This dataset represents the GPS coordinates of where a ground vehicle drove while it actively applying treatment for mosquitoes in 2019.

Asset access statistics for the previous 6 months.

Note:

Within this data, it is possible that a full day's worth of data may be incomplete. This could be for a number of reasons, be it technical, environmental or equipment failure.
Also, this data is raw data, coming straight from the monitoring equipment. It has not undergone the rigour of a Quality Control and/or Quality Assurance process.

Please check this google sheet for contact info and data/device related issues: https://docs.google.com/spreadsheets/d/1e8HHjsiaLf7UMgXOuQ0pRDKPlEBU74Mzl3wysWvfk4w/edit?usp=sharing

This dataset contains bicycle only or bicycle and pedestrian counts that are currently being monitored at a number of locations (see https://data.edmonton.ca/Monitoring-and-Data-Collection/Bike-Counter-Locations-Eco-Counter-/py7x-4d39) along bike lanes in addition to some key cyclist/pedestrian traffic areas.

This map is generated from an extraction from the following publicly accessible feeds:
Lime:
https://data.lime.bike/api/partners/v1/gbfs/edmonton/free_bike_status.json

Bird:
https://mds.bird.co/gbfs/platform-partner/birdcanada/edmonton/free_bike_status.json

For more information on Bike and Electric Scooter Sharing, goto:
https://www.edmonton.ca/transportation/cycling_walking/bike-electric-scooter-sharing

This dataset contains bicycle only or bicycle and pedestrian counts that are currently being monitored at 18 locations along the new bike lanes in addition to some key cyclist/.pedestrian traffic areas.

Note:

Within this data, it is possible that a full day's worth of data may be incomplete. This could be for a number of reasons, be it technical, environmental or equipment failure.
Also, this data is raw data, coming straight from the monitoring equipment. It has not undergone the rigor of a Quality Control and/or Quality Assurance process.

A story explaining how to navigate the Mobile Automated Traffic Enforcement Tickets Issued map and the Intersection Safety Device Tickets Issued map.

Asset access statistics for the previous 6 months.

Speed surveys are done with sensors placed on the roadway directly in the traffic lane(s). These sensors are typically left in place for seven days and provide accurate speed and traffic volume information.

This dataset lists the bicycle only or bicycle and pedestrian counter locations in the city. There are a number of locations along bike lanes in addition to some key cyclist/pedestrian traffic areas.

This dataset contains 2-way bike count data, on the dates indicated and also by the hours indicated. These bike count locations are set up for the City to gather bicycle volume data for analysis purposes.

Note:

These Bike Counts are historic counts at various locations and should in now way be related to the Bike Counts (Eco-Counter) dataset - which is the monitoring locations and updated daily.

This dataset represents the GPS coordinates of where a helicopter flew while it actively applying treatment for mosquitoes in 2020.

This dataset represents the GPS coordinates of where a ground vehicle drove while it actively applying treatment for mosquitoes in 2018.

This dataset represents the GPS coordinates of where a ground vehicle drove while it actively applying treatment for mosquitoes in 2019.

This dataset shows the pesticide treatment activity of the Tree Insects & Other Pests Management Program.

A story board that draws attention to speed data as it relates to playground zones (or 30 km/h zones) or a 50 km/h zone data that occurs just before the 30 km/h zone, at École Frère Antoine Catholic Elementary School.

The data is drawn from the Driver Feedback Sign data and transformed to produce this dataset:

The City has a number of Driver Feedback Signs (DFS) installed around the city. These units collect data as traffic approaches them and in some cases may display a message or a speed that is being detected. Also, these units are radar based and can only track one vehicle at a time (strongest signal).

Due to the number of DFS installations combined with the volume of data collected, each DFS has its own dataset.

Details of how the data is collected by the DFS are as follows:

- Data is accumulated and reported in 15 minute intervals
- Vehicle speeds are captured/reported in speed intervals (bins)
- Speed range/interval for the bins are determined by parameters/settings set for the DFS (Minimum/Maximum Speed Detection Setting)
- Two speed values are recorded for every vehicle - a Highest Speed Detected and a Slowest Speed Detected (explaining why there are two vehicle counts)
- The bins go from Bin 1 to Bin 10. Bin 1 can also be referred to a LO BIN and Bin 10 can also be referred to as HIGH BIN.

Things to note:

DFS devices are not to be used as or confused with traffic counters, as they are not.
DFS devices have a minimum detectable speed of approximately 6 km/hr.
DFS devices have a maximum (theoretical) detectable speed of approximately 225 km/hr.
DFS devices are programmable with different parameters that can also follow a timed schedule.

Data across the various Driver Feedback Sign datasets are then transformed into 5 km speed range columns to help produce this story.

This dataset represents the GPS coordinates of where a helicopter flew while it actively applying treatment for mosquitoes in 2018.

This dataset represents the GPS coordinates and other relevant information for where backpack, vehicle, or helicopter application/treatment took place for mosquitoes during the current calendar year.

This dataset is an extraction from the following publicly accessible feeds:
Lime:
https://data.lime.bike/api/partners/v2/gbfs/edmonton/free_bike_status.json

Bird:
https://mds.bird.co/gbfs/v2/public/edmonton/free_bike_status.json

Neuron: https://mds.neuron-mobility.com/yeg/gbfs/2/en/free_bike_status

For more information on Bike and Electric Scooter Sharing, goto:
https://www.edmonton.ca/transportation/cycling_walking/bike-electric-scooter-sharing

This dataset contains bicycle only or bicycle and pedestrian counts that are currently being monitored at 18 locations along the new bike lanes in addition to some key cyclist/.pedestrian traffic areas.

Note:

Within this data, it is possible that a full day's worth of data may be incomplete. This could be for a number of reasons, be it technical, environmental or equipment failure.
Also, this data is raw data, coming straight from the monitoring equipment. It has not undergone the rigor of a Quality Control and/or Quality Assurance process.

This dataset represents the GPS coordinates and other relevant information of where backpack application/treatment took place for mosquitoes for 2020.

A brief description of how it works:

GPS coordinates are obtained from a cell phone, which is connected to an Arduino. A stretch sensor connected to the Arduino is used to detect where pesticide is sprayed.

Things to consider when working with this dataset:

The setup has been tested for accuracy but it is possible for equipment to report incorrect data. Values may be changed due to correction or re-calibration. Values may also be incorrect due to malfunctioning equipment that went undetected for a period of time.

This dataset represents the GPS coordinates and other relevant information of where backpack application/treatment took place for mosquitoes for 2019.

A brief description of how it works:

GPS coordinates are obtained from a cell phone, which is connected to an Arduino. A stretch sensor connected to the Arduino is used to detect where pesticide is sprayed.

Things to consider when working with this dataset:

The setup has been tested for accuracy but it is possible for equipment to report incorrect data. Values may be changed due to correction or re-calibration. Values may also be incorrect due to malfunctioning equipment that went undetected for a period of time.

To show the treatment activity of the Mosquito Management Program by helicopters and ground vehicles.

This dataset represents the GPS coordinates of where a ground vehicle drove while it actively applying treatment for mosquitoes in 2020.

A story board that draws attention to speed data as it relates to playground zones (or 30 km/h zones) at Minchau School.

The data is drawn from the Driver Feedback Sign data and transformed to produce this dataset:

The City has a number of Driver Feedback Signs (DFS) installed around the city. These units collect data as traffic approaches them and in some cases may display a message or a speed that is being detected. Also, these units are radar based and can only track one vehicle at a time (strongest signal).

Due to the number of DFS installations combined with the volume of data collected, each DFS has its own dataset.

Details of how the data is collected by the DFS are as follows:

- Data is accumulated and reported in 15 minute intervals
- Vehicle speeds are captured/reported in speed intervals (bins)
- Speed range/interval for the bins are determined by parameters/settings set for the DFS (Minimum/Maximum Speed Detection Setting)
- Two speed values are recorded for every vehicle - a Highest Speed Detected and a Slowest Speed Detected (explaining why there are two vehicle counts)
- The bins go from Bin 1 to Bin 10. Bin 1 can also be referred to a LO BIN and Bin 10 can also be referred to as HIGH BIN.

Things to note:

DFS devices are not to be used as or confused with traffic counters, as they are not.
DFS devices have a minimum detectable speed of approximately 6 km/hr.
DFS devices have a maximum (theoretical) detectable speed of approximately 225 km/hr.
DFS devices are programmable with different parameters that can also follow a timed schedule.

Data across the various Driver Feedback Sign datasets are then transformed into 5 km speed range columns to help produce this story.

A story board that draws attention to speed data as it relates to playground zones (or 30 km/h zones) at St. Dominic Catholic Elementary School.

The data is drawn from the Driver Feedback Sign data and transformed to produce this dataset:

The City has a number of Driver Feedback Signs (DFS) installed around the city. These units collect data as traffic approaches them and in some cases may display a message or a speed that is being detected. Also, these units are radar based and can only track one vehicle at a time (strongest signal).

Due to the number of DFS installations combined with the volume of data collected, each DFS has its own dataset.

Details of how the data is collected by the DFS are as follows:

- Data is accumulated and reported in 15 minute intervals
- Vehicle speeds are captured/reported in speed intervals (bins)
- Speed range/interval for the bins are determined by parameters/settings set for the DFS (Minimum/Maximum Speed Detection Setting)
- Two speed values are recorded for every vehicle - a Highest Speed Detected and a Slowest Speed Detected (explaining why there are two vehicle counts)
- The bins go from Bin 1 to Bin 10. Bin 1 can also be referred to a LO BIN and Bin 10 can also be referred to as HIGH BIN.

Things to note:

DFS devices are not to be used as or confused with traffic counters, as they are not.
DFS devices have a minimum detectable speed of approximately 6 km/hr.
DFS devices have a maximum (theoretical) detectable speed of approximately 225 km/hr.
DFS devices are programmable with different parameters that can also follow a timed schedule.

Data across the various Driver Feedback Sign datasets are then transformed into 5 km speed range columns to help produce this story.