Detection of Land Use Change and Future Prediction with Markov Chain Model in a Part of Narmada River Basin, Madhya Pradesh

2014 ◽  
pp. 3-14 ◽  
Author(s):  
Arun Mondal ◽  
Deepak Khare ◽  
Sananda Kundu ◽  
Prabhash Kumar Mishra
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
River Basin ◽  
Markov Chain Model ◽  
Madhya Pradesh ◽  
Chain Model ◽  
Narmada River ◽  
Future Prediction

scholarly journals Integration of GIS and Markov chain model for land use change assessment: A case study in the upstream Ba river basin, Gia Lai province

2021 ◽  
Vol 20 (04) ◽  
pp. 69-77
Author(s):  
Huyen T. Nguyen
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
River Basin ◽  
Land Use Planning ◽  
Land Use Changes ◽  
Chain Model ◽  
Forest Land ◽  
Change Assessment ◽  
South Central

Ba river is the biggest river system in the South-Central Coast of Vietnam and plays a significant role in the socio-economic development of the region. Recently, land-use changes in Gia Lai province have been significantly transformed. Hence, to provide the information for land-use planning, there is an urgent need for land-use change assessment in the upstream Ba river basin. This study employed the Markov chain coupled with GIS to assess land-use changes between 2010 - 2015 and 2015 - 2020 periods. The results showed that during the period 2010 - 2015, there was no significant conversion of agricultural and reserve forest land. Meanwhile, a large proportion of unused (86%) and water and aquacultural land (57.5%) was converted into the other land-use types. Between 2020 and 2015, unused land decreased while the surface water and aquacultural land increased. The forest land accounted for a significant area (51.16%) during the 2015 - 2020 period. In addition, the driving forces leading to these changes were also analyzed, providing a more comprehensive of land-use change in the study area. In general, GIS and Markov were suitable for assessing land-use change. This study outcomes provide a general framework for land-use planning in Gia Lai province.

scholarly journals Improving land-use change modeling by integrating ANN with Cellular Automata-Markov Chain model

Heliyon ◽  
2020 ◽  
Vol 6 (9) ◽  
pp. e05092
Author(s):  
Anne Gharaibeh ◽  
Abdulrazzaq Shaamala ◽  
Rasha Obeidat ◽  
Salman Al-Kofahi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Land Use Change ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Change Modeling

scholarly journals Modeling And Spatial Analysis Of Change Settlement And Fair Market Land Price Using Markov Chain Model In Banyumanik District

2019 ◽  
Author(s):  
S Subiyanto ◽  
Andri Suprayogi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
Markov Chain Model ◽  
Rapid Development ◽  
Satellite Image ◽  
Predictive Ability ◽  
Chain Model ◽  
Land Prices ◽  
Fair Market

Banyumanik District is located on the outskirts of Semarang with very rapid development. Indicated with the many changes in land that occur, due to the construction of settlements and other physical buildings continues to increase. Changes in land use will also be followed by changes in market land prices. These changes will continue in line with the increasing number and activities of the population in carrying out economic, social and cultural life. Most of the studies was conducted to analyze changes in future land use are based on the use of a model. Land use modeling changes is a method or approach that can be used to understand the causes and effects of these dynamic changes. The Multi-Layer Perceptron (MLP) Neural Network and Markov Chain methods are used in this study to determine which locations or areas of land use are vacant land and agriculture has the potential to change into settlements and test the predictive ability that will be produced by the model. The driving factor for land use change as an input model consists of distance to the road, distance to the area experiencing changes in land use, slope, elevation and fair market land prices. This study aims to (1) predict settlement and its changes in Banyumanik District using High Resolution Satellite Image in 2011-2019, (2) build a model of settlement land use change with the Markov Chain methods and (3) projection of Banyumanik District land use in 2028.

scholarly journals Application of Markov Chain Model and ArcGIS in Land Use Projection of Ala River Catchment, Akure, Nigeria

2021 ◽  
Vol 18 (1) ◽  
pp. 30-38
Author(s):  
P.A. Adegbola ◽  
J.R. Adewumi ◽  
O.A. Obiora-Okeke
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
Land Cover ◽  
Markov Chain Model ◽  
Urban Expansion ◽  
Efficiency Index ◽  
Landsat 8 ◽  
Chain Model ◽  
Negative Consequences

Increase land use change is one of the consequences of rapid population growth of cities in developing countries with its negative consequences on the environment. This study generates previous and present land use of Ala watershed and project the future land use using Markov chain model and ArcGIS software (version 10.2.1). Landsat 7, Enhanced Thematic mapper plus (ETM+) image and Landsat 8 operational land imager (OLI) with path 190 and row 2 used to generate land use (LU) and land cover (LC) images for the years 2000, 2010 and 2019. Six LU/LC classes were considered as follows: developed area (DA), open soil (OS), grass surface (GS), light forest (LF), wetland (WL) and hard rock (HR). Markov chain analysis was used in predicting LU/LC types in the watershed for the years 2029 and 2039. The veracity of the model was tested with Nash Sutcliffe Efficiency index (NSE) and Percent Bias methods. The model results show that the study area is growing rapidly particularly in the recent time. This urban expansion results in significant decrease of WL coverage areas and the significant increase of DA. This implies reduction in the available land for dry season farming and incessant flood occurrence. Keywords: Land cover, land use change, Markov chain, ArcGIS, watershed, urbanization

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