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 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 Analysis of Land Use and Land Cover Change in Gummidipoondi Using Remote Sensing and GIS Tools

2021 ◽  
Vol 9 (6) ◽  
pp. 675-682
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing And Gis ◽  
Rural Land ◽  
Anthropogenic Pressures ◽  
Rural Land Use ◽  
Gis Tools ◽  
Liss Iii ◽  
Surrounding Areas

The aim of the study was to evaluate the changes in land use and land cover (LULC) in Gummidipoondi and the surrounding areas in Thiruvallur district, Tamilnadu India.Spatio-temporal variation in the land use and land cover were analysed on a decadal basis for the period from 1990 to 2019 using remote sensing and GIS based tools. The Landsat 5 (TM) and Resource-Sat 2 (LISS-III) data was used for the LULC classificationin the study area. During the study period from 1990 to 2019, built-up area including industrial, urban and rural land use increased by about 147%. Predominant change was also noticed in the mudflat category where more than 95% of it was lost to various other land uses such as agriculture and marsh area. This observation calls for planning and conservation of sensitive ecosystems in the study area that may be lost due to anthropogenic pressures via pollution and undesirable conversion of LULC. The study revealed no significant changes in the extent of other LULC classes such as agriculture, forests, plantations, land with or without scrub, rivers and waterbodies in the study area

Rural land use and land cover change

1995 ◽  
Vol 12 (3) ◽  
pp. 223-236 ◽  
Author(s):  
Donna L Erickson
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Rural Land ◽  
Rural Land Use

scholarly journals The Roles of Precipitation Increases and Rural Land-Use Changes in Streamflow Trends in the Upper Mississippi River Basin

2010 ◽  
Vol 14 (20) ◽  
pp. 1-12 ◽  
Author(s):  
J. P. Kochendorfer ◽  
J. A. Hubbart
Keyword(s):  
Land Use ◽  
Mississippi River ◽  
Land Use Changes ◽  
The United States ◽  
Climatic Data ◽  
Rural Land ◽  
Peak Flows ◽  
Rural Land Use ◽  
Streamflow Trends ◽  
The U.S

Abstract Recent trends in precipitation and streamflow in the United States have become a particular focus of hydroclimatic research. The U.S. Hydro-Climatic Data Network (HCDN) has proven to be especially useful for the analysis of long-term streamflow trends. The U.S. Geological Survey (USGS) scientists selected sites for inclusion in the HCDN from the USGS stream-gauge network on the basis of streamflows being relatively free of nonclimatic anthropogenic influences. Consequently, most previous analyses of flow trends at those sites have either implicitly or explicitly attributed the trends to climate change and variability. In this paper, trends in seasonal and annual precipitation, and annual 7-day low, mean, and peak flows are examined for 48 medium-sized HCDN streams in the upper Mississippi (UM) water-resource region over 1939–2008. Using the concept of precipitation elasticity of flow, it is shown that the observed magnitudes of statistically significant increases in mean and low flows were up to a factor of 3 greater than expected from observed precipitation increases alone. Peak flows increased less than expected, and in the case of the Driftless Area at the center of the UM basin, decreased despite increased precipitation. It is proposed that the differences between expected and observed changes in streamflow can be explained by rural land-use changes in this principally agricultural region.

scholarly journals A Review of Land Use Land Cover Change in The Catchment Area of Musi Hydropower Plant in Bengkulu Province

2021 ◽  
Vol 305 ◽  
pp. 04001
Author(s):  
Sukisno ◽  
Widiatmaka ◽  
Januar J. Purwanto ◽  
Bambang Pramudya N ◽  
Khursatul Munibah
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Catchment Area ◽  
Negative Impact ◽  
Land Use Changes ◽  
Hydropower Plant ◽  
Land Use Land Cover ◽  
Dry Land ◽  
Land Cover Map

This research was conducted to review land use land cover change in the catchment area of Musi Hydropower Plant in Bengkulu Province. The data used in this research is land use land cover map year 2000 to 2018 from Ministry of Environment and Forestry of the Republic of Indonesia. The analyse was done by overlaying time series map of land use land cover map from 2000 to 2018 on the map of forest area. The result shows that primary dryland forest degradated significantly, around 568 ha less than 20 years. In the other side, settlements and built-up area significantly increase, 1.331 ha in 20 years. Meanwhile, the land use of agricultural dry land mixed with shrubs, in agregat decreased by 1.078 ha. The area of agricultural dry land mixed with shrubs was increase during period of 2000 to 2014, and then slightly decrease in the period of 2014 to 2018. Land use changes on the catchment area have negative impact on the quality of environmental services, such as erosion and sedimentation on the reservoir of Musi Hydropower Plant. Intervention needed to reduce the negative impact of the land use change on ecosystem services.

scholarly journals IMPACT OF SPATIAL FILTER ON LAND-USE CHANGES MODELLING USING URBAN CELLULAR AUTOMATA

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 429-433 ◽  
Author(s):  
M. Omidipoor ◽  
N. N. Samani
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Changes ◽  
Spatial Filter ◽  
Kappa Index ◽  
Spatial Filters ◽  
Size And Shape ◽  
Neighbourhood Size ◽  
Different Shapes ◽  
The Impact

Urban cellular automata is used vastly in simulating of urban evolutions and dynamics. Finding an appropriate neighbourhood size in urban cellular automata modelling is important because the outputs are strongly influenced by input parameters. This paper investigates the impact of spatial filters on behaviour and outcome of urban cellular automata models. In this study different spatial filters in various sizes including 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15 and 17*17 cells are used in a scenario of land-use changes. The proposed method is examined changes in size and shape of spatial filter whereas the resolution was kept fixed. The implementation results in Ahvaz city demonstrated that KAPPA index is changed in different shapes and types at the time when different spatial filters are used. However, circular shape with size of 5*5 offers better accuracy.

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.

Urban and rural land use in Puerto Rico

2008 ◽  
Author(s):  
Sebastian Martinuzzi ◽  
William A. Gould ◽  
Olga M. Ramos Gonzalez ◽  
Maya Quinones ◽  
Michael E. Jimenez
Keyword(s):  
Land Use ◽  
Puerto Rico ◽  
Rural Land ◽  
Rural Land Use
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