Annotated Bibliography

Jiarui Qi

Word count: 1661

1.Md. Arzoo Ansari, Jacob Noble, Archana Deodhar, G.N. Mendhekar, Dilkash Jahan, Stable isotopic (δ18O andδ2H) and geospatial approach for evaluating extreme rainfall events, Global and Planetary Change, Volume 194, 2020, 103299, ISSN 0921-8181, https://doi.org/10.1016/j.gloplacha.2020.103299. (https://www.sciencedirect.com/science/article/pii/S0921818120301909)

In this article, the author discussed the formation and pattern of two natural events: the Cyclone Ockhi and a torrential rainfall event. In 2017 and 2005 severe natural disasters had dealt large scale devastation, loss of lives and properties. To study the formation of extreme rainfall, scientists used stable isotopes (δ18O andδ2H) of precipitation and geospatial data like Sea Surface Temperature (SST),Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) to analyze the situation. It is necessary to study extreme rainfall events because as these disasters cause huge damage to society, the economy development would be severely affected. As a result, in Amartya Sen’s view, people’s freedom would be restricted. After figuring out the reason and development of extreme rainfall disasters, people can formulate countermeasures and managements to minimize the damage of the disaster, achieving the goal of sustainable development by protecting the environment from being harmed. In order to show those data more clearly, the authors presented several graphs, maps and equations. In the graph of the stable isotopes, the author showed the depletion of isotopes during cyclones.

In the graph of the d-excess of rainwater, the authors measure the kinetic fractionation during evaporation. It turns out that during Cyclone Ockhi, the d-excess is high. During heavy rainfall event, the d-excess is middle. During normal rain, the d-excess is the lowest. By studying the d-excess in different weathers, the authors found the potential way of detecting rainfall disasters. Not only did the scientists focus on the cyclone itself, they also compared the data of OLR between different dates before, during, and after the cyclone, as presented in the maps.

The benefits of comparing OLR between dates of the cyclone and date out of it is that scientists can easily figure out the differences and therefore focus on it.In the graph, extremely low OLR may indicates heavy rainfall. For the whole passage, the writer has been using different geospatial approaches to present more information about the two serious disasters. In order to push human development forward, people have to do this to improve their disaster management. If people can forecast these extreme climates, they can make preparations and remedies faster, which can bring less economy losses. Reduce the damage as much as possible is the sustainable development goals in this research. In modern society, while the economy and technology is developing fast, it is hard to afford if disasters are not managed correctly. However, if we use geospatial ways and study data about natural disasters, the economic loss would be acceptable and will not do such great harms to the society. That is, a kind of human development.

2.Phuong-Thao Thi Ngo, Tien Dat Pham, Nhat-Duc Hoang, Dang An Tran, Mahdis Amiri, Thu Trang Le, Pham Viet Hoa, Phong Van Bui, Viet-Ha Nhu, Dieu Tien Bui, A new hybrid equilibrium optimized SysFor based geospatial data mining for tropical storm-induced flash flood susceptible mapping, Journal of Environmental Management, Volume 280, 2021, 111858, ISSN 0301-4797, https://doi.org/10.1016/j.jenvman.2020.111858. (https://www.sciencedirect.com/science/article/pii/S0301479720317837)

Scientists has been studying flash flood-one of the most dangerous natural disasters. Basically, flash floods have high flow rates, which can bring severe economic losses, deaths, and harms to the environment. According to Amartya Sen, economic losses can lead to great restrictions of human development, which relates to many other aspects like people’s average income, life expectancy, and rate of child survival. So it is extremely important to control and forecast these disasters efficiently for coast countries like Vietnam.

One of the ways scientists are trying is to map the region in which likely too have flash floods, like the Van Yen district and Yen Bai province of Vietnam. After mapping the regions using geospatial methods, people have enough information of it and can predict and prepare for the flash flood, which enables people to achieve the ultimate sustainable goal of protecting the natural ecosystem, lives, assets, and properties.

Scientists used decision trees and developed a new ensemble approach called Systematically Developed Forest of Multiple Decision Trees (SysFor).A set of hyperparameters is indentified to construct the ensemble approach.

  1. The total number of trees in the ensemble.
  
  2. The minimum samples per leaf.
  
  3. The goodness parameter.
  
  4. The confidence factor.

Also, scientists have to acquire ten influencing factors to map the study area: LULC( land use and land cover), rainfall, slope, curvature, elevation, aspect, Topographic wetness index, stream, density, soil type, and geology. Carefully, analyzing and making use of these data, scientists can know the topography well and easily map the study area. These 10 factors were sufficiently shown by the ESRI file geodatabase to obtain 3732 data samples.

When it comes to the data science method, as mentioned before, the author mainly used the HE-SysFor model. The best combination of the four parameters is determined by the EO algorithm.

Through the whole passage, the authors have been investigating how to deal with flash floods using geospatial data science methods. This is just one small part of human development of discovering and adjusting nature. If people can coexist with nature, the developments in different fields will be more stable. While discussing how to map the terrain and predict the flash flood, the authors tried to seek the answer of how to understand nature as much as possible and avoid or prepare for some of the most dangerous disasters from harming people’s lives and the economy.

3.Deelstra, A., Bristow, D. Characterizing Uncertainty in City-Wide Disaster Recovery through Geospatial Multi-Lifeline Restoration Modeling of Earthquake Impact in the District of North Vancouver. Int J Disaster Risk Sci 11, 807–820 (2020). https://doi.org/10.1007/s13753-020-00323-5

On the way of human development, the relation between human and the nature is always important. The author’s research discussed this point by mentioning disaster management of earthquakes.

While predicting and preparing for disasters is important, the recovery of different functions of cities is also a crucial part of disaster management. In this passage, the author discussed the city-wide recovery of earthquake in North Vancouver.

After experiencing a disaster, a city’s critical infrastructure lifelines like power, water systems and road networks urgently need to recover. If the administrators can take actions to facilitate the recovery, the losses of he disaster can be minimized. While the economic losses is reduced and the city recovered fast, it is a different kind of economic development. According to Amartya Sen, when the economic losses decreased, human development is accelerated and people’s freedom is guaranteed. Also, fast recovery from the earthquakes can also reduce its harm to nature environment. So the sustainable goal is to both achieve city recoveries and natural protections at the same time. The authors used data about the recovery of 3 critical infrastructure lifelines as geospatial datasets: water distribution and wastewater collection, power distribution and road networks.

The author used Hazus, a software with geographic and infrastructure system data to estimate the likelihood of recovery and level of damage of different infrastructure systems of the city. To acquire more information, the authors also used GMOR( the Graph Model for Operational Resilience) to track the recovery of systems over time. Based oh these research, scientists get the mean, maximum and minimum time of recovery and the standard derivation. It turns out that electrical power and road systems are highly variable and influential in the whole recovery process. Water and waste water are expected to recover most quickly. Knowing these information about system recoveries enables people make proper plans of the restoration of the city.

The authors mainly investigated natural laws that is precious for human development like the patterns of disasters. The scientific question the author tried to answer is how to plan the recovery of the city under disasters like earthquakes better to accelerate its process and minimize the economic loss. To figure out the answer, the authors have to first solve some specific questions like the recovery time build some important models based on geospatial data. Solving these problems step by step, the authors made remarkable progress on disaster managements.

4.Gupta, S., Roy, A., Bhavsar, D. et al. Forest Fire Burnt Area Assessment in the Biodiversity Rich Regions Using Geospatial Technology: Uttarakhand Forest Fire Event 2016. J Indian Soc Remote Sens 46, 945–955 (2018). https://doi.org/10.1007/s12524-018-0757-3

Forests is extremely important in a country’s ecological system, with numerous natural resources and biodiversity. They have the functions of purifying air and regulating climates. Therefore, it is necessary to protect forest in order to achieve sustainable development of human with nature as the authors discussed in this article.

One of the biggest threats of forests is the forest fire and it is likely happen in places with steep terrain, high summer temperature, high wind velocity and inflammable materials. Also, forest fires can cause great bio-diversity loss and economic loss, which bring huge damage to human development in many way. According to Amartya Sen’s view, forest fires influence people’s freedom indirectly. Besides, it is also very hard to recover, making it urgent to solve.

In this article, the authors mainly discussed the Uttarakhand Forest Fire event in northern India. Firstly, the authors presented the basic information of Uttarakhand. The most important data is the forest area, the average rainfall, and vegetation types in different altitudes. After that, the authors showed statistics of the forest types and biological richness in the burnt area. Using the geospatial method of Moderate Resolution Imaging Spectroradiometer (MODIS), scientists analyzed the specific information of the forest fire. However, it turns out that the estimation is inaccurate because it failed to detect small and short fires in dense forests, which have a high frequency in the state of Uttarakhand. In order to acquire accurate assessments for post-fire rehabilitation, the authors made the point that they should improve their prediction by using weather data from Automatic Weather Stations (AWS).

Mapping the burnt area is also an important step to study details of the forest fire. Scientists used AWiFS satellite data the get images and classified them into colors form violet to black in False Color Composite. To access the extent of damage and biodiversity, the authors used forest type maps and biological richness map in the burnt areas and analyzed them using ArcGIS 10.1 and Erdas Imagine 2014.

Throughout the whole passage, the authors tried to find out how to assess the damage of the forest fire in the most effective way. Based on these data, state administrators can make a long term recovery plan.

In the process of human development, people must value the importance of disaster management because it makes a huge difference if these problems are not solved properly. Investigating how to deal with the nature is a great part of human development.