scholarly journals Application of 3D Laser Image Scanning Technology and Cellular Automata Model in the Prediction of the Dynamic Process of Rill Erosion

2021 ◽  
Vol 13 (13) ◽  
pp. 2586
Author(s):  
Song Li ◽  
Qiqi Li ◽  
Jian Chen ◽  
Yu Han

Black soil areas are strongly affected by rill erosion due to the geomorphic characteristics of flood plains and heavy rainfall. To study the problem of rill erosion in black soil areas and achieve ecological restoration, based on the method of artificially simulated rainfall, the effects of rainfall intensity and slope on the characteristics of flow and sand production on the slope surface of black soil areas were studied, and the erosion pattern of the slope surface after rainfall was monitored by a 3D laser scanner to analyze the erosion of the soil on the slope surface. The slope erosion model was constructed on the basis of the cellular automata (CA) method, and the results of the model’s operation were compared with actual rainfall measurement results to deepen research on the slope erosion mechanism in black soil areas. By analyzing the slope erosion pattern after rainfall, it was found that the surface area and erosion volume of serious slope erosion areas increased with increases in slope gradient. Based on the physical model test results combined with the CA model to simulate flow and sand production on bare slopes under different rainfall intensities, comparison showed that the CA model can accurately simulate flow and sand production on a slope where the Ens coefficient of the flow production rate is between 0.70 and 0.97, thus theoretically verifying the reliability of the model, and on this basis, the erosion pattern of the slope after rainfall was predicted to explore the evolution and development law of erosion.

2007 ◽  
Vol 34 (4) ◽  
pp. 708-724 ◽  
Author(s):  
Daniel Stevens ◽  
Suzana Dragićević

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.


2021 ◽  
Vol 10 (3) ◽  
pp. 149
Author(s):  
Nuno Pinto ◽  
António P. Antunes ◽  
Josep Roca

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.


Technologies ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 54
Author(s):  
Bozkurt ◽  
Karwowski ◽  
Çakıt ◽  
Ahram

This study presents a cellular automata (CA) model to assist decision-makers in understanding the effects of infrastructure development projects on adverse events in an active war theater. The adverse events are caused by terrorist activities that primarily target the civilian population in countries such as Afghanistan. In the CA-based model, cells in the same neighborhood synchronously interact with one another to determine their next states, and small changes in iteration yield to complex formations of adverse event risks. The results demonstrate that the proposed model can help in the evaluation of infrastructure development projects in relation to changes in the reported adverse events, as well as in the identification of the geographical locations, times, and impacts of such developments. The results also show that infrastructure development projects have different impacts on the reported adverse events. The CA modeling approach can be used to support decision-makers in allocating infrastructure development funds to stabilize active war regions with higher adverse event risks. Such models can also improve the understanding of the complex interactions between infrastructure development projects and adverse events.


2005 ◽  
Vol 12 (1) ◽  
pp. 83-90
Author(s):  
R. Šiugždaite

The development of regional urban system still remains one of the main problems during the human race history. There are a lot of problems inside this system like overcrowded cities and decaying countryside. All these situations can be reproduced by modelling them using Cellular Automata (CA) [1, 2, 5]. CA models implement algorithms with simple rules and parameter controls, but the result can be a complex behaviour. A stability of naturally formed self‐organized urban system depends on its critical state parameter τ in the power law log(f(x)) = ‐τlog(x). If the system reaches self‐organized critical (SOC) state then it remains in it for a long time. The CA model URBACAM (URBAnistic Cellular Automata Model) describes the long‐lasting term behaviour and shows that the change in behaviour is sensitive to the urban parameter τ of the power law. Regionines urbanistines sistemos vystymasis išlieka viena iš opiausiu problemu žmonijos istorijoje. Keletas tokiu uždaviniu kaip miestu perpildymas, nykstančios kaimo vietoves ir t.t. gali būti nesunkiai modeliuojami naudojant lasteliu automatus (LA). LA metodas ypatingas tuo, kad realizuoja algoritma paprastu taisykliu bei parametru valdymo pagalba, tačiau rezultate galima gauti sudetinga elgsena. Natūraliai susiformavusiu urbanistiniu sistemu stabilumas priklauso nuo sistemos krizines savirangos būsenos (KSB) parametro τ. Jei sistema pasiekia KSB, tai ji ilga laika išlieka joje. LA modelis URBACAM charakterizuoja ilgalaike elgsena ir parodo, jog modelyje jos kitimus itakoja eksponentinio desnio urbanistinis parametras τ.


2019 ◽  
Vol 11 (9) ◽  
pp. 2464
Author(s):  
Cong Ou ◽  
Jianyu Yang ◽  
Zhenrong Du ◽  
Xin Zhang ◽  
Dehai Zhu

An effective simulation of the urban sprawl in an urban agglomeration is conducive to making regional policies. Previous studies verified the effectiveness of the cellular-automata (CA) model in simulating urban sprawl, and emphasized that the definition of transition rules is the key to the construction of the CA model. However, existing simulation models based on CA are limited in defining complex transition rules. The aim of this study was to investigate the capability of two unsupervised deep-learning algorithms (deep-belief networks, DBN) and stacked denoising autoencoders (SDA) to define transition rules in order to obtain more accurate simulated results. Choosing the Beijing–Tianjin–Tangshan urban agglomeration as the study area, two proposed models (DBN–CA and SDA–CA) were implemented in this area for simulating its urban sprawl during 2000–2010. Additionally, two traditional machine-learning-based CA models were built for comparative experiments. The implementation results demonstrated that integrating CA with unsupervised deep-learning algorithms is more suitable and accurate than traditional machine-learning algorithms on both the cell level and pattern level. Meanwhile, compared with the DBN–CA, the SDA–CA model had better accuracy in both aspects. Therefore, the unsupervised deep-learning-based CA model, especially SDA–CA, is a novel approach for simulating urban sprawl and also potentially for other complex geographical phenomena.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Liqiang Ji ◽  
Yongsheng Qian ◽  
Junwei Zeng ◽  
Min Wang ◽  
Dejie Xu ◽  
...  

In public places, the high pedestrian density is one of the direct causes leading to crowding and trample disaster, so it is very necessary to investigate the collective and evacuation characteristics for pedestrian movement. In the occupants’ evacuation process, the people-people interaction and the people-environment interaction are sufficiently considered in this paper, which have been divided into the exit attraction, the repulsion force between people, the friction between people, the repulsion force between human and barrier, and the attraction of surrounding people. Through analyzing the existing models, a new occupant evacuation cellular automata (CA) model based on the social force model is presented, which overcomes the shortage of the high density crowd simulation and combines the advantages that CA has sample rules and faster calculating speed. The simulating result shows a great applicability for evacuation under the high density crowd condition, and the segregation phenomena have also been found in the bidirectional pedestrian flow. Besides these, setting isolated belt near the exit or entrance of underpass not only remarkably decreases the density and the risk of tramper disaster but also increases the evacuation efficiency, so it provides a new idea for infrastructure design about the exits and entrances.


Author(s):  
Nirmalya Sundar Maiti ◽  
Soumyabrata Ghosh ◽  
Parimal Pal Chaudhuri

2015 ◽  
Vol 26 (10) ◽  
pp. 1550114 ◽  
Author(s):  
A. Troisi

Pollution represents one of the most relevant issues of our time. Several studies are on stage but, generally, they do not consider competitive effects, paying attention only to specific agents and their impact. In this paper, it is suggested a different scheme. At first, it is proposed a formal model of competitive noxious effects. Second, by generalizing a previous algorithm capable of describing urban growth, it is developed a cellular automata (CA) model that provides the effective impact of a variety of pollutants. The final achievement is a simulation tool that can model pollution combined effects and their dynamical evolution in relation to anthropized environments.


2013 ◽  
Vol 27 (13) ◽  
pp. 1350090 ◽  
Author(s):  
YUAN XUE ◽  
YONG-SHENG QIAN ◽  
XIAO-PING GUANG ◽  
JUN-WEI ZENG ◽  
ZHI-LONG JIA ◽  
...  

With the application of the dynamic control system, Cellular Automata model has become a valued tool for the simulation of human behavior and traffic flow. As an integrated kind of railway signal-control pattern, the four-aspect color light automatic block signaling has accounted for 50% in the signal-control system in China. Thus, it is extremely important to calculate correctly its carrying capacity under the automatic block signaling. Based on this fact the paper proposes a new kind of "cellular automata model" for the four-aspect color light automatic block signaling under different speed states. It also presents rational rules for the express trains with higher speed overtaking trains with lower speed in a same or adjacent section and the departing rules in some intermediate stations. In it, the state of mixed-speed trains running in the section composed of many stations is simulated with CA model, and the train-running diagram is acquired accordingly. After analyzing the relevant simulation results, the needed data are achieved herewith for the variation of section carrying capacity, the average train delay, the train speed with the change of mixed proportion, as well as the distance between the adjacent stations.


Sign in / Sign up

Export Citation Format

Share Document