Cellular automata for simulating land-use change with a constrained irregular space representation: A case study in Nanjing city, China

2020 ◽  
pp. 239980832094988
Author(s):  
Jie Zhu ◽  
Yizhong Sun ◽  
Shuyin Song ◽  
Jing Yang ◽  
Hu Ding
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Space ◽  
Spatial Reasoning ◽  
Land Use Changes ◽  
Space Representation ◽  
Change Models ◽  
Geographic Space ◽  
Ca Model

Traditional cell-based cellular automata (CA) models use a regular cellular grid to represent geographic space, and new approaches to CA models have explored the use of a vector representation of space instead of a regular grid to characterize urban space more realistically. However, less attention has been paid to modeling the interaction between the geospatial information and the irregular cells. To date, the majority of spatial boundaries have been created by individual agencies in an uncoordinated manner. As a consequence, the potential uses of the data collected for land-use change models are limited. In this paper, we propose a new vector-based CA model based on a new constrained irregular space representation using the theory of hierarchical spatial reasoning. For dividing the geographic space considering different items, first land patches are considered as the minimum division unit; then aggregation rules, including attribute, geometric and boundary barrier constraints, are defined; and finally different levels of spatial units are formed through land patches based on aggregation rules. The proposed model is used to simulate the land-use changes in Nanjing, Jiangsu Province, China. The performance validation and comparison illustrate the feasibility of the proposed space representation in a CA model. By using this model, it is expected that the use of the real spatial boundaries that are employed in urban planning could help provide a flexible paradigm to consider various drivers or constraints for realistically simulating land-use changes.

Land use change simulation and analysis using a vector cellular automata (CA) model: A case study of Ipswich City, Queensland, Australia

2019 ◽  
Vol 47 (9) ◽  
pp. 1605-1621 ◽  
Author(s):  
Yi Lu ◽  
Shawn Laffan ◽  
Chris Pettit ◽  
Min Cao
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Growth ◽  
Basic Unit ◽  
Change Models ◽  
Processing Times ◽  
Ca Model ◽  
Artificial Neural Network Ann ◽  
Model Transition

The loss of accuracy in vector-raster conversion has always been an issue for land use change models, particularly for raster based Cellular Automata models. Here we describe a vector-based cellular automata (CA) model that uses land parcels as the basic unit of analysis, and compare its results with a raster CA model. Transition rules are calibrated using an artificial neural network (ANN) and historical land use data. Using Ipswich City in Queensland, Australia as the study area, the simulation results show that the vector and raster CA models achieve 96.64% and 93.88% producer’s spatial accuracy, respectively. In addition, the vector CA model achieves a higher kappa coefficient and more consistent frequency of misclassification, while also having faster processing times. Consequently, the vector-based CA model can be applied to explore regulations of land use transformation in urban growth process, and provide a better understanding of likely urban growth to inform city planners.

A GIS-Based Irregular Cellular Automata Model of Land-Use Change

2007 ◽  
Vol 34 (4) ◽  
pp. 708-724 ◽  
Author(s):  
Daniel Stevens ◽  
Suzana Dragićević
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Spatial Data ◽  
Cellular Automata Model ◽  
Population Growth Rates ◽  
Asynchronous Development ◽  
Canadian City ◽  
Ca Model ◽  
Developing Area

This study proposes an alternative cellular automata (CA) model, which relaxes the traditional CA regular square grid and synchronous growth, and is designed for representations of land-use change in rural-urban fringe settings. The model uses high-resolution spatial data in the form of irregularly sized and shaped land parcels, and incorporates synchronous and asynchronous development in order to model more realistically land-use change at the land parcel scale. The model allows urban planners and other stakeholders to evaluate how different subdivision designs will influence development under varying population growth rates and buyer preferences. A model prototype has been developed in a common desktop GIS and applied to a rapidly developing area of a midsized Canadian city.

scholarly journals A Cellular Automata Model for Integrated Simulation of Land Use and Transport Interactions

2021 ◽  
Vol 10 (3) ◽  
pp. 149
Author(s):  
Nuno Pinto ◽  
António P. Antunes ◽  
Josep Roca
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Studies ◽  
Particle Swarm Algorithm ◽  
Cellular Automata Model ◽  
Integrated Simulation ◽  
The Road ◽  
Ca Model ◽  
The City

Cellular automata (CA) models have been used in urban studies for dealing with land use change. Transport and accessibility are arguably the main drivers of urban change and have a direct influence on land use. Land use and transport interaction models deal with the complexity of this relationship using many different approaches. CA models incorporate these drivers, but usually consider transport (and accessibility) variables as exogenous. Our paper presents a CA model where transport variables are endogenous to the model and are calibrated along with the land use variables to capture the interdependent complexity of these phenomena. The model uses irregular cells and a variable neighborhood to simulate land use change, taking into account the effect of the road network. Calibration is performed through a particle swarm algorithm. We present an application of the model to a comparison of scenarios for the construction of a ring road in the city of Coimbra, Portugal. The results show the ability of the CA model to capture the influence of change of the transport network (and thus in accessibility) in the land use dynamics.

scholarly journals CELLULAR AUTOMATA MODEL – LANDSCAPE DYNAMICS SIMULATION TOOL IN THE PROCESS OF CHANGE IN LAND USE AND COVER IN THE CITY OF GAÚCHA DO NORTE – MT

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 447-451
Author(s):  
E. A. L. Pinheiro ◽  
N. A. Camini ◽  
M. R. S. Soares ◽  
S. S. Sumida
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Land Use Changes ◽  
Environmental Modeling ◽  
Dynamics Simulation ◽  
Cellular Automata Model ◽  
The City ◽  
Land Use And Cover ◽  
Main Factor

Abstract. The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left Brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.

scholarly journals ARAHAN PENGENDALIAN PERUBAHAN PENGGUNAAN LAHAN MENGGUNAKAN MARKOV - CELLULAR AUTOMATA DI KABUPATEN CIANJUR

2017 ◽  
Vol 18 (4) ◽  
pp. 211
Author(s):  
Rani Yudarwati ◽  
Santun R.P Sitorus ◽  
Khursatul Munibah
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Environmental Sustainability ◽  
Land Use Changes ◽  
Landuse Change ◽  
The Past ◽  
Land Use Scenario ◽  
Environment Sustainability ◽  
Spatial Plan

Controlling the rate of land use change is necessary due to maintaining environment sustainability.  One of the efforts is studying the changes that occur in the past few years. These changes can be studied by Markov - Cellular Automata model.Cianjur is one of the regency that has a high risk of landslide hazard, so it is necessary to control land use change in order to realize environmental sustainability in accordance with the spatial plan of Cianjur regency (RTRW). The purpose of this study was to see land use changes that occurred and evaluated with the spatial plan (RTRW) and also to conduct controlling scenarios of land use changes. The analysis showed that Cianjur regency has drastically decreased in forest area up to 10,3% and landuse inconsistencyof 10,4%. The prediction results showed that landuse change without intervention would dramatically increase inconsistency up to 20,5%. Land use scenario of restoring forest could reduce inconsistency up to 16,6%.

scholarly journals Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

2020 ◽  
Vol 13 (7) ◽  
pp. 3203-3220 ◽  
Author(s):  
Lei Ma ◽  
George C. Hurtt ◽  
Louise P. Chini ◽  
Ritvik Sahajpal ◽  
Julia Pongratz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Carbon Emissions ◽  
Forest Cover ◽  
Land Use Changes ◽  
Change Models ◽  
Translation Rule

Abstract. Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation in land-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine) rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover.

scholarly journals SPATIAL SIMULATION BASED ON GEOGRAPHIC INFORMATION SYSTEM (GIS) AND CELLULAR AUTOMATA (CA) FOR LAND USE CHANGE MODELING IN SINGARAJA CITY AND ITS SURROUNDING AREA

2019 ◽  
Author(s):  
Nyoman Arto Suprapto
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Areas ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Geographic Information ◽  
Spatial Simulation ◽  
Land Use Change Modeling ◽  
The City

Singaraja is the second largest city after Denpasar in Bali. The magnitude of the potential of the region both trade and services, agriculture and tourism in Buleleng Regency has given a very broad impact not only on the economy but also the use of land. Economic development in the city of Singaraja cause some effects such as population growth, an increasing number of facilities (social, economic, health, and others), as well as changes in land use.Changes in land use have a serious impact on the environment in the city of Singaraja. The development of urban areas of Singaraja has given the excesses of increasing the land conversion. Suburb dominated by wetland agriculture has now turned into buildings to meet the needs of shelter, trade and services as well as urban utilities. This study was conducted by mean to determine how changes in land use from agricultural land into build up land during twelve years (period of 2002 - 2014) and the prediction of land use within the next 12 years (period of 2020 and 2026). Prediction of land use changes will be done using spatial simulation method which is integrating Cellular Automata (CA) and Geographic Information Systems (GIS) which analyzed based on land requirement, the driving variable of land use changes (population and road) and the inhabiting variable of land use change (slope steepness and rivers).Keywords : Land Use Change, Land Use Change Modeling, Celullar Automata, GIS

A Cellular Automata Model for Urban Land-Use Simulation

2005 ◽  
Vol 32 (2) ◽  
pp. 247-263 ◽  
Author(s):  
Kwok Hung Lau ◽  
Booi Hon Kam
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Distance Function ◽  
Alternative Model ◽  
Resistance To Change ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Allocation ◽  
Ca Model

This paper presents an urban land-use simulation model using cellular automata (CA). In the model urban growth is regarded as the result of a global process underpinned by local actions and land-use change as the joint action of three different effects: attribute, heterogeneity, and gravity. The attribute and heterogeneity effects are regarded as different aspects of a local driving force for change constituted by changing accessibility and other attributes resulting from the interaction of land use and transport at the neighborhood level. The gravity effect is a universal resistance to change as a result of inertia and agglomeration of compatible land uses in the vicinity. To ensure that local actions would lead to global behavior, a multipass, in addition to a single-pass, land-use-allocation algorithm is designed to mimic land-use changes. With metropolitan Melbourne in Australia as a case study, the performance of the model in replicating land-use changes is compared with that of an alternative model developed by using only a distance function. The results of the comparison show that the proposed CA model outperforms the alternative model with only a distance function, confirming the importance of incorporating local attributes in modeling land-use changes.

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