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 Modeling Major Rural Land-Use Changes Using the GIS-Based Cellular Automata Metronamica Model: The Case of Andalusia (Southern Spain)

2020 ◽  
Vol 9 (7) ◽  
pp. 458 ◽  
Author(s):  
Rafael M. Navarro Cerrillo ◽  
Guillermo Palacios Rodríguez ◽  
Inmaculada Clavero Rumbao ◽  
Miguel Ángel Lara ◽  
Francisco Javier Bonet ◽  
...  
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Cover ◽  
Land Use Changes ◽  
Growth Patterns ◽  
Kappa Index ◽  
Rural Land ◽  
Dry Land ◽  
Rural Land Use ◽  
Clustered Network

The effective and efficient planning of rural land-use changes and their impact on the environment is critical for land-use managers. Many land-use growth models have been proposed for forecasting growth patterns in the last few years. In this work; a cellular automata (CA)-based land-use model (Metronamica) was tested to simulate (1999–2007) and predict (2007–2035) land-use dynamics and land-use changes in Andalucía (Spain). The model was calibrated using temporal changes in land-use covers and was evaluated by the Kappa index. GIS-based maps were generated to study major rural land-use changes (agriculture and forests). The change matrix for 1999–2007 showed an overall area change of 674971 ha. The dominant land uses in 2007 were shrubs (30.7%), woody crops on dry land (17.3%), and herbaceous crops on dry land (12.7%). The comparison between the reference and the simulated land-use maps of 2007 showed a Kappa index of 0.91. The land-cover map for the projected PRELUDE scenarios provided the land-cover characteristics of 2035 in Andalusia; developed within the Metronamica model scenarios (Great Escape; Evolved Society; Clustered Network; Lettuce Surprise U; and Big Crisis). The greatest differences were found between Great Escape and Clustered Network and Lettuce Surprise U. The observed trend (1999–2007–2035) showed the greatest similarity with the Big Crisis scenario. Land-use projections facilitate the understanding of the future dynamics of land-use change in rural areas; and hence the development of more appropriate plans and policies

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 Spatio-temporal analysis of land use/land cover dynamics in Sokoto Metropolis using multi-temporal satellite data and Land Change Modeller

2020 ◽  
Vol 52 (3) ◽  
pp. 306
Author(s):  
Murtala Dangulla ◽  
Latifah Abd Manaf ◽  
Firuz Ramli Mohammad
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Open Space ◽  
Urban Expansion ◽  
Land Use Land Cover ◽  
Land Change ◽  
Landsat Images ◽  
Green Area ◽  
Rate Of Increase ◽  
Green Areas

Urbanization is currently one of the most pressing environmental issues which cuts across all countries at unprecedented rates and intensities, with far reaching consequences on ecosystems, biodiversity and human wellbeing. This paper assessed urban expansion and land use/land cover changes in Sokoto metropolis, North-western Nigeria using Remote Sensing and GIS. Landsat images of 1990, 1999 and 2015 were processed for LULC classification and change detection using the Maximum Likelihood Classification, Post Classification Comparison techniques and the Land Change Modeler. The classification revealed five broad land cover classes which include Built-up Area, Farmland, Green Area, Open Space and Wetland/Water. The Built-up and Green areas continuously increased while Farmland and Open space decreased throughout the study period. The metropolis expanded radially at a faster rate between 1999 and 2015 with the highest rate of increase (1890.5ha per annum) recorded in the Built-up Area. This implies a doubling time of approximately 30 years at the expense of Farmland and Open space which may be completely exhausted in 40 and 29 years respectively. Infrastructural provision should thus align with the rate and direction of growth and where the Green Area is converted, replacement should be made to ensure continued supply and stability of the numerous ecosystem services green areas provide.

scholarly journals Modeling the Impact of Urbanization on Land-Use Change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov Chain Approach

Land ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 115 ◽  
Author(s):  
Melaku Bogale Fitawok ◽  
Ben Derudder ◽  
Amare Sewnet Minale ◽  
Steven Van Passel ◽  
Enyew Adgo ◽  
...  
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Urban Expansion ◽  
Land Use Changes ◽  
Sustainable Urban Development ◽  
Bahir Dar ◽  
Landsat Images ◽  
The Impact ◽  
The City

The fast-paced urbanization of recent decades entails that many regions are facing seemingly uncontrolled land-use changes (LUCs) that go hand in hand with a range of environmental and socio-economic challenges. In this paper, we use an integrated cellular automata–Markov chain (CA–MC) model to analyze and predict the urban expansion of and its impact on LUC in the city of Bahir Dar, Ethiopia. To this end, the research marshals high-resolution Landsat images of 1991, 2002, 2011, and 2018. An analytical hierarchy process (AHP) method is then used to identify the biophysical and socioeconomic factors underlying the expansion in the research area. It is shown that, during the period of study, built-up areas are rapidly expanding in the face of an overall decline of the farmland and vegetation cover. Drawing on a model calibration for 2018, the research predicts the possible geographies of LUC in the Bahir Dar area for 2025, 2034, and 2045. It is predicted that the conversions of other land-use types into built-up areas will persist in the southern, southwestern, and northeastern areas of the sprawling city, which can mainly be traced back to the uneven geographies of road accessibility, proximity to the city center, and slope variables. We reflect on how our findings can be used to facilitate sustainable urban development and land-use policies in the Bahir Dar area.

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 Land-Use and Land Cover Changes on the Slopes of Mount Meru-Tanzania

2018 ◽  
Vol 13 (3) ◽  
pp. 331-352
Author(s):  
ALDO. J. KITALIKA ◽  
REVOCATUS. L. MACHUNDA ◽  
HANS. C. KOMAKECH ◽  
KAROLI. N. NJAU
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Cover ◽  
Land Use Changes ◽  
Mixed Forest ◽  
Spatial Filter ◽  
Software Environment ◽  
Agriculture Land ◽  
The Future ◽  
Environmental Transitions

The study of spatial land use and land change is inevitable for sustainable development of land use plans. Environmental transitions analysis was done in part of the land on the slopes of the foothills of Mount Meru in thirty (30) years’ time from 1986 to 2016 using satellite-derived land use/cover maps and a Cellular Automata (CA) spatial filter under IDRISI software environment and assessed the important land use changes. Also, the future land use for 2026 which is the next ten (10) years was simulated based on Cellular-Automata Markov model. The results showed significant land use transitions whereby there is a huge land use change of bush land (BL) and agriculture land (AG) into human settlement (ST) which resulted into conversion of Arusha town into a City. In addition, the changes have caused slight changes in water bodies into mixed forest. Moreover, the future land use/land cover (LULC) simulations indicated that there will be unsustainable LULC changes in the next ten years since most of bush land and part of agriculture land will be used for building different structures thus interfering with fresh water and food availability in the City. These changes call upon the relevant planning authorities to put in place the best strategies for good urban development.

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