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 spatial distribution modeling based on CLUE-S model in the Huangshui River Basin

2013 ◽  
Vol 33 (3) ◽  
pp. 985-997 ◽  
Author(s):  
冯仕超 FENG Shichao ◽  
高小红 GAO Xiaohong ◽  
顾娟 GU Juan ◽  
亢健 KANG Jian ◽  
郭丽峰 GUO Lifeng ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
River Basin ◽  
Distribution Modeling ◽  
S Model

scholarly journals Adaptability Evaluation of Human Settlements in Chengdu Based on 3S Technology

2021 ◽  
Author(s):  
Wende Chen ◽  
kun zhu ◽  
QUN WU ◽  
Yankun CAI ◽  
Yutian LU ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Development Planning ◽  
Residential Environment ◽  
Vegetation Coverage ◽  
High Grade ◽  
Human Settlement ◽  
Human Settlements ◽  
Suitability Index ◽  
Correlation Degree

Abstract Taking Chengdu as the research object, the natural eco-environmental factors such as topography, climate, vegetation, land use and vegetation cover were selected, together with human disturbance factors such as traffic and GDP, and the index weights were calculated by AHP. Based on 3S technology, projection transformation, remote sensing interpretation, information extraction and analysis are carried out, and evaluation model of Chengdu's residential environment adaptability is constructed, which reflects the zoning and spatial distribution characteristics of Chengdu's residential environment adaptability. The results show that: 1) The adaptability index of Chengdu's human settlement environment is between 15.98 and 76.75, and the suitability of human settlement environment is gradually decreasing from the middle to the east and west of Chengdu, and most areas are restricted by human production activities and natural conditions. 2) According to the actual situation, the suitability index can be divided into High-grade suitable areas (284.36 km2, 2.01%), relatively High-grade suitable areas (1802.13 km2, 12.71%), moderately suitable areas (3721.49 km2, 26.24%) and low suitable areas (3731.49 km2, 26.31%). 3) The correlation degree between the spatial distribution of Chengdu population and each index factor is as follows: per capita GDP> topographic relief > temperature and humidity > vegetation coverage > traffic network density > land use > hydrological factors. 4) There is a good correlation between Chengdu human settlements suitability index and the current population density grid layer, and its correlation coefficient is 0.7326. 5) The leading impact indicators of human settlements in different regions are different. The results show that the natural environment conditions in Chengdu are superior and the ecological environment quality is relatively stable, but the human settlement suitability index in the southeast and Longmenshan areas of Chengdu is relatively low. Therefore, in the future development planning of Chengdu, it is necessary to combine the actual environmental conditions and resource carrying capacity, and rationally carry out urban optimization and beautiful countryside construction.

scholarly journals Land use land cover analysis with pixel-based classification approach

2019 ◽  
Vol 16 (3) ◽  
pp. 1327
Author(s):  
Haslina Hashim ◽  
Zulkiflee Abd Latif ◽  
Nor Aizam Adnan
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Maximum Likelihood ◽  
Land Cover ◽  
Urban Area ◽  
Rapid Development ◽  
Development Planning ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Classification Approach

<p>Rapid development in certain urban area will affect its natural features. Therefore, it is important to identify and determine the changes occur for further analysis and future development planning. This process will influence several factors such as area development, environmental issues and human social activities. The selection of remote sensing data and method will derive the accurate land use land cover maps. This research study accessed the classification accuracy of different classifier approach for land use land cover classification in urban area. The objective of this paper is to compare the accuracy of the classification for each technique used. The study was conducted in a highly urbanized area in Kuala Lumpur, Malaysia. The dataset used for this study is the multi temporal LANDSAT satellite imageries for the year of 2001,2006,2011 and 2016. The pre-processing and analysis of the dataset has been done using software ENVI 5.3. Five land use classes (Urban/built up area, Forest, Agriculture, Water Body and fallow land) were identify for classification process. The classification approach for this study is the supervised classification with two algorithms namely Maximum Likelihood (ML) and Support Vector Machine (SVM). The overall accuracy and kappa statistic of the classification indicate that support vector machine algorithm was more accurate than maximum likelihood algorithm for five different time intervals.Therefore, this classification approach is acceptable and highly recommended for mapping the changes of land cover.</p>

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 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.

scholarly journals Environmental crime predictors and the spatial distribution of crime. The case of stare Baluty in Lodz, Poland

2020 ◽  
pp. 121-136
Author(s):  
Stanisław Mordwa ◽  
Patrycja Laskowska
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Urban Space ◽  
Environmental Crime ◽  
Potential Threat ◽  
Important Conclusion ◽  
Safe Spaces ◽  
Public Facilities ◽  
The Creation

  The article refers to various studies on the creation of safe spaces as well as works on the influence of land-use on the distribution of crime in urban space. The goal of the study is to identify places and facilities which constitute a potential threat to safety and impact the spatial distribution of crime. An analysis of relationships between various types of crime predictors and the spatial distribution of crimes at the address-level has also been made. The most important conclusion drawn from the study is that the distribution of crime predictors strongly impacts the presence of crime in their direct vicinity and this influence on crime gradually lessens as the distance increases. The influence of such crime predictors as honeypots and public facilities on attracting crime as well as movement predictors and conflicts of land use on repelling crime was determined.

scholarly journals The Effects of Map Reading Expertise and Map Type on Eye Movements in Map Comparison Tasks

2021 ◽  
Author(s):  
Claus Rinner ◽  
Susanne Ferber
Keyword(s):  
Land Use ◽  
Response Times ◽  
The Other ◽  
Geographical Information ◽  
Gis Technology ◽  
Cognitive Approach ◽  
Map Comparison ◽  
Map Reading ◽  
Wide Range ◽  
Land Use Maps

Comparing maps of different geographical phenomena, or maps of the same geographical phenomenon at different points in time, is a frequent task in many disciplines. The process of map comparison has been studied occasionally by cartographers since the 1970s, but recent improvements in neuropsychological testing equipment and in geographical information system (GIS) technology had us review this topic in a new light. We propose a cognitive approach using eye movement recording to understand the process of comparing two static maps displayed simultaneously on a screen. Two groups of subjects with different levels of expertise with map reading were shown pairs of maps and asked to judge their similarity or difference. We used three types of maps that differed in their spatial granularity: (A) randomly generated, 64-by-64 pixel, black-and-white images, (B) grayscale choropleth maps representing socio-economic variables for counties in lower Michigan, and (C) land-use maps of the surroundings of selected Canadian cities in different years resulting from classified satellite imagery. Subjects were asked whether two maps presented on the screen were similar (tests A and B) or different (test C). Response times, fixation durations and fixation counts differed significantly for the three map types. Land-use maps required the longest response times indicating that they were most difficult to compare. At the same time, land-use maps required more fixations than the other two types of maps, while the duration of these fixations was not different from the other map types. When comparing two maps of the same type, saccades between the two maps provide information on the subject’s decision-making process. We found that for the land-use maps, the number of these cross-saccades was significantly smaller than for the two other map types. Pairs of land-use maps were characterized by a fine raster grid and fewer pixel-by-pixel differences between the two maps, while both, random grids in test A and county maps in test B consist of clear-cut spatial units. We conclude that whenever spatial units can be distinguished on a map and corresponding units on a second map can be found easily, subjects will tend to compare the two maps in a unit-by-unit approach. In contrast, if maps consist of smoother spatial patterns, subjects will try to memorize patterns on one map (usually the one on the right-hand side), and make fewer saccades to compare these patterns with those on the other map. The results from this experiment could be used to provide context-adaptive tools for map comparison in GIS. The behavioral differences between groups (experts vs. novices) in this experiment were mostly not significant. This supports the notion of developing standard GIS tools that are offered to users with a wide range of expertise.

scholarly journals The Effects of Map Reading Expertise and Map Type on Eye Movements in Map Comparison Tasks

2021 ◽  
Author(s):  
Claus Rinner ◽  
Susanne Ferber
Keyword(s):  
Land Use ◽  
Response Times ◽  
The Other ◽  
Geographical Information ◽  
Gis Technology ◽  
Cognitive Approach ◽  
Map Comparison ◽  
Map Reading ◽  
Wide Range ◽  
Land Use Maps

Comparing maps of different geographical phenomena, or maps of the same geographical phenomenon at different points in time, is a frequent task in many disciplines. The process of map comparison has been studied occasionally by cartographers since the 1970s, but recent improvements in neuropsychological testing equipment and in geographical information system (GIS) technology had us review this topic in a new light. We propose a cognitive approach using eye movement recording to understand the process of comparing two static maps displayed simultaneously on a screen. Two groups of subjects with different levels of expertise with map reading were shown pairs of maps and asked to judge their similarity or difference. We used three types of maps that differed in their spatial granularity: (A) randomly generated, 64-by-64 pixel, black-and-white images, (B) grayscale choropleth maps representing socio-economic variables for counties in lower Michigan, and (C) land-use maps of the surroundings of selected Canadian cities in different years resulting from classified satellite imagery. Subjects were asked whether two maps presented on the screen were similar (tests A and B) or different (test C). Response times, fixation durations and fixation counts differed significantly for the three map types. Land-use maps required the longest response times indicating that they were most difficult to compare. At the same time, land-use maps required more fixations than the other two types of maps, while the duration of these fixations was not different from the other map types. When comparing two maps of the same type, saccades between the two maps provide information on the subject’s decision-making process. We found that for the land-use maps, the number of these cross-saccades was significantly smaller than for the two other map types. Pairs of land-use maps were characterized by a fine raster grid and fewer pixel-by-pixel differences between the two maps, while both, random grids in test A and county maps in test B consist of clear-cut spatial units. We conclude that whenever spatial units can be distinguished on a map and corresponding units on a second map can be found easily, subjects will tend to compare the two maps in a unit-by-unit approach. In contrast, if maps consist of smoother spatial patterns, subjects will try to memorize patterns on one map (usually the one on the right-hand side), and make fewer saccades to compare these patterns with those on the other map. The results from this experiment could be used to provide context-adaptive tools for map comparison in GIS. The behavioral differences between groups (experts vs. novices) in this experiment were mostly not significant. This supports the notion of developing standard GIS tools that are offered to users with a wide range of expertise.

scholarly journals Land use changes in Zhangjiakou from 2005 to 2025 and the importance of ecosystem services

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12122
Author(s):  
Kaipeng Xu ◽  
Yanyan Chi ◽  
Rongfeng Ge ◽  
Xiahui Wang ◽  
Siyang Liu
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Water Conservation ◽  
Land Use Changes ◽  
Urban Ecosystem ◽  
Development Planning ◽  
Ecosystem Functions ◽  
Operating Characteristics ◽  
Land Use Types ◽  
S Model

Changes in local land use affect regional ecological services, development planning, and optimal use of space. We analyzed the effects of changes in land use from 2000 to 2025 on the spatial distribution of ecosystem services using CLUS-S modeling to evaluate ecosystem functions in Zhangjiakou, China. We found that the urban ecosystem area in Zhangjiakou increased and farmland decreased between 2000–2025. Water conservation was relatively high and was concentrated in the nature reserves of southern Zhangjiakou. Soil conservation was mainly distributed in eastern and southern counties. The results of the CLUE-S model showed that the relative operating characteristics of the six land use types were > 0.70, and the logistic regression equation was able to successfully explain the distribution pattern of the different types of land use.

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