scholarly journals Spatial differences and pattern evolution of Multi-scale Urban Land between China and India

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Qinke Sun ◽  
Liang Zhou ◽  
Xuewei Dang ◽  
Bowei Hu ◽  
Haowei Mu
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Regional Development ◽  
Urban Expansion ◽  
Urban Land ◽  
Expansion Rate ◽  
Low Level ◽  
Multi Scale ◽  
China And India ◽  
High Level

<p><strong>Abstract.</strong> “The dragon and the elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As an engine of global economic growth, China and India have similar development processes, different development models as well as differences in urban development, which have attracted widespread attention from scholars. Based on the 1992&amp;ndash;2012 consecutive annual nighttime lighting data (DMSP-OLS), this paper uses the Gini coefficient, the Getis-Ord Gi* index and the Compounded Night Light Index (CNLI) to conduct a multi-scale comparative analysis of the differences in urban development between China and India from the perspective of geospatial. The results show that: (1) The space of urban land in the two countries expanded rapidly, with an average annual expansion rate of 5.24% and 3.85% respectively. China's urban land expansion rate is 1.36 times that of India. Among them, the arid resource towns in northwest China and the resource towns in central India have recently developed rapidly. (2) India’s imbalance in development is more prominent than China’s. China's regional and provincial imbalances are narrowing, while the regional differences in India are gradually widening. (3) The spatial pattern of land use in both countries shows a certain degree of coastal and inland differences. The main spatial pattern of China's regional development is the difference between East-Central-West, while the spatial pattern of regional development in India is North-South difference. (4) The strength of the expansion of the core cities of the two countries is quite different. From 1997 to 2007, China's core urban expansion intensity remained at a relatively high level while India was at a relatively low level. But from 2007 to 2012, India's core cities expanded at a relatively high level while China was at a relatively low level.</p>

scholarly journals Comparison on Multi-Scale Urban Expansion Derived from Nightlight Imagery between China and India

2019 ◽  
Vol 11 (16) ◽  
pp. 4509 ◽  
Author(s):  
Liang Zhou ◽  
Qinke Sun ◽  
Xuewei Dang ◽  
Shaohua Wang
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Regional Development ◽  
Urban Expansion ◽  
Central India ◽  
Urban Land ◽  
Expansion Rate ◽  
Multi Scale ◽  
China And India ◽  
The Difference

“The Dragon and the Elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As engines of global economic growth, the two rising powers have followed similar courses of development but possess important differences in modes of development and urban development, which have attracted the widespread attention of scholars. From a geospatial perspective, and based on continuous annual night light data (Defense Meteorological Satellite Program-Operational Linescan System, DMSP-OLS) from 1992 to 2012, this paper conducts a multi-scale comparative analysis of urban development differences between China and India by employing various approaches such as the Gini coefficient, Getis–Ord Gi* index, and the Urban Expansion Intensity Index (UEII). The results show that: (1) The urban land space of the two countries expand rapidly, with the average annual expansion rate of China and India being 5.24% and 3.85%, respectively. The urban land expansion rate in China is 1.36 times faster than that in India. Resource-typed towns in arid northwest China and the resource-typed towns in central India have developed rapidly in recent years. (2) The unbalanced development in India is more prominent than in China; and the regional and provincial development imbalances in China are shrinking, while India’s imbalances are improving slowly and its regional differences are gradually widening. (3) The spatial pattern of land use in both countries shows significant coastal and inland differences. The difference between the east, the central regions, and the west is the main spatial pattern of China’s regional development, while the difference between the north and the south is the spatial pattern of India’s regional development. (4) There are obvious differences in the expansion intensity of core cities between the two countries. From 1997 to 2007, the expansion intensity of core cities in China was relatively higher than that in India, while that in India was relatively higher than that in China from 2007 to 2012.

scholarly journals ANALYZING AND MODELING THE SPATIOTEMPORAL DYNAMICS OF URBAN EXPANSION: A CASE STUDY OF HANGZHOU CITY, CHINA

2019 ◽  
Vol 27 (4) ◽  
pp. 228-241
Author(s):  
Jie Zhao ◽  
Wenfu Yang ◽  
Junhuan Peng ◽  
Cheng Li ◽  
Zhen Li ◽  
...  
Keyword(s):  
Urban Development ◽  
Spatial Pattern ◽  
Urban Expansion ◽  
Urban Land ◽  
Spatiotemporal Dynamics ◽  
Sustainable Urban Development ◽  
Spatial Metrics ◽  
Spatiotemporal Characteristics ◽  
Ca Model ◽  
Coordination Development

Understanding the spatiotemporal characteristics of urban expansion is increasingly important for assisting the decision making related to sustainable urban development. By integrating remote sensing (RS), spatial metrics, and the cellular automata (CA) model, this study explored the spatiotemporal dynamics of urban expansion and simulated future scenarios for Hangzhou City, China. The land cover maps (2002, 2008, and 2013) were derived from Landsat images. Moreover, the spatial metrics were applied to characterize the spatial pattern of urban land. The CA model was developed to simulate three scenarios (Business-As-Usual (BAU), Environmental Protection (EP), and Coordination Development (CD)) based on the various strategies. In addition, the scenarios were further evaluated and compared. The results indicated that Hangzhou City has experienced significant urban expansion, and the urban area has increased by 698.59 km2. Meanwhile, the spatial pattern of urban land has become more fragmented and complex. Hangzhou City will face unprecedented pressure on land use efficiency and coordination development if this historical trend continues. The CD scenario was regarded as the optimized scenario for achieving sustainable development. The findings revealed the spatiotemporal characteristics of urban expansion and provide a support for future urban development.

scholarly journals Dynamic simulation of urban expansion based on cellular automata and logistic regression model: Case study of Hyrcanian region of Iran

2016 ◽  
Author(s):  
Meisam Jafari ◽  
Seyed Masoud Monavari ◽  
Hamid Majedi ◽  
Ali Asghar Alesheikh ◽  
Mirmasoud Kheirkhah Zarkesh
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Cellular Automata ◽  
Urban Development ◽  
Rural Areas ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
High Rate ◽  
Hyrcanian Forests

Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.

scholarly journals Automatic Detection of Track and Fields in China from High-Resolution Satellite Images Using Multi-Scale-Fused Single Shot MultiBox Detector

2019 ◽  
Vol 11 (11) ◽  
pp. 1377 ◽  
Author(s):  
Zhengchao Chen ◽  
Kaixuan Lu ◽  
Lianru Gao ◽  
Baipeng Li ◽  
Jianwei Gao ◽  
...  
Keyword(s):  
Satellite Images ◽  
Automatic Detection ◽  
Image Resolution ◽  
Track And Field ◽  
Single Shot ◽  
Feature Map ◽  
Low Level ◽  
Multi Scale ◽  
High Resolution Satellite Images ◽  
High Level

Object detection is facing various challenges as an important aspect in the field of remote sensing—especially in large scenes due to the increase of satellite image resolution and the complexity of land covers. Because of the diversity of the appearance of track and fields, the complexity of the background and the variety between satellite images, even superior deep learning methods have difficulty extracting accurate characteristics of track and field from large complex scenes, such as the whole of China. Taking track and field as a study case, we propose a stable and accurate method for target detection. Firstly, we add the “deconvolution” and “concat” module to the structure of the original Single Shot MultiBox Detector (SSD), where Visual Geometry Group 16 (VGG16) is served as a basic network, followed by multiple convolution layers. The two modules are used to sample the high-level feature map and connect it with the low-level feature map to form a new network structure multi-scale-fused SSD (abbreviated as MSF_SSD). MSF-SSD can enrich the semantic information of the low-level feature, which is especially effective for small targets in large scenes. In addition, a large number of track and fields are collected as samples for the whole China and a series of parameters are designed to optimize the MSF_SSD network through the deep analysis of sample characteristics. Finally, by using MSF_SSD network, we achieve the rapid and automatic detection of meter-level track and fields in the country for the first time. The proposed MSF_SSD model achieves 97.9% mean average precision (mAP) on validation set which is superior to the 88.4% mAP of the original SSD. Apart from this, the model can achieve an accuracy of 94.3% while keeping the recall rate in a high level (98.8%) in the nationally distributed test set, outperforming the original SSD method.

scholarly journals An Exploratory Analysis in Mapping of Asthma Risk in Western Australia

2018 ◽  
Vol 50 (1) ◽  
pp. 97
Author(s):  
Hendra Kurnia Febriawan ◽  
Carla Maria Da Silva Sodre
Keyword(s):  
Spatial Analysis ◽  
Spatial Pattern ◽  
Western Australia ◽  
Exploratory Analysis ◽  
Annual Rainfall ◽  
Asthma Prevalence ◽  
Low Level ◽  
Asthma Risk ◽  
Confirmatory Analysis ◽  
High Level

Exploratory Analysis as one of the spatial analysis tools that has been used widely in many study fields. This tool is usually intended to obtain the spatial pattern to observe and get relationship between study variables. The exploratory analysis is usually followed by the confirmatory analysis to exhibit the hypothesis that already obtain in the exploratory analysis. This study is aimed to investigate the prevalence of asthma in Western Australia since there are many factors that cause the asthma dispersion.  Many provided variables have been tested to get the best correlation with the asthma percentage variable and four variables (humidity, annual rainfall, EVI and SEIFA) were chosen and tested with high asthma percentage variable. The result of confirmatory analysis indicates that the high level of humidity and low level of SEIFA confirm with the hypothesis and means that those factors can contribute significantly in Asthma prevalence in Western Australia.

scholarly journals Simulation and prediction of Shanghai urban spatial change based on random forest and CA-Markov model

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Xuewei Dang ◽  
Liang Zhou ◽  
Xiaoen Li ◽  
Haowei Mu ◽  
Lei Che ◽  
...  
Keyword(s):  
Urban Planning ◽  
Urban Development ◽  
Urban Growth ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
City Center ◽  
Urban Simulation ◽  
The City ◽  
Red Line

<p><strong>Abstract.</strong> In the context of rapid urbanization, accurate assessment of urban expansion has become increasingly important for urban sustainable development, and smart growth theory has been put forward to avoid urban sprawl. Previous studies about urban expansion simulation focused only on ecological constrain which prevent urban growth from developing in specific regions. However, government decision-making and urban planning greatly influence urban development and limit the disorderly expansion of the urban. In this paper, we consider planning policies into urban simulation and uses the ecological protection red line, farmland protection red line and cultural protection control line as limiting factors for future urban simulation. Choosing Shanghai as the study area, we integrated Random Forests Algorithm (RFA), Markov chain and Cellular Automata (CA) to simulate urban expansion in 2015, and further predict the urban expansion in 2020, 2025 and 2030. The results show that the overall accuracy of urban land use simulation in 2015 is 93.86%, and the kappa coefficient is 0.8577. The model has a good simulation effect. Furthermore, the predicted results in 2020, 2025 and 2030 show that the urban land area in Shanghai is still increasing, and the spatial distribution of urban land has obvious circle structure and regional differences. The urban areas within 10km from the city center are growing slowly, and the region within 30km from the city center is growing faster, and there are more new urban points from 2025 to 2030. But in the area 30km away from the city center, different administrative areas show different urban growth phenomena. Among them, there are a large number of new urban points in the junction area between Songjiang District and Jinshan District, which may be the focus of future urban development planning in Shanghai. The proposed model and the results can help planners study the evolution of urban patterns and develop further urban planning.</p>

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

Determinants of Abuse of the Bodies of the Dead

2019 ◽  
pp. 71-77
Author(s):  
Margarita Khomyakova
Keyword(s):  
Low Income ◽  
Criminal Code ◽  
Value Judgments ◽  
Legal Norms ◽  
Low Level ◽  
Medical Institutions ◽  
Specific Object ◽  
The Subject ◽  
The Dead ◽  
High Level

The author analyzes definitions of the concepts of determinants of crime given by various scientists and offers her definition. In this study, determinants of crime are understood as a set of its causes, the circumstances that contribute committing them, as well as the dynamics of crime. It is noted that the Russian legislator in Article 244 of the Criminal Code defines the object of this criminal assault as public morality. Despite the use of evaluative concepts both in the disposition of this norm and in determining the specific object of a given crime, the position of criminologists is unequivocal: crimes of this kind are immoral and are in irreconcilable conflict with generally accepted moral and legal norms. In the paper, some views are considered with regard to making value judgments which could hardly apply to legal norms. According to the author, the reasons for abuse of the bodies of the dead include economic problems of the subject of a crime, a low level of culture and legal awareness; this list is not exhaustive. The main circumstances that contribute committing abuse of the bodies of the dead and their burial places are the following: low income and unemployment, low level of criminological prevention, poor maintenance and protection of medical institutions and cemeteries due to underperformance of state and municipal bodies. The list of circumstances is also open-ended. Due to some factors, including a high level of latency, it is not possible to reflect the dynamics of such crimes objectively. At the same time, identification of the determinants of abuse of the bodies of the dead will reduce the number of such crimes.

scholarly journals Evaluation of ESV Change under Urban Expansion Based on Ecological Sensitivity: A Case Study of Three Gorges Reservoir Area in China

2021 ◽  
Vol 13 (15) ◽  
pp. 8490
Author(s):  
Hongjie Peng ◽  
Lei Hua ◽  
Xuesong Zhang ◽  
Xuying Yuan ◽  
Jianhao Li
Keyword(s):  
Three Gorges Reservoir ◽  
Urban Expansion ◽  
Urban Land ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Ecological Sensitivity ◽  
Reservoir Area ◽  
Green Development ◽  
Source Data

In recent years, ecosystem service values (ESV) have attracted much attention. However, studies that use ecological sensitivity methods as a basis for predicting future urban expansion and thus analyzing spatial-temporal change of ESV are scarce in the region. In this study, we used the CA-Markov model to predict the 2030 urban expansion under ecological sensitivity in the Three Gorges reservoir area based on multi-source data, estimations of ESV from 2000 to 2018 and predictions of ESV losses from 2018 to 2030. Research results: (i) In the concept of green development, the ecological sensitive zone has been identified in Three Gorges reservoir area; it accounts for about 35.86% of the study area. (ii) It is predicted that the 2030 urban land will reach 211,412.51 ha by overlaying the ecological sensitive zone. (iii) The total ESV of Three Gorges Reservoir area showed an increasing trend from 2000 to 2018 with growth values of about USD 3644.26 million, but the ESVs of 16 districts were decreasing, with Dadukou and Jiangbei having the highest reductions. (iv) New urban land increases by 80,026.02 ha from 2018 to 2030. The overall ESV losses are about USD 268.75 million. Jiulongpo, Banan and Shapingba had the highest ESV losses.

scholarly journals An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

2021 ◽  
Vol 13 (4) ◽  
pp. 766
Author(s):  
Yuanmao Zheng ◽  
Qiang Zhou ◽  
Yuanrong He ◽  
Cuiping Wang ◽  
Xiaorong Wang ◽  
...  
Keyword(s):  
Urban Development ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Development Planning ◽  
Urban Land ◽  
Sustainable Urban Development ◽  
Land Use Patterns ◽  
Water Index ◽  
Nighttime Light

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

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