Urban Dynamic Expansion Computer Simulation of RF-NH-CA Model Considering Neighborhood Heterogeneity

“Neighborhood” as the principle of “the closer the distance, the more relevant the attributes”, is often used as a key driving factor for the urban dynamic modeling of cellular automata; however, the current implementation of the “neighborhood” idea is mostly adopted Mean probability method. This method affects the accuracy of urban dynamic simulation to a certain extent because it ignores the spatial heterogeneity of neighboring cells. Based on the random forest method to evaluate the suitability probability of land use, this study uses the intensity gradient change characteristics of the luminous data to endow the traditional neighborhood cell heterogeneity characteristics, and builds a random forest neighborhood heterogeneity CA model (Random forest Neighborhood Heterogeneity Cellular Automata, RF-NH-CA), and verified the effectiveness of the model by simulating the changes in urban land use in the 21 districts of Chongqing’s main city from 2010 to 2017 through a multi-scheme comparative experiment. The results showed that the overall simulation accuracy of the RF-NH-CA model reached 97.59%, and the Kappa coefficient reached 0.7434; compared with the traditional models RF-CA, ANN-CA and Logistic-CA, FoM increased by 0.0274,0.0383,0.0579, respectively. The Kappa coefficient increased by 0.0162,0.0229,0.0351 respectively. Studies have shown that giving the neighborhood cell heterogeneity through luminous data has played a role in improving the accuracy of land use simulation, which is more in line with the real urban expansion.

Potential of urban greening for carbon dioxide reduction from transportation sector

Various urban activities which exist in different lands uses in Mojokerto City such as settlement, commercial area, public service, and industrial area form the urban dynamic. Urban dynamic is stimulated by some factors including mobility of people and goods, information, and money. People’s mobility which dominates the urban mobility is accommodated by transportation mode causing transportation sector ranks the top first sector contributing to carbon dioxide (CO2) emissions in urban area, including Mojokerto City. Therefore, the study aims to propose reasonable solution for CO2 emissions reduction from transportation sector. The total amount of CO2 emissions is calculated first, and vegetation capacity to absorb CO2 is calculated afterwards using the formula for emission generation and bio capacity respectively. Development of urban greening is proposed to improve the bio-capacity of urban greening to absorb the remaining emissions. Based on the emission calculation, the total amount of CO2 emissions from transportation sector ranges between 6.6 to to 262.1 ton/year depending on the traffic volume and the distance covered by motorized vehicles. Meanwhile, calculation of bio capacity shows that the average absorption of vegetation in Mojokerto City is only 863.91 ton/yr. Improving urban greening area by planting more trees with higher absorption capacity is proposed to absorb the remaining emission. Calculation shows that enhanced urban greening can increase the emission absorption from 4% to 7% of the total emission from transportation sector.

A floating dream: urban upgrading, population control and migrant children’s education in Beijing

In recent years, Beijing has implemented urban renewal policies aimed at forcing out rural migrants to restrict the city’s population. One such policy restricts their access to public schools. We use the demolition of the Beijing Sun Palace Farmers’ Market to examine the long-term impacts of these policies on the educational status of migrant children in Beijing. Based on a survey and in-depth interviews with migrant vendors, we find that government-initiated urban remodelling campaigns have an enduring impact on their social mobility and the educational opportunities of their children. Despite severe limitations to their mobility and economic opportunities, many migrant vendors were still determined to stay in Beijing. Subsequently, their worsened living status significantly affected their children’s prospects. Migrant children caught in this urban dynamic either struggle in substandard informal migrant schools in Beijing or are left behind in their hometowns, with little hope of a good education or improved social status.

Transient marginal identities and networks in early modern Madrid: the 1614 case of the ‘Armenian’, ‘Greek’ and ‘Turkish’ counterfeiters

This article centres on a trial held in Madrid in 1614 involving a group identified as ‘vagrants’ of ‘Armenian’ and ‘Greek’ background. In order to tease out the ways in which the presence of foreigners challenged the institutions and citizens, this article approaches these defendants as relationally defined actors in the urban dynamic. It reveals the tactics marginal groups employed vis-à-vis strategic attempts by the municipal government to control foreigners by assigning them identities based on ethnicity. This case-study thus calls into question notions of vagrancy and identification based on ethnicity (‘Armenian’ and ‘Greek’, in particular) in Madrid under Phillip III and IV. In doing so, it shows marginality to be a key yet elusive site for cultural encounters and collaboration in early modern Europe, in which multilingual and culturally fluid social actors related to the Armenian diaspora played a central role.

Urban Dynamic: Inspirasi Kemacetan Tanah Abang Jakarta

Perkembangan varian trend fashion dapat dikembangkan melalui kombinasi antara situasi dan kondisi yang ada pada suatu daerah atau kota. Situasi Pusat Perbelanjaan Tanah Abang memberikan suatu ide tersendiri dalam membuat koleksi busana. Penelitian ini menjelaskan bagaimana implementasi dari suasana kemacetan yang terjadi di Pasar Tanah Abang, Jakarta Pusat, ke dalam suatu koleksi busana. Metode penelitian yang digunakan adalah kualitatif deskriptif. Hasil dari penelitian adalah koleksi busana berjudul Urban Dynamic yang bergaya sporty dramatic dengan tampilan urban contemporary.

Monitoring Regional Urban Dynamics Using DMSP/OLS Nighttime Light Data in Zhejiang Province

Accurate monitoring of urban regions and urban sprawls is critical to the detection and assessment of regional development. The nighttime light images of Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) provide us direct solutions to make spatial descriptions of urban regions. Unfortunately, accurate monitoring of urban regions is apt to be hampered due to the shortages of the DMSP/OLS data. In this study, we utilized a new urban region extraction strategy based on the edge-detection method which is widely applied in automatic digital image processing. The edges of urban areas in Zhejiang province were identified based on the distributions and values of pixels. Compared with other traditional methods, the urban regions extracted in this study present a higher overall accuracy and kappa coefficient (OA = 93.1409%; Kappa = 0.8755). Two periods of the urban dynamic process and urban sprawl pattern in Zhejiang from 1992–2013 were further detected by the proposed method. At city level, the drastic increase in urban areas was found in cities of Hangzhou and Ningbo. This study provides an objective and convenient solution to the accurate identification of urban regions, which is also an important step to better understand the urban dynamics and urban development.

Detecting and Analyzing the Increase of High-Rising Buildings to Monitor the Dynamic of the Xiong’an New Area

As an effort to monitor the urban dynamic of the Xiong’an new area, this paper proposed a novel procedure to detect the increase of High-Rising Buildings (HRBs) from multi-temporal Sentinel-2 data based on Fully Convolutional Networks. The procedure was applied to detect the increase of HRBs between 2017 and 2019 in 39 counties in the center of the Xiong’an new area. The detected increases were validated and then analyzed in terms of their quantities, spatial distribution and driving forces at the county level. The results indicate that our method can effectively detect the increase of HRBs in large urban areas. The quantity and spatial distribution of the increased HRBs varies a lot in the 39 counties. Most of the increase is located in the north-east and the mid-west of the study region. As to the driving forces, it seems that no single factor can fully explain the increase. Among the five selected factors, Gross Domestic Product (GDP) and transportation accessibility have clear high impacts than others. Number of Permanent Residents (NPR) and policy follow as the secondary group. The terrain has the lowest influence on the increase. Our method provides a useful tool to dynamically monitor HRBs in large areas and also the increase of HRBs can be employed as a new indicator to characterize urban development.

DYNAMIC MONITORING METHOD OF ILLEGAL BUILDINGS USING SPATIOTEMPORAL BIG DATA BASED ON URBAN HIGH LYING ZONES

China's urban illegal buildings are emerging in an endless stream with a large number. There is a wide demand for urban illegal buildings monitoring in urban management departments, including Beijing, Shanghai, Guangzhou and other regions where urban management is facing increasingly serious problems of illegal buildings. It is urgent to solve the common problem of "urban disease" caused by urban illegal buildings, and a new automatic monitoring method that can reduce the cost of urban management is urgently needed. This kind of automated monitoring method of illegal buildings has a wide market demand in Urban Management and Law Enforcement and the Ministry of Land and Resources. Existing technologies cannot realize long-term, autonomous, rapid and intelligent dynamic real-time monitoring of urban illegal buildings, which leads to the problem that illegal buildings’ behaviors cannot be stopped in time. There is a possibility to solve these problems using the ubiquitous network of base stations in cities to monitor illegal buildings.This paper proposes a dynamic monitoring method of illegal buildings using spatiotemporal big data based on urban high lying zones. Through the Spatiotemporal sensor network technology, the tilt-type stereo camera is set up at the high lying zones around the survey area. According to the real-time ambient temperature and humidity numerical data fed back by the temperature and humidity sensor, the tilt-type stereo camera uses intelligent time-lapse photogrammetry technology to obtain multiple stereo pairs. The tilted remote sensor transmits the multiple stereo pairs to the urban dynamic analysis service network using wireless transmission. The urban dynamic analysis service network will complete a series of analysis and processing operations without any human intervention, and then transmit the results of the analysis to the early-warning terminal successively through the base station, WIFI and other wireless transmission methods. Finally, the illegal building data is uploaded to the terminal. That is to say, the urban dynamic analysis service network can realize the intelligent, automatic analysis and processing of spatial analysis server and the operation of calling all database data and storing data.The method proposed in this paper uses the high lying zones around the survey area to expand the monitoring range, improve the accuracy of monitoring data, realize long-term real-time monitoring, and fully utilize the characteristics of Spatiotemporal sensing network technology intelligent, autonomous, wireless transmission, etc., significantly reducing labor. It greatly shortens the process from the emergence to the discovery of illegal buildings in cities. The workload of monitoring has improved the efficiency of dynamic monitoring and warehousing of illegal buildings data in cities.