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

scholarly journals Analisis Perubahan Penggunaan Lahan Dan Prediksinya dengan Menggunakan Markov – Cellular Automata Di Wilayah Peri Urban Kota Malang

2021 ◽  
Vol 23 (3) ◽  
pp. 307-319
Author(s):  
Mirza Permana ◽  
Santun Risma Pandopatan Sitorus ◽  
Darmawan Darmawan
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Significant Influence ◽  
Urban Areas ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Spatial Dynamics ◽  
Urban Life ◽  
Unique Region ◽  
The City

Peri Urban Area is a unique region with spatial dynamics that continues to experience changes that have an important role to play in the urban life in the future. There are 8 sub-districts in Malang Regency which are directly adjacent to Malang City and have a significant influence on the development of the city. Objectives of this research are to determine the dynamics of land use change from 2008 - 2018 and to predict land use in 2030. The method used is the analysis of land use changes from landsat TM 8 images in 2008 and 2013 to predict land use in 2018 which then tested the validity to get a level of accuracy. The results showed the development of built-up area has increased by 12% while agricultural land has experienced a declining trend. Significant changes occurred in Singosari, Pakisaji and Karangploso sub-district. Validation of land use between the predictions of 2018 and actual land use in 2018 showed that the value of kappa was quite high, at 87%. The trend of land use in peri-urban areas until the year 2030 is predicted to have built up area of 26,456 ha, which means an increase 17,686 ha (33.6%) from the existing year 2018. The potential incompatibility of the RTRW with the predicted land use in 2030 is 11,950 ha or 22.7%.

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 Simulation and Analysis of Land Use Changes Applying Cellular Automata in the South of Quito and the Machachi Valley, Province of Pichincha, Ecuador

2021 ◽  
Vol 13 (17) ◽  
pp. 9525
Author(s):  
René Ulloa-Espíndola ◽  
Susana Martín-Fernández
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Urban Areas ◽  
Land Use Changes ◽  
Urban Land Use ◽  
The South ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Urban Settlements ◽  
The City

Rapid urban growth has historically led to changes in land use patterns and the degradation of natural resources and the urban environment. Uncontrolled growth of urban areas in the city of Quito has continued to the present day since 1960s, aggravated by illegal or irregular new settlements. The main objective of this paper is to generate spatial predictions of these types of urban settlements and land use changes in 2023, 2028 and 2038, applying the Dinamica EGO cellular automata and multivariable software. The study area was the Machachi Valley between the south of the city of Quito and the rural localities of Alóag and Machachi. The results demonstrate the accuracy of the model and its applicability, thanks to the use of 15 social, physical and climate predictors and the validation process. The analysis of the land use changes throughout the study area shows that urban land use will undergo the greatest net increase. Growth in the south of Quito is predicted to increase by as much as 35% between 2018 and 2038 where new highly vulnerable urban settlements can appear. Native forests in the Andes and forest plantations are expected to decline in the study area due to their substitution by shrub vegetation or agriculture and livestock land use. The implementation of policies to control the land market and protect natural areas could help to mitigate the continuous deterioration of urban and forest areas.

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.

Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting

2018 ◽  
Vol 190 (6) ◽  
Author(s):  
Fatemeh Jahanishakib ◽  
Seyed Hamed Mirkarimi ◽  
Abdolrassoul Salmanmahiny ◽  
Fatemeh Poodat
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Land Use Change Modeling

Ecosystem Valuation of Agricultural Land Use Change

2022 ◽  
pp. 90-126
Author(s):  
Dimple Behal
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
Urban Areas ◽  
Agricultural Land ◽  
Policy Instruments ◽  
Social Progress ◽  
Agricultural Ecosystem ◽  
Underlying Causes ◽  
Rapid Pace

With the rapid pace of urbanization, land-use change is essential for economic and social progress; however, it does not come without costs. With such rapid urbanization, there comes pressure on the land and its resources, like that of food and timber production with a significant impact on the livelihood of millions of people. With the loss of agricultural land due to developmental activities, future agriculture would be very intensive. Therefore, it is likely with the existing pattern of allocating land uses for future development that we may lose the ecosystem services and highly productive agricultural lands. The value of these ecosystem services to agriculture is enormous and often underappreciated. The study focuses on identifying underlying causes of the land-use change, ecosystem services affected due to land-use change in peri-urban areas of Chandigarh using spatial mapping of affected ecosystem services and suggesting proposals for promoting agricultural ecosystem values using economically-informed policy instruments.

scholarly journals Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

2019 ◽  
Vol 8 (10) ◽  
pp. 454 ◽  
Author(s):  
Junfeng Kang ◽  
Lei Fang ◽  
Shuang Li ◽  
Xiangrong Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Markov Model ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing Images ◽  
Mapreduce Framework ◽  
Construction Land ◽  
Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

scholarly journals Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

2018 ◽  
Vol 10 (11) ◽  
pp. 4287 ◽  
Author(s):  
Yantao Xi ◽  
Nguyen Thinh ◽  
Cheng Li
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Urban Areas ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Local Level ◽  
Land Use Changes ◽  
Landscape Patterns ◽  
Rapid Urbanization ◽  
Barren Land

Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

scholarly journals Link between Land Use and Flood Risk Assessment in Urban Areas

Proceedings ◽  
2020 ◽  
Vol 30 (1) ◽  
pp. 62
Author(s):  
Zahra Kalantari ◽  
Johanna Sörensen
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Green Infrastructure ◽  
Flood Risk ◽  
Urban Areas ◽  
Land Use Changes ◽  
Drainage System ◽  
Property Owners ◽  
Pluvial Flooding ◽  
The Impact

The densification of urban areas has raised concerns over increased pluvial flooding. Flood risk in urban areas might increase under the impact of land use changes. Urbanisation involves the conversion of natural areas to impermeable areas, causing lower infiltration rates and increased runoff. When high-intensity rainfall exceeds the capacity of an urban drainage system, the runoff causes pluvial flooding in low-laying areas. In the present study, a long time series (i.e., 20 years) of geo-referenced flood claims from property owners has been collected and analysed in detail to assess flood risk as it relates to land use changes in urban areas. The flood claim data come from property owners with flood insurance that covers property loss from overland flooding, groundwater intrusion through basement walls, as well as flooding from drainage systems; these data serve as a proxy of flood severity. The spatial relationships between land use change and flood occurrences in different urban areas were analysed. Special emphasis was placed on examining how nature-based solutions and blue-green infrastructure relate to flood risk. The relationships are defined by a statistical method explaining the tendencies whereby land use change affects flood risk.

Sign in / Sign up

Export Citation Format

Share Document