Students
Tom Avikasis-Cohen, MA. Gardens in Mandatory Jerusalem using GIScience & machine learning (co-supervised with Prof. Ilan Shimshoni)
Lior Svirsky, MA. GIScience and planetary mapping
Olivia Ayres, MA. Look Up, Look Out, Look All Around: Lookouts and Landmarks in Greek and Roman Mediterranean (co-supervised with Dr. Emmanuel Nantet)
Yonathan Zigmond, MA, Spatial analysis of the Matson Photograph collection (co-supervised with Prof. Ilan Shimshoni)
Yulia Mazor-Verbitzky, MA, Spatial analysis of the mounds ('Tulilat el-Anab') in the vicinity of Shivta
Adi Ophir, PhD. Analyzing sequences of historical earthquakes along the Dead Sea Transform
Subham Mukherjee, Post-doc, Comparative analyses of freshwater ecosystem services and adaptation strategies towards a sustainable water secured future for coastal urban areas (co-supervised with Prof. Eran Feitelson and Prof. Brigitta Schutt)
Graduated
Neta Yalon, MA. The impact of ‘stone mounds’ on soil moisture in a slope in the Israeli desert (co-supervised with Prof. Dan Malkinson)
Lian Kombelis, MA. Historical geography and natural hazards in Shivta (co-supervised with Dr. Yotam Teper)
Almog Arad, MA. Temporal damage patterns in Jerusalem during the last 3000 years
Liat David, MA. Analyzing old drawings using GIScience integrated with computer vision - (co-supervised with Prof. Ilan Shimshoni)
Amichay Sadeh, MA. GIScience for the analysis of ancient roads (co-supervised with Dr. Tali Erickson-Gini)
Ongoing projects
Analysis of spatial and temporal damage cycles of historical earthquakes during the last 3,500 years along the Dead Sea Transform
Earthquakes were always meaningful to mankind as one of the most destructive natural hazards. The seismotectonic unit associated with much of the destructive earthquakes in the Levant is the Dead Sea Transform (DST) system. Thus, there is an ongoing effort to investigate the DST. Nevertheless, the research is limited to quantitative data which is available only for the last century, since the deployment of the first seismograph. Unfortunately, this period is too short in comparison with the slow tectonic processes and seismogenic cycles around and along the plate tectonic borders, including the DST. Thus, in order to inspect longer periods of seismic activity, other qualitative sources such as historical accounts, archaeoseismic remains and paleoseismic evidence must be used. Since the majority of these sources cannot indicate accurately of the size and origin of the earthquakes, the damage descriptions become the most effective information for the characterization of the triggering earthquakes.
The target of the proposed study is to examine the cumulative damage associated with the DST activity during the last 3,500 years and characterize potential temporal and spatial patterns. It is proposed to construct a consistent database of the damage caused by the historical earthquakes, adapt the EMS-98 intensity scale to the typical construction in historical times and accordingly assign intensity values. Once intensities are assigned, it will enable us to examine the spatial and temporal patterns of the earthquakes as well as the damage they caused and characterize the historical seismic activity. Previous studies showed that northern Israel was hit by many earthquakes that were originated from sources in the north, outside of Israel. The results of our work are expected to clarify and even quantify this type of events. It is also suggested to examine the cumulative damage in well-populated ancient cities of the Levant, and evaluate accordingly the potential hazard that threatens them. It is also anticipated that the study will allow to characterize the historical seismology associated with the activity of the DST as a complete seismotectonic unit as well as to assist planners and decision makers in understanding the shape of future earthquakes to come. The results of the study, GIS formatted, will be open to the public, thus increasing the awareness of seismic hazards in Israel.
The research is funded by the Ministry of Energy
Zohar, M., Salamon, A., Rapaport, C., (2023). How Expert Is the Crowd? Insights into Crowd Opinions on the Severity of Earthquake Damage. Data 2023, 8 (6), 108. DOI: https://doi.org/10.3390/data8060108
Zohar M. (2020). Temporal and spatial patterns of seismic activity associated with the Dead Sea Transform (DST) during the past 3000 yr. Seismological Research Letters. DOI: https://doi.org/10.1785/0220190124.
Bellow: Spatial and temporal damage patterns of historical earthquakes occurred in the Levant in the last 3000 years
Using Twitter for near real-time alerts and damage analysis of natural hazards in Israel and its close surrounding
During the last decade, the social network of Twitter has become a robust platform for distributing messages (tweets) among numerous subscribers worldwide. To date, Twitter is used by more than 500 million users worldwide. In Israel the growth of twitter subscribers is by ~100,000 per year since 2014 and to date consists of over 1,000,000 subscribers. The tweets, up to 280 characters only, can be sent via web pages, mobile devices or third-party Twitter applications. During and around the occurrence of natural hazards, people tend to over-tweet and consequently, the number of tweets raise significantly. While Twitter is already in use for near real-time alerts, processes for extracting reported damage from tweets and examining the resulted spatial distribution are still under development. In this study we acquire tweets sent prior to and after natural hazards such as floods, fire and earthquakes that occurred in Israel and its close surroundings and the United states. We temporally and spatially analyze the fetched tweets in order to (1) achieve near real-time alerts; (2) analyze damage patterns and affected regions; (3) validate initial damage estimations and calibrate reference scenarios used for preparing the initial damage estimations and (4) inspect how this data can assist in management of cascading events during the first hours after a catastrophe occurs.
The research is funded by the National Knowledge and Research Center for Emergency Readiness & the Ministry of Science and Technology
Zohar M. (2021). Geolocating tweets in Israel via spatial inspection of information inferred from tweet meta-fields. International Journal of Applied Earth Observation and Geoinformation. DOI: https://doi.org/10.1016/j.jag.2021.102593.
Zohar, M., Gennosar, B., Avny, R., Tessler, N. Gal, A., (2023). Spatiotemporal analysis in high resolution of tweets associated with the November 2016 wildfire in Haifa (Israel). International Journal of Disaster Risk Reduction. DOI: https://doi.org/10.1016/j.ijdrr.2023.103720
Links:
Detecting cascading events during the November 2016 wildfire in Haifa and its close surroundings (link)
Bellow: Spatial and temporal distribution of Tweets in Haifa and environment during the November fire 2016
A new look at urban and human activity in Late Ottoman Palestine: Virtualization of Jerusalem and Haifa using Historical GIS (HGIS) and Machine Learning
With Prof. Ilan Shimshini, department of Information Systems, University of Haifa
Between the 19th and early 20th centuries, significant developments affected Ottoman Palestine. The Napoleon campaign (1799), the Egyptian occupation of Palestine (1831), the Tanzimat reforms, the end of the Crimean war (1856), the opening of the Suez Canal (1869), and Britain’s entry into Egypt (1882), all fostered international interest in the region. Additionally, substantial demographic changes occurred with the arrival of the 1st and 2nd waves of Jewish immigration. Notable changes occurred also in the large settlements such as the expansion outside the Old City of Jerusalem and Haifa as well as increased population and infrastructure establishments. These changes were documented in numerus textual sources but also in visual sources such as maps, drawings and photographs. Although textual sources are being widely used, visual sources are occasionally omitted. The latest technological developments enable an accurate interpretation and examination of these sources. In previous studies, I have used HGIS (Historical GIS) for historical map analysis and past cityscape reconstruction of Tiberias prior to and after the 1837 earthquake. In the proposed study, the recreation of historical scenes will be implemented by incorporating also machine learning capabilities. It is suggested to virtualize chronological cityscape key phases of Jerusalem and Haifa and accordingly examine the urban development, asses the residing population and identify changes in the human activity. The importance of the study is threefold: (1) the establishment of geospatial semi-automatic framework integrating traditional methodologies and technological innovations such as HGIS and machine learning for cityscape reconstructions; (2) adding new theoretical information about late Ottoman Jerusalem and Haifa by using visual sources that were insufficiently exploited so far; and (3) adding innovative methodologies and tools for interpreting and analyzing historical visual sources.
The research is funded by the Israeli Science Foundation
Zohar, M. (2022) A land without (a) people? The GIScience approach to estimating the mid-19th-century population of Ottoman Palestine. Applied Geography 141. DOI: https://doi.org/10.1016/j.apgeog.2022.102672 (map story)
Zohar M., Shimshoni I. (2021). GIScience integrated with computer vision for the examination of old engravings and drawings. International Journal of Geographical Information Science. DOI: https://doi.org10.1080/13658816.2021.1874957
Zohar, M., Shimshoni, I., & Khateb, F. (2020). GIScience Integrated with Computer Vision for the Interpretation and Analysis of Old Paintings. In Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1 (233-239): GISTAM, Prague, Czech Republic. DOI: https://doi.org/10.5220/0009464902330239
Links:
A land without people? population estimation of Late Ottoman Palestine using GIScience approach (link)
Github [Zohar M., Shimshoni I. (2021)]: https://github.com/zoharmot2/GIScience-CV-old-drawings
Zenodo [Zohar M., Shimshoni I. (2021)]: https://zenodo.org/record/7003906#.Yv0fmhxByUk
Bellow: Running a RANSAC algorithm for feature detection upon the drawing of Frederik Henniker (1823)
