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Decision Support Models and Algorithms for Determining the Anthropogenic Load of Large Urban Agglomerations in the Context of Digitalization
Abstract
Modern decision support systems in ecology are aimed at resolving the contradiction between the inability of megacities ecosystems to meet the growing needs of society. Scientific and methodological approaches have been developed to determine the anthropogenic load of large urban agglomerations in the context of digitalization based on cellular automata and network models of quantitative and qualitative characteristics of ecosystems. A comparative analysis of environmental and socio-economic indicators has been carried out, which makes it possible to assess the level of variation of the analyzed target indicators to ensure the sustainable development of megacities ecosystems.
KeywordsDecision makerEcosystemDigital transformationDecision support system
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Ecological security patterns are employed to characterize the health and integrity of an ecosystem. It is essential to achieve sustainable and high-quality development of cities and urban agglomerations and to enhance human well-being. Considering the Guanzhong Plain urban agglomeration as an example, this paper proposes a technical framework for the delineation of ecological security patterns at the urban agglomeration scale with the objective of protecting and restoring mountains-rivers-forests-farmlands-lakes-grasslands. The ecological sources were indicated by the importance-sensitivity ecological assessment method. Ecological corridors were identified by a minimum resistance model, and the ecological security pattern was derived. Twenty-three important ecological source sites were identified within the urban agglomeration, mainly located in the southern part of the Guanzhong Plain urban agglomeration, with an area of 9122.36 km², accounting for 8.52% of the study area. The ecological sensitivity of the mountainous areas was relatively high, with ecological corridors showing a denser distribution in the south. The results of the study suggest that green infrastructure in the northern region should be strengthened, that the ecological functions of ecologically sensitive areas should be protected and enhanced, and that the connectivity of ecological corridors should be strengthened. The results provide guidance for the optimization of regional ecological security patterns for and the joint prevention and control of environmental pollution in the Guanzhong Plain.
Urbanization provides benefit to modern civilization, while it also creates a series of ecological issues at different scales. The study of landscape pattern and connectivity change caused by urban agglomeration is the hotspot of regional ecological security research. In this study, morphological spatial pattern analysis (MSPA) and Patch Importance Index (dPC) were used to evaluate landscape heterogeneity and landscape connectivity in the Huangshui River Valley, Qinghai-Tibet Plateau. Then the spatial relationship was revealed by bivariate spatial autocorrelation analysis and three-dimensional curved surface graph. The results showed that in the past 30 years, urbanization has increased more than 25%, with the decrease of farmland and the fluctuation of natural habitat. Heterogeneity and fragmentation were more obvious in the central region with great urban agglomeration. MSPA revealed significant spatial differences in the interaction between natural habitat and urbanization. The landscape connectivity of natural habitat in the central region was severely damaged by urban agglomeration and was spatially correlated with the landscape pattern index. Three-dimensional surface graph showed that the connectivity of farmland and natural habitat experienced fluctuation to decline trend with the expansion of construction land, which indicating a complex correlation and interaction between different land use types. In order to maintain the integrity of the ecosystem, it was necessary to take effective measures to improve the sustainability of cities and appropriately limit the expansion of urbanization. This study explored the landscape heterogeneity and connectivity from perspectives of the whole landscape, natural habitat, construction land, farmland and their correlation, which provided a theoretical basis for further optimization of urban coordinated ecological management.
Global warming-induced land use change in middle and high latitude regions remains an important and challenging topic for sustainable development. Although a large amount of remote sensing imageries is available for extracting land use information, there are unavoidable inconsistencies among land use products from different platforms. This study proposes a framework which integrates multiscale fusion method and cellular automata to simulate spatiotemporal land use change in middle and high latitude regions. Five types of remote sensing-based land use products were used to extract land use information of Northeast China in 2001, 2009, and 2017. The results demonstrate that the fused land use product from the integration of remote sensing-multiscale fusion and cellular automata has a higher accuracy. The simulated land use map for 2017 using CA-Markov model was validated by the actual land use classification of 2017, and the stochastic Kappa (Kno), location related Kappa (Klocation) and traditional Kappa (Kstandard) were 0.90, 0.94 and 0.86, respectively. The results of land use change from 2001 to 2017 show the biggest increase (5.9%) in farmland, mainly from grassland and forest. The predicted results indicate that this trend will persist until 2025 with a continuous augmentation of farmland in Northeast China. The areas of grassland will decrease by 4.3% from 2017 to 2025, with a major conversion to farmland and forest. The increasing farmland is a potential threat to ecology environment in the region as it will heavily sacrifice grassland and forest. These findings provide useful information on understanding spatiotemporal land use change in middle and high latitude regions and allow us maintaining food security for sustainable development.
Context dependence is widely invoked to explain disparate results in ecology. It arises when the magnitude or sign of a relationship varies due to the conditions under which it is observed. Such variation, especially when unexplained, can lead to spurious or seemingly contradictory conclusions, which can limit understanding and our ability to transfer findings across studies, space, and time. Using examples from biological invasions, we identify two types of context dependence resulting from four sources: mechanistic context dependence arises from interaction effects; and apparent context dependence can arise from the presence of confounding factors, problems of statistical inference, and methodological differences among studies. Addressing context dependence is a critical challenge in ecology, essential for increased understanding and prediction.
Environmental projects have a high degree of uncertainty and risk of their implementation. In the process of assessing their effectiveness, it is necessary to take into account the interests of all the participants in the environmental project. The environmental projects effectiveness evaluation is formalized in the form of a mathematical problem of nonlinear programming with Boolean variables with constraints such as equality and inequality. To solve it, the interactive genetic algorithm for the environmental projects implementation trajectory formation was developed.
Problems of the field of Ecological Economics are inherently complex and by definition involve trade-offs among multiple criteria. Moreover, the decisions made involve multiple parties, often with conflicting interests. For these reasons, the multiple criteria decision aid (MCDA) paradigm appears as a valuable tool for the field of Ecological Economics and indeed as an indispensable tool in the cases where participatory decisions must be made. In this work we apply a robustness-oriented MCDA approach to reach a solution for a land use problem in Northern Greece. The mathematical modeling as well as the case study results are presented. (C) 2013 The Authors. Published by Elsevier Ltd.
The countervailing cellular automata (CVCA) is a loose coupled program designed to work in conjunction with SLEUTH (an urban cellular automata simulation model). CVCA operationalises a set of landscape ecological strategies for urban planning. CVCA first assesses a landscape against a set of landscape metrics. It then evaluates the proposed urban cells from SLEUTH against the metrics and allocates future land uses according to a suite of planning strategies (offensive, defensive, protective, opportunistic). This paper describes the development of CVCA, the theory behind the landscape strategies, and the actions taken to bring CVCA into a computable environment. An application of CVCA in two metropolitan areas in Portugal (Porto and Lisbon) is made and discussed. The results of implementing it are then discussed and evaluated. The paper concludes that the implementation of the cellular automata model CVCA, loose coupled with SLEUTH (a cellular automaton urban model), provides a robust and useful application of landscape ecological strategies in metropolitan planning. The applied strategies vary locally as a function of the specifics concerning particular patterns and processes to be promoted. Besides the quantitative analysis they provide, these patterns and processes can also be assessed and compared in terms of the resulting images of urban growth, the location and the shape of corridors, buffers, and the relative importance of the different landscape ecological planning strategies.The paper ends with a comprehensive discussion of the four main subject areas, in the context of cellular automaton and dynamic models: the importance of integrated planning strategies for the territory; the lack of planning tools; the importance of cellular automaton approaches and applications; and the results of applying SLEUTH and CVCA to two metropolitan areas.
Urban agglomeration is an important carrier that promotes urbanization into an advanced stage, addressing its unbalanced development is an important task for the newly established territorial spatial planning in China. This research proposed a collaborative optimal allocation of urban land (COAUL) model which provides a simulation tool both for the quantity and spatial structure optimization of urban agglomeration. COAUL first optimizes the quantity structures of every city according to the current situation, potential development capacity and spatial policy. And then the optimized quantity structure is assigned into geo-space with land use spatial optimization model. COAUL has been applied to Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a fast-developing urban agglomeration located in Southern China, and three main findings are obtained: (1) COAUL model can optimize the quantity and spatial structure of urban agglomeration for the goal of balanced development, which could provide scientific reference scenario for the delimitation of the urban agglomerations growth boundaries (UAGB). (2) As cities in urban agglomeration have strong connections with each other, collaborative optimal allocation of urban land could considerably relieve the pressures of developed central cities and also promote the growth of undeveloped edge cities. (3) COAUL can unlimitedly reduce the imbalanced development tendency of urban agglomeration, which is performance better than traditional land use planning models. This research demonstrated that delimiting the UAGB with COAUL model is an important government measure for promoting the balanced development of urban agglomeration areas.
The modular decomposition of a symmetric map δ:X×X→Υ (or, equivalently, a set of pairwise-disjoint symmetric binary relations, a 2-structure, or an edge-colored undirected graph) is a natural construction to capture key features of δ in terms of a labeled tree. A map δ is explained by a vertex-labeled rooted tree (T,t) if the label δ(x,y) coincides with the label of the lowest common ancestor of x and y in T, i.e., if δ(x,y)=t(lca(x,y)). Only maps whose modular decomposition does not contain prime nodes, i.e., the symbolic ultrametrics, can be explained in this manner. Here we consider rooted median graphs as a generalization of (modular decomposition) trees to explain symmetric maps. We derive a linear-time algorithm that stepwisely resolves prime vertices in the modular decomposition tree to obtain a rooted and labeled median graph that explains a given symmetric map δ.
Rapid urbanisation has not only affected the division of urban administrative regions and economic development but also caused changes in land use patterns and urban-rural conflicts. Apart from being the main determinants of regional integration, urban agglomerations also represent a new form of spatial organisation to realise coordinated regional development. This study investigates China’s national urban agglomeration development planning, which is guided by government decision-making and various plans aimed at sustainable land use. We use the TF-IDF algorithm, NVivo and statistical methods to analyse the keywords of urban agglomeration policies and the correlation between keywords. We also compare the positioning goals, focus areas and development paths of urban agglomeration policies. The main conclusions are as follows: (1) Urban agglomeration development planning mainly focuses on industrial construction, with additional emphasis on ‘ecology’, ‘service’, ‘cooperation’, ‘innovation’ and ‘region’ (2) On the basis of development and cooperation, urban agglomeration development planning puts forward research objectives and positioning suitable for development; (3) Urban agglomeration development should further develop modern agriculture, emergency systems, ecological construction and internal cooperation. This study’s findings describe new ideas found by comparing urban agglomeration policies, which is helpful to understand the basis of formulating urban agglomeration development planning policies in China, and look forward to the long-term planning for the development of regional integration characteristics in China.
The Beijing(Jing)-Tianjin(Jin)-Hebei(Ji) (JJJ) urban agglomeration is one of the three major urban agglomeration in China, which plays an important strategic role in China’s regional development pattern. Based on the concern of inter-relationship within urban agglomeration, this paper creatively proposed a comprehensive gravity-Gram Schmidt Orthogonalization coupling model (CG-GSO) to quantitatively measure the urbanization development level at different regional scales. Compared with the information entropy method, the CG-GSO model was more reliable and fairer in evaluating the urbanization development of an urban agglomeration in the inter-annual dimension. We used the obstacle factor model to find out important ways to realize sustainable development at different regional scales. According to the trends from 2003 to 2017, the urbanization development levels were predicted by using the gray forecast model at different regional scales during 2018–2030. There was an upward trend in urbanization development at different regional scales. Compared with the internal single regions, a high starting and slow developing trend was in the urban agglomeration. In Beijing, the obstacle factors in urbanization development were in the demographic, social and eco-environmental subsystems. However, the obstacle factors were in the economic, eco-environmental and social subsystems in Tianjin, Hebei and JJJ urban agglomeration. The forecast results showed that urbanization development was going strong in internal regions from 2018 to 2030, while the overall urbanization development was slow in urban agglomeration. Urbanization development should focus on labor redistribution, weakening the boundary on social welfare, improving the efficiency of economic development and paying attention to protecting eco-environment for taking the sustainable development road in the JJJ urban agglomeration.
With the steady progress of regional integration, economic agglomeration effect plays an irreplaceable role in energy conservation and emission reduction. However, there is relatively little research on the two-way effect of economic agglomeration, energy and carbon emissions from a spatial perspective. This paper measures the degree of economic agglomeration from three aspects: factor agglomeration, industrial agglomeration and urban agglomeration in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) of China. Using spatial simultaneous equation models, the study analyzes the interaction between economic agglomeration, energy intensity and carbon intensity. The results show that the agglomeration level of the PRD and the YRD is higher than the BTH region. The relationship between economic agglomeration and carbon intensity is consistent with the interaction between economic agglomeration and energy intensity. Carbon intensity has spatial spillover effect on economic agglomeration in the three regions. Economic agglomeration has a negative impact on energy intensity in the BTH region. Energy intensity has a negative impact on economic agglomeration in the YRD region, and vice versa. There is an obvious two-way restraining relationship between carbon intensity and economic agglomeration in the PRD region.
The coupled map lattices (CML) is a spatiotemporal chaotic system with complex dynamic behavior. In this paper, we propose a spatiotemporal chaotic system with a novel pseudo-random coupling method based on elementary cellular automata (ECA), and introduce different perturbations into lattices in each iteration according to ECA. We investigate the spatiotemporal dynamic properties and chaotic behaviors of the proposed system such as bifurcation diagrams, Kolmogorov Sinai entropy, and uniformity. Moreover, the randomness of sequences generated by the proposed system and the correlation between any two lattices are discussed. Theory analyses and simulations indicate that the new system has better performance in complexity, ergodic and unpredictability than other CML systems such as adjacent CML and nonlinear CML based on fractional order logistic equation, etc. Furthermore, the correlation coefficient between any two lattices in the proposed system is significantly lower than other systems, and another advantage of the proposed system is utilizing the output of ECA to perturb the chaotic system which can effectively alleviate the dynamical degradation in digital system. The excellent performance of the proposed system demonstrates that it has great potential for crypto-system.
An infrastructure that provides geospatial analysis, better understands simulations, great potential for visualizing natural and artificial landscapes, and the universal recognition of the use of the Wireless Internet of Things. Everyday devices, whose platform is the Internet of Things, will be smarter in their daily processing, richer in their daily communication, and smarter. The Wireless Internet of Things still wants its landscape design. Still, its impact is already looking at the scene where the Wireless Internet of Things and GIS (Geographic Information System) systems were connected to make incredible advances. It opens up architecture-specific research and the usual architectural landscape area. It can be used for soil mapping studies and can be used for remote sensing in other engineering areas to obtain a wide range of weather compensation. It encourages the use of geographic information systems for geotechnical applications in soil. Geographic information systems can manipulate georeferenced information to be displayed, store, assemble and create georeferenced data from existing data, and generate multiple missing spatial data based on the attributes attached to it. The system briefly introduces street architecture landscape applications and promotes a street landscape design environment for Wireless Internet of Things and GIS system architecture. The proposed system is described as a thing and GIS as network technology, especially in smart design, street architecture and landscape wireless network connectivity. This is an overview of smart network providers, first to help explore some essential landscapes, equipped with wireless internet and geographic information systems, and how it is used in street architecture.
New technologies have vastly increased the available data on animal movement and behaviour. Consequently, new methods deciphering the spatial and temporal interactions between individuals and their environments are vital. Network analyses offer a powerful suite of tools to disentangle the complexity within these dynamic systems and we review these tools, their application, and how they have generated new ecological and behavioural insights. We suggest that network theory can be used to model and predict the influence of ecological and environmental parameters on animal movement, focusing on spatial and social connectivity, with fundamental implications for conservation. Refining how we construct and randomise spatial networks at different temporal scales will help establish network theory as a prominent, hypothesis-generating tool in movement ecology.
The main goal of this work is to show an extension of well known Hedlund’s theorem which states that in the Cantor topology the cellular automata are the continuous shift preserving maps. This extension maintains the topological structure and uses the concept of barriers of Set Theory to generalize the notion of local rule in the definition of cellular automata.