Assignment 1

Miao Liu

Feb 23, 2020

Problem statement

Because of its large economy, urbanization in India is no longer a domestic problem. With the largest population in the world, India has a had time balancing economic growth and social development, leaving its urbanization messy. Uneven urban growth threatens the social stability and people’s living environment. For example, In Delhi, poisonous microscopic particles have spiked to 75 times the level considered safe by World Health Organization (Tom Batchelor); about 100 million people still live in slums (Mimi Kirk); mega cities are so overcrowded that 44 percent of urban households occupied one room or less (Smriti Chand).

Before rushing to create a sustainable urban planning, it is necessary to understand urbanization first. Some of the previous studies were ineffective or incomplete because they applied inaccurate datasets. Such research offers misleading advice and weakens institutional efforts at urban growth. My sources aim to investigate the classification of urban development and demographics of India.

Annotations

1. Urbanization in India. (n.d.). Retrieved from https://www.worldbank.org/en/news/feature/2011/09/22/india-urbanization

   The report presented by World Bank primarily explains what problems urbanization has brought to India and possible solutions to alleviate those problems. Firstly, the report defines urbanization as a procedure of increasing aggregate population in urban settlements. It is not a side effect of economic growth; it is an integral part of the process. India’s rapid economic growth leads to a massive urban transformation, which poses unprecedented challenges to providing housing and infrastructure (water, sewage, transportation, etc.), and addressing slums.

   This source provides statistics to exemplify the seriousness of uneven urban development. For instance, slums now account for about 26% of all urban population in cities. In Mumbai specifically, more than half of the population lives in slums. Unlike in most other cities in developing countries, many Indian slums are situated near employment centers in the heart of town. To improve the situation, local governments must actively participate in urban planning.

   How does this relate to Amartya Sen’s idea about human development? In his article, Sen introduces five distinct types of freedom: (1) political freedoms, (2) economic facilities, (3) social opportunities, (4) transparency guarantees and (5) protective security. These distinct types advance the general capability of the society. This source has covered the second and the third type, stressing the high correlation between economic development and urban planning. In the beginning of the report, it is emphasized that India takes up a great percentage of the world’s population and economic production. If messy urbanization remains in India, domestic challenges will ultimately spark global problems. To ameliorate the living condition of people in slums, the government should maximize the benefits of economic facilities and offer more employment opportunities to the poor.

   The article proposes several ways to address problems caused by rapid uneven urbanization. One of them is to establish city wide frameworks for planning, while increasing the transparency. It also aims to document services and budgets for convenient governance.

   To investigate the existing problems and progress being made, the author looks for specific data and programs that target major cities in India. In the capital city, over 50% of the people live in slums, without clean water and proper sanitation. While India has experienced tremendous growth in Mumbai, its infrastructure and social welfare fails to catch up. With a huge population and limited land, the local government is having a hard time distributing available resources in an efficient way. The administration needs to figure out more effective policies. Most of the problems are environmental. Water access and uncontaminated food are also significant components of high living standards. Regulations can protect poor people from being discriminated against. The government can also call upon private sectors to open up opportunities in employment.

   The author proposes that India’s weaknesses lead to domestic, uneven development. Though rapidly growing, India’s economic condition is limited by the scarcity of resources and fluctuation from financial markets. The source acknowledges India’s resource limitations and encourages urban related ministries to launch programs to confront current challenges.

   Despite its highlight, I consider the report incomprehensive because it only covers one city in India. Although it mentions the national rate of economic output and urban population, there should be more specific data that helps researchers to analyze. The most helpful part in the article is the identification of current problems and advice on possible programs.

2. Balk, D., M. R. Montgomery, H, Engin, N. LIN, E. Major and B. Jones, “Urbanization in India: Population and Urban Classification Grids for 2011” Data 2019, 4(1), 35; https://doi.org/10.3390/data4010035

   In contrast to its big population, India is one of the least urban countries in the world. Although official report maintains a decent percentage of urbanization, most Indians have difficulty enjoying high living standards. To prevent further people from being crowded into slums, we need to pinpoint the socioeconomic problems and take the correct actions with the help of detailed spatial data. However, the availability of reliable datasets remains low. Without precise statistics, it would be hard to analyze and reconcile differences.

   This source, fortunately, presents gridded estimates of population at a high resolution. Moreover, the author cross-classified the census data and the remotely-sensed data, combining traditional methods with latest technology. Once constructed to the representation of urban settlement, these statistics can provide an empirical basis for analyzing the urbanization of India through population and urban classification grids.

   In his work Development of Freedom, Amartya Sen claims that the quality of life illustrates the effectiveness of human development. The article includes exhaustive information on India’s trajectory of urbanization in 2011, which helps to assess the progress of human development. Meanwhile, this article coincides with Sen’s fourth dimension of human development. Since it covers various kinds of data, the stage of urbanization becomes more transparent. For instance, satellite data can identify areas where human activities take place, assessing the prosperity of specific locations. Additionally, accurate data helps research institutes to take correct actions when solving problems.

   The selected article relates to several sustainable development goals. The most obvious one would be sustainable cities and communities because the work displays current urbanization process and specifies urban classifications. Its application extends to reducing inequalities and reducing poverty.

   To generate high-resolution grids of India’s urban areas and population distribution, the author collects three kinds of data. One is population census abstracts (PCAs), which describe the population of different settlements, the number of households, and additional characteristics. The second dataset is digital records of settlement boundaries. Since the government of India did not publish the boundary data, the article uses the ML Infomap LLC. Lastly, the author employs the Global Human Settlement Layer (GHSL) that identifies areas of human activity.

   After data-collection, the research team uses geospatial tools to link spatial units with census tabulations. To create Thiessen polygons, they apply a geoprocessing tool in ArcGIS. Next, they transform irregular vector data to a uniform grid by using a proportional allocation rule. Eventually, a GHSL-Based classification is generated.

   At a 1-km resolution, these new data are not just numbers estimating a country’s population. They allow researchers to monitor the progress of urbanization, to redirect the distribution of wealth, and to devise sensible arrangements for the destitute. I chose this source because it provides a detailed description of the data selection process. Besides, the author adopts multiple methods in an organized way. Although I was not familiar with every method, each of them is introduced along with its function and significance.

3. Elfie Swerts, Denise Pumain, Eric Denis. The future of India’s urbanization. Futures, Elsevier, 2014, 56, pp.43-52. 10.1016/j.futures.2013.10.008. halshs-01061210

   Unlike my previous sources that focus on summarizing the past progress of India’s urbanization, this source tries to make predictions about the future of urban development. Over fifty percent of the world’ population now lives in cities. Beginning in the ninetieth century, “Urban transition” is likely to complete in this century. Developed countries have already completed this transformation due to their small population. Developing countries such as India are also catching up. With the help of known dynamics, we can construct models that predict the distribution of urban growth.

   The article is tightly related to Amartya Sen’s idea because of its careful analysis on urban transition, which encourages economic activities and social programs. Once we get a reasonable level of accuracy from data-collection, the government can come up with better solutions to poverty and social inequalities. These two improvements also belong to dimensions of human development Sen has discussed in his work.

   The author acknowledges India’s enormous urban population, but has concerns about the remaining space for future expansion. Multiple organizations under United Nations have projects that stimulate urban growth, but they focus on linear inter-census growth rates that result in overestimation. To avoid the problem, the author utilizes a different approach along with two complementary geo-databases. The first one is named IndianCensus. As the name suggests, it is based on the official towns as given by the census series from 1901. The second geo-database is called Indiapolis, which uses satellite imagery to ensure its precision.

   Based on the hierarchical distribution of Indian cities, the author chooses the rank-size as the first data science method. Graphs within the article show the singularity of Indian cities’ distribution that is similar to European urbanization. Figure 2 shows the trajectories of Indian cities in the last century through the combination of census data and Indiapolis data. To predict urban population growth in the next 50 years, the author uses proportional projections for his calculation. The first table contains major cities in India and its expected population in 2025 and 2050. UN Projection is also listed for comparison.

   The best part of this source is in the end where it lays out possible ways to apply the growth rates. As the title suggests, the author seeks to forecast India’s urban future. Given its growth trajectory, India is likely to embrace huge transformation of landscape, economic structure, and social life. The rapid rate of urbanization not only produces benefits but also poses a sustainability challenge.

4. Eric Denis and Kamala Marius-Gnanou, « Toward a better appraisal of urbanization in India », Cybergeo : European Journal of Geography [Online], Systems, Modelling, Geostatistics, document 569, Online since 28 November 2010, connection on 21 February 2020. URL : http://journals.openedition.org/cybergeo/24798 ; DOI : https://doi.org/10.4000/cybergeo.24798

   High urban growth does not ameliorate Indians’ living conditions. The weak management of local governments deteriorates the huge gap between the poor and the wealthy. Like other developing countries, increasing urban population requires better infrastructure, institutions, and resources. Many of the studies on India’s urbanization, however, have a narrow focus on official urban figures in the taken census. This source attempts to avoid biases by using the Geopolis approach. This new option suggests that India is undergoing a much-diffused process of urbanization instead of class separation, challenging the mainstream view on India’s urbanization.

   As Amartya Sen has mentioned, human development is an inclusive project that enlarges people’s freedom. Poverty and inequality are two important factors that affect the degree of freedom. The article indicates that poverty and inequality are exaggerated because researchers selected the biased approach. Therefore, the article’s new perspective may bring a more appropriate set of programs for the development of India.

   Among key dimensions of human development, the source relates to two of them-a decent standard of living and a long and healthy life. Urbanization ensures clean water and tidy living conditions, satisfying the above two dimensions.

   The source criticizes the ambiguity of definitions on which the Census of India relied. The concept of Urban Agglomeration is inaccurate for its narrow scope. Geopolis database, one database the article refers, improves the representation of small cities. Geopolis definition allows people to make uniform assessment and includes more urban areas that had been neglected. Another geospatial database the author draws information from is Indiapolis geodatabase, which stores more specific figures. From the database, urban geographical extension appears to be decreasing in 2001. However, urban encroachment is underestimated.

   The Desakota model is one of the methods the article applies in Kerala, which is exhibited to be a mature urban state. This discovery implies the diversity of Indian urbanization and an oriented process of urban planning. The Geopolis method, on the other hand, uses satellite imagery to observe over ten thousand agglomerates. Those small agglomerates are significant because their emergence is changing the urban setting by increasing available services. Once consumption rises, more job opportunities appear to flourish the region’s economy and contribute to the urban development.

   In sum, the author tries to explain the urban dynamics in India by yielding an accurate analysis on the country’s urbanization rate. Its result acknowledges the success of urban decentralization, encouraging the future studies to be more precise and careful. It is crucial to remind researchers that we should avoid the metropolis-biased vision. Without the right data, neither policies nor projects can ever take effect.

5. Taubenböck, H., Wegmann, M., Roth, A., Mehl, H., & Dech, S. (2008, October 29). Urbanization in India – Spatiotemporal analysis using remote sensing data. Retrieved from https://www.sciencedirect.com/science/article/pii/S0198971508000604

   As a worldwide phenomenon, urbanization is chiefly prevalent in India. The country has experienced a striking growth rate since the late 20th century. Due to this unprecedented condition, policy makers did not prepare to gather data and process information. No appropriate tools were in hand to measure, monitor, and understand urban sprawl processes. Luckily, data scientists develop multitemporal remote sensing for analyzing rapid urban changes. Time-series of Landsat data helps us to classify urban footprints. The scale of analysis has grown continuously to exhibit different urban types.

   This article corresponds with Amartya Sen’s idea that “freedom is a principal determinant of social effectiveness” (Sen 18). We have gained more freedom through increasing the transparency of data. These statistics are generated for improving current patterns of urbanization, making our social programs more effective. The author’s research addresses one dimension of human development-be knowledgeable. It shares a method that quantifies spatiotemporal growth and detects urban growth types with other researchers. The contribution of new methodology inspires further experiments in this area.

   The research fits the development goal of constructing sustainable cities and communities. It studies twelve urban agglomerations, including three mega cities in India. Based on population, those agglomerations are classified into three groups. Then, the author adopts remote sensing data sets that provide continuous Landsat data. The object-oriented hierarchical approach works well on measuring changes in the urban extension. Therefore, the article selects this most appropriate methodology. The absence of ground truth data complicates the assessment of classification result. To increase the accuracy of data, the author compares his results to the Landsat data.

   In general, urbanization is associated with a city’s economy and demography. To obtain more details, the research is conducted at different scales. Parameters and landscape metrics are aggregate measurements that must be displayed at a specific resolution. Location-based analysis must reflect how distance affects the built-up density.

   Like my last source, this source also contains a way of classifying urban types. Interestingly, the ways they categorize urban growth are quite different. This article combines parameters and metrics by using descriptive statistics. A collection of spider charts is created for comparisons between cities’ sizes and landscapes. The spider charts demonstrate that spatiotemporal urbanization has no impact on defining India’s urban type. They also indicate similarities between mega cities. Altogether, spider charts precisely display the characteristics of the twelve cities. Therefore, the analysis answers the author’s question on India’s urban growth types.