The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model

Abstract. Barak valley is a region in north east part of India where the practice of shifting cultivation is quite prevalent. Population growth coupled with the geographic isolation of the area have led to an increased pressure on land and a consequent decline in forest cover. The decrease of forests observed is spatially distributed and dependent on neighborhood rules. Hence, we look towards modelling the land use change to understand the land use changes and the factors affecting them. In this paper, we modify an agent-based land use model for modelling shifting cultivation to determine how various policy changes at a larger scale might affect the shifting cultivation practice in the region at the micro level. We explore scenarios like drastic population increase and availability of irrigation infrastructure in the area. Through the scenario analysis we explore how policies play a role in agriculture patterns and influence land use patterns.

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A cellular automata land use model for the R software environment

10.31235/osf.io/suy2c ◽

2019 ◽

Author(s):

Richard J Hewitt ◽

Jaime Díaz-Pacheco ◽

Borja Moya-Gómez

Keyword(s):

Land Use ◽

Cellular Automata ◽

Land Use Change ◽

Tips And Tricks ◽

Software Environment ◽

R Software ◽

Land Use Model ◽

Software Updates

SIMLANDER stands for SIMulation of LAnd use changE using R, and is a prototype Cellular Automata (CA) land use model built for the R software environment. The following document provides a description of the model, full user documentation including a step-by-step guide to building a simple land use model. At the end some tips and tricks are provided for advanced users, and software updates are recorded.

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Deferring Crisis

10.1093/oso/9780190865177.003.0002 ◽

2018 ◽

Author(s):

Erin Stewart Mauldin

Keyword(s):

Land Use ◽

Environmental Impacts ◽

Shifting Cultivation ◽

Crop Production ◽

Animal Husbandry ◽

Antebellum South ◽

Westward Expansion ◽

The Cost ◽

Land Use Practices ◽

Ecological Regime

This chapter explores the ecological regime of slavery and the land-use practices employed by farmers across the antebellum South. Despite the diverse ecologies and crop regimes of the region, most southern farmers employed a set of extensive agricultural techniques that kept the cost of farming down and helped circumvent natural limits on crop production and stock-raising. The use of shifting cultivation, free-range animal husbandry, and slaves to perform erosion control masked the environmental impacts of farmers’ actions, at least temporarily. Debates over westward expansion during the sectional crisis of the 1850s were not just about the extension of slavery, they also reflected practical concerns regarding access to new lands and fresh soil. Both were necessary for the continued profitability of farming in the South.

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

Environment and Planning B Planning and Design ◽

10.1068/b32098 ◽

2007 ◽

Vol 34 (4) ◽

pp. 708-724 ◽

Cited By ~ 87

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.

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Multi-Scenario Prediction of Intra-Urban Land Use Change Using a Cellular Automata-Random Forest Model

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10080503 ◽

2021 ◽

Vol 10 (8) ◽

pp. 503

Author(s):

Hang Liu ◽

Riken Homma ◽

Qiang Liu ◽

Congying Fang

Keyword(s):

Land Use ◽

Random Forest ◽

Cellular Automata ◽

Land Use Change ◽

Urban Land ◽

Urban Land Use ◽

Random Forest Model ◽

Growth Trend ◽

Related Factors ◽

Forest Model

The simulation of future land use can provide decision support for urban planners and decision makers, which is important for sustainable urban development. Using a cellular automata-random forest model, we considered two scenarios to predict intra-land use changes in Kumamoto City from 2018 to 2030: an unconstrained development scenario, and a planning-constrained development scenario that considers disaster-related factors. The random forest was used to calculate the transition probabilities and the importance of driving factors, and cellular automata were used for future land use prediction. The results show that disaster-related factors greatly influence land vacancy, while urban planning factors are more important for medium high-rise residential, commercial, and public facilities. Under the unconstrained development scenario, urban land use tends towards spatially disordered growth in the total amount of steady growth, with the largest increase in low-rise residential areas. Under the planning-constrained development scenario that considers disaster-related factors, the urban land area will continue to grow, albeit slowly and with a compact growth trend. This study provides planners with information on the relevant trends in different scenarios of land use change in Kumamoto City. Furthermore, it provides a reference for Kumamoto City’s future post-disaster recovery and reconstruction planning.

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Multi-Temporal Built-Up Grids of Brazilian Cities: How Trends and Dynamic Modelling Could Help on Resilience Challenges?

Sustainability ◽

10.3390/su13020748 ◽

2021 ◽

Vol 13 (2) ◽

pp. 748

Author(s):

Iana Rufino ◽

Slobodan Djordjević ◽

Higor Costa de Brito ◽

Priscila Barros Ramalho Alves

Keyword(s):

Land Use ◽

Urban Planning ◽

Cellular Automata ◽

Land Use Change ◽

Spatial Pattern ◽

Urban Growth ◽

Spatial Information ◽

Dynamic Modelling ◽

Urban Models ◽

Extreme Hazards

The northeastern Brazilian region has been vulnerable to hydrometeorological extremes, especially droughts, for centuries. A combination of natural climate variability (most of the area is semi-arid) and water governance problems increases extreme events’ impacts, especially in urban areas. Spatial analysis and visualisation of possible land-use change (LUC) zones and trends (urban growth vectors) can be useful for planning actions or decision-making policies for sustainable development. The Global Human Settlement Layer (GHSL) produces global spatial information, evidence-based analytics, and knowledge describing Earth’s human presence. In this work, the GHSL built-up grids for selected Brazilian cities were used to generate urban models using GIS (geographic information system) technologies and cellular automata for spatial pattern simulations of urban growth. In this work, six Brazilian cities were selected to generate urban models using GIS technologies and cellular automata for spatial pattern simulations of urban sprawl. The main goal was to provide predictive scenarios for water management (including simulations) and urban planning in a region highly susceptible to extreme hazards, such as floods and droughts. The northeastern Brazilian cities’ analysis raises more significant challenges because of the lack of land-use change field data. Findings and conclusions show the potential of dynamic modelling to predict scenarios and support water sensitive urban planning, increasing cities’ coping capacity for extreme hazards.

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Landscape pattern and economic factors’ effect on prediction accuracy of cellular automata-Markov chain model on county scale

Open Geosciences ◽

10.1515/geo-2020-0162 ◽

2020 ◽

Vol 12 (1) ◽

pp. 626-636

Author(s):

Wang Song ◽

Zhao Yunlin ◽

Xu Zhenggang ◽

Yang Guiyan ◽

Huang Tian ◽

...

Keyword(s):

Land Use ◽

Markov Chain ◽

Cellular Automata ◽

Markov Model ◽

Prediction Accuracy ◽

Driving Mechanism ◽

Economic Factors ◽

Chain Model ◽

The Impact ◽

County Scale

AbstractUnderstanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.

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