Spatial Pattern Simulation on Land Use Change in Nanchang Based on CLUE-S Model

2013 ◽  
Vol 295-298 ◽  
pp. 2523-2527 ◽  
Author(s):  
Jun Hong Liu ◽  
Jun Gong ◽  
Jian Hong Chen
Keyword(s):  
Land Use ◽  
Reference Value ◽  
Experimental Result ◽  
Basic Unit ◽  
Slope Aspect ◽  
Driving Mechanism ◽  
Kappa Index ◽  
Gis Technology ◽  
Land Use Pattern ◽  
S Model

The CLUE-S model is a widely used method in the aspect of spatial simulation. CLUE-S model to simulate the land use space pattern of Nanchang in 2005, and compare the simulated results with the land use status figure of Nanchang in 2005 was built on the basis of taking Nanchang as research region, analyzing the land use data of Nanchang in 1995 based on GIS technology, combining natural and social economic factors such as railway, highway, river, settlements, DEM, slope, aspect, etc. and filtering decisive driving factors to the spatial change of Nanchang’s main land use types with SPSS Logistic regression analysis. In the basic unit of 150M*150M grid level, KAPPA index reaches 0.870, the experimental result is ideal. At the same time, predicting the land use pattern of the year 2017 is based on the land use data of Nanchang in 2005. Experimental results indicate that CLUE-S model has good predicting ability to urban spatial structure development, and has reference value to driving mechanism research of the urban layout and analyzing urban development.

scholarly journals Scenario Simulation and Landscape Pattern Dynamic Changes of Land Use in Mining Area

2021 ◽  
Author(s):  
Xiaoyan Chang ◽  
Feng Zhang ◽  
Kanglin Cong ◽  
Xiaojun Liu
Keyword(s):  
Land Use ◽  
Mining Area ◽  
Tidal Wetland ◽  
Kappa Index ◽  
Land Use Pattern ◽  
Construction Land ◽  
Farmland Protection ◽  
Ecological Protection ◽  
S Model ◽  
Rural Construction

Abstract In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use change and the related 7 driving factors at a scale of 60m * 60m. Using the CLUE-S model, combined with Markov model, the simulation of land use under three scenarios–namely, natural development scenario, ecological protection scenario and farmland protection scenario–were explored. Firstly, using land use map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual land use map in 2016 with the simulated map of land use pattern in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the distribution of land use pattern in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for land use changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.

scholarly journals Land Use / Cover Change and Vulnerability Evaluation in Olomuc, Czech Republic

2014 ◽  
Vol II-8 ◽  
pp. 77-82 ◽  
Author(s):  
M. S. Boori ◽  
V. Vozenilek ◽  
K. Choudhary
Keyword(s):  
Land Use ◽  
Czech Republic ◽  
Numerical Model ◽  
Driving Forces ◽  
Research Work ◽  
Geographical Information ◽  
Slope Aspect ◽  
Gis Technology ◽  
Environmental Vulnerability ◽  
Vulnerability Evaluation

This research work analyse environmental vulnerability evaluation from 1991 to 2013 in Olomouc, Czech Republic. Remote sensing (RS) and geographical information system (GIS) technology were used to develop an environmental numerical model for vulnerability evaluation based on spatial principle component analysis (SPCA) method. Land use/cover changes shows that 16.69% agriculture, 54.33% forest and 21.98% other areas (settlement, pasture and water-body) were stable in all three decade. Approximately 30% of the study area maintained as a same land cove type from 1991 to 2013. Based on environmental numerical modal an environmental vulnerability index (EVI) for the year of 1991, 2001 and 2013 of the study area were calculated. This numerical model has five thematic layers including height, slope, aspect, vegetation and land use/cover maps. The whole area vulnerability is classified into four classes: slight, light, medial and heavy level based on cluster principle. Results show that environmental vulnerability integrated index (EVSI) was continuously decreased from 2.11 to 2.01 from the year 1991 to 2013. The distribution of environmental vulnerability is vertical and present heavy in low elevation and slight in high elevation. The overall vulnerability of the study area is light level and the main driving forces are socio-economic activities.

scholarly journals Scenario simulation of land use and land cover change in mining area

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoyan Chang ◽  
Feng Zhang ◽  
Kanglin Cong ◽  
Xiaojun Liu
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Mining Area ◽  
Tidal Wetland ◽  
Kappa Index ◽  
Construction Land ◽  
Farmland Protection ◽  
Ecological Protection ◽  
S Model ◽  
Rural Construction

AbstractIn this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and the related 7 driving factors at a resolution of 60 m. Using the CLUE-S model, combined with Markov model, the simulation of LULC under three scenarios—namely, natural development scenario, ecological protection scenario and farmland protection scenario—were explored. Firstly, using LULC map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual LULC map in 2016 with the simulated map in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the spatial distribution pattern of LULC in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for LULC changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.

CLUE-S Model-Based Simulation of Land Use Dynamic Variation in Yangzhou Urban

2013 ◽  
Vol 347-350 ◽  
pp. 3247-3251
Author(s):  
Li Wang ◽  
Xi Min Cui ◽  
De Bao Yuan ◽  
Yi Zhao ◽  
Xue Qian Hong
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Urban Area ◽  
Urban Space ◽  
Development Planning ◽  
Model Parameters ◽  
Gis Technology ◽  
Simulation Accuracy ◽  
S Model ◽  
Land Use Maps

Land Use/Cover Change (LUCC) is a commonly concerned issue. The CLUE-S model was applied to Yangzhou urban area in this paper to simulate the land use spatial distribution in the urban area from 2003 to 2010. Combined with RS & GIS technology, three periods of remote sensing images were firstly preprocessed and three periods of land-use maps were obtained by means of object-oriented method. Then, corresponding model parameters were defined in the CLUE-S model to obtain the spatial distribution of land use of Yangzhou urban in 2003~2010. After that, the extracted and the simulated land use maps in 2007 were compared to evaluate the simulation accuracy. CLUE-S model can be used to simulate the distribution pattern of the development of smaller-scale regional urban space, to provide guidance for the smaller scale urban development planning, and is worthy of popularization and application of land use and land cover change model.

Land Use Pattern in India and Karnataka: A Comparative Analysis

2012 ◽  
Vol 2 (10) ◽  
pp. 1-3 ◽  
Author(s):  
Dr. Premakumara Dr. Premakumara ◽  
◽  
Seema Seema
Keyword(s):  
Land Use ◽  
Comparative Analysis ◽  
Land Use Pattern ◽  
Use Pattern

Analysis of Land Use/Land Cover Change in Yangzhou City Based on CLUE-S Model

2011 ◽  
Vol 13 (5) ◽  
pp. 695-700
Author(s):  
Zhihua TANG ◽  
Xianlong ZHU ◽  
Cheng LI
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Land Cover ◽  
S Model

scholarly journals An Automatic and Operational Method for Land Cover Change Detection Using Spatiotemporal Analysis of MODIS Data: A Northern Ontario (Canada) Case Study

2021 ◽  
Vol 10 (5) ◽  
pp. 325
Author(s):  
Ima Ituen ◽  
Baoxin Hu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Land Cover Change ◽  
Basic Unit ◽  
Operational Method ◽  
Northern Ontario ◽  
Modis Data ◽  
Forest Fire Management ◽  
Land Cover Change Detection

Mapping and understanding the differences in land cover and land use over time is an essential component of decision-making in sectors such as resource management, urban planning, and forest fire management, as well as in tracking of the impacts of climate change. Existing methods sometimes pose a barrier to the effective monitoring of changes in land cover and land use, since a threshold parameter is often needed and determined based on trial and error. This study aimed to develop an automatic and operational method for change detection on a large scale from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Super pixels were the basic unit of analysis instead of traditional individual pixels. T2 tests based on the feature vectors of temporal Normalized Difference Vegetation Index (NDVI) and land surface temperature were used for change detection. The developed method was applied to data over a predominantly vegetated area in northern Ontario, Canada spanning 120,000 sq. km from 2001–2016. The accuracies ranged between 78% and 88% for the NDVI-based test, from 74% to 86% for the LST-based test, and from 70% to 86% for the joint method compared with manual interpretation. Our proposed method for detecting land cover change provides a functional and viable alternative to existing methods of land cover change detection as it is reliable, repeatable, and free from uncertainty in establishing a threshold for change.

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