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 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 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 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 Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 42 ◽  
Author(s):  
Wei Sun ◽  
Zhihong Liu ◽  
Yang Zhang ◽  
Weixin Xu ◽  
Xiaotong Lv ◽  
...  
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Correlation Coefficient ◽  
Urban Areas ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Simulation Results ◽  
The City ◽  
Better Than

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25° × 0.25°-resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased. (2) The microphysical scheme WSM3 (WRF Single–Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM2.5 in urban areas was higher than that in the suburbs, and the concentration of PM2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas.

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 PREDIKSI SPASIAL DINAMIKA AREAL TERBANGUN KOTA SEMARANG DENGAN MENGGUNAKAN MODEL REGRESI LOGISTIK

2016 ◽  
Vol 18 (2) ◽  
pp. 95 ◽  
Author(s):  
Irmadi Nahib
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Cellular Automata ◽  
Land Cover ◽  
Open Space ◽  
Land Use Changes ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Rate Of Increase ◽  
The City

<p class="JudulABSInd"><strong>ABSTRAK</strong></p><p class="abstrak">Salah satu indikator perkembangan fisik wilayah kota dapat diidentifikasi melalui fenomena perubahan tutupan lahan bervegetasi menjadi lahan terbangun. Perubahan lahan tersebut dapat berdampak terhadap penurunan kualitas lingkungan, akibat berkurangnya ruang terbuka hijau. Kota Semarang dengan visi terwujudnya Semarang sebagai kota perdagangan dan jasa yang berbudaya menuju masyarakat sejahtera, merupakan  wilayah yang rentan mengalami perubahan penggunaan lahan yang cenderung kearah lahan terbangun. Penelitian ini mengintegrasikan model <em>Cellular Automata</em> (CA) dan regresi logistik biner untuk memprediksi dinamika lahan terbangun di Kota Semarang. Citra yang digunakan adalah Citra Ikonos 2002, Ikonos 2006 dan <em>Quic</em><em>kbird</em> 2012. Model CA pada penelitian ini digunakan untuk memprediksi sebaran penutup lahan tahun 2022 dan 2032 dengan mempertimbangkan jarak terhadap jalan, jarak terhadap sungai, jarak terhadap lahan terbangun, ketinggian, kepadatan penduduk, <em>evidence likelihood </em>perubahan lahan dan indeks pengembangan kelurahan yang diakomodasi dalam peta sub-model transisi hasil model regresi logistik biner. Hasil penyusunan model ini adalah peta prediksi penutup lahan dengan akurasi 78,21 % validitas model yang dihasilkan dapat dikategorikan “<em>moderate</em>” mengindikasikan bahwa peta yang dihasilkan dapat digunakan. Hasil pemodelan menunjukkan bahwa Kota Semarang pada tahun 2022 terjadi pertambahan luas lahan terbangun rata-rata 284 ha/tahun dan pada tahun 2032 rata-rata 226 ha/tahun.</p><p><strong><em>Kata </em></strong><strong><em>k</em></strong><strong><em>unci</em></strong><em>: </em><em>cellular automata, pemodelan, regresi logistik biner, lahan terbangun</em></p><p class="judulABS"><em><strong>ABSTRACT</strong></em></p><p class="Abstrakeng">One indicator of the physical development of the city can be identified by phenomenon of land expansion, vegetated land cover changes to be built-up area. The land use changes can impact to environmental degradation, due to reduced green open space. Semarang as a city of trade and services cultured toward a prosperous community, a region that is vulnerable to changes in land use tends toward small plots. This research integrates the model of Cellular Automata (CA) and binary logistic regression to predict the dynamics of builtup area in the city of Semarang. The image used is a Ikonos imagery (2002), Ikonos imagery (2006) and Quickbird (2012). Model CA in this research use to predict the distribution of land cover 2022 and 2032 with respect to: distance to roads, the distance to the river, the distance to the built-up area, elevation, population density, evidence likelihood of land use change and development villages index were accommodated in the map sub-model transition binary logistic regression model results. The results of this study are predictive maps of built-up area  with an accuracy of 78,21 % so that the validity of the resulting model can be categorized as "moderate", indicates that the probability map is valid. Modeling results showed that Semarang City in 2022 predicted rate of increase of  built-up area an average 284  ha / year and in 2032 rate of increase of built-up area an average 226 ha / year.</p><p><strong><em>Keywords</em></strong><em>: cellular automata, modelling, binary logistic regression, built-up area</em></p>

scholarly journals Spatial Analysis Of Land Use Changes Towards Banjarbaru City's Regional Spatial Plan

2021 ◽  
Vol 1 (11) ◽  
Author(s):  
Setya Etika Mulyasari ◽  
Suyanto Suyanto ◽  
Gusti M. Hatta ◽  
Bambang Joko Priatmadi
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Vacant Land ◽  
City Development ◽  
Dry Land ◽  
Wetland Agriculture ◽  
The Village ◽  
The City ◽  
Spatial Plan

Banjarbaru City is one of the cities in South Kalimantan Province which is developing quite rapidly from year to year. Hence,  it is necessary to research and study changes in land use and their suitability with the city development plan. The purpose of this study is to examine changes in the area and types of land use changes in Banjarbaru City within a period of 8 years, from 2013 to 2021, determine the rate of land use change, and assess the suitability of land use changes to the applicable Banjarbaru City spatial plan. This research method is an overlay to see changes in land use and the suitability of changes in land use with the direction of spatial functions in the Regional Spatial Plan. The result of this research is that in an area of ​​16,414.00 ha (53.7%) there is a change in land use in Banjarbaru City in the period 2013-2021. The biggest land use changes are dry land agriculture, vacant land, wetland agriculture, housing, and villages. The use of dry land  and agricultural land has the largest decrease in area, which is 15,090.71 ha or a decrease of 365.5%. The use of vacant land increased in an area of ​​14,715.684 hectares or an increase of almost 4 times. Wetland agriculture has decreased in an area which is reduced by 986.55 ha or decreased by 65.8%. The use of land for housing/residential in the form of housing or villages has also undergone considerable changes. The use of residential land has increased by 528.105 hectares (44.626%) and the village area to 444.32 ha (21.2%). The suitability of land use with the RTRW in Banjarbaru City is 16,742.86 ha (54.8%) categorized as appropriate, while an area of ​​13,779.69 ha (45.2%) is categorized as not in accordance with the applicable RTRW.

scholarly journals Application of the SWAT model in the Pinios river basin under different land-use scenarios

2013 ◽  
Vol 5 (2) ◽  
pp. 71-79 ◽  
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Agricultural Land ◽  
Swat Model ◽  
Land Use Changes ◽  
Time Step ◽  
Pinios River ◽  
Monthly Runoff ◽  
The One ◽  
Main Components

This paper investigates the hydrological effects of specific land use changes in a catchment of the river Pinios in Thessaly (Ali Efenti catchment), through the application of the Soil and Water Assessment Tool (SWAT) on a monthly time step. The model's calibration efficiency is verified by comparing the simulated and observed discharge time series at the outlet of the watershed, where long series of hydrometrical data exist. The model is used to simulate the main components of the hydrologic cycle, in order to study the effects of land use changes. Three land use change scenarios are examined, namely (A) expansion of agricultural land, (B) complete deforestation of the Trikala sub-basin and (C) expansion of urban areas in the Trikala sub-basin. All three scenarios resulted in an increase in discharge during wet months and a decrease during dry periods. The deforestation scenario was the one that resulted in the greatest modification of total monthly runoff.

Sign in / Sign up

Export Citation Format

Share Document