Pine wilt disease (PWD) has become a devastating that impacts China’s forest management. It is of great significance to accurately predict PWD on geospatial scale prevent its spread. Using the Cellular Automata (CA)–Markov model, this study predicts occurrence area in Anhui Province 2030 based PWD-relevant factors, such as weather, terrain, population, and traffic. spatial autocorrelation analy...

Conversion rule is a key element for cellular automata (CA) model, and it significant challenging issue both domestic international experts. Traditional research regarding CA models often constructs single conversion the entire study area, without differentiating on basis of unique growth features each location. On this, partitioned heterogeneous land-use simulation model (PHLUS) constructed by...

In order to promote the healthy development of Nanchang city in future and maintain virtuous cycle urban ecosystem, this paper uses CA-Markov model simulate forecast land use 2030 explore urbanization process city. Firstly, changes from 2000 2020 are described, followed by simulations for as a verification accuracy, projections based on accuracy requirements. The results show that: (1) rate exp...

We devise a cross-layer design (CLD) of carrier sensing multiple access with collision avoidance (CSMA/CA) at the medium access control (MAC) layer with spectrum sensing (SpSe) at the physical layer for cognitive radio networks (CRNs). The proposed CLD relies on a Markov chain model with a state pair containing both the SpSe and the CSMA/CA with exponential backoff from which we derive the tran...

This paper investigates the potential of a cellular automata (CA) model based on logistic regression (logit) and Markov Chain Monte Carlo (MCMC) to simulate the dynamics of urban growth. The model assesses urbanization likelihood based on (i) a set of urban development driving forces (calibrated based on logit) and (ii) the land-use of neighboring cells (calibrated based on MCMC). An innovative...