scholarly journals Simulating Carbon Sequestration using Cellular Automata and land use assessment; Case of: Karaj City, Iran

2017 ◽  
Author(s):  
Ali Khatibi ◽  
Sharareh Pourebrahim ◽  
Mazlin Mokhtar
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Cellular Automata ◽  
Dry Weight ◽  
Soil Samples ◽  
Barren Area ◽  
Average Value ◽  
Class Average ◽  
Effective Use ◽  
The City

Abstract. In this study, in the city of Karaj five classes of land use-cover including residential, agriculture, rangeland, forest and barren areas were considered and randomly in each class a total of 20 points were selected and vegetation and soil samples were taken. In plant samples, the amount of carbon sequestration was determined by calculating the amount of organic carbon by dry weight and in soil samples, the amount of carbon sequestration was determined by using Walleky and Black method, too. For each area, the average value of carbon sequestration of samples was introduced as carbon sequestration index of that class. Average values for each category were determined as an indicator of carbon sequestration of that class and then by using the DINAMICA EGO software a simulation was conducted using cellular automata approach to simulate changes in the classes of land use-cover in the city of Karaj. Finally, by using carbon sequestration index and the results of the simulation, changes in carbon sequestration in each class were calculated. On this basis, it was found that in the 15-year period from 2014 to 2029, not considering the residential class as the effective use of carbon sequestration, the greatest amount of carbon sequestration was found in the agricultural class and the lowest carbon sequestration was found in barren area. Also, agriculture class will be faced with the huge reduction of carbon sequestration, because of expansion of the residential area.

scholarly journals Simulating carbon sequestration using cellular automata and land use assessment for Karaj, Iran

Solid Earth ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 735-744 ◽  
Author(s):  
Ali Khatibi ◽  
Sharareh Pourebrahim ◽  
Mazlin Bin Mokhtar
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Cellular Automata ◽  
Urban Areas ◽  
Agricultural Land ◽  
Effective Means ◽  
Population Expansion ◽  
Soil Samples ◽  
Plant Weight ◽  
Service Areas

Abstract. Carbon sequestration has been proposed as a means of slowing the atmospheric and marine accumulation of greenhouse gases. This study used observed and simulated land use/cover changes to investigate and predict carbon sequestration rates in the city of Karaj. Karaj, a metropolis of Iran, has undergone rapid population expansion and associated changes in recent years, and these changes make it suitable for use as a case study for rapidly expanding urban areas. In particular, high quality agricultural space, green space and gardens have rapidly transformed into industrial, residential and urban service areas. Five classes of land use/cover (residential, agricultural, rangeland, forest and barren areas) were considered in the study; vegetation and soil samples were taken from 20 randomly selected locations. The level of carbon sequestration was determined for the vegetation samples by calculating the amount of organic carbon present using the dry plant weight method, and for soil samples by using the method of Walkley and Black. For each area class, average values of carbon sequestration in vegetation and soil samples were calculated to give a carbon sequestration index. A cellular automata approach was used to simulate changes in the classes. Finally, the carbon sequestration indices were combined with simulation results to calculate changes in carbon sequestration for each class. It is predicted that, in the 15 year period from 2014 to 2029, much agricultural land will be transformed into residential land, resulting in a severe reduction in the level of carbon sequestration. Results from this study indicate that expansion of forest areas in urban counties would be an effective means of increasing the levels of carbon sequestration. Finally, future opportunities to include carbon sequestration into the simulation of land use/cover changes are outlined.

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.

scholarly journals Allometric equation of local bamboo for estimating carbon sequestration of bamboo riparian forest

2021 ◽  
Vol 905 (1) ◽  
pp. 012002
Author(s):  
C Prayogo ◽  
C Muthahar ◽  
R M Ishaq
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Riparian Forest ◽  
Dry Weight ◽  
Allometric Equation ◽  
Total Carbon ◽  
Destructive Sampling ◽  
Industrial Activities ◽  
Bamboo Stem ◽  
The Relationship

Abstract The cause of global warming is the increasing carbon concentration arising from industrial activities, burning of fossils, and land-use change. The purpose of this research was to find out the allometric equation to calculate the local bamboo biomass and then to be able to calculate how much carbon sequestration at bamboo riparian forest since this area was rarely being explored. The parameters observed were the height and diameter of the bamboo stem at 1.3 m height of 6 types of local bamboo using destructive sampling, along with the measurement of bamboo weight. The carbon content of the bamboo biomass, litter, and soil was measured to complement the estimation of total carbon sequestration. The results showed that the allometric equation for estimating local bamboo biomass is Y=0.6396 X1.6162 with R2=0.77, obtained from the relationship equations between dry weight and the diameter. Total carbon sequestration of this system ranged between 81 to 215 tons C ha−1.

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 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.

Carbon Sequestration in the Soils under Different Land uses in Yamunanagar District of Haryana

2013 ◽  
Vol 36 (1) ◽  
pp. 17-22
Author(s):  
M.K. Gupta ◽  
S. Sharma
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Carbon Sequestration ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Samples ◽  
Land Uses ◽  
Dead Biomass ◽  
Organic Carbon Pool ◽  
One Way Anova

Soil Organic Carbon has been ignored since long because it was treated as a dead biomass. After the awareness of climate change, its importance has been recognized worldwide. Therefore, this study was conducted in four land uses viz. Forests, Plantations, Horticulture and Agroforestry in Yamunanagar district of Haryana. Over all, fifty nine numbers of sampling sites (Four hundred and fourteen soil samples) were selected in all land uses from the district. Variation in the number of samples was due to difference in area available under particular land uses. In Yamunanagar district, maximum SOC pool was under Forests (51.05 t ha-1) followed by Plantations (35.32 t ha-1), Horticulture (33.58 t ha-1) and the least was under Agroforestry (29.22 t ha-1). SOC pool under Forests was 44.54 %, 52.03% and 74.71% higher as compared to Plantations, Horticulture and Agroforestry land uses respectively. SOC pool under Plantations was marginally higher as compared to Horticulture (5.18 %) while it was 20.88 % higher in comparison to Agroforestry. Organic carbon pool in the soils under Horticulture land use was 14.92 % higher as compared to soils under Agroforestry land use. When SOC pool under different land uses were tested by one - way ANOVA, it was found that SOC pool under all land uses were significantly different. SOC pool under Forests was statistically significantly different with the SOC pool under Plantation, Agroforestry and Horticulture. Results of one - way ANOVA indicates that SOC pool between the different plantations was significantly different at 0.05 level.

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