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1.
Calibration of cellular automata models using differential evolution to simulate present and future land use 
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下载免费PDF全文 A key issue in cellular automata (CA) modeling is the minimization of the differences between the actual and simulated patterns, which can be mathematically formulated as an objective function. We develop a new hybrid model (termed DE‐CA) by integrating differential evolution (DE) into CA to solve the objective function and retrieve the optimal CA parameters. Constrained relations among factors were applied in DE to generate different sets of CA parameters for prediction of future scenarios. The DE‐CA model was calibrated using historical spatial data to simulate 2016 land use in Kunming and predict multiple scenarios to the year 2026. Assessment of quantitative accuracy shows that DE‐CA yields 92.4% overall accuracy, where 6.8% is the correctly captured urban growth; further, the model reported only 5.0% false alarms and 2.6% misses. Regarding the simulation ability, our new CA model performs as well as the widely applied genetic algorithm‐based CA model, and outperforms both the logistic regression‐based CA model and a no‐change NULL model. We projected three possible scenarios for the year 2026 using DE‐CA to adequately address the baseline urban growth, environmental protection and urban planning to show the strong prediction ability of the new model. 相似文献
2.
Kuntal Ganguly Rajiv Kumar K. Mruthyunjaya Reddy P. Jagadeeswara Rao Manoj Raj Saxena G. Ravi Shankar 《国际地球制图》2017,32(7):777-796
This study investigated land use/land cover change (LULCC) dynamics using temporal satellite images and spatial statistical cluster analysis approaches in order to identify potential LULCC hot spots in the Pune region. LULCC hot spot classes defined as new, progressive and non-progressive were derived from Gi* scores. Results indicate that progressive hot spots have experienced high growth in terms of urban built-up areas (20.67% in 1972–1992 and 19.44% in 1992–2012), industrial areas (0.73% in 1972–1992 and 3.46% in 1992–2012) and fallow lands (4.35% in 1972–1992 and ?6.38% in 1992–2012). It was also noticed that about 28.26% of areas near the city were identified as new hot spots after 1992. Hence, non-significant change areas were identified as non-progressive after 1992. The study demonstrated that LULCC hot spot mapping through the integrated spatial statistical approach was an effective approach for analysing the direction, rate, spatial pattern and spatial relationship of LULCC. 相似文献
3.
土地利用变化模拟模型及应用研究进展 总被引：9，自引：0，他引：9
元胞自动机CA(Cellular Automata)和多智能体ABM(Agent-Based Model)模型是土地利用格局和演化模拟的主流方法,两者在模拟自然因素影响和人文驱动机制方面具有突出优势,为LUCC研究提供了重要的工具。当前,ABM无论在模型构建还是应用研究方面,CA和ABM均取得了显著进展。论文从数据基础、模拟尺度、CA转换规则挖掘、ABM行为规则定义、CA和ABM的耦合4个方面梳理土地利用模拟模型和方法的研究进展。并总结这些模型在虚拟城市模拟与理论验证、真实城市模拟与规划预测以及多类用地模拟与辅助决策等方面的应用。最后,总结土地利用模拟模型在精细模拟和全球变化研究方面存在的局限性,认为未来发展将主要集中于解决从2维模型向3维模型发展、大数据与规则精细挖掘以及大尺度模拟与知识迁移等问题。 相似文献
4.
The objectives of this study are to assess land suitability and to predict the spatial and temporal changes in land use types (LUTs) by using GIS-based land use management decision support system. A GIS database with data on climate, topography, soil characteristic, irrigation condition, fertilizer application, and special socioeconomic activities has been developed and used for the evaluation of land productivity for different crops by integrating with a crop growth model—the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS for the predictions of how crop demands and crop market prices will change under alternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models, which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can effect the distribution of agricultural land use. A test for integrated simulation is taken in each 0.1o by 0.1o grid cell to predict the change of agricultural land use types at global level. Global land use changes are simulated from 1992 to 2050. 相似文献
5.
IntroductionAgriculturallandusepatternsandtheirchangesaretightlyrelatedwithagriculturepolicyandfoodsecurityissuesundergrowingfooddemand,assess mentofglobalclimatechangeimpactsonagricul ture,environmentalissuesduetotheintensificationofagriculturallandusessuchaswaterpollution,soildegradation,andrecentlywaterscarcityissues.Soasustainableandholisticplanningandmanage mentoflandresourcesshouldcombineallthesere latedinformationwithefficienttoolsforassessmentandevaluationinordertopermitbroad ,interact… 相似文献
6.
Sandeep Maithani 《国际地球制图》2015,30(2):163-185
Land cover transformation is one of the foremost aspects of human-induced environmental change, having an extensive history dating back to antiquity. The present study aims to simulate the process of land cover change based on different policy-based scenarios so as to provide a basis for sustainable development in Doon valley, India. For this purpose, an artificial neural network-based spatial predictive model was developed for the Doon valley. The predictive model generated future land cover patterns under three policy scenarios, i.e. baseline scenario, compact growth scenario and hierarchical growth scenario (HGS). The simulated land cover patterns mirror where land cover patterns are headed in the valley by year 2021. The result suggests that unabated continuation of the present pattern of land cover transformation will result in a regional imbalance. However, this skewed development can be corrected by altering the current growth trend as revealed in the compact growth and HGSs. 相似文献
7.
8.
Abubakr A.A. Al-sharif 《国际地球制图》2015,30(8):858-881
Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved. 相似文献
9.
Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models 总被引：1，自引：0，他引：1
This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern. 相似文献
10.
Tara Sharma Jeff Carmichael Brian Klinkenberg 《Journal of the Indian Society of Remote Sensing》2005,33(2):353-363
The transition to agricultural sustainability involves difficult choices and an understanding of the complex trade-offs associated
with agricultural activities. Decision support tools and techniques assist in making the informed decisions for a transition
to sustainable agriculture. Georgia Basin — Quite Useful Ecosystem Scenario Tool (GB-QUEST) is a computer-based, user-friendly
tool that has been developed to look at the future sustainability scenarios of the Georgia Basin in British Columbia. The
objective of this paper is to describe the agricultural model that has been developed for implementation in GB-QUEST. We present
its framework, spatial methodology for land-use simulation, and the initial results of its application.
The agriculture model is a spatial model that examines the social, economic and environmental consequences of user-defined
agricultural development strategies. The model simulates changes in the Georgia Basin from the year 2000 to 2040 in decadal
steps. User choices of local and global development factors, along with their "worldview" choices, are important inputs in
the model that determine the effects on environmental and socio-economic systems. The model has two components — Generation
of land-use scenarios, and Development of Indicator models. The first component uses cell-based spatial algorithms to simulate
likely changes/conversions in land-use up to the year 2040. The approach used here integrates the functionality of Multi-Criteria
Evaluation (MCE) and Cellular Automata (CA) techniques in order to simulate the land-use conversions. It uses Geographic Information
Systems (GIS) and remote sensing techniques for creating, storing and deriving the data sets required for the model. The second
component develops the indicator models for relating scenario variables to socio-economic and environmental variables such
as physical and economic yields, economic operation costs and nutrient surplus per unit area. These indicator models are used
to evaluate land-use scenarios generated by the users. The model encourages understanding of sustainability, by allowing one
to explore different possible scenarios of the future for their environmental and socio-economic consequences. 相似文献
11.
通过模型对区域土地利用/覆盖变化（LUCC）进行分析已经成为了当前全球的研究主要内容之一。元胞自动机（CA）模型是一种通过定义局部的简单的计算规则来模拟和表示整个系统中复杂现象的时空动态模型,其＂自下而上＂的研究思路,强大的复杂计算功能及高度动态,使得它在模拟空间复杂系统的时空动态演变方面具有很强的能力。CA模型通过与其他模型相结合,在综合考虑各种限制因素和转换规则的前提下,通过反复迭代综合空间分析与非空间分析,模拟土地利用变化情景,在国内外已经形成了较为成熟的研究模型。本文首先提出了CA模型在土地利用变化中应用的背景及其特点;然后,分析了CA模型的构成原理以及在国内外的应用进展与现状;最后,详细阐述了CA模型在土地利用变化中的发展趋势及今后研究工作中应注意的问题。 相似文献
12.
《制图学和地理信息科学》2013,40(4):369-380
Insufficient research has been done on integrating artificial-neural-network-based cellular automata (CA) models and constrained CA models, even though both types have been studied for several years. In this paper, a constrained CA model based on an artificial neural network (ANN) was developed to simulate and forecast urban growth. Neural networks can learn from available urban land-use geospatial data and thus deal with redundancy, inaccuracy, and noise during the CA parameter calibration. In the ANN-Urban-CA model we used, a two-layer Back-Propagation (BP) neural network has been integrated into a CA model to seek suitable parameter values that match the historical data. Each cell's probability of urban transformation is determined by the neural network during simulation. A macro-scale socio-economic model was run together with the CA model to estimate demand for urban space in each period in the future. The total number of new urban cells generated by the CA model was constrained, taking such exogenous demands as population forecasts into account. Beijing urban growth between 1980 and 2000 was simulated using this model, and long-term (2001–2015) growth was forecast based on multiple socio-economic scenarios. The ANN-Urban-CA model was found capable of simulating and forecasting the complex and non-linear spatial-temporal process of urban growth in a reasonably short time, with less subjective uncertainty. 相似文献
13.
Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng,China 总被引：2，自引：0，他引：2
Simulations of intra-urban land use changes have gradually attracted more attention as these approaches are extremely helpful in regard to decision making and policy formulation. While prior studies mostly focused on methods of developing intra-urban level simulations, very little research has been conducted explain the factors driving intra-urban land use change. Urban planners are highly concerned with how inner-city structures are formed and how they function. Here, to simulate multiple intra-urban land use changes and to identify the contribution of different driving factors, we developed a random forests (RF) algorithm-based cellular automata (CA) simulation model. In this study, the model applied diverse categories of spatial variables, including traffic location factors, environmental factors, public services, and population density, as the driving factors to enhance our understanding of the dynamics of internal urban land use. The CA model was tested using data from the Huicheng district of Huizhou city in the Guangdong province of China. The Model was validated using actual historical land use data from 2000 to 2010. By applying the validated model, multiple intra-urban land use maps were simulated for 2015. Simultaneously, spatial variable importance measures (VIMs) were calculated by using the out-of-bag (OOB) error estimation approach of the RF algorithm. Based on the calculation results, we assessed and analysed the significance of each intra-urban land use driver for this region. This study provides urban planners and relevant scholars with detailed and targeted information that can aid in the formulation of specific planning strategies for different intra-urban land uses and support the future evolution of this area. 相似文献
14.
基于GIS与空间统计分析的可持续发展度量方法研究——以缅甸Myingyan District为例 总被引：15，自引：0，他引：15
利用空间信息系统所提供的强大空间数据处理和分析能力，并将之与统计分析软件包的统计分析功能进行有效的集成，建立了基于空间统计分析的可持续发展定量分析评价模型（ＳＢＳＡ）。从在缅甸中部Myingyan县的应用实例来看，该模型能够提示影响Myingyan县可持续发展能力的主导因子，通过对这些因子和可持续发展综合指数的定量化、空间化的分析，为政府部门规划区域综合发展方案，制定发展政策提供很好的决策支持。 相似文献
15.
Najat Qader Omar Mohd Sanusi S. Ahamad Wan Muhd Aminuddin Wan Hussin Narimah Samat Siti Zubaidah Binti Ahmad 《Journal of the Indian Society of Remote Sensing》2014,42(1):165-178
The cellular automata (CA) model is an important tool in land use change studies. Swift increases in population and long-term expectations of rapid urbanization have led to extensive land use change, and normal living conditions have affected the natural resources of the land. This paper highlights and analyzes the historical urban changes in Kirkuk City, Iraq, considering repeated changes undergone by the state such change as government infrastructures, wars, and economic blockade. In this paper, an integrated model, built-in multi regression model, and multi-criteria evaluation were considered to improve the representation of CA transition rules. Environmental and socioeconomic factors were used to produce Suitable Maps (SMs). These SMs were practicalities to create factor layers and weight usage, rating method process for variance expert decision-making groups, and geographic information systems for the periods 1984, 1990, 2000, and 2010. The roots of the equation (R2) values are compared and these values are chosen to produce a good model of suitable maps. The approach used in this study provides a mechanism for monitoring suitability maps in Kirkuk. Furthermore, the model Markov CA is implemented and evaluated. The results indicate that the model, its related concepts performs sufficiency 相似文献
16.
Eduardo E. Maeda Cláudia Maria de Almeida Arimatéa de Carvalho Ximenes Antonio R. Formaggio Yosio E. Shimabukuro Petri Pellikka 《International Journal of Applied Earth Observation and Geoinformation》2011
The present work is committed to simulate the expansion of agricultural and cattle raising activities within a watershed located in the fringes of the Xingu National Park, Brazilian Amazon. A spatially explicit dynamic model of land cover and land use change was used to provide both past and future scenarios of forest conversion into such rural activities, aiming to identify the role of driving forces of change in the study area. The employed modeling platform – Dinamica EGO – consists in a cellular automata environment that embodies neighborhood-based transition algorithms and spatial feedback approaches in a stochastic multi-step simulation framework. Biophysical variables and legal restrictions drove this simulation model, and statistical validation tests were then conducted for the generated past simulations (from 2000 to 2005), by means of multiple resolution fitting methods. Based on optimal calibration of past simulations, future scenarios were conceived, so as to figure out trends and spatial patterns of forest conversion in the study area for the year 2015. In all simulated scenarios, pasturelands remained nearly stable throughout the analyzed period, while a large expansion in croplands took place. The most optimistic scenario indicates that more than 50% of the natural forest will be replaced by either cropland or pastureland by 2015. This modeling experiment revealed the suitability of the adopted model to simulate processes of forest conversion. It also indicates its possible further applicability in generating simulations of deforestation for areas with expanding rural activities in the Amazon and in tropical forests worldwide. 相似文献
17.
Although traditional cellular automata (CA)‐based models can effectively simulate urban land‐use changes, they typically ignore the spatial evolution of urban patches, due to their use of cell‐based simulation strategies. This research proposes a new patch‐based CA model to incorporate a spatial constraint based on the growth patterns of urban patches into the conventional CA model for reducing the uncertainty of the distribution of simulated new urban patches. In this model, the growth pattern of urban patches is first estimated using a developed indicator that is based on the local variations in existing urban patches. The urban growth is then simulated by integrating the estimated growth pattern and land suitability using a pattern‐calibrated method. In this method, the pattern of new urban patches is gradually calibrated toward the dominant growth pattern through the steps of the CA model. The proposed model is applied to simulate urban growth in the Tehran megalopolitan area during 2000–2006–2012. The results from this model were compared with two common models: cell‐based CA and logistic‐patch CA. The proposed model yields a degree of patch‐level agreement that is 23.4 and 7.5% higher than those of these pre‐existing models, respectively. This reveals that the patch‐based CA model simulates actual development patterns much better than the two other models. 相似文献
18.
Apostolos Lagarias 《国际地球制图》2015,30(9):1033-1051
This study addresses the issue of urban sprawl through the application of a cellular automata (CA)-based model in the area of Thessaloniki, Greece. The model integrates a multiple regression model at the regional level with a CA model at the local level. New urban land is allocated in a disaggregated field of land units (cells) taking into account a wide range of data. Particular emphasis is placed on the way zoning regulations and land availability data are inserted into the model, so that alternative land use policy scenarios could be examined. Thessaloniki, a typical Mediterranean city, is used as a case study. The model is used to compare two scenarios of urban growth up to year 2030; the first one assuming a continuation of existing trends, whereas the second one assuming the enactment of various land use zoning regulations in order to contain urban sprawl. 相似文献
19.
Enhancing a GIS Cellular Automata Model of Land Use Change: Bayesian Networks, Influence Diagrams and Causality 总被引：1，自引：0，他引：1
Cellular Automata (CA) models at present do not adequately take into account the relationship and interactions between variables. However, land use change is influenced by multiple variables and their relationships. The objective of this study is to develop a novel CA model within a geographic information system (GIS) that consists of Bayesian Network (BN) and Influence Diagram (ID) sub‐models. Further, the proposed model is intended to simplify the definition of parameter values, transition rules and model structure. Multiple GIS layers provide inputs and the CA defines the transition rules by running the two sub‐models. In the BN sub‐model, land use drivers are encoded with conditional probabilities extracted from historical data to represent inter‐dependencies between the drivers. Using the ID sub‐model, the decision of changing from one land use state to another is made based on utility theory. The model was applied to simulate future land use changes in the Greater Vancouver Regional District (GVRD), Canada from 2001 to 2031. The results indicate that the model is able to detect spatio‐temporal drivers and generate various scenarios of land use change making it a useful tool for exploring complex planning scenarios. 相似文献
20.
Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model’s parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China’s Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model’s parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation. 相似文献