Owen Zhang
This article describes the potential future increase in the world’s population, but especially that of China. Urbanization has grown at an extreme rate in China since 1970 and the rates of urbanization are expected to increase even further which could potentially pose a threat to the sustainability of urban areas and the social welfare of people living in those conditions (Gaughan et al. 2016). According to data, there has been insane progression and growth in the number of cities and towns that have been created due to the influx of money and population growth (Gaughan et al. 2016). This study is aimed towards the social and economic aspects of human development and the study is trying to address the sustainable development goal of sustainable cities and communities. By keeping track of population levels and predicting future population levels as well as studying patterns of growth from the past China can plan for the future better and to obtain a more accurate hold of how large their population could eventually become. As population levels increase, citizens in urban areas could suffer economic disadvantages and basic human necessities for socioeconomically challenged citizens might be overlooked due to just how crowded living conditions could possibly become. This study relates to Amartya Sen’s definition of human development in that it by mapping population as it allows the country to make changes in infrastructure and housing so that their citizen’s freedoms are not limited or lost. Datasets of mainland China (excluding the Tibet Autonomous Region, Taiwan, and islands in the South China Sea) were pulled from WorldPop such as the Random Forest-based model to study population change (Gaughan et al. 2016). The methods they used were a density estimation and dasymetric population mapping. In order to accomplish density estimation, they used a Random Forest regression, which creates unpruned decisions trees and then aggregates them to obtain a final estimate. After an estimation is obtained, a map of population density can then be generated for each year since 1990 to account for the large amount of change that has occurred over time (Gaughan et al. 2016). The fact that China is an extremely large country and has a large population contributes greatly to making mapping more difficult. After Random Forest regression is complete, a normal dasymetric approach can be used (Gaughan et al. 2016). Overall, the scientific question that the authors are seeking to answer seems to be “How can we map the population and make predictions for the better of China as a whole and for its citizens? “
This study was conducted on population mobility in China, which is defined as migration within a population. By studying population mobility, studies can show patterns between migration and different economic or social factors (Pan and Lai 2019). In China, migration and population mobility are extremely important due to the size of the country and how fast the country has progressed due to political and government reforms. The article states that Chinese migration is an “important for China as part of the processes of urbanization, informatization, industrialization, and globalization” (Pan and Lai 2019). The article also states that by obtaining an accurate picture of population migration, China map out urban and land plans better as well as improve urbanization. There is also a separate section where the article explains how big data is much more accurate then conventional data which allows for new perspective (Pan and Lai 2019). The developmental problem that this article addresses is excess issues in planning and infrastructure in cities and others places of China due to mass migration during holidays such as the MidAutumn Festival. This problem is complex due to the size of the migration. The article states that “the migrant population size increased by 109%” from 2000-2010 which shows just how many people would possibly (Pan and Lai 2019). The objectives of the paper are to “propose an effective framework to evaluate intensity and characteristic of population daily mobility in special holidays using big data and to construct the spatial relationship matrix of China’s urban population flow network as well as exploring the rationality and necessity of spatio-temporal location big data in the study of the daily flow of the population “(Pan and Lai 2019). This article relates to Amartya Sen’s definition of human development as the issue it addresses can affect human freedoms. This issue is being addressed on the social dimension. The sustainable development goals that affect this are economic growth, infrastructure and industry and sustainable cities and communities. The reason all these goals are affected is because of how large and important population mobility is, especially in a country like China where the population of the country is massive. The researchers used LBS, which allows location services to be used by acquiring the location of a mobile terminal user (Pan and Lai 2019). Smart phones are a big reason why this system can be used because of how widespread smart phone use is. By studying the patterns that come from all the smart phone use, it is possible to see specific patterns and trajectories that multiple people take. The data used in the study were taken from Tencent, which is a large internet company in China. It is deemed accurate because of just how many people use its location service, and how widespread Tencent is used, even in products like WeChat. There is a complex flow relationship and node connection of urban population flow network from flow direction. The method used in this study was a complex network analysis method. The researchers used a bidirectional matrix to characterize flow (Pan and Lai 2019). The results showed that the cities on the top ten list of population flow were major cities with high levels of administration, a developed economy, and well-developed infrastructure. Beijing had the most inflow and outflow due its influence and many other major cities ranked highly. Overall, this article addresses the issues of migration and population flow in cities of China and hopes to find patterns so that urban planning in the future can become more efficient and more effective in the future.
This article aims to cover the urban sprawl that has occurred in China over time. Because of all the advancements in the urban sector of China with the large increases in population and changes in government policies, a downside and issue that stems from that is urban sprawl, which is where urban development in cities is uninhibited with little care for urban planning, which can lead to issues such as environmental damage and an increase in traffic. Urban sprawl is a large issue in urban areas around the world, but in China it is on an larger scale due to the extremely rapid urban expansion and population growth that China has experienced. The article states that some of the issues China has seen on the rise are “shrinking farmland, low levels of efficiency in land use, landscape fragmentations…” (Deng et al. 2019). The article also states that the urban expansion stems from a land-centered financial system and that land supply was the main driving factor (Deng et al. 2019). The objective of this paper is to predict and figure out the future pattern of urban sprawl through studying the current urban sprawl in China (Deng et al. 2019). This article relates to Amartya Sen’s definition of human development as the the mix of government policies involving urban expansion from past administration has made it unclear what kind of urban planning should be set in stone. Because of that administration issue, other issues with nature and cities has risen, which could possibly affect Chinese citizen’s perception of freedom. This study address the social and economic portion of urban development in that urban sprawl affects both aspects negatively. The sustainable goals that should be considered when addressing this issue are sustainable communities and cities, economic growth, and industry, innovation and infrastructure. The method used was a classic rank-size model. They set up variables to see if the estimate of the slope would change. If q is a higher value, then higher ranked cities have an advantage. If q is lower, then small or medium level cities have an advantage (Deng et al. 2019). The researchers mention the advantages of the rank-size model, but also the disadvantages, which is that it only shows general trends in city scale and nothing specific. In order to combat this, the researchers split China into 4 regions and added more specific parameters (Deng et al. 2019). The source that they got their data from was the land cover data package of climates changes initiative. They used the 300 m x 300 m raster data from different years to study urban expansion in China. Their findings concluded that urban built-up area were increased substantially during 1992-2015. With no surprise, Beijing and Shanghai were ranked first and second respectively. They also found that between 2000-2010, the urban area growth grew much faster than after that period, so it can be assumed that China made moves to slow down the urban sprawl, resulting in the decreased urban growth after 2010. Overall, this article covers the massive urban sprawl that has been caused by aggressive Chinese economic and population growth which has only just slowed down in the past decade as more effort is put into urban planning.
This article wants to investigate the migration from rural areas to urban areas in China. Over time, there has been a large amount of human migration in China due to the economic changes and the large-scale urbanization. People want to pursue better opportunities that the major cities in China offer so they migrate or send their children there. The article states that this has caused multiple issues to spring up in urban areas, such as “economic issues, health issues, sociological issues and policy issues” (Ma et al. 2018). It is surprising that a single issue like migration can cause so many issues but the population in China is so large that migration will be on a much larger scale compared to other countries. It is hard to picture just how many people have migrated due to limited coverage, but knowing such a number is necessary in order for the Chinese government to plan for the future in an economic sense and an urban sense. The researchers wanted to look for answers to two questions, one was “how prevalent is rural flight in today’s China?” while the other one was “Are there notable differences in rural depopulation” (Ma et al. 2018). This article relates to Amartya Sen’s definition of freedom as increasing issues could possibly affect the rates of migration as government policies could be set in place to reduce migration, possibly affecting citizen’s freedoms. Multiple developmental goals can be considered on this topic, such as poverty, good health, economic growth, and industry. The method and source they used was from Tencent’s location big data map (Ma et al. 2018). They obtained a gridded data set from all of the location requests from smart-phone users. Similar to a previous article, Tencent is used by a lot of apps and phones, allowing mostly accurate data to be pulled since it covers so many people. Another method they were looking to use was census data, which is conducted on a large-scale, but there were no direct census’ to pull information from (Ma et al. 2018). To combat this, the researchers used certain counties that met set criteria and then merged the county level data so that they could generate data for province and city level data. According to the article, the study concluded that about a quarter of the urban population returned to the countryside and that most of the data that was collected were taken from younger smart-phone users (Ma et al. 2018). They also concluded that there was significant differences among the different regions. Overall, this study on rural to urban migration and vice versa explains why an increase in population occurs and just how large scale the movement of people is in China and hopes to help China focus on sustainable land use as well as infrastructure and economic development for the future in case migration continues to increase.
This article looked to explore migration in China and different factors that migration affects. Rural to urban migration used to be restricted, but different changes in policies have allowed for a large increase in migration. Migration seems to be skewed due to the fact that not every region in China is equal in terms of development. The article explains that China eventually transitioned into improving its economy and turned to manufacturing, which shows shy they eventually looked to rural areas for people to hire for labor (Fan). This article relates to Amartya Sen’s definition of development as when China was still under Mao’s rule, certain freedoms were denied such as migration, and only until after China improved its economic status and passed new policies were these freedoms then granted even if they were only granted for labor reasons. Chinese migration covers multiple sustainable developmental goals, such as sustainable communities and cities, economic growth, and industry and infrastructure. The researcher used census’ from China in 1990 and 2000 and looked for change between the two. The article mentions that the two census’ actually had different criteria for the spatial and temporal aspects of migration. The researcher also compared economic differences among regions as well as population redistribution. The results help further prove that “population movement is strongly related to regional economic development” as shown when Beijing and some other cities who enjoyed good economic development also saw an increase in migration levels,.(Fan). It is possible that this is from people wanting to obtain better opportunities as certain regions become more advanced. The question this article looks to answer is “How have economic policies and government change in regions increased migration over time?”. Although this article was more about the past then the future, I was surprised with how much correlation and info the researcher was able to find just using census’ even without the advanced technology and datasets that we are able to create now.
Migration is a large problem in China, especially with rising population levels and the economic growth that has been seen over time. Economic development, urbanization and migration seem to all go hand in hand as they all relate and can affect each other. Without proper management and planning, an excess population could cause multiple problems on the social and economic parts of development. One such issue that could occur is urban sprawl, causing destruction of natural land in favor of urban development and new cities. Issues with migration and population are common around the world, but China’s extremely large and still growing population along with its rate of urbanization make it unique and harder to address than normal. Having disparities between development of regions of China and different socioeconomic levels of citizens also make it harder to see exactly to what extent migration has truly grown to.
Hu, M. (2019). Visualizing the largest annual human migration during the Spring Festival travel season in China. Environment and Planning A: Economy and Space, 51(8), 1618–1621. https://doi.org/10.1177/0308518X19845908
This purpose of this article was to quantify just how large of a migration occurs during the Spring Festival in China. The Spring Festival is the beginning of the new year on the traditional Chinese calendar. It is a time to travel back home and eat meals with your family along with numerous other activities. Because it is a long time tradition, it is expected for all Chinese citizens to do it and ditching is frowned upon. Not all Chinese families live together as many move to places in search of a chance to earn good income or more suitable living conditions so traffic and traveling can reach a peak due to the people who must return home. Because of this, the Spring Festival is an optimal time to look at migration of the Chinese people. In the article, it was possible to see patterns of economic inequality in families by looking for a high level of migration from urban to rural areas. The researchers used big data from Tencent since it is one of the main internet-based product developers. Because of this, Tencent has basically everyone who has a phone in China using some app that is has developed, whether it be Wechat or QQ. Using location tracking services, it becomes possible to track the patterns and distribution of people. The main data that was used was the daily heatmap data, which had a 0.01 x 0.01 degree distribution. The users were aggregated into two average data sets, and then re-projected through the process of replacing the geographic areas with the population percentage. They then looked at the Pearson correlation coefficient during the holiday days and then compared it with the coefficient when there was no holiday. From their findings, Chongqing was the city with the highest population during the Spring Festival. Something surprising that was found was that Shanghai had less than 1 percent of the total population which means that even though Shanghai is a urban hotspot and major city a lot of people leave during the Spring Festival holiday, leading to lower population numbers. By understanding the trends of urban to rural migration, it becomes possible to see other trends and patterns in the data.
Wu, Y., Wang, L., Fan, L., Yang, M., Zhang, Y., & Feng, Y. (2020, March 5). Comparison of the spatiotemporal mobility patterns among typical subgroups of the actual population with mobile phone data: A case study of Beijing. https://www.sciencedirect.com/science/article/pii/S0264275119316725
This article echoes some of the problems and benefits based on the other articles that I read. This articles addresses that knowing factors like size and distribution of populations are crucial to help governments with urban planning and preparing for population growth among other things. The articles explains why census’ are outdated due to the fact that some residents don’t stay permanently and are temporary. Because of this, big data is more reliable because it can track individual digital footprints and then combine them so that overall patterns and trends can be seen. Nowadays phone data is seen as a possible standard for tracking people’s movements since many people around the world have cellphones. Because of location services, it is possible to track location patterns from the movements of people with cell phones. The article states that their purpose was to study mobility patterns of subgroups of a population. These subgroups were created through inferences of the purpose for a certain person’s visit. By knowing these patterns and data, it is possible to improve urban planning and accommodations in response to the data. The data was pulled from China Unicom, which is the second largest telecom operator in China and has many of its stations in Beijing. They split people into 3 subgroups by basing the system off the days that someone stayed in Beijing. They then used different coefficients to obtain results on spatial mobility and temporal mobility such as Spatial Analysis in GIS. With regard to spatial mobility, there were different land-use types classified such as leisure and residence as the two main characteristics used to study sub-groups were proportion of distribution between ring roads and Land-Use Visitation Intensity. According to results, there are a lot of people that aren’t residents of China and that those people could make up about ten percent of the population based on the amount of days they stayed. This article was beneficial because they addressed a gap in current studies, which is how certain and different social groups move around and interact instead of considering the population as whole. The fact that the researchers had to use daily data instead of monthly data to make computations was surprising due to the fact that if the researchers had used monthly data, there would be too much data to compute.
Zhang, W., Chong, Z., Li, X., & Nie, G. (2020, February 13). Spatial patterns and determinant factors of population flow networks in China: Analysis on Tencent Location Big Data. https://www.sciencedirect.com/science/article/pii/S0264275119311862
Population flow has affected many different aspects of the world, especially places like China where the population is massive. There are many economic, structural, and environmental benefits from knowing data and patterns about the population in China that could potentially affect the world. The researchers in this article wanted to explore the evolution of spatial patterns in population flow of China and the basic determinants of population flows in cities. This article expressed that using big data is more accurate than using census data like studies in the past because it is more time-sensitive. It is also different because it analyzes the evolution of population mobility over time. The big data that was used was from Tencent, which is a company that specializes in releasing internet products. Almost all of the Chinese population that has a phone has some form of a Tencent product on it, so Tencent covers a large portion of the population. Because Tencent covers so much of the population, it’s location data is one of the more accurate sources of data for this study. They created a matrix of inter-city population flows and then created a 328x328 network matrix was created. They then used a walk trap algorithm and an ERGM model to explain the data. According to the results, the population flows between major cities actually weakened over time. A reason given for why the population flow decreased was that due to change in economic structure, some cities didn’t have a need for large amounts of cheap labor, which reduced the amount of people who would normally look for jobs to travel there. This article concluded that urbanization, industry and other factors do play a big role in determining population flows.
Zong, W., Cheng, L., Xia, N., Jiang, P., Wei, X., Zhang, F., … Li, M. (2018, August 22). New technical framework for assessing the spatial pattern of land development in Yunnan Province, China: A “production-life-ecology” perspective. https://www.sciencedirect.com/science/article/pii/S0197397518302674
Although the majority of the article did not have migration as a focus, there were still parts of traffic flow that contributed overall to how the cities were seen. Instead, the overall focus was more on studying the spatial patterns of land development. However, the reason they were studying land development partly stems from the fact that rural-urban migration has caused many different issues in China. Part of the assessment of land development includes traffic flow and migration from city to city and the methods they used to calculate that and portray it were very similar to the methods other researchers used in their studies as well. Like many of the other studies, the researchers used data from Tencent because it is one of the more reliable sources of data and because it has such a wide reach. The researchers utilized the API from Tencent to get data on population migration through rail or bus. They then used that information and an equation to calculate and portray the traffic flow between other cities. A darker line meant that the traffic flow was more intense and that there was more traffic over time. Throughout this process, they discovered that sometimes the capital had a higher traffic intensity even when it was a farther distance. It can be assumed that this is because the capital is probably the most prosperous and since it is the center of human activity in that province there are more people traveling to and from it everyday as compare to other cities which may be smaller. It seems that many of the studies seem to use Tencent’s data because of the large proportion of the population that it covers with its Internet-based products. Because of the amount of people this company can cover and the size of the population, Tencent seems to be one of the more popular and more accurate methods to pull data from.
Zhang, G., Zheng, D., Wu, H., Wang, J., & Li, S. (2019, November 21). Assessing the role of high-speed rail in shaping the spatial patterns of urban and rural development: A case of the Middle Reaches of the Yangtze River, China. https://www.sciencedirect.com/science/article/pii/S0048969719353926
High speed rail is a very valuable type of transportation as it allows for fast travel. High speed rail is extremely popular in China, which is also where most of the worlds high speed rails are. High speed rail allows for fast travel and can play a role in how people migrate. This article strays a little from that intended path and instead focuses on urban and rural development based on the high speed rails. The article stressed how important urbanization related to spatial development and talked about how there was a decreasing rural population due to migration to more urban areas. The two questions the researchers were trying to answer were “How have the spatial patterns of urban and rural areas been evolved in the MRYR? Has there been a correlation between the two?” and “How have the attributes of and proximity to HSR stations affected the spatial patterns of the urban and rural areas?” The researchers used 8 landscape indices such as patch density and contrasting edge proportion to characterize different parts of the land with different equations to calculate each. The data they used were datasets from RESDC and the datasets themselves were created with 30 m resolution. They then calculated the indices using ArcGIS. In order to find correlation, they then used Pearson’s coefficient to calculate. Even with recent rural populations being smaller due to migration, there is still correlation in spatial development between rural areas and urban areas. Being closer to a high speed rail also seemed to help spatial development as rural areas that weren’t as close seemed to have slower development. Overall, it seems that high speed rails have a bigger impact than just transportation as being near a high speed rail allows for better spatial development and better communication as well as possibly reducing the spread of excess urban expansion.