Michal Ben Gal
מחקר בהתהוות
דר' דניאל זייצ'יק
מחקר זה בוחן את ההתמודדות של רשויות מקומיות עם משבר הקורונה, בדגש על חמישה תחומי ליבה: ניהול המשבר, ציות הציבור להנחיות, אכיפה, התחסנות, ושיתוף פעולה עם השלטון המרכזי וארגונים אחרים. בעזרת סקר לרשויות המקומיות בישראל, המחקר מנסה להבין את השוני בין הרשויות ביחס לאתגרים, לאופן ההתנהלות, ולמתן המענה, על מנת לזהות דרכים להתאים מדיניות ותמיכה ממשלתית לטובת הרמה המקומית.
Dr. Danielle Zeichik
This research aims to describe the experience of local governments managing the COVID-19 epidemic, with a focus on five key areas: crisis management, public obedience, law enforcement, vaccinations, and cooperation with other agencies and organizations. The research surveys local governments in Israel about the challenges and approaches taken with regards to these topics, with the goal of identifying differences between localities and understanding how to better tailor policies and central government support to effectively serve local interests.
Itai Beeri, Nufar Avni, Danielle Zeichik and Yonat Rein
This research aims to understand the success of municipal governments in Israel in minimizing the impact of the COVID-19 epidemic at the local level. After defining measures of success, the research identified the factors- primarily the policies implemented, management, and cooperative efforts- that allowed successful municipalities to minimize the impact of the pandemic in their towns and cities. These factors, as well as policy recommendations for both the central government and local governments, were identified and detailed.
See here for final report (in Hebrew)
צוות המחקר: איתי בארי, נופר אבני, דניאל זייצ'יק, יונת ריין ואלכס אלטשולר
משבר הקורונה טומן בחובו אתגרים רבים: בריאותיים, חברתיים, כלכליים וניהוליים, עימם נדרשו להתמודד כל גופי השלטון. לאור התפקיד המרכזי של השלטון המקומי בטיפול באוכלוסייה בעתות חירום, חשוב להבין את אופני הפעולה של הרשויות המקומיות ותפקודן במהלך משבר הקורונה. מחקר זה בוחן את התנהלות הרשויות המקומיות בישראל במהלך משבר הקורונה. המחקר בוחן מהם הגורמים אשר סייעו לרשויות מקומיות להציג תפקוד מוצלח וביצועים גבוהים בהתמודדות עם משבר הקורונה, ולחילופין, מהם החסמים אשר עיכבו רשויות מקומיות וגרמו לביצועים ירודים בהתמודדות עם המשבר.
Bibliographic details:
Yan, X., Xu, K., Feng, W. et al. A Rapid Prediction Model of Urban Flood Inundation in a High-Risk Area Coupling Machine Learning and Numerical Simulation Approaches. Int J Disaster Risk Sci 12, 903–918 (2021).
Abstract:
Climate change has led to increasing frequency of sudden extreme heavy rainfall events in cities, resulting in great disaster losses. Therefore, in emergency management, we need to be timely in predicting urban floods. Although the existing machine learning models can quickly predict the depth of stagnant water, these models only target single points and require large amounts of measured data, which are currently lacking. Although numerical models can accurately simulate and predict such events, it takes a long time to perform the associated calculations, especially two-dimensional large-scale calculations, which cannot meet the needs of emergency management. Therefore, this article proposes a method of coupling neural networks and numerical models that can simulate and identify areas at high risk from urban floods and quickly predict the depth of water accumulation in these areas. Taking a drainage area in Tianjin Municipality, China, as an example, the results show that the simulation accuracy of this method is high, the Nash coefficient is 0.876, and the calculation time is 20 seconds. This method can quickly and accurately simulate the depth of water accumulation in high-risk areas in cities and provide technical support for urban flood emergency management.
Bibliographic details:
Masoumi, Z. (2021). Flood susceptibility assessment for ungauged sites in urban areas using spatial modeling. Journal of Flood Risk Management, e12767.
Abstract:
In urban areas, flood susceptibility assessment is of special importance because of the high settlement population, properties, and infrastructures. Geospatial information science (GIS) provides a tool for investigating flood susceptibility based on several aspects including economic damages and critical infrastructures in cities. This study aims to provide a tool based on GIS analyses to support decision-makers in identifying flood hazards in urban areas, in which previous flood data, flood causative factors, and urban infrastructure data are not adequately available. To assess flood susceptibility in the study area, the related spatial high-resolution data were produced. Then, flood zones were estimated for different recurrence intervals using meteorological data. Finally, susceptibility was assessed in urban areas for different urban infrastructures using GIS modeling. The model was designed based on the assumption that any critical urban infrastructure, such as power towers, was affected by flood zones and, in addition to flooding, could cause hazards by itself. Moreover, five scenarios were defined to calculate susceptibility when in the problematic locations of the floodway. DoAsb Floodway was chosen as a case study located in Zanjan city, northwest of Iran. The results indicated the high-susceptible areas around the floodway. Moreover, the flood susceptibility level for each urban infrastructure in the study area was calculated and classified into five classes from low susceptible to very high susceptible. Also, the results of the five scenarios showed if some parts of the floodway had problems, the susceptibility rate would be high. The generated flood susceptibility maps of this model can be used to plan suitable programs in order to avoid flood damage and ensure public safety.
Webpage: https://onlinelibrary.wiley.com/doi/full/10.1111/jfr3.12767
Bibliographic details:
Yu, I., Park, K., & Lee, E. H. (2021). Flood Risk Analysis by Building Use in Urban Planning for Disaster Risk Reduction and Climate Change Adaptation. Sustainability, 13(23), 13006.
Abstract:
In this study, focusing on buildings as the smallest unit of urban space, the distribution characteristics of risk factors were examined by building use as an adaptable measure for urban flooding disasters. Flood risk is calculated as a function of hazard, exposure, and vulnerability. The flood risk for a building was classified into five classes, and the distribution characteristics of buildings were examined according to England’s flood risk vulnerability classification system, known as Planning Policy Statement 25 (PPS25). After analyzing the risk of flooding in Ulsan Metropolitan City, one of Korea’s representative urban areas, it was found that while Dong-gu District can be considered relatively safe, districts of Jung-gu and Nam-gu, as well as Ulju-gun, have highly vulnerable buildings with red and orange ratings, which include motor vehicles-related facilities, education and welfare facilities, and residential facilities. There has been evidence to prove that urban flood disaster affects topography and the environment, in addition to having a significant effect on adaptability depending on the facility groups that resulted from urbanization. This study is expected to serve as a scientific database for disaster risk reduction and climate change adaptation to floods during land-use planning, which would eventually allow for systematic management of high-risk buildings through verification of location suitability of buildings by facility group.
Webpage: https://doi.org/10.3390/su132313006
Bibliographic details:
Ebi, K. L., Hasegawa, T., Hayes, K., Monaghan, A., Paz, S., & Berry, P. (2018). Health risks of warming of 1.5 C, 2 C, and higher, above pre-industrial temperatures. Environmental Research Letters, 13(6), 063007.
Abstract:
Background: In response to the Paris Agreement under the United Nations Framework Convention on Climate Change, the research community was asked to estimate differences in sectoral-specific risks at 1.5 °C and 2 °C increases in global mean surface air temperature (SAT) above pre-industrial temperatures. Projections of the health risks of climate change typically focus on time periods and not on the magnitude of temperature change.
Objective: Summarize projections of health risks associated with temperature extremes and occupational heat stress, air quality, undernutrition, and vector-borne diseases to estimate how these risks would differ at increases in warming of 1.5 °C, 2 °C, and higher.
Methods: A comprehensive search strategy included English language publications since 2008 projecting health risks of climate change identified through established databases. Of 109 relevant publications, nearly all were for future time periods (e.g. in 2030 and 2050) rather than future SAT thresholds. Time periods were therefore converted to temperature changes based on the models and scenarios used.
Results: Warming of 1.5 °C is reached in about the 2030s for all multi-model means under all scenarios and warming of 2 °C is reached in about the 2050s under most scenarios. Of the 40 studies projecting risks at 1.5 and 2 °C increases of SAT, risks were higher at 2 °C for adverse health consequences associated with exposures to high ambient temperatures, ground-level ozone, and undernutrition, with regional variations. Risks for vector-borne diseases could increase or decrease with higher global mean temperatures, depending on regional climate responses and disease ecology.
Conclusions: The burden of many climate-sensitive health risks are projected to be greater at an increase of 2 °C SAT above pre-industrial temperatures than at 1.5 °C. Future projection studies should report results based on changes in global and regional mean SATs and time, to facilitate quantitative analyses of health risks and to inform the level of ambition and timing of adaptation interventions.
Webpage: https://iopscience.iop.org/article/10.1088/1748-9326/aac4bd/meta
Prof. Eran Feitelson and Yonat Rein, the Hebrew University in Jerusalem; Prof. Pnina Plaut and Smadar Amir, the Technion; Prof. Deborah Shmueli, Prof. Eli Salzberger, Dr. Alex Altshuler and Dr. Michal Ben Gal, University of Haifa
Abstract
Analyses of the effects of COVID-19 tend to focus on the health and economic implications of the pandemic. Yet, it is clear that there are wider effects, such as effects on social relations, stress, livelihood and effects on the environment. As is increasingly recognized, the GDP per capita is an insufficient measure to assess the state of countries and citizens within them (Stiglitz et al., 2009). Hence well-being is increasingly promoted as measures to assess the state of countries and citizens, and as a basis for policy decision-making. In particular the OECD (2017) advanced a set of 39 indicators for well-being. Similarly, since 2016, the Israeli CBS (Central Bureau of Statistics) has published a yearly report of “Quality of life, sustainability and resilience”, based on 114 criteria in 11 fields (employment, personal safety, health, housing and infrastructure, education and skills, civic engagement and governance, environment, personal and social welfare, material standard of living, leisure, culture and community and information technologies).
This research aims to identify the well-being criteria that are influenced by and influence the Coronavirus crisis, analyze these effects in the Israeli arena, identify policy measures that may have a positive influence on well-being, and suggest “policy packages” that may reduce negative influence and enable better life with the virus.
The first part of the study was conducted in collaboration with IIASA (International Institute for Applied Systems Analysis) as part of the agreement between the Government of Israel and IIASA, in which the possible effects of aiding systems analysis were identified.
See: Feitelson, E., Plaut, P., Salzberger, E., Shmueli, D., Altshuler, A., Ben Gal, M., Israel, F., Rein-Sapir, Y., Zaychek, D., 2022. "The Effects of COVID-19 on Wellbeing: evidence from Israel", Sustainability, Special Issue "Economic and Social Consequences of the COVID-19 Pandemic", Vol. 14, 3750. https://doi.org/10.3390/su14073750
Bibliographic details:
Zohar, M. (2021). Geolocating tweets via spatial inspection of information inferred from tweet meta-fields. International Journal of Applied Earth Observation and Geoinformation, 105, 102593. https://doi.org/10.1016/j.jag.2021.102593
Abstract:
In the last 10, years the Twitter social network has become a robust messaging platform. To date, Twitter has more than 500 million users worldwide. A given tweet can contain the geographic location of the transmitting device if the geolocation services are activated or the IP address can be geocoded, which is applicable to only 1–3% of all tweets. Nevertheless, tweets also contain more than 40 other meta-fields, some of which are inserted by the user and may include spatial information that can be tapped to infer locations associated with the tweet. This study implemented the publicly available GeoNames and Open Street Map (OSM) datasets in conjunction with curated dataset of 2001 tweets from Israel. With both Geonames and OSM, the inference of the tweets’ geographic locations was implemented using the meta-fields of the text (resulting in 600 geolocated tweets), the user location (857 tweets), and the user description (425 tweets). The inferred locations were then spatially examined to verify if they can serve as potential proxies. It was found that the distance between the inferred locations using the text and user-location meta-fields is well correlated with the distance between their midpoint and the device location. Thus, it may indicate the actual device location as well the location of the phenomenon described in the tweet.
Link to paper: https://www.sciencedirect.com/science/article/pii/S0303243421003007