https://brookdalecommcollege-my.sharepoint.com/:w:/g/personal/gsimon2_my_brookdalecc_edu/EXYP9oc1DlNHnrfzG8B88iEBLus_oamH9Jr9crBkz2nMeA?email=gisimon23%40gmail.com&e=aIuheh
Data 150
Annotated Bibliography
Gianna Simon
Professor Brewer
The College of William & Mary
References
Ding, Y., Fan, Y., Du, Z., Zhu, Q., Wang, W., Liu, S., & Lin, H. (2014). An integrated geospatial information service system for disaster management in china Informa UK Limited. doi:10.1080/17538947.2014.955540
This article focuses on disaster management specifically in China under their government and circumstances. There has been a rise in the occurrence of natural disasters, specifically in China, and they attribute this the to the change in climate. Because of the increasing threat of natural disasters and the rising population, researchers in this article looked at disaster management in broad terms. They took things into account such as forecasting, prevention, assessing losses and analyzing. Having so many aspects making up disaster management is what leads to the complexity of solving how to best monitor and react to natural disasters. The authors discuss what has been used in the past several years, describing the system to use a top-down data-centric style with limited capability. These systems do not provide full utilization of information. With such complexity it is easy for issues to arise. The problems discovered in the previous system include lack of accessibility, an active disaster information service, exploitation of high-resolution data, among others. Further they go into the importance of creating a new disaster management mechanism. In creating the new mechanism, they include services for sensors, maps, data, data processing, and analysis. They put into an orbit a Focusing Service Mechanism (FSM) meant to better the use of resources. Additionally, they provide a layout of how their IDISS, or Integrated Disaster Information Service System would be used, with examples. Creating this new system was complex but will overall improve the ability to manage disasters in China where the population is extremely large and natural disaster have been increasing. This article relates to Amartya Sen’s definition of human development because the researchers are aiming to create a system to utilize more information to eliminate some of the harm caused by natural disasters. By working on these systems, the people of China become better off as the threat of natural disasters should subside allowing freedoms to enjoy other aspects to grow. The dimension of human development addressed by this article includes living a long and healthy life and a decent standard of living. If systems can predict disaster, individuals have higher chances of survival. The standards of living also increase if the effects of disasters become mitigated with new systems. The goal being considered in relation to this article is to make sure all information is properly taken advantage of in hopes of using it beneficially. The specific goal in this article is to have a system that can use the data in a way to address all the aspects of disaster management so individuals can be better prepared as well as assisted. The datasets and data science methods used by the authors include Geographic Information System and Remote Sensing data, IDISS, National Disaster Reduction Application System, FSM, and many other web services. The authors are investigating the ways in which natural disasters can be looked at through data in order to minimize harm. They are trying to answer the question of which systems will do their best to perform accurate and up-to-date mapping and analysis of areas in danger.Sweta, L. O., & Bijker, W. (2013). Methodology for assessing the usability of earth observation-based data for disaster management. Natural Hazards (Dordrecht), 65(1), 167-199. doi:10.1007/s11069-012-0351-x
The authors of this article focus on earth observation (EO) data in response to natural disasters. Disaster response is incredibly important but the ways to respond, such as EO, are still lacking in areas, leading to challenges. The authors claim the most crucial aspect of natural disasters is to have quick availability of spatial information. EO data is directly affected by how up to date and reliable geographical data sets are. Authors delve into the four phases of the production of EO data, the problems surrounding EO data, and its importance. They then developed a methodology where they could assess, understand, and rate the usability of EO data. They even applied what they found to real world disasters. In concluding remarks, the researchers discussed the many different aspects and characteristics of EO data and products used for disaster management. They conclude it is important for the products to be held to standards, guidelines, and rules. All suggestions are for the purpose of creating the best way to keep data organized and accurate for the best disaster management. This article relates to Amartya Sen’s definition of human development because it focuses on increasing standards. Specifically, the standards of disaster response systems which will in turn give individuals a better quality of life by having higher chances of survival and escaping many of the effects of natural disasters. The dimension of human development that is primarily addressed is a long and healthy life. Also, a decent standard of living. The datasets and data science methods used by the authors include earth observation (EO) data, geographic information science technologies, quality information templates. EO is what they focused on primarily. The authors are investigating the information that is readily available after natural disaster strikes. They are trying to answer what the quickest and most accurate way to receive and utilize information after disaster is. Their main focus is getting the correct information to the correct people in the quickest time possible while retaining integrity.Yang, Y., Qiu, X., Li, S., Wang, J., Chen, W., Hung, P. C. K., & Zheng, Z. (2019). Energy-efficient data routing in cooperative UAV swarms for medical assistance after a disaster. Chaos (Woodbury, N.Y.), 29(6), 063106. doi:10.1063/1.5092740
This article focuses on the best ways to provide medical assistance after disaster. Its primary means of data collection after disaster is unmanned aerial vehicles abbreviated UAV. They want to address the harm of individuals being in crucial need of medical help once disaster strikes. How quick survivors are reached after disaster strikes can be the difference between life and death. But finding and rescuing those individuals can be extremely challenging which is why data science and technology can help tremendously. UAVs can collect information around disaster sites including the locations and conditions of individuals and their nearest emergency or medical centers. This data collection helps to efficiently put response teams together and send them directly to the survivors instead of having to spend time aimlessly searching. The article goes further into discussing the limitation of these UAVs in that their battery life is poor, making it harder to survey larger areas for reasonable amounts of time. There may also be issues in delivering the data being collected in a quick and clear manner. The researchers’ purpose was to optimize the energy of the UAVs to eliminate problems. To figure this out they created multiple scenarios, working through data algorithms and systems. They ultimately decide on a specific makeup of UAVs to perform their job the best while minimizing the amount of energy that must be used. This article relates to Amartya Sen’s definition of human development by aiming to remove deprivation which is an example of unfreedom. People in poorer areas are least likely to receive quick help in times of disaster so the systems being proposed in this article would allow these individuals to be targeted through need. This article would fall under the category of a long and healthy life because it concerns receiving medical aid. Sustainable development goals being considered in relation to this article would be creating routes to reach victims of disasters in cost efficient, time sensitive, and safe ways. When it comes to data sets and data science used by researchers include cyber-physical systems, U2U network, U2G network, multihop data routing. They used different techniques to find the best algorithm for collecting data sets through UAVs. The authors are investigating the conditions that arise once disaster has struck. Many individuals seek immediate care, but medical aid does not know the exact spots to find them. The authors want to answer the question of which is the most efficient and valid way to identify and send response teams to survivors of disaster. They worked to find this answer by creating the most cost efficient and responsive UAVs that would be able to cover large areas of land and pinpoint individuals in need while sending the information to response teams.
Zhang, C., Zhao, T., Usery, E. L., Varanka, D., & Li, W. (2020). Improving geospatial query performance of an interoperable geographic situation‐awareness system for disaster response. Transactions in GIS, 24(2), 508-525. doi:10.1111/tgis.12614
The goal of the researchers in this article was to find the best ways to improve the functionality of IGSAS or interoperable geographic situation awareness systems, through the use of the Geospatial Sematic Web for the benefit of disaster management. They are addressing the universal concerns of the damage caused by natural disasters and the large numbers of people affected. Figuring out ways to deal with natural disasters is super complex and challenging. It can especially be hard to locate those in need if areas that have not been mapped out or out of date data. Response for individuals and areas affected increase alongside of geospatial information technologies. The authors address the specific problem of a gap between online systems and data sources by an optimization of caching techniques, filtering, and spatial indexing. They developed technologies to improve the real-time condition of areas to aid in response efforts. This article relates to Amartya Sen’s definition of human development because it is about bridging gaps. In this case it is the gap between online systems and data sources. But bridging this gap leads to better disaster response. When the gap between freedoms and unfreedoms is lessened it leads to human development. Additionally having a better system for disaster response helps human development as a whole. The dimension of human development addressed in this article is living a long healthy life. By increasing speed and organization of disaster response, individuals have a better chance of survival when faced with natural disaster. The datasets and data science methods used by the authors include Geospatial Semantic Web technologies, the interoperable geographic situation-awareness system, web services, Open Geospatial Consortium, among others. Authors are assessing the patters of disaster response and the systems used to gather information. They are trying to answer the question of which ways the data collection can be improved and used considering the current geospatial data applications have flaws.