research reveals distinct patterns of construction land distribution and evolution in Mianning County, shaped by the ecological and geological landscape. Notably, the Anning River wide valley exhibits a concentrated and contiguous development mode, while the Yalong River deep valley showcases a decentralized development pattern, and the Dadu River basin manifests an aggregation development mode centered around high mountain lakes. Over the study period, all three river basins witnessed varying degrees of construction land expansion, transitioning from quantitative expansion to qualitative enhancement. Edge expansion predominantly characterizes the expansion mode, complemented by leapfrog and infilling modes, accompanied by conversions from cropland and forest land to construction land. An analysis of the spatial pattern and drivers of construction land change highlights human-induced factors dominating the Anning River Basin, contrasting with natural factors prevailing in the Yalong River Basin and the Dadu River Basin. Future efforts should prioritize climate change considerations and environmental capacity, aiming for an ecologically resilient spatial pattern of construction land.

Urban expansion and vegetation dynamics: The role of protected areas in preventing vegetation loss in a growing mega city

The decrease in vegetation cover due to urban expansion poses serious challenge to urban sustainability. Protected areas (PAs) are the most effective tools to prevent the loss of urban vegetation cover and to control urban expansion. Hence, this study aims to assess the importance of PAs in protecting urban vegetation and the urban expansion in the mega city of Delhi. For this, Landsat datasets were used for land use and land cover (LULC) mapping and then land cover change rate (LCCR) and land cover intensity (LCI) were calculated. For assessing urban expansion dynamics, mean landscape expansion index (MLEI) and the area-weighted LEI (AWLEI) were calculated. To evaluate the significance of PAs in protecting vegetation cover, kernel density estimation (KDE) was applied to assess the spatial variation and concentration of vegetation cover under different PAs. The result shows that urban expansion in Delhi was initially characterized by edge expansion during 1991–2001, followed by outlying expansion of built-up area during 2001–2021, while infilling of open and vegetated areas by built-up area was consistent during 1991–2021. Vegetation cover on the other hand, has followed a fluctuating trend in the city, but has overall it has declined from 13.36% to 9.30% during 1991–2021. The vegetation cover has declined significantly in eastern, northern, and western parts of Delhi but has increased significantly in central and southern parts, especially during 2001–21. This is because the central and southern parts of Delhi are well planned and have several PAs while the western, northern, and eastern parts of Delhi are unplanned regions and have only a few PAs. The KDE chart shows that the PAs have played an important role in protecting the vegetation cover in Delhi with R2 value > 0.70. Hence, this study suggests to give special emphasis on preservation and expansion of PAs in urban planning for the long-term conservation of urban vegetation cover and sustainable urban development.

Short-term evolution pattern in salt marsh landscapes: the importance of physical constraints

ContextSalt marsh landscapes at the land-sea interfaces exhibit contrasting spatiotemporal dynamics, resulting from varying physical constraints that limit new marsh establishment. The expansion of salt marsh landscapes towards the sea or their retreat towards the land is determined by patch-level changes, relying on the balance of power between the intrinsic biota traits and external physical disturbances.ObjectivesExamine how marsh dynamics respond to physical constraints, and clarify the pathway from coupled physical processes involving hydrodynamic forces, sediment transport, and morphological changes to rapid patch evolution and landscape changes.MethodsWe defined and distinguished four types of marsh changes based on patch proximities from five-month drone images in two typical marsh pioneer zones of the Yangtze Estuary, China: outlying expansion, edge expansion, infilling expansion, and retreat. Hydrodynamics and sediment transport were synchronously measured and compared near the two marsh edges, and morphological changes were generated by drone-derived digital elevation models (DEMs).ResultsWe identified distinct seasonal patterns of net marsh expansion at the accretion-prone site, that is: Net marsh expansion started from the outlying expansion in spring, followed by edge expansion in summer and infilling expansion in autumn. However, at the erosion-prone site that experienced high bed shear stress, low sediment availability and high seaward sediment transport, we only observed limited infilling and edge expansion in spring. This suggests that the potential for long-distance patch formation beyond the initial marsh edges is diminished in areas subjected to intensive physical disturbances.ConclusionsPatch evolution dynamics in response to site-specific physical constraints drive state differentiation of salt marsh landscape changes. Consequently, the heterogeneous evolution in salt marsh landscapes should be taken into account in restoration practice.

Characterizing urban actively populated area growth in the Yangtze River Delta using nighttime light data

Understanding the spatiotemporal evolution of urban actively populated area (UAPA) in urban agglomerations is crucial for sustainable development. This study fills a gap in previous research that overlooked urban population dynamics, leading to inaccurate UAPA characterizations. We utilized nighttime light (NTL) data, which reflects both urban construction status and population dynamics, to characterize UAPA growth pattern in the Yangtze River Delta. We developed a novel search method for extracting UAPA that demonstrated greater accuracy and adaptability than traditional threshold method. We employed expansion rate (ER) and annual growth rate (AGR), and a method for recognizing urban expansion patterns, to illustrate the characteristics and spatial changes in the Yangtze River Delta. We divided the research stage (1992–2019) into six stages based on China’s Five-Year Plan. The results demonstrated that the UAPA size at the end of the sixth stage (2016–2019) was about 6 times greater than that at the end of the first stage (1992–1995). The ER and AGR were approximately 15% during the first stage (1992–1995), and dropped dramatically following the fourth stage (2006–2010). Edge expansion is a typical predominant spatial expansion pattern for UAPA. While the proportion of patches with newly generated expansion showed an initial upward and then a downward trend, the percentage of patches with infilling expansion exhibited a pattern of first decreasing and then increasing. This study aims to provide support for future development planning and policy formulation.

The population exposure risk of urban heat island effect: From the perspective of urban spatial expansion in China

Urban spatial expansion is a critical aspect of urbanization, but it must occur in a manner that ensures the sustainable development of the urban climate. The primary objective of this study was to assess the population exposure risk of urban heat island (UHI) effect from the perspective of urban spatial expansion. Additionally, the population weighted urban heat island intensity (UHII) index (Ep) was proposed to compare the population exposure risk of UHI effects in different types of urban spatial expansion in China during the summer of 2005–2020. It was found that, in China, urban land increased by an area of 74,894 km2 (1.01-fold) from 2005 to 2020. Leapfrogging emerged as the predominant pattern of urban spatial expansion and was primarily driven by the conversion of cropland to urban land. It witnessed a significant increase in the area covered by UHIs of 107,119 km2 (1.20-fold), accompanied by a rise in the UHII of 0.12 °C in China. Notably, the UHII for infilling urban expansion was significantly higher at 2.03 °C, in contrast to 1.66 °C for edge expansion and 1.47 °C for leapfrogging. Correspondingly, the Ep was markedly larger under the infilling urban expansion (2.10 °C) in contrast to edge expansion (1.75 °C) and leapfrogging (1.67 °C). However, edge expansion dominated the newly developed urban land, contributing to 18.60 % of the Ep, which was still far less than the contribution of the pre-existing urban land to Ep (61.24 %). Importantly, the dominant driver of the increased Ep was the increasing UHII. This study established a connection between inevitable urban spatial expansion and the population exposure risk of UHI effect, providing a strong theoretical basis and practical guidance for the active adaptation and mitigation of urban environmental hazards in urban regions.

A structure theorem for homology 4-manifolds with g2 ≤ 5

Numerous structural findings of homology manifolds have been derived in various ways in relation to g2-values. The homology 4-manifolds with g2≤5 are characterized combinatorially in this article. It is well-known that all homology 4-manifolds for g2≤2 are polytopal spheres. We demonstrate that homology 4-manifolds with g2≤5 are triangulated spheres and are derived from triangulated 4-spheres with g2≤2 by a series of connected sum, bistellar 1- and 2-moves, edge contraction, edge expansion, and edge flipping operations. We establish that the above inequality is optimally attainable, i.e., it cannot be extended to g2=6.

Analysing Sustainable Urban Growth: Spatio-Temporal Dynamics of Urban Expansion in Gampola Urban Centre

Urbanization is a dynamic process which can be considered as one of the most significant indicators of development. It occurs both horizontally and vertically on the Earth’s surface according to a pattern which has positive and negative implications. Some countries measure their development by the level of urbanization because it directly affects for a country’s economy. During past decades, Gampola urban centre was experiencing a gradual urban growth and several implications. This study focuses on investigating urban expansion pattern of Gampola during 16 years by analysing three distinct years 2006, 2013, and 2022. Geographic Information System (GIS) and Remote Sensing (RS) techniques were employed to examine spatio-temporal transformations and urban expansion patterns of Gampola and its outskirts. Landsat images for three distinct years were classified using pixel-based supervised classification to determine Land Use Land Cover (LULC) of the study area which achieved an impressive overall accuracy of approximately 90%. Four major LULC types were identified those are prominent in the area namely, water, built-up, forest, paddy lands and bare lands. Temporal changes of vegetation cover for 16 years were analysed further using Normalized Difference Vegetation Index (NDVI). Consequent implications on Land Surface Temperature (LST) across the time period were analysed using thermal band of Landsat images. NDVI value has decreased from +0.7 to +0.5 during 2006-2013 and up to +0.4 during 2013-2022. LST analysis revealed a rise in temperature, increasing from 29.89° C up to 31.11° C during 2006- 2013 and surging to 33.14° C by 2022. Quantifying the urban expansion of Gampola was performed using buffer analysis. Analysis of urban areas grown within 1km distanced five buffer zones from urban core was performed to quantify urban expansion. Fourth buffer zone exhibited the highest urban growth, while first buffer zone displayed lowest urban growth during 2006 to 2022. In the interval between 2013 and 2022, the fifth buffer zone appeared as the zone with the highest urban growth. Further, Landscape Expansion Index (LEI) was employed to identify the urban expansion patterns, and Gampola urban area displayed an Edge Expansion growth type. We recommend the development of urbanized areas in a sustainable and efficient manner to mitigate adverse consequences and promote balanced growth.
 
 Keywords: GIS and RS, Urban expansion, LEI, LST, Sustainable development

Optimizing Mesh to Improve the Triangular Expansion Algorithm for Computing Visibility Regions

This paper addresses the problem of improving the query performance of the triangular expansion algorithm (TEA) for computing visibility regions by finding the most advantageous instance of the triangular mesh, the preprocessing structure. The TEA recursively traverses the mesh while keeping track of the visible region—the set of all points visible from a query point in a polygonal world. We show that the measured query time is approximately proportional to the number of triangle edge expansions during the mesh traversal. We propose a new type of triangular mesh that minimizes the expected number of expansions assuming the query points are drawn from a known probability distribution. We design a heuristic method to approximate the mesh and evaluate the approach on many challenging instances that resemble real-world environments. The proposed mesh improves the mean query times by 12–16% compared to the reference constrained Delaunay triangulation. The approach is suitable to boost offline applications that require computing millions of queries without addressing the preprocessing time. The implementation is publicly available to replicate our experiments and serve the community.

Spatial congruency or discrepancy? Exploring the spatiotemporal dynamics of built-up expansion patterns and flood risk

Most coastal cities have been experiencing unprecedented urbanization-induced flood risk, climatic events, and haphazard anthropogenic activities, jeopardizing residents' lives and building environments. Despite mounting flood-related studies, analyzing the correlation between the spatiotemporal dynamics of Built-up Expansion patterns (BE) and flood risk remains unknown and holds divergent perspectives. In this context, the coastal city of Alexandria, Egypt, characterized by multiple urban patterns and experiencing heavy rainfall annually, was selected as a testbed. Our method defined the spatiotemporal rates of BE from 1995 to 2023, quantified flood risk spatially, and finally investigated the correlation between BE and flood risk through spatial and statistical analysis. Our results show the built-up area occupied 30.32 % of the total city area till 2023, and the infilling pattern dominated the BE growth by 45.21 % of the total built-up area, followed by leapfrogging and edge expansion by 33.25 % and 21.55 %, respectively. The unplanned-infilling pattern is predominantly highly correlated with the flood-vulnerable peaks (correlation coefficient (rk) = 0.975, p-value < 0.05) and lowers dramatically towards planned-infilling regions with flood protections. Meanwhile, a spatial mismatch exists between high-risk peaks and leapfrogging and edge expansion (rk = 0.118 and 0.662, respectively, with a p-value < 0.01), indicating that controlling the built-up amount is inadequate for mitigating flood risk. Porosity-based urban configuration and spatial distribution of built-up patches in harmony with nature-based solutions are recommended for shaping flood-resilient and effective urban planning.

Resilient urban expansion: Identifying critical conflict patches by integrating flood risk and land use predictions: A case study of Min Delta Urban Agglomerations in China

The increasing occurrence of floods due to global climate change is a challenge to the growth of urban resilience. However, few studies have investigated strategies to avoid flood risks during long-term and comprehensive land use and development. To address this issue, this study proposes a method that integrates flood risk and land use predictions to identify critical conflict patches that impact urban resilience. Further strategies for differential development based on the attributes of these critical conflict patches were formulated. Taking the Min Delta Urban Agglomeration (MDUA) in China as a case study, critical conflict patches for expanded urban resilience were identified based on a multi-source data set, a random forest (RF) algorithm, and a patch-generating land use simulation model (PLUS) combined with cellular automata (CA). These patches were categorized into three levels of risk prediction—low, medium, and high risk—based on flood risk attributes. These risk forecast levels were further divided into seven categories. The best land use approach was determined by assessing the quantity, spatial distribution, and risk-based priority ranking of these conflict patches. The results demonstrated that most conflicting patches were located in bare land within built-up areas, urban-rural intersection zones, and remote suburban areas with high traffic accessibility. The identified conflicting patches were applied to three different land use patterns: intra-city renewal, urban edge expansion, and the creation of derived cities. The total number of conflicting patches for land use decisions in the MDUA was 122 (170.82 km2) in 2025 and 685 (1205.81 km2) in 2035. Approximately 108 km2 of urban land was added for resilience expansion following optimization. In all development scenarios, the optimized land use pattern facilitated resilient growth of urban development while maintaining the stability of the flood disaster environment. Based on our methodology and case study, we proposed a decision-making framework to assist cities or potential urban regions to avoid water-related problems and related issues. This approach could also contribute to decisions involving different geographical areas for resilient land use.

Banda Aceh Metamorphosis: Analyzing The Impact of Urban Sprawl in Meuraxa District

The rapid development of Banda Aceh City has led to a surge in population growth, causing unstructured development in suburban areas, particularly in Meuraxa District, where the land use has undergone a significant transformation. This research aims to analyze the impact of urban sprawl on the form of the city of Banda Aceh in terms of the physical condition of Meuraxa District. Utilizing a quantitative approach with geographic analysis, the study employs remote sensing and GIS (Geographic Information System) applications, specifically ArcGIS SHP map data. The analysis covers the period from 2010 to 2020, revealing a noteworthy increase in housing land use in Meuraxa District. The findings indicate that Meuraxa District has experienced urban sprawl, evidenced by the reduction in undeveloped land, there was an increase in land use for housing, improved accessibility, and increased availability of facilities. The GIS data-based urban sprawl development model categorizes Meuraxa District as an "edge expansion" type, with a calculated T value falling in the 0 &lt; T &lt; 0.5 range.

Spatial and temporal inequity of urban land use efficiency in China: A perspective of dynamic expansion

In the face of conflicting land-resource supply and demand, land-use efficiency is critical for sustainable urbanization. In this study, we unified the consistent boundaries of land, population, and economic development, identified urban expansion patterns (infilling, edge expansion and leapfrogging), and precisely estimated urban land-use efficiency (ULUE) in 260 Chinese cities from the perspective of dynamic expansion during 2000–2015. With the consideration of the dynamics of outward expansion and internal development of urban land, the results showed that China's main expansion pattern gradually shifted from edge expansion with lower ULUEs to infilling with higher ULUEs. Over the 15-year period, ULUEs in all expansion areas increased from 0.065–0.18 to 0.093–0.31. Inequity remained significant in terms of expansion patterns, built-up layers, regions and urban sizes. ULUE increased more quickly in the super-large cities of the central and western regions, whereas it increased more slowly in the northeast and even decreased in expansion built-up area formed during 2005–2010 (EBUA (2005–2010)). Importantly, ULUE decreased in most cities with edge expansion. Based on the findings, we concluded that the urbanization of China was progressing toward sustainability but still had room for improvement, and we suggested that policymakers should pay more attention to the complex, systemic nature of urban development.

Experimental study on the diffusion characteristics of nonaqueous reactive expansive polymers in sand and gravel media under dynamic water conditions

Grouting is an effective method to solve water inrush from sand and gravel. However, due to the self-expandability of nonaqueous reactive expandable polymers, the diffusion behaviour of polymers in injected media becomes more complex, which brings great uncertainty to the selection of grouting parameters in grouting practice. For this reason, a series of diffusion experiments of nonaqueous reactive expansive polymers in sand and gravel media under dynamic water conditions were carried out using a homemade experimental device. The effects of grouting parameters such as dynamic pump pressure, mass fractal dimension, and grouting volume on the effective diffusion length and water plugging rate of the slurry were revealed. The results show that (1) the diffusion behaviour of nonaqueous reactive expansive polymers in sand and gravel media can be summarized as edge dispersion, downstream diffusion, and expansion diffusion. (2) The diffusion consolidated bodies of nonaqueous reactive expansive polymers mostly exhibit a hemispherical or columnar shape with a wide top and a narrow bottom. (3) The greater the pressure of the moving water pump is, the smaller the effective diffusion length of the slurry. Under the same grouting volume, with increasing mass fractal dimension, the effective diffusion length of the slurry first increases and then decreases. (4) Under the conditions of high dynamic water pump pressure and low mass fractal dimension, increasing the grouting volume has a better water plugging effect.

Analyzing spatial and geometrical patterns of Tiruchirappalli and Tier-urban centers using Spatial Metrics

Abstract Understanding spatial and geometrical patterns of urbanization is crucial in tackling associated problems. As urbanization progresses through various stages of development, it reflects different forms, patterns, and interactions based on its physical and functional aspects. Spatial metrics is a well-acclaimed technique for quantifying urban morphological characteristics. The current study was conducted for Tiruchirappalli and six tier-urban centers located within a 40-kilometers radius to comprehend the comparative growth and spatial patterns. The urban centers are divided into eight zones based on direction for more precise quantification. The study employed Landsat 5 and 8 satellite images to classify land use/cover for the periods 1996, 2008, and 2020. FRAGSTAT is the software application used to analyze spatial metrics, at patch, class, and landscape levels. The study generated a significant amount of data about spatial and geometric patterns of growth. Area, edge, and aggregation metrics indicated that zones in Manachanallur, Manapparai, Musiri, Thiruverumbur, and Thuraiyur had protrusive urban growth during the study period. Transport networks have been the instrumental factor for such growth. Diversity metrics revealed Tiruchirappalli and Thiruverumbur have abundant patches of various classes in many of their zones since they retain patches like open, vegetation, and water bodies extensively. Shape metrics across all urban centers during the period 1996-2008 were more irregular in shape; it has become significantly smooth during 2008-2020 due to infill developments on the fringe areas. The period 1996-2008 recorded a huge transition of open areas into built-ups, attributing to infill development, especially inside the urban centers; similarly, during the period 2008-2020, edge expansion has been recorded widely across the urban centers. The current study is a significant contribution to urban research in understanding relative spatial and geometric patterns of urbanization.

Understanding Urban Expansion and Its Landscape Responses with Long-Term Landsat Data in Guangzhou, China

Quantifying the spatio-temporal pattern of urban expansion is essential to understanding the ecological consequences of urbanization and supporting optimal urban management strategies. As one of the most developed regions in China, Guangzhou has experienced rapid urban expansion over the past decades. However, little is known about the detailed process of urban expansion across long-term periods. Combining remote sensing data with GIS techniques, we attempted to quantify the spatio-temporal pattern of urban expansion in Guangzhou. We mapped the urban landscape in Guangzhou using Landsat images between 1973 and 2017. The urban land developed and change process was also examined, including urban expansion direction, urban expansion types, and landscape responses to urban expansion. The results showed that the building nearly increased by 90-fold from 1973 to 2017, and over half of the newly developed buildings mainly came from farmland. Edge expansion is the main type of urban growth. The urban trajectory shows that the expansion mainly occurred in the southwest to northeast direction. Urban growth led to radical changes in the urban landscape, leading to sharp decreases in soil and farmland. The results from this study provide key information for future planning to make eco-friendly megacities as well as sustainable development.

A characterization of normal 3-pseudomanifolds with at most two singularities

Characterizing face-number-related invariants of a given class of simplicial complexes has been a central topic in combinatorial topology. In this regard, one of the well-known invariants is g2. Let K be a normal 3-pseudomanifold such that g2(K)≤g2(lk(v))+9 for some vertex v in K. Suppose either K has only one singularity or K has two singularities (at least) one of which is an RP2-singularity. We prove that K is obtained from some boundary complexes of 4-simplices by a sequence of operations of types connected sums, bistellar 1-moves, edge contractions, edge expansions, vertex foldings, and edge foldings. In case K has one singularity, |K| is a handlebody with its boundary coned off. Further, we prove that the above upper bound is sharp for such normal 3-pseudomanifolds.