Global Impacts of Earthquakes and Natural Disasters

Geovis Project Assignment @RyersonGeo, SA8905, Fall 2018

Author: Katrina Mavrou

Date: Tuesday November 13th 2018

Topic: Global Impacts of Earthquakes and Natural Disasters

Link: Natural Disasters: Earthquake


To educate an audience with a wide variety of educational backgrounds on natural disaster impacts and side effects through visualization of spatial data using Esri’s Story Map Applications. As well, to gain a personal understanding  and experience using ArcGIS online and available tools.

Data Source: USGS Earthquake Database, 2018; Global International Displacement Database, 2018.

Software: ArcGIS Pro, ArcGIS Online


The topic of this project is Natural Disaster impacts, in specific Earthquakes, and analyzes the global displacement and infrastructure loss. The platform used is ArcGIS Online, using hosted feature layers, web maps and mapping applications, such as a variety of Esri’s story map applications. The data is provided from USGS Earthquake database and Global International Displacement Database. The purpose of this exercise is to utilize multiple Esri story map functions, and other online plat forms into one map.

The first step was to clean up the datasets. The CSV files were imported into Microsoft SQL Server Management Studio to preform spatial queries and extract data needed from each dataset for the displacement dataset data was extracted by year and imported into a new table. The subset data was imported into ArcGIS Pro, where is was joined to the global shapefile and exported as new layers. Each year created a new layer so that the animation tool could be used on the time enabled field to create a time lapse of displacement. Each new layer was exported as a shapefile zipped folder so that it could be imported into ArcGIS Online as a hosted feature layer.

The first section, monthly earthquake report, of the story map is created by using a live link to publish data. To do this a web map is created using the live updating CSV from USGS. The data is collected and published every 5 minutes, therefore each time the story map is opened or refreshed the map will look different from the previous time. The data is displayed using the magnitude and depth of the earthquake (Image 1). This process was repeated for the second section, the weekly earthquake report. Another feature that was used for this map is pop-ups. Each instance displayed on the map when clicked will introduce a pop-up window that gives the user more information on that specific earth quake.

Live data of Monthly Earthquakes

Image 1: Live data of Monthly Earthquakes

The next section introduces the user to fault lines, specifically San Andreas Fault located in California, USA (Image 2). Using KML and KMZ files LiDAR layers of the fault lines are displayed on a satellite image map. Data of the most tragic earthquakes are also displayed on the map. This is historic data of earthquakes with magnitude greater than 5. By clicking on each earthquake location a pop-up is enabled and gives historical facts about each instance.

San Andreas Fault and Earthquakes

Image 2: San Andreas Fault and Earthquakes

The following section of the story map regards displacement caused by earthquakes. The main screen includes a heat map of displaced people from 1980-2018. The side panel includes a story map slide show. This was created from a simple web map with time enabled layers. The presentation function was then used to create a time lapse of global displacement for each year from 2010 to 2017 (Image 3). The presentation was then embedded into the side panel of the displacement section of the story map.

Presentation of Timelapse

Image 3: Presentation timelapse

The slide displacement VS population includes a swipe and slide story map embedded into the main story map. This is a global map that swipes two layers global displacement due to natural disasters for 2017 and world population for 2017 (Image 4). The swipe and slide map allows the user to easily compare the two layers side-by-side.

Swipe and Slide Map

Image 4: Swipe and Slide Map

The last section uses a story map shortlist to display images of earthquake impacts. This uses geocoded images to place images on a map (Image 5). The main panel holds with map with pointers indicating the coordinates of the geocoded images. The side panel displays the images. When an image is clicked on it pops up with the map and information regarding the image and earthquake can be found.

Geocoded image and reference map

Image 5: Geocoded image and reference map

The purpose of this technology is to easily display spatial data for individuals who are unfamiliar with utilizing other Esri products. Story maps are an easy and interactive way for users will all backgrounds of knowledge to interact with spatial maps and learn new information on a topic.

Limitations and Summary:

The final project is a story map journal with easy navigation and educational purpose. In the future I would like to incorporate even more of Esri’s online functions and applications, to expand my understanding. As well, a limitation to the project is the amount of space allotted to each student at Ryerson with ArcGIS online. Some processing functions were unavailable or used too much space, therefore these procedures had to be processed using ArcPro and then import the final product into ArcGIS online. Overall, the project reached its purpose of providing contextual information on spatial impacts of earthquakes.

Urban Development of San Francisco

By Hannah Burdett

SA8905 Geovisualization Project, Ryerson University

The Development of San Francisco

San Francisco is located in the center of Northern California. It started as a base for the gold rush of 1849, the city quickly became one of the most populated cities in the United States. Shortly thereafter, San Francisco was devastated by the 1906 earthquake. Development peaked in the 1900’s as San Francisco rebuilt areas demolished by the earthquake and fires to compensate the growing population. During the 1930’s the San Francisco-Oakland Bay Bridge and the Golden Gate Bridge were opened. Additionally, during World War II, San Francisco was a major mainland supply point and port of embarkation for the war in the Pacific. Both factors led to another peak in construction. After World War II, many American military personnel who had fallen in love with the city while leaving for or returning from the Pacific settled in the city. This led to promoting the development of the Sunset District, Visitacion Valley, and the total build-out of San Francisco. Starting in the latter half of the 1960’s, San Francisco became most recognized for the hippie movement. Currently, San Francisco has become known for finance and technology industries. There is a high demand for housing, driven by its close proximity to Silicon Valley, and a low supply of available housing has led to the city being one of America’s most expensive places to live.


The data used for the time series animation was imported from is a repository for the US Governments open source data. The imported data included a Land use Shapefile for San Francisco. The shapefile included information such as land use, shape area, street address, street number, etc. The land use shapefile also included the year the building was built. The building years range from 1848 to 2016 displaying 153 years of urbanization. The buildings were represented as polygons throughout San Francisco. Additionally, a grey scale base map from ArcGIS Pro was displayed to create a more cohesive map design.



Time Series Animation

To develop the reconstruction of San Francisco throughout the years, both QGIS and ArcGIS Pro were utilized. Both platforms were used so to provide a comparison between time series animation tools from an open source application and a non-open source application.

QGIS is an open source geographic information systems application that provides data visualization, editing, and analysis through functions and plugins. To create the time series animation the Time Manager plugin was utilized. The Time Manager plugin animates vector features based on a time attribute. For this study the time attribute was the years built.

ArcGIS Pro is the latest professional desktop GIS from Esri. ArcGIS Pro enables users to view, explore, analyze, edit and share maps and data. Unlike QGIS, no additional plugins are required to create the animated time series.

QGIS Methodology

To generate the time series in QGIS, the land use shapefile was downloaded and opened in QGIS. The attribute table from the land use shapefile was then exported and opened in Excel so that the yrbuilt column could be reformatted to meet QGIS Time Manager requirements. The yrbuilt column had the data presented as YYYY format for building dates. QGIS Time Manager requires timestamps to be in YYYY-MM-DD. To correct the format, -01-01 was added to the end of each building year. The modified values were then saved into a new column called yrbuilt1. The Excel sheet was then imported into QGIS and joined to the land use shapefile.

In QGIS, each of the buildings was presented as polygons. The shapefile symbology was changed from single symbology to quantified symbology. In other words, the symbology for each of the polygons was broken down to seven classes defined by years. Each class was then distinguished by color, so that one may differentiate the oldest building from the newest buildings. Furthermore, a grey scale basemap was added to create a more cohesive map.

Furthermore, in the Time Manager settings, “Add Layer” was selected. The land use shapefile was chosen as the Layer of interest. The start time was set to the yrbuilt1 attribute, whereas the end time was set to “No end time – accumulate features”. This allows newer buildings to be added without older buildings being removed from the map. For the animation, each time frame will be shown for 100 milliseconds. The Time Manager plugin was then turned on so that the time series may run.


In order to export the time series animation, Time Manager offers an “Export Video” option. However, this exports the animation as an image series, not as an actual video. To correct this, the image series was uploaded to Mapbox where additional Mapbox styles were used to render the map. It was then exported as a Gif from Mapbox.

ArcGIS Pro Methodology

In ArcGIS Pro, the land use shapefile was imported. The symbology for each of the polygons was then broken down to seven classes defined by years. The same colours utilized in QGIS were applied to the classes in ArcGIS Pro to differentiate between the building years. Within the layer’s properties, the Layers Time was selected as “each feature has a single time field”. Furthermore, the start and end times were set to the newest and oldest building years. The number of steps were assigned a value of sixteen. In View, the animation was added, and the Time Slider Steps were imported. The time frames were set to match the QGIS animation so that both time series animations would run at the same speed. The time series animation was then exported as a Gif.

Final Animated Map

Finally, to create a cohesive animated map the exported Gif’s were complied together in PowerPoint. Additional map features, such as a legend, were designed within PowerPoint. A bar graph was added along the bottom of the map to show years of peak building construction. The final time series map was then exported as a .mp4 and upload to YouTube.