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Taylor & Francis
Introduction
The COVID-19 coronavirus pandemic is the defining global crisis of our time and the most devastating challenge the world has faced since World War II, profoundly affecting how we perceive the world and our daily lives. As a result, the world is facing unprecedented social and economic changes and challenges in all industries and sectors at all levels (from local to national to global).
Critical Role of Location Information
Using location intelligence and GIS to understand this outbreak and its relationships with infrastructure, population, businesses and other location-based information requires a clear understanding of relevant geospatial principles and related aspects of monitoring, planning and data mapping.
Impact of COVID-19 on the Sustainable Development Goals (SDGs)(SDGs)
With the Integrated Geospatial Information Framework (IGIF) at its core, the UN-GGIM published findings on what components are needed to respond to the COVID-19 crisis, such as leadership, governance, law and policy, data and technology. Similarly, the response to COVID-19 also requires the ability to share integrated geospatial information in real time.
Digital Innovation During a Pandemic
For example, IGIF is very useful in disaster response where data sharing and geospatial information are critical. Both in achieving the Sustainable Development Goals and in responding to a pandemic, geospatial information is a key integrator that enables informed decision-making and enables the visualization and analysis needed to communicate key data to decision-makers and the general public.
Collaboration and Engagement
The COVID-19 crisis reminds us that we need to nurture the socially beneficial applications of digital technologies and work to improve accessibility and use in the countries and territories that need the most leverage and assistance. There are many examples of digital innovation around the world, including in the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the International Business Machines Corporation (IBM) supporting the development and deployment of public health mobile applications to help manage the pandemic by providing informed data-driven decisions and social distancing measures.
Opportunities Emerging from the Pandemic
For example, digitization lessons from industry can be applied to public sector services to deliver better and more efficient access, while maintaining provision in the face of budget shortfalls. In the wake of COVID-19, governments and companies have the opportunity to envision greener, fairer and more sustainable days.
Moving Forward from the Pandemic
A sustainable recovery is not just about job creation; it's about creating high-quality, accessible jobs that improve people's lives, which in turn creates more sustainable societies. The pandemic has also raised environmental fears among the public, as the mandatory pause for industrial pollution and travel has resulted in cleaner air where CO2.
This Book, Objectives, Chapter Outline
Zhixuan (Jenny) Yang reports on online higher education in Chapter 21, focusing on how online education facilitated by Information and Communication Technology (ICT) was implemented in China during the COVID-19 pandemic. Mark Allan outlines the lessons learned from managing the Melbourne COVID-19 pandemic in Chapter 42.
Introduction
Land Administration and Authentic Geospatial Information: Lessons from Disasters to Support Building Pandemic Resilience. Readiness should include investments in Land Administration Systems (LAS) and National Spatial Data Infrastructure (NSDI).
Emergencies – Disasters and Pandemics
The speed and depth with which the COVID-19 recession has hit suggests the possibility of a sluggish recovery. The COVID-19 pandemic is not the first global pandemic and it will not be the last, may almost be cliché now.
Economic and Financial Impacts of Disasters and Pandemics
The scale of the financial challenge for developing countries is measured in trillions of US dollars. However, the rapid global economic impacts of the pandemic highlight the fragility of the sustainability of SDG Goal 1, the reduction of extreme poverty [1].
Overview of WB-FAO Partnership
The sudden reversal of capital flows has helped finance extraordinary fiscal packages in developed economies, but has left emerging market and developing economies exposed. Pandemic-related external financing gaps for active International Development Association (IDA)3 countries could be in the range of $25-100 billion per year – assuming that additional financing needs arising from the crisis are in the range of 2-10 percent of GDP and that only half of them can be met domestically.
Resilience Enablement Through LAS and NSDI
LAS and NSDI support economic and social recovery, support minimization of the shocks of disasters and pandemics, and enable faster recovery. LAS and NSDI can only fulfill their role if they themselves are resilient – and therefore also have to be sustainable.
COVID-19: Specific Challenges
In addition, in April 2020 the EU issued 'Guideline 04/2020 on the use of location data and contact tracing tools in the context of the COVID-19 outbreak'. In the context of COVID-19, vulnerable communities around the world are expected to face increased land grabbing, migration, displacement, corruption and evictions.
Pragmatic Rapid Assessment of LAS and NSDI Maturity in Resilience ContextsResilience Contexts
Experiences with pragmatic rapid assessment of LAS and NSDI maturity in resilience contexts within selected countries. Continuation – Experiences with pragmatic rapid assessment of LAS and NSDI maturity in resilience contexts within selected countries.
Build Back Better
In assessing LAS and NSDI requirements, the WB and FAO examine various tools to support and inform the work, including a range of geo-development and SDI preparedness instruments9, while also considering and evaluating other available geo-development and NSDI preparedness tools, including the Integrated Geospatial Information Framework (IGIF) developed under the United Nations Global Geospatial Information Management Initiative (UN-GGIM). Experiences with IGIF NSDI diagnostics, alignment with policy drivers, socio-economic assessment and action planning, as piloted for example in Guyana, help draw parallels and inform approaches elsewhere.
Concluding Remarks
Ensuring resilient communities and food supplies in the face of the COVID-19 pandemic with investments led by the CFS-RAI. This chapter examines open geospatial data responding to the COVID-19 challenge: which data are useful for studying the spatio-temporal distribution of the virus.
Introduction
Third, open geospatial data are also collected and published by researchers to encourage data reuse. The chapter concludes with an assessment of the availability and suitability of open geospatial data for responding to the challenge of COVID-19.
What Data Is Useful for Responding to the COVID-19 Challenge?Challenge?
Frequent and thorough hand hygiene is one of the most important measures to prevent the spread of COVID-19 [11]. Environmental data sets on the concentration of air pollution and data on the prevalence and spatial distribution of non-communicable diseases can help identify parts of the population that are vulnerable to COVID-19.
What is the Availability of such Open Data With Global Coverage?Coverage?
- COVID-19 Infections
- Reference Information
- Places Frequented by many People
- Travel Networks and Mobility
- Global High-resolution Land Cover Maps
- Address Data
- Demographic Data
- Concentration of Air Pollutants
- Water Sources
- Health Facilities
While the data discussed in other subsections can also be used as reference information on maps (eg the travel network in 3.3.4), in this section we focus on base maps, images, place names and administrative areas. General data on the health status of the population (again at the country level) can be found on the WHO website.
Discussion and Conclusion
URLhttps://read.oecd-ilibrary.org/view/?ref jm4ul2jun9&title=Environmental-health- and-Strengthening-resilience-to-pandemics. URLhttps://www.un-ilibrary.org/population- and-demography/world-population-prospects-2019-volume-ii-demographic-profiles_7707d011-en.
Introduction
These new interdisciplinary ideas of a remote sensing approach have emerged to detect, evaluate, and map factors affecting public health. Finally, an approach to predict the occurrence of the COVID-19 epidemic using remote sensing and surface data is proposed.
Remote Sensing and Health
- What is a Virus?
- How is a Virus related to Remote Sensing?
They found a similar influence of the temperature and relative humidity on the effective reproduction number (R-values) of COVID-19 for both China and the USA. They studied the relative risk of COVID-19 due to weather conditions and air pollution.
Remote Sensing Methods to Predict Health-related Outbreaks
- Malaria Case Study
- Materials and Methods
- Study area
- Malaria Distribution Maps for Incidence Factors
However, they believed that none of the three meteorological variables could explain influenza B activity. The shooting date should be between August and November and between February and May, when the most rainfall occurs in the region.
Vegetated Area Mapping
Vegetated Area Mapping 61 for those months, and k is a scale factor equal to 1,000. Table 4.2 shows the health centers, the regional population and the calculated incidence index for the Minab and Kahnooj regions, respectively.
Water Body Mapping
For regions containing water body patches, humidity has a value greater than -0.0710. Using this threshold in the figure and again the 2-km flight area for mosquitoes around water bodies, Figures 8 and 9 were produced for Minab and Kahnooj, respectively.
Land Surface Temperature
The bodies of water detected in Kahnooj's image were as small as one pixel and thus cannot be detected visually in the image.
Air Temperature
Relative Humidity
Results and Analysis
Discussion
The zeros in the image are due to the lack of information for those regions. However, the satellite capability in detecting high-risk potential regions can provide non-expensive information on a routine basis, not only in malaria, but also for other epidemics, where studies in those areas are the objectives of these authors.
Cholera Case Study
Conclusions
Work currently underway has shown the dependence of flu outbreaks, and to some extent, COVID-19, on air temperature, humidity, wind speed and direction, and population density. Remotely sensed surrogates of meteorological data for studying the distribution and abundance of disease-carrying arthropods. Annals of Tropical Medicine.
Introduction
Although drone technology is well established, there are still factors that require further investigation to fully utilize drones. This chapter presents an overview of current drone technology and future developments and the exploration of some existing and proposed applications.
Developments in Drone Technology
The chapter then discusses the issues facing successful implementation of the use of drones for these applications, and the issues that need to be overcome in order for this technology to become mainstream in the future. The phone and tablet apps now available allow for either very basic basic autonomous flights (Litchi) or more advanced grid pattern flight paths (Pix4D) that allow the pilot to customize the overflight pattern, e.g.
The Impact of COVID-19
- Delivering Essential Goods and Services
- Battling the Spread of Coronavirus
Impact of COVID-19 73 with roles that may be useful in helping to address the actual and perceived impact of the COVID-19 pandemic. These are all ways drones can help reduce the spread of the corona virus.
Summary and Conclusions
URL https://www.kiro7.com/news/local/drones-detecting-body-temperature-being-used-covid-19-response/. URL https://www.eastlothiancourier.com/news/national-news/18573416.covid-19-test-kit-delivery-drones- receive-funding-boost.
Introduction
This chapter examines the role of social and built environments in social interactions in Melbourne before and during the COVID-19 pandemic and discusses potential social and built environment interventions to increase social interactions. This chapter aims to look at the role of social and built environments in social interactions in Melbourne before and during the COVID-19 pandemic and discuss possible social and built environment interventions during and after the pandemic to increase social interactions.
Pre COVID-19
6] investigated the relationship between social isolation and mental health outcomes during the COVID-19 pandemic (n=278) in the United States. During COVID-19 81, the importance of social and built environments in the frequency and satisfaction of social interactions was expected to vary across age groups.
During COVID-19
- Social and Physical Distancing Restrictions in Melbourne
- Social Interactions During the Pandemic
The latter connects older adults with volunteers who spend time with them during the pandemic. Direct face-to-face social interactions and the use of social and built environments (and amenities) in the neighborhood were minimized during the first lockdown and further restricted during the second lockdown in Melbourne (Figure 6.1).
Post COVID-19
They found that downtown activities were halted, but the use of public spaces is similar to pre-pandemic and places offering activities (e.g. playgrounds) were used more than ever [41]. This differs from the Melbourne context, as the use of public spaces (e.g. playgrounds, benches) was restricted.
Concluding Comments
URL https://www.theage.com.au/national/victoria/generational-catastrophe-how-covid-19-could-reshape-melbourne-20200715-p55c7b.html. This chapter reports on a study that aims to contextualize social vulnerability to pandemic situations in the aftermath of the COVID-19 pandemic.
Introduction
As a result, three main components of social vulnerability to pandemics are identified: social determinants, determinants of the built environment and individual characteristics. This chapter is primarily intended to contextualize societal vulnerability to pandemic situations following the COVID-19 crisis.
Social Vulnerability and Pandemics
While the use of the term "social vulnerability" in scientific literature can be traced back to the 1970s (e.g. [8]), after the mid-1990s this concept began to be widely used in the field of disaster management [3, 5, 9]. The next part of this chapter is devoted to indicators of social vulnerability in the context of the COVID-19 pandemic.
Social Vulnerability Indicators
- Individual Characteristics
- Built Environment Determinants
Although people of all ages can become infected with the COVID-19 virus, the elderly appear to be more susceptible to it. Given the unique nature of the COVID-19 pandemic, this section identifies the following preliminary indicators as determinants of the built environment of the pandemic.
Discussion and Conclusion Remarks
This study is an early attempt to understand social vulnerability to disease outbreaks by learning from the COVID-19 pandemic and its socio-economic consequences on society. The first limitation comes from the highly complex nature and the rapidly changing and still unfolding implications of the COVID-19 pandemic.
Introduction
The algorithm has been demonstrated in areas in South Africa, a developing country with one of the highest cases of COVID-19 globally. Here we provide a broader overview of the problem, especially in relation to the COVID-19 pandemic.
Literature
Informal roads are not necessarily straight, but may be visually irregular or winding, as determined by the navigational needs and environmental constraints from which the roads arose. This chapter presents a practical solution to the problem of detecting informal paths and assessing their associated uncertainty.
Uncertainty Measures in Remote Sensing
It is therefore necessary to consider sources of uncertainty and ways of quantifying their influence that are appropriate to the purpose and structure of the algorithm. Uncertainty during data collection and earlier steps of the algorithm propagates and necessarily affects the final results [51].
Road Extraction Algorithm
The size parameters vary depending on the spatial resolution of the image, as well as the typical sizes of roads and objects in the image. The final output of the algorithm is the final path objects along with their associated certainty.
Accuracy Assessment
Measurements per pixel are calculated by comparing each pixel of the extraction to each pixel of the reference. The calculation of center lines depends on the full size of the objects, including their edges.
Application
- Study Area and Data
- Demonstration for Area 1
- Results for All Areas
The safety associated with the extracted road objects is determined in the safety measure defined in section 8.4, based on the compactness and extension of the road objects. This explanation also shows the greater similarity between measures for area 2 compared to area 1, as area 2 contained more false positives than area 1. The results show that area 3 had more false positives and negatives, while area 1 had fewer.
Discussion
In area 1 (Figure 8.13(a)), some buildings were not eliminated in the NDVI threshold step and contributed to the detected false positives. In area 2 (Figure 8.13(b)), a high number of false positives was caused by the large part of the formal road being falsely detected as road.
Conclusion and Future Work
Self-diagnosis within automatic road network extraction. International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences. Statistical evaluation and analysis of reclamation methodologies using a unique remote sensing dataset.Remote Sensing.
Introduction
- The Use of Geospatial Data and Systems
- Impacts on the Maritime Community
- Significance of Machine Learning for Maritime During COVID-19
- The Maritime Ecosystem’s Needs for Data & Challenges
- Challenges Faced by Information Product Providers
- Working Remotely and Disconnected
Due to the reduced demand for freight, many companies have gone out of business due to the pandemic. Depending on the objectives of the maritime community, all approaches have the potential to answer important questions relevant to supply chain and trade activity during the COVID-19 pandemic.
Case Studies
- National Oceanic and Atmospheric Administration – Office of Coast Survey
- Space-Time Analytics for Quantying Impacts of COVID-19 on Shipping Trade
- Disseminating Live Traffic Data During the Pandemic: ESRI Ireland
We use time series clusters and spatio-temporal patterns in the Oxford COVID-19 Government Response Tracker (OxCGRT) stringency index that quantifies the extent to which governments are taking steps to limit daily activities [31]. Space-time patterns of the severity index are exploited by classifying the local changes to the Getis-Ord Statistics, namely the G∗i statistics (Getis and Ord, 1992).
Conclusions
Geographically tracking and mapping of coronavirus disease covid-19/severe acute respiratory syndrome coronavirus 2 (sars-cov-2) epidemic and related events around the world: how 21st century gis technologies support global fight against outbreaks and epidemics, 2020. The effects of covid-19 induced lockdown measures on coastal marine settings. Science of The Total Environment, page.
