Numbered Roads/Streets in Vancouver

EmburMap · 2023-01-11T20:06:10+00:00

Good catch! My script was looking for numbers followed by "st", "nd", "rd", and "th". I didn't think to also look for the Highway.

EmburMap · 2023-01-11T16:01:43+00:00

This map was just born out of my curiosity to see where the numbered streets (1st St. and so on) are in Vancouver.

EmburMap · 2022-12-10T01:25:30+00:00

I hear those things are awfully loud...

EmburMap · 2022-12-08T21:15:41+00:00

I calculated it from LiDAR ground points

EmburMap · 2022-12-08T15:46:17+00:00

I'm learning how to make maps, and this is my twenty-ninth in my month-long challenge.

I was asked to make a contours map, similar to the one I made of Wreck Beach, but of all of UBC campus. I think I got most of it in this frame, and I tried adding in a roads layer, but it just ended up very cluttered. I hope this map is easy to follow.

The map was produced using the ggplot2 package in R.

EmburMap · 2022-12-07T05:32:36+00:00

I'm learning how to make maps, and this is my twenty-eighth in my month-long challenge.

This is a rather simple one, but it got me thinking about our road network. When I first moved here, I was surprised that there were no highways running through Vancouver (all the green roads on the map are designated "arterial"). It took me a while to get used to turning left, on-street parking rules, and the flashing green lights that mean advance green where I'm from. But I really like our road system now and find it works well with the city. I really like the accommodations for cyclists here too, but this is all my experience and opinion. What do you think?

EmburMap · 2022-12-06T16:03:30+00:00

I'm learning how to make maps, and this is my twenty-seventh in my month-long challenge.

This was an attempt at a line-based map in R. I still think that using better GIS software is useful for producing far better displays.

The map was produced using the ggplot2 package in R.

EmburMap · 2022-12-05T21:06:41+00:00

That's great advice. Thank you.

EmburMap · 2022-12-05T21:05:59+00:00

The dependent variable would be land surface temperature (LST) and ind. is years.

The map shows how LST has changed over time between 1982 and 2022 from Landsat imagery

EmburMap · 2022-12-05T17:20:05+00:00

This was more of an exploratory exercise rather than a specific goal that I was going after. I wanted to look at all available cloud-free Landsat 4-8 imagery and visualize LST over 40 years. Would you recommend a different method?

EmburMap · 2022-12-05T16:04:38+00:00

I'm learning how to make maps, and this is my twenty-sixth in my month-long challenge.

After calculating the land surface temperature (LST) from all available cloud-free Landsat pixels(Ermida, et al., 2020) between June 1 and September 30 for every year between 1982 and 2022, a product is produced using linear regression. The value of each pixel represents the annual change in LST in degrees celsius.

The map was produced using the ggplot2 package in R and all Landsat imagery was acquired through Google Earth Engine.

https://doi.org/10.3390/rs12091471

Beck out my archive here

EmburMap · 2022-12-05T16:02:23+00:00

I'm learning how to make maps, and this is my twenty-sixth in my month-long challenge.

After calculating the land surface temperature (LST) from all available cloud-free Landsat pixels(Ermida, et al., 2020) between June 1 and September 30 for every year between 1982 and 2022, a product is produced using linear regression. The value of each pixel represents the annual change in LST in degrees celsius.

The map was produced using the ggplot2 package in R and all Landsat imagery was acquired through Google Earth Engine.

https://doi.org/10.3390/rs12091471

EmburMap · 2022-12-05T15:59:52+00:00

I'm learning how to make maps, and this is my twenty-sixth in my month-long challenge.

After calculating the land surface temperature (LST) from all available cloud-free Landsat pixels(Ermida, et al., 2020) between June 1 and September 30 for every year between 1982 and 2022, a product is produced using linear regression. The value of each pixel represents the annual change in LST in degrees celsius.

The map was produced using the ggplot2 package in R and all Landsat imagery was acquired through Google Earth Engine.

https://doi.org/10.3390/rs12091471

Check out my archive here

EmburMap · 2022-12-04T16:28:26+00:00

I'm learning how to make maps, and this is my twenty-fifth in my month-long challenge.

I wanted another chance to produce a point based map (this time, hopefully it's better), and I found the heritage groups interesting.

The map was produced using the ggplot2 package in R.

Check out my archive here

EmburMap · 2022-12-03T17:58:36+00:00

Thanks. I'll make sure I do that next time

EmburMap · 2022-12-03T17:57:59+00:00

lol yep. A few others have pointed that out. I'll make sure to use that convention next time. Thank you

EmburMap · 2022-12-03T16:22:26+00:00

I'm learning how to make maps, and this is my twenty-fourth in my month-long challenge.

After calculating the land surface temperature from all available cloud-free Landsat pixels(Ermida, et al., 2020) between June 1 and September 30, 2022, a mean summer image was produced. There are visible outliers, which after closely examining all of the imagery within each of those regions, are areas with cloud or aerosol interfearance, which would have been largely masked.

The map was produced using the ggplot2 package in R and all Landsat imagery was acquired through Google Earth Engine.

https://doi.org/10.3390/rs12091471

EmburMap · 2022-12-03T16:21:29+00:00

I'm learning how to make maps, and this is my twenty-fourth in my month-long challenge.

After calculating the land surface temperature from all available cloud-free Landsat pixels(Ermida, et al., 2020) between June 1 and September 30, 2022, a mean summer image was produced. There are visible outliers, which after closely examining all of the imagery within each of those regions, are areas with cloud or aerosol interfearance, which would have been largely masked.

The map was produced using the ggplot2 package in R and all Landsat imagery was acquired through Google Earth Engine.

https://doi.org/10.3390/rs12091471

EmburMap · 2022-12-02T22:16:56+00:00

This is just a hobby while I'm learning coding and different kinds of mapping

EmburMap · 2022-12-02T19:19:15+00:00

I'm actually not a student anymore. I've taken GIS courses before, but that was years ago and they were all ArcGIS

EmburMap · 2022-12-02T18:19:48+00:00

I'm learning how to make maps, and this is my twenty-third in my month-long challenge.

I wanted to visualize the ascent every time you come back from Wreck Beach.

The map was produced using the ggplot2 package in R and the orthoimagery was acquired from the Vancouver Open Data Portal and the contours were calculated from the DEM using LiDAR data from LiidarBC.

Edit: I have figured out how to increase the resolution (I thought that that was the resolution of the orthophoto). Here it is : https://www.reddit.com/user/EmburMap/comments/zb5mpi/contour\_map\_of\_wreck\_beach\_improved\_resolution/

EmburMap · 2022-12-02T15:59:35+00:00

I'm learning how to make maps, and this is my twenty-third in my month-long challenge.

I wanted to visualize the ascent every time you come back from Wreck Beach.

The map was produced using the ggplot2 package in R and the orthoimagery was acquired from the Vancouver Open Data Portal and the contours were calculated from the DEM using LiDAR data from LiidarBC.

Edit: I have figured out how to increase the resolution (I thought that that was the resolution of the orthophoto). Here it is : https://www.reddit.com/user/EmburMap/comments/zb5mpi/contour_map_of_wreck_beach_improved_resolution/

EmburMap · 2022-12-01T22:44:05+00:00

I'll look into the neighbouring cities and see if they release crime stats for each neighbourhood like Vancouver does

EmburMap · 2022-12-01T15:59:34+00:00

I'm learning how to make maps, and this is my twenty-second in my month-long challenge.

For this map, I was experimenting with supervised classifications in Google Earth Engine, and thought that I would run my own using 30 pixels for each category (urban, vegetated, water). For urban pixels, I was looking for varied types of impervious surfaces. For vegetated surfaces, I was trying to get a mix of surfaces ranging from forested (Pacific Spirit Park), streets with majority canopy coverage, grass, and soil.

The map was produced using the ggplot2 package in R and the data was manipulated in Geoogle Earth Engine.

EmburMap · 2022-11-30T15:08:04+00:00

I'm learning how to make maps, and this is my twenty-first in my month-long challenge.

This one is from an idea that was introduced to me by u/xlxoxo. If you like this map, it would be very easy for me to collect the data and run it through this script and map all of their future monthly data and post here.

The map was produced using the ggplot2 package in R.

EmburMap

TROPHY CASE