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The Use of Geospatial and Remote Sensing Techniques to Track The Increase of Peri-Urban Areas and Associated Health Risks in Disease and Flooding in Vietnam

Word Count: 4611

Introduction

Topic Description

The following literature review analyzes and evaluates the ongoing problems experienced in Vietnam. The literature views these problems in the context of their relation with increased peri-urbanization, a blend of urban and rural land that urban planners assemble as a result of a large demand for increased urban area but lack of proper resources and time. Peri-urbanization is the root of the following problems due to its lack of proper planning or predictable long term expansion. The specific problems examined in this literature review include the ill effects of peri-urbanization, health and economic, with the subtopics of the transmission of the Avian Influenza and increased rate of catastrophic flooding. The central research question of this literature review is what are the negative effects of unchecked peri-urbanization in Vietnam as a result of increased foreign direct investment. The specific development goals of the literature review as defined by the United Nations include Sustainable Cities and Communities, Good Health and Well-Being, and Climate Action.

Region of Study and Associated Complexities

The area of Vietnam, and more specifically Ho Chi Minh City, has had an acceleration in economic growth caused by increased foreign investment starting in the 1990s that has encouraged many to move into the urban areas. Investment has been driven by tax incentives which are most lucrative in the urban areas, further encouraging the populus to move to those areas. This has led to a widespread increase in build up areas that are developed quickly with more focus on the present rather than long term impacts and conditions to meet the desires of the people moving into urban areas. Those urban areas which are put together quickly and still have a blend of urban and rural characteristics are defined as peri-urban and are a major focus on the presented issues of spreading disease and increased flood risk. The increased expansion of the peri-urban area leads to a major amount of both direct and indirect risks. Coupled with the growing economy, the predominantly wet and grassy environment of the area leaves Ho Chi Minh City prone to flooding and less conducive to conventional urban build up. The combined factors of the growing economy pushing rapid urbanization and the unique landscape making conventional urban planning less viable make Vietnam and Ho Chi Minh City a critical area to research and understand further.

Intersection of Urbanization’s impact on Health in Vietnam and Amartya Sen’s definition of Human Development

The increase in economic activity and growth in Vietnam and specifically Ho Chi Minh City has catalyzed the aforementioned widespread growth in urbanization, leading to accelerated build up of urban areas which replace previously rural areas. This rapid urbanization and changing landscape has caused a variety of health and environmental effects which negatively impact the Vietnamese people. Those ill effects include but are not limited to the spread of the Avian Influenza and increased volume and intensity of flooding. These ill effects have a direct impact on the freedoms of those people on the receiving end.

Amartya Sen’s definition of human development is the increase of freedoms for the people. The development goals in regard to Ho Chi Minh City, increased flooding, and spreading disease have direct ties to Amartya Sen’s definition. Surface flooding runs over impervious ground material with ease, including those materials used in urban areas, meaning that economic centers in Ho Chi Minh city are currently at increased risk of being flushed away by flood waters that at times reach 100 centimeters. This potential degradation of economic centers as a result of flooding limits the economic freedoms of the people, as they are left jobless when their local businesses are ripped away from them. Furthermore, flooding has the potential to destroy homes, crop land, and threatens drowning. These multifaceted effects have directly endangered the people’s freedoms of health as it impedes the fundamentals required for livelihood.

Concurrently, increased transmission of Avian Influenza as a result of unplanned urbanization has a clear impact on the freedom of life as it threatens to kill those it infects as well as their economic foundation, poultry. Death of poultry, the cornerstone of the economic activity in Vietnam, has cost producers 3 trillion VND. For these reasons, the presented sources fall within Amartya Sen’s definition of development since they attempt to increase the freedoms of the people by better understanding the exact vulnerabilities of the current urbanization planning.

Important Methods and Datasets from Annotated Bibliography

The examined articles use a variety of data science methods. The most notable method was a combination of remote sensing data with a machine learning algorithm. The remote sensing data consisted of Landsat or QuickSCAT satellite data of varying levels of spatial resolution, often ranging from 30 m to sub-one meter resolution. This remote sensing data was also verified by Google Earth imaging as well as in person field study. The remote sensing data was then used in conjunction with a machine learning algorithm, one example being a support vector machine (SVM) classifier. This combination of techniques was often verified by field study as well as census data to ensure accurate predictions. Together the methods were capable of producing high resolution images with classifications in a geographical information system to better understand the spread or likelihood of types of urbanization, flooding, and disease in a visual medium.

Themes/Topics, Processes, and Methods

Increased Peri-Urbanization and Effect on Land Use

Studies throughout academia have observed the increase of peri-urbanization using remote sensing techniques to document the exact spread in Ho Chi Minh City. Furthermore, they document the way that these changes have altered land use and viability to better understand potential negative impacts of the problem. These studies serve as an important illustration of growing urbanization to further contextualize and frame the exasperated spread of disease and flooding.

The research article Monitoring peri-urbanization in the Greater Ho Chi Minh City Metropolitan Area [1] clearly illustrates this peri-urbanization trend. The authors mentioned the effects of increased foreign direct investment, FDI, following Vietnam’s switch to a more open economy around the 1990s. They described how this foreign aid became a large part of the Vietnamese economy, accounting for 13% of the GDP, with Ho Chi Minh being the center of that investment, comprising 53% of all FDI investment. The authors reason that the tax incentives of Ho Chi Minh city made it an appealing location for investment, driving a mass urbanization in and around the city [1].

To quantitatively illustrate this trend, the researchers used a combination of Landsat satellite imagery and census information provided by the city to track movement and development from 1990 to 2012. They input the data into a support vector machine classifier, creating categories including urban, peri-urban, and rural. The results showed that 660.2 km^2 of cropland had been converted to built up areas, with 62% of that expansion being strictly peri-urban. The focus on peri-urban expansion is unsettling as the ill effects are further laid out with the spread of deadly diseases, catastrophic flooding, and decreased crop yields.

Likewise, the article MultiScale Remote Sensing of Urbanization in Ho Chi Minh CIty, Vietnam- A Focused Story of the South [2] provides further evidence for growing urbanization in Ho Chi Minh City. The authors used a combination of sub-meter, 2.5 meter, and 10-15 meter resolution remote sensing to track land cover changes in Ho CHi Minh City from 2000-2010. The data was classified into a variety of categories: build up 1 including highly dense housing, build up 2 including larger and less dense housing, water, vegetation, and road. These classifications then provided a clear picture of the changing landscape and urbanization patterns and changes throughout the years [2].

The results of the studies provided concrete illustrations of the changing urban trend. For example, the results determined an increase of dense build up on the North side of the city where there was higher elevation. Likewise, there was a significant decrease in the amount of land classified as vegetation, bare, and water. In fact, there was a 28% decrease in the vegetation, meaning a concerning decrease in wetland and croplands. In addition, the increase in urbanization in the North on higher ground led to increased flooding in the South as will be further explained in the literature review [2]. The article in totality serves to cement evidence for the growing trend of urbanization in and around Ho Chi Minh City Vietnam, with examples of potential ill effects to come.

Lastly, Analysis of Land Cover Changes in Northern Vietnam Using High Resolution Remote Sensing Data [3] narrowed in on changing crop land as a result of growing peri-urbanization. The researchers used 15 meter STER, Landsat, and PALSAR images to track changes from 2007-2015 in conjunction with a kernel-based probabilistic classification system which is similar to a bayesian inference. The combination built a generative model to better understand the changes. This model had a total of 9 classifications for comparison: water, urban and built up, rice, other crops, grasslands, orchards, barren, forest, and mangrove [3].

The results of the study illustrated a clear decrease in cropland alongside an increase in water area. The results are striking as it increases the risk of flooding with water levels rising and Ho Chi Minh City being described as one of ten cities most expected to be negatively impacted by climate change [2]. Furthermore, the decrease in cropland poses a threat to food security in the city, making it all two likely that food shortages can plague the country on top of increased likelihood of floods destroying crops.

The aforementioned sources lay a groundwork for the rest of the literature review, establishing a clear quantitative increase in areas dedicated to urbanization, and more importantly peri-urbanization. The rest of the sources grapple with the ill effects this uncontrolled expansion brings, most specifically focusing on disease spread and flooding, both of which negatively impact the freedoms of the people, risking their livelihood and economic participation.

Peri-urbanization and Increased Transmission of Avian Influenza

Similarly to its confirmation of growing urbanization trends, the literature identifies and models the spread of Avian Influenza in Vietnam, proposing a variety of potential solutions. Currently, the literature looks at areas all across the Vietnamese area but fails to examine the Ho Chi Minh City area. However, the given literature provides a beneficial starting point for potential analysis in such a critical location.

Does Unplanned Urbanization Pose a Disease Risk in Asia? The Case of Avian Influenza in Vietnam [4] documented the background to the Avian Influenza outbreak in Vietnam. The authors described how the disease is spread through poultry, a mainstay in the Vietnamese markets. Furthermore, they discussed the current method of maintaining the outbreak: vaccinate or kill the poultry. That program cost the Red River Delta region in 2015 a total of $9.7 million while only reducing the rate of disease by 62% [4].

The authors of the study attempted to find a better solution, however. They sought to model the area using Rural, Agricultural, and Fishery census taken by the Vietnamese government every 5 years. This data gave researchers the ability to model the area using the classifications of rural, peri-urban, urban, and urban core. They described peri-urban areas as having a lack of necessary water and sanitation, with the highest likelihood of interaction between the people of the area and the poultry [4].

The results of the study showed that peri-urban areas, as would be expected by their description, are 1.5 times more likely of receiving Avian Influenza than rural or urban communities. As well, they showed that there were no outbreaks in the urban core. With the results in hand, the researchers concluded a variety of important factors which raise the likelihood of transmission: high land use diversity or density of chicken, proximity to national highways because of commercial movement, and low annual rainfall. These factors lay a clear guideline for tracking and more importantly alleviating the spread of Avian Influenza. As well as indicating risk factors, the researchers proposed what they believe to be the most viable solution to the issue. They urged local governments to focus on vaccinating peri-urban areas regularly every 8 weeks to coincide with the commercial cycle. They showed that this method would have a 93% reduction rate compared to the current 63% while also decreasing the current cost of $9.6 million to $6.92 million [4].

Emerging Infectious Disease, the Household Built Environment Characteristics, and Urban Planning: Evidence on Avian Influenza in Vietnam [5] likewise looked at the specific factors of peri-urbanization and how they may lead to increased spread of the Avian Influenza. For their methods, they used a multivariate logistic regression (MLR) to look at the likelihood of spreads. Their data set was the government records on Avian outbreak from each commune and district. The variables they observed and considered were building material, water supply, and sanitation system. They used these variables to determine if each peri-urban area was traditional, transitional, or modern. In order to measure the poultry density in each area, the researchers used a ArcGIS-generated area measure.

The results of the study showed the importance of household level infrastructure such as water supply, sanitation, and construction materials. They illustrated that these variables were viable predictors of where the Avian Influenza is likely to occur. Those areas that were the most in transition were more likely to experience a large outbreak of the disease. These findings further show the downfalls of having a whole area concurrently in a transitioning urban area as it leaves the populus at unacceptable levels of threat. The potential solution outlined by the authors is to increase the levels of household infrastructure, focusing on sanitation and water supply.

Spatio-Temporal Occurrenence Modeling of Highly Pathogenic Avian Influenza Subtype H5N1: A Case Study in the Red River Delta, Vietnam [6] similarly attempted to model the spread and transmission of Avian Influenza, this time in the Red River Delta area. They used a combination of regression modeling and geospatial techniques to develop monthly predictive maps. The authors highlighted background information to further contextualize the ongoing issue, citing from 2003-2010 that 57/64 provinces in Vietnam had the virus and that the disease has cost the poultry industry 3 trillion VND. In addition, the disease killed a total of 59 people.

The researchers used a logistic regression model that resulted in an odds ratio, where 1 indicated no relationship, greater than 1 is a positive relationship, and less than 1 is a negative relationship. In addition, an ArcMap with 36 raster layers representing precipitation, humidity, and temperature was constructed. The authors modeled the poultry density using Shuttle Radar Topography Mission 90-meter resolution digital elevation model data. The combination of the results in a GIS model that illustrated predictive spread [6].

The results found a positive relationship between disease occurrence and mean temperature with disease density, with odds ratios of 1.518 and 1.368 respectively. Contrarily, the authors found a negative correlation between humidity, precipitation, and elevation with disease density, with odds ratios of .949, .975, and .716 respectively. These findings allow a predictive model which is updated monthly, allowing proper solutions to the ongoing transmission of the Avian Influenza [6].

The literature shows a clear method to tracking, modeling, and potentially alleviating the transmission of Avian Influenza in Vietnam. These methods as applied around the country must be used in Ho Chi Minh City to understand disease spread accompanied with ongoing peri-urbanization. In addition, the literature illustrates the disastrous effects the avian influenza has had on the poultry production in Vietnam, a major component of their economy, and has shown a potential for the disease to take human life. For those reasons, it is critical to use the aforementioned data method techniques to track and minimize the transmission.

Peri-urbanization and Increased Risk of Floods

In addition to increasing the risk of disease transmission, peri-urbanization poses the increased threat of catastrophic flooding. The literature has documented this trend in full, using remote sensing techniques and statistical methods to visualize at risk areas based on a variety of landscape characteristics. When these models are used effectively, they can better direct prevention methods and give insight on what characteristics to look out for.

Application of Remote Sensing and GIS-Based Hydrological Modelling for Flood Risk Analysis: A Case Study of District 8, Ho Chi Minh City, Vietnam [7] serves as a clear introduction to the flooding issues in Ho Chi Minh City. The authors described reasons for their inquiry, with the most significant reason being that a majority of the area is only 1.5 meter above sea level. Given that climate change is predicted to increase sea levels by 1 meter in the next century, the area is at critical risk of disastrous flooding and being submerged in water. The authors predicted that this would negatively affect 660,000 residents, putting their lives at risk. From this information, the authors sought to understand which type of flooding poses the most risk to the city: rainfall or tidal?

The researchers used remote sensing QuickBird imagery to predict rainfall patterns and a Digital Elevation Model in GIS framework to predict tidal floods. The GIS framework created a set of classifications including water bodies, traffic routes, construction land, bare land, and green areas. In addition, the authors used a TR-55 model to account the classifications from the GIS as well as flow length and channel slope. To make a visual representation the authors used the plus tools in ArcGIS. The combination of these methods created a predictive model for future flooding and at risk areas [7].

The study provided insightful results. They determined that 80% of the study area was at risk of flooding and those areas which were closer to sea level were at risk of up to 100 cm flood heights. In addition, those areas which were made of impervious materials like concrete, the material that is most characteristic of urban areas, were at higher risk of runoff. The coefficient of determination for that impervious material and runoff correlation was .73, showing a significant positive correlation. In addition, the researchers showed that areas that had a longer flow length were at decreased risk of flooding, with a coefficient of determination of -.86 [7].

The sound conclusions from the provided evidence is that the current form of urbanization does not have the appropriate drainage capabilities to reduce flood risk. In addition, the researchers showed that areas which had been developed for a longer period of time were still at high risk of flooding, an indication that their water infrastructure was outdated and in need of renovation. The study illustrates the specific areas most in need of improvement, aiding a strategic solution procedure.

A New Modeling Approach for Spatial Prediction of Flash Flood With Biogeography Optimized CHAID Tree Ensemble and Remote Sensing Data [8] similarly illustrates the frequency and impact of flooding. The authors describe the effects of flash floods including death, economic destruction, destruction of crops, degrading to ecosystems, and disease transmission on waterways. As methods, the researchers used Sentinel-1 Sar data from the European Space Agency, and ArcGIS software system, and a CHAID (Chi-square automatic interaction detection) decision tree to create classifications. The classification derived from these data techniques included bare land, crop areas, forest areas, grassland, orchard area, paddy rice, urban and built up, and water bodies.

The study produced results which illustrated the observed correlations. They found that there was a r=0.65 positive correlation between land use and slope factors. As well, there was an insignificant r=-.56 negative correlation between topographic position index and slope factors. In addition, the results indicate a higher susceptibility to flash flooding in high, steep mountainous areas and flash flood most likely during storm season. Areas in the lowlands were least likely to be affected [8].

Together the sources illustrate a trend of increased flooding, following patterns related to landscape characteristics including elevation, land type, soil type, location of water bodies, and more. Both studies clearly represent the dangerous effects which peri-urbanization poses in the context of flood patterns. Sea level changes related to the changing climate only further exacerbate the flooding issues from peri-urbanization. These data science methods provide a solid groundwork for further investigation of flooding and its impact on the residents of Ho Chi Minh City, providing an opportunity to model and track flooding more effectively.

Methods and Data Sets

As mentioned throughout the body of the review, the literature has used a variety of data science methods and sets to achieve their goal of monitoring peri-urbanization and its effects. In most presented articles, the authors started with some sort of geospatial remote sensing technique. Many used a variation of Landsat or QuickBird imaging to have a top down overview of the targeted area. These image methods are derived from satellites using passive remote sensing to produce a top down image with varying resolution. This view then provides the researchers with the raw data to begin to analyze topographic features as well as land use patterns, as is critical when attempting to understand the peri-urbanization trends.

Many articles took advantage of a data science technique to create classifications for the Landsat or QuickBird imaging. These classification methods were critical in transforming the raw data of remote sensing imagery to then comprehensible sections and distinctions. The presented works took advantage of classifiers including support vector machines, digital elevation models, and kernel based probabilistic classification. In addition to these classifiers, the authors took advantage of linear and logistic regression to establish significant correlations between factors.

Data sets were spread out among the articles and were dependent on the specific issue at hand. For example, those articles which looked at the increase in Avian Influenza transmission in Vietnam used a number of census data sets. Most notably, authors used the Vietnamese Rural, Agricultural, and Fishery census data to graph where outbreaks occurred. Similarly, authors gathered their remote sensing data from the United States Geological Survey, the European Space Agency, or Google Images. Their remote sensing findings were verified by field study reports.

Lastly, the researchers commonly used a geographic information system framework to visualize their models and results. An ArcGIS model was similarly popular due to its capabilities to put layers of numerical or visual data together into a coherent medium. This method then allowed for the researchers to have a vizual, interactive medium to showcase the data in a comprehensive and cohesive manner.

Themes and Their Sustainable Human Development Goals

The proposed issue of peri-urbanization and its ill-effects intersects well with the broader human development goals as defined by the United Nations. Most directly, the issue of peri-urbanization on a whole deals with the goal of sustainability of cities as it seeks to understand the failings of current infrastructure. The sources repeatedly show the inferior nature of indoors infrastructure as well as current cities lacking the appropriate water stability infrastructure. These sources shed light on the insecurities of the current city development plans, presenting an important path forward. Cities must understand the current failings as addressed by the presented sources to then adjust their strategies, allowing for proper planning to decrease the harms of current peri-urbanization.

The represented issues as illustrated by the literature also include good health and well-being. This goal is most directly addressed by the issue of the persistent transmission of Avian Influenza. This linkage is solidified by the 59 cases in humans which risks the health and good being of those infected. Even more so, those 59 cases pose the risk of further transmission, total outbreak, or a mutated virus which would further negatively impact the health of the Vietnamese people. The presented sources effectively model and predict current and future outbreaks, allowing a template for target areas and necessary solutions.

Similarly, the presented literature deals with the sustainable human development goal of climate action, and more specifically preventing the effects of rising sea level. The sources centered around persistent flooding in Vietnam echoed that flooding had a likely relationship with rising sea levels and the low elevation of the area. They used a variety of visual mediums to show the likelihood of flooding in each distinct commune, presenting the city with the critical information to plan where flooding infrastructure is most necessary to combat increased flooding and rising sea levels.

Conclusion

Reflecting on the Holistic Effect on the Vitenamese People

The presented sources make it evident that the Vietnamese people are at increased risk of Avian Influenza transmission and catastrophic flooding as a result of peri-urbanization. Peri-urbanization lacks the critical infrastructure for sanitary living or proper flood mitigation. This poses real concern with a majority of current urbanization expansion in Vietnam being characterized by peri-urbanization. If this pattern persists, a larger percentage of the Vietnamese population will be at an increased risk of disease transmission and flooding, risking the lives and well-being of millions. For this reason, the issue must be better analyzed in Ho Chi Minh City due to its perceived pattern of urbanization and high rate of foreign investment, driving movement to the city.

Observed Gap in the Literature and Defined Research Goal

The literature clearly analyzes the holistic issue of peri-urbanization and its impact on disease transmission and increased flooding in Vietnam. This analysis does not exemplify the necessary breadth and specificity to truly understand and solve the issue, however. The clearest gap in the literature is a comprehensive overview of the perceived issues in Ho Chi Minh City. The current literature illustrates a clear trend of peri-urbanization in Ho Chi Minh City but fails to specifically analyze the transmission of the Avian Influenza and increased rate of catastrophic flooding. The studies for both sub-topics only concentrate on this critical area briefly or fail to mention it at all. It is paramount that the literature turns its focus to the Ho Chi Minh City area specifically, applying the same methods and techniques as they did to the previous areas. For that reason, my defined research goal is to model and predict the spread of Avian Influenza and flooding in the Ho Chi Minh City area in the context of increased peri-urbanization.

How can data science help us to better understand human development? What role does complexity play in advancing this better understanding?

Data science provides the ability to directly model and track human development quantitatively. This differs from past methods of qualitative analysis. The ability to capture and understand big data using data science provides an unparalleled opportunity to better understand the complexities of target areas, taking into account previously unknown variables. As Owen Barder articulated throughout his presentation, previous approaches to human development have been too narrow in the variables they consider and naive in their analysis of the complexities which followed. Each method focused on one variable, professing that they had found the one factor which would change human development for the better. Each method was true in some way but wrong in their certainty. Each presented factor was critical in human development, but past researchers were wrong in the importance they laid on each.

Data science provides the unique opportunity to find critical patterns in the collected data and to model predictions based on these patterns. The machine learning algorithms applied to each problem comprehend the complexity of each variable in a way human minds cannot. Furthermore, graphical interfaces like the aforementioned Geographic Information Service frameworks provide a visual representation of issues in a medium which is better understood by people. The ability to fully comprehend the complexities and then provide an articulate model makes data science and its techniques unparalleled in its aid in human development.

Refrences

  1. Kontgis, C., Schneider, A., Fox, J., Saksena, S., Spencer, J., & Castrence, M. (2014, July 30). Monitoring peri-urbanization in the greater Ho Chi Minh City metropolitan area. Retrieved October 11, 2020, from https://www.sciencedirect.com/science/article/pii/S0143622814001477

  2. Vu, T., Thy, P., & Nguyen, L. (2018, February 21). Multiscale remote sensing of urbanization in Ho Chi Minh city, Vietnam - A focused study of the south. Retrieved September 09, 2020, from https://www.sciencedirect.com/science/article/pii/S0143622816301655

  3. Hoang, T., Nasahara, K., & Katagi, J. (2017, October 05). Analysis of Land Cover Changes in Northern Vietnam Using High Resolution Remote Sensing Data. Retrieved September 18, 2020, from https://link.springer.com/chapter/10.1007/978-3-319-68240-2_9

  4. Saksena, S., Finucane, M., Tran, C. C., Duong, N. H., Spencer, J. H., & Fox, J. (2017, January). Does Unplanned Urbanization Pose a Disease Risk in Asia? The Case of Avian Influenza in Vietnam. Retrieved September 14, 2020, from https://scholarspace.manoa.hawaii.edu/bitstream/10125/43702/api128.pdf

  5. Spencer, J., Finucane, M., Fox, J., Saksena, S., & Sultana, N. (2019, October 14). Emerging infectious disease, the household built environment characteristics, and urban planning: Evidence on avian influenza in Vietnam. Retrieved October 11, 2020, from https://www.sciencedirect.com/science/article/pii/S0169204619313465

  6. Tran, C., Yost, R., Yanagida, J., Saksena, S., Fox, J., & Sultana, N. (2013, November 28). Spatio-Temporal Occurrence Modeling of Highly Pathogenic Avian Influenza Subtype H5N1: A Case Study in the Red River Delta, Vietnam. Retrieved October 14, 2020, from https://www.mdpi.com/2220-9964/2/4/1106/htm

  7. Dang, A., & Kumar, L. (2017, November 03). Application of remote sensing and GIS-based hydrological modelling for flood risk analysis: A case study of District 8, Ho Chi Minh city, Vietnam. Retrieved September 17, 2020, from https://www.tandfonline.com/doi/full/10.1080/19475705.2017.1388853?src=recsys

  8. Nguyen, V., Yariyan, P., Amiri, M., Dang Tran, A., Pham, T., Do, M., . . . Tien Bui, D. (2020, April 26). A New Modeling Approach for Spatial Prediction of Flash Flood with Biogeography Optimized CHAID Tree Ensemble and Remote Sensing Data. Retrieved October 11, 2020, from https://www.mdpi.com/2072-4292/12/9/1373/htm