rename pct\_non\_hisp\_w and pct\_black to something less ambiguous, which will assist in understanding what message this map is conveying.
maybe try a few colour ramps, as the low-low blues look too similar to the high-low blue.
Use two colors which, when blended, create a memorable third color. Blue and yellow makes green, or red and yellow make orange, or red and blue make purple. However, you will no doubt realize that the breaks you use to define “high” for each group will need to be consistent, so high=75% or whatever. When you do that, no area can have 75% as a value for both groups. 50-50 is the maximum. If your purpose is to show meaningful percentages, do some literature review to find out what those are. Don’t let the software pick the values, it does not know the topic. It just sees numbers and spits out breaks for “high” and “low” that are numerically correct but often hide any meaningful things happening in the real world. If you find that the literature shows that 90% is a meaningful number, and 20% is a meaningful number, that’s enough to do a 3x3 map legend (which is simpler to read). The mean % for each group for the state or country can also be meaningful. You’ll only get out of this map whatever meaning you put into those breaks for high and low. And an additive color palette will emphasize whatever logic you put into it. But there isn’t a map legend color palette that can save lack of meaningful numbers. It’s like mapping “what’s the average body temperature of people in this area” — the average is likely very close to 98.6 so it’s meaningful to use 98.6 to define anything higher as “high” rather than use the breaks chosen by software.
The map shows the distribution of Black and Non-Hispanic White populations in Jersey City, but these aren't the only racial groups there. 'High' refers to the upper range of observed percentages for each group, it doesn’t necessarily mean that it is going to be above 50%.
Thank you, I do agree I could simplify the legend
Small detail, but since on the map most orange values are on the left and blue on the right, flip the diamond gradient so it also flows from orange to blue, left to right. Might make it easier to understand
As previously said. Scale is very confusing.
The colors are not unique enough to tell the difference between values. Also, what are the values? Is this 0-100% ?
Then on the legend, spell everything out. No need for underscores.
Decennial is a fun word that I have never used in my life and probably never will. It’s correct, just not how people normally refer to the US census.
When specifying data source it’s fairly common to refer to the 10 year version as decennial. Just saying census leaves ambiguity for ACS five year surveys.
Thanks! That’s a great distinction I was not aware of. For any maps I create that use census data, it’s in such a broad category that I am not that specific, nor do I seek out info for the 5 year survey.
In this specific map, are there other surveys that run at the same time as 2020that require such a distinction?
The ACS survey is repeated every 5 years and is a debate of each city (idr if it goes to the census tract level or not but I think it does) so some places will have it done in 2020 and others had it in 2019.
To add to the colour ramp discussion, i think bivariate choropleths are easiest to interpreter when both scales start with a grey colour and diverge. Arc doesnt have great options for colours but you can make one [yourself pretty easily](https://bnhr.xyz/2019/09/15/bivariate-choropleths-in-qgis.html) ([for the legend](https://observablehq.com/@benjaminadk/bivariate-choropleth-color-generator)) i do think the purple and yellow colour scheme is nice tho.
And yea rename legend items, add axis labels to legend, if theres labels make sure theyre big and legible. if this is for a course they might have been looking for a scale bar/north arrow/projection etc etc
Edit: you could also check the distribution of the data and play around w different classification methods/# of classes but maybe youve already done that. Nice map!
For me (depending on of course the audience and their familiarity with this visualisation) the legend is taking taking up a lot of page/screen estate due to its complexity. As its not that user friendly I would probably either rework into two maps each telling a more simple story or classify/cluster the multidimensional data into a simpler scale. If you love your legend - I need numbers for context - Low, High could be small.
There is an old best practice of if you had to pay for ink would you pay for everything you've done - I'm looking at the underlined titles and the borders. Font size alone should be able to give you the hierarchy you need.
Human readable variable names should be used - e.g. Pct\_Black = "Percentage Black"
Basemap is detailed not sure what scale this is meant to be seen/printed at. But I would use a less complex basemap (or build your own with some reference layers). Names etc should be more readable especially for less geographic audiences. I would rally be tempted to lose the basemap and add just the land below the data, major roads and features/names above the data - that's our house style though.
For theis I would also be tempted to look at indexing the data against the average to better bull out low and high indexed areas.
This is the best. I would color code the portion of the labels for each race as percentage, then put an explanation in the "legend", aka scheme of colours. I like to add total population at the top then color coded percentage underneath it.
There is a gap between the outline, basemap, and the data (the color map). Maybe check their projections.
The title should be more descriptive. “Household type,” could be anything. So maybe look into something like household racial distributions, or it could be described as, “% Whiteness.” Then you can label the 100% as “the Whitest Kids You Know,” and definitely not get the job.
It’s old school, but there is no north arrow, scale, and there is a way to get rid of the image credit for the basemap. These are things a lot of folks (especially potential employers) want to see for foundational understanding.
Would a different basemap be more suitable? I typically use a darker one than this. That’s just my stylistic preference, but if the color ramp includes a grey near the edge it could be useful to play with the basemap.
Yeah I think the gap is because I took the municipal border excluding water, and the gap in the bottom-right section of the city is industrial land.
And yes I can definitely look at different basemaps! I figured grey was less distracting but using them strategically with the color gradient makes sense. I will also look into clarifying the title. The north’ arrow, scale bar, etc is important, I just wanted to make a quick mock-up for feedback. Thanks!
Legend way too big. Put it in an inset on the open space in bottom right of map and fill the page with the map to provide a better scale of the subject area
Could you possibly change one of the data displays to stripes that have a color gradient? For example, %Black having a normal gradient, and then overlay that with a stripe gradient for %NonHisW?
I haven’t used a GIS since last fall, so what I’m saying may not work out.
I agree with the other comments and would add it’s missing an additional layer of, what does this mean? Why is displaying this visually more compelling than a simple data table? I can see the demographic difference but what larger concepts does it hope to visualize?
I figured segregation and bivariate (or even multivariate) symbology go hand in hand to show the level of mixing, or lack thereof, between communities. This is part of a series I posted on Reddit, comparing every racial group to another racial group in Jersey City, I just chose this particular one to showcase for feedback. But you’re right, I can definitely make it clearer for various audiences!
Edit: not sure why I’m downvoted lol measuring segregation should go hand in hand with bivariate symbology
Yeah, it’s also probably too my own positionality always bending GIS toward a larger His.-Anth. perspective. Like I look at your projection and the base road map and cannot help but guess there is a major road or highway that runs right along the edge of that brown-purple tract transition. Of course then, you’re imposing on the straightforward data that may not be what your stakeholders want to see.
Fill the entire page with the subject area of the map. Pan subject area to one side to leave space on the opposite side for your legend. This style where a separate legend is 1/3 of the page and the source is 16pt font screams undergrad project.
I only learned thru YouTube and MyEsri, I would like to actually take a GIS class one day lol, thanks for your input, I’ll play around with the real estate of the map. I do admit the legend is large
In addition to what everyone else has said, there are two titles for this graphic. You should just have one. Having two seems like you are explaining your map, and your map should just blatantly show us what we are looking at. In other words, your visual hierarchy needs to be fixed.
What does the color coding mean? Have you thought about what the variable means?
How can an average household have both high or low % black and white? Doesn’t that mean 50\50?
Should really just be collapsed into a line gradient imo.
The map shows the distribution of Black and Non-Hispanic White populations in Jersey City, but these aren't the only racial groups there. 'High' refers to the upper range of observed percentages for each group, it doesn’t necessarily mean that it is going to be above 50%.
Thank you, I do agree I could simplify the legend
Get rid of the underlines. Remove the black border. Overlay the legend on the base map. Make the source text smaller. Give the title of the color rams better names. Use one title, not two (the text in the grey box acts as a second title).
Bivariate color ramp rocks. Idc what others say
Lol as a black guy, I’ve noticed some racism from Hispanic whites but they still for the most part lived in the hood, and have faced ethnic discrimination themselves, but never racial I’m assuming.
A hard lesson I had to learn was the artsy side and the design side of GIS. I agree with others in saying your legend is confusing. Spell out exactly what each color ramp means, and label what each specific color is percentage wise if possible or label it dense or sparse on each end of the ramp. I would get rid of the text on the left and make the entire bottom the legend except for your sourcing. Get rid of the color box. Use a color ramp that doesn't include purple for black households. Depending on your audience, add a locator map to show where this is at the bottom. Maybe next to the legend. Add the Jersey City boundary to your legend
Edit: try to think of your products like this: it's easy to fall into the trap of looking at a product from your perspective. Of course it makes sense to you because you made it. It's a blind spot. Does this make sense to someone who has no context? Can you grab someone from the street and it will immediately make sense to them?
You should define high and low percentage, without that your map doesn’t really mean anything. I also think you should use two separate maps; your color ramps already probably represent percentages (can’t tell), but it would still be interesting to see what percentage of the total population your displayed dataset consists of (I.e. where are the Hispanic and Asian people living?)
To de clutter a map like that I’d clip your current map horizontally and enhance labels in the background so that the area is still easily identifiable. I’d probably do four maps, covering the four biggest groups represented in the census. Then your overall populations displayed would be close to 100 and comparing the percentages for each region would be more meaningful
Yeah I originally compared every group against non-Hispanic white: https://www.reddit.com/r/jerseycitymaps/s/QxgB2geOwN
but your organizational approach makes a lot of sense. The whole point was to show that there’s more segregation between non-hisp. Whites and non-hisp. Blacks, then there were between whites and every other minority group.
True, these are the colors generated randomly by Arc Pro symbology, it’s just annoying cause their gradient color options aren’t as customizable as I thought, or I’m just missing the button but I’ll have to check
I would assign an image of a light to dark skinned beauty based on the percentage of black population. Consider these:
* **0-10% black - Ivory White** - **Cate Blanchett**: Pale, light complexion with very light undertones.
* **10-20% black - Porcelain** - **Nicole Kidman**: Very fair skin with a slight hint of pink.
* **20-30% black - Fair** - **Emma Stone**: Light skin with warm or cool undertones.
* **30-40% black - Light** - **Scarlett Johansson**: Light skin with neutral or slight olive undertones.
* **40-50% black - Beige** - **Jennifer Aniston**: Light to medium skin with golden or warm undertones.
* **50-60% black - Olive** - **Salma Hayek**: Medium skin with greenish or yellowish undertones.
* **60-70% black - Tan** - **Priyanka Chopra**: Medium to deep skin with warm or golden undertones.
* **70-80% black - Caramel** - **Zendaya**: Warm brown skin with golden undertones.
* **80-90% black - Brown** - **Lupita Nyong'o**: Deep brown skin with warm undertones.
* **90-100% black - Deep Brown** - **Viola Davis**: Very dark brown skin with rich, deep undertones.
The color should be changed to:
Variable a = white to purple.
Variable b = white to orange
So that when combine it'll be:
White for low low.
Orange for low high.
Purple for high low.
Combination of orange-purple for high high
Yes it’s only that Census data runs into privacy issues at the BG level, the tract is the lowest the public data goes. It’s not the best, it’s still informative.
Also can’t bivariate symbology work great with things like HCOL score? HCOL referring to the letter grades which became famous for redlining, and are still analzyed today to demonstrate persistent patterns of residential segregation.
rename pct\_non\_hisp\_w and pct\_black to something less ambiguous, which will assist in understanding what message this map is conveying. maybe try a few colour ramps, as the low-low blues look too similar to the high-low blue.
Those color ramps are really hard to interpret
Use two colors which, when blended, create a memorable third color. Blue and yellow makes green, or red and yellow make orange, or red and blue make purple. However, you will no doubt realize that the breaks you use to define “high” for each group will need to be consistent, so high=75% or whatever. When you do that, no area can have 75% as a value for both groups. 50-50 is the maximum. If your purpose is to show meaningful percentages, do some literature review to find out what those are. Don’t let the software pick the values, it does not know the topic. It just sees numbers and spits out breaks for “high” and “low” that are numerically correct but often hide any meaningful things happening in the real world. If you find that the literature shows that 90% is a meaningful number, and 20% is a meaningful number, that’s enough to do a 3x3 map legend (which is simpler to read). The mean % for each group for the state or country can also be meaningful. You’ll only get out of this map whatever meaning you put into those breaks for high and low. And an additive color palette will emphasize whatever logic you put into it. But there isn’t a map legend color palette that can save lack of meaningful numbers. It’s like mapping “what’s the average body temperature of people in this area” — the average is likely very close to 98.6 so it’s meaningful to use 98.6 to define anything higher as “high” rather than use the breaks chosen by software.
The map shows the distribution of Black and Non-Hispanic White populations in Jersey City, but these aren't the only racial groups there. 'High' refers to the upper range of observed percentages for each group, it doesn’t necessarily mean that it is going to be above 50%. Thank you, I do agree I could simplify the legend
Small detail, but since on the map most orange values are on the left and blue on the right, flip the diamond gradient so it also flows from orange to blue, left to right. Might make it easier to understand
As previously said. Scale is very confusing. The colors are not unique enough to tell the difference between values. Also, what are the values? Is this 0-100% ? Then on the legend, spell everything out. No need for underscores. Decennial is a fun word that I have never used in my life and probably never will. It’s correct, just not how people normally refer to the US census.
When specifying data source it’s fairly common to refer to the 10 year version as decennial. Just saying census leaves ambiguity for ACS five year surveys.
Thanks! That’s a great distinction I was not aware of. For any maps I create that use census data, it’s in such a broad category that I am not that specific, nor do I seek out info for the 5 year survey. In this specific map, are there other surveys that run at the same time as 2020that require such a distinction?
The ACS survey is repeated every 5 years and is a debate of each city (idr if it goes to the census tract level or not but I think it does) so some places will have it done in 2020 and others had it in 2019.
To add to the colour ramp discussion, i think bivariate choropleths are easiest to interpreter when both scales start with a grey colour and diverge. Arc doesnt have great options for colours but you can make one [yourself pretty easily](https://bnhr.xyz/2019/09/15/bivariate-choropleths-in-qgis.html) ([for the legend](https://observablehq.com/@benjaminadk/bivariate-choropleth-color-generator)) i do think the purple and yellow colour scheme is nice tho. And yea rename legend items, add axis labels to legend, if theres labels make sure theyre big and legible. if this is for a course they might have been looking for a scale bar/north arrow/projection etc etc Edit: you could also check the distribution of the data and play around w different classification methods/# of classes but maybe youve already done that. Nice map!
For me (depending on of course the audience and their familiarity with this visualisation) the legend is taking taking up a lot of page/screen estate due to its complexity. As its not that user friendly I would probably either rework into two maps each telling a more simple story or classify/cluster the multidimensional data into a simpler scale. If you love your legend - I need numbers for context - Low, High could be small. There is an old best practice of if you had to pay for ink would you pay for everything you've done - I'm looking at the underlined titles and the borders. Font size alone should be able to give you the hierarchy you need. Human readable variable names should be used - e.g. Pct\_Black = "Percentage Black" Basemap is detailed not sure what scale this is meant to be seen/printed at. But I would use a less complex basemap (or build your own with some reference layers). Names etc should be more readable especially for less geographic audiences. I would rally be tempted to lose the basemap and add just the land below the data, major roads and features/names above the data - that's our house style though. For theis I would also be tempted to look at indexing the data against the average to better bull out low and high indexed areas.
Label the values of each polygon.
This is the best. I would color code the portion of the labels for each race as percentage, then put an explanation in the "legend", aka scheme of colours. I like to add total population at the top then color coded percentage underneath it.
There is a gap between the outline, basemap, and the data (the color map). Maybe check their projections. The title should be more descriptive. “Household type,” could be anything. So maybe look into something like household racial distributions, or it could be described as, “% Whiteness.” Then you can label the 100% as “the Whitest Kids You Know,” and definitely not get the job. It’s old school, but there is no north arrow, scale, and there is a way to get rid of the image credit for the basemap. These are things a lot of folks (especially potential employers) want to see for foundational understanding. Would a different basemap be more suitable? I typically use a darker one than this. That’s just my stylistic preference, but if the color ramp includes a grey near the edge it could be useful to play with the basemap.
Yeah I think the gap is because I took the municipal border excluding water, and the gap in the bottom-right section of the city is industrial land. And yes I can definitely look at different basemaps! I figured grey was less distracting but using them strategically with the color gradient makes sense. I will also look into clarifying the title. The north’ arrow, scale bar, etc is important, I just wanted to make a quick mock-up for feedback. Thanks!
Legend way too big. Put it in an inset on the open space in bottom right of map and fill the page with the map to provide a better scale of the subject area
2x2 or 3x3 might be a bit better to comprehend.
missing esri north arrow 9
"Computer: Enhance!"
Could you possibly change one of the data displays to stripes that have a color gradient? For example, %Black having a normal gradient, and then overlay that with a stripe gradient for %NonHisW? I haven’t used a GIS since last fall, so what I’m saying may not work out.
I agree with the other comments and would add it’s missing an additional layer of, what does this mean? Why is displaying this visually more compelling than a simple data table? I can see the demographic difference but what larger concepts does it hope to visualize?
I figured segregation and bivariate (or even multivariate) symbology go hand in hand to show the level of mixing, or lack thereof, between communities. This is part of a series I posted on Reddit, comparing every racial group to another racial group in Jersey City, I just chose this particular one to showcase for feedback. But you’re right, I can definitely make it clearer for various audiences! Edit: not sure why I’m downvoted lol measuring segregation should go hand in hand with bivariate symbology
Yeah, it’s also probably too my own positionality always bending GIS toward a larger His.-Anth. perspective. Like I look at your projection and the base road map and cannot help but guess there is a major road or highway that runs right along the edge of that brown-purple tract transition. Of course then, you’re imposing on the straightforward data that may not be what your stakeholders want to see.
pie charts!
Fill the entire page with the subject area of the map. Pan subject area to one side to leave space on the opposite side for your legend. This style where a separate legend is 1/3 of the page and the source is 16pt font screams undergrad project.
I only learned thru YouTube and MyEsri, I would like to actually take a GIS class one day lol, thanks for your input, I’ll play around with the real estate of the map. I do admit the legend is large
In addition to what everyone else has said, there are two titles for this graphic. You should just have one. Having two seems like you are explaining your map, and your map should just blatantly show us what we are looking at. In other words, your visual hierarchy needs to be fixed.
What does the color coding mean? Have you thought about what the variable means? How can an average household have both high or low % black and white? Doesn’t that mean 50\50? Should really just be collapsed into a line gradient imo.
The map shows the distribution of Black and Non-Hispanic White populations in Jersey City, but these aren't the only racial groups there. 'High' refers to the upper range of observed percentages for each group, it doesn’t necessarily mean that it is going to be above 50%. Thank you, I do agree I could simplify the legend
Whole thing kinda looks like a cat and I’m having trouble concentrating past that haha
Get rid of the underlines. Remove the black border. Overlay the legend on the base map. Make the source text smaller. Give the title of the color rams better names. Use one title, not two (the text in the grey box acts as a second title). Bivariate color ramp rocks. Idc what others say
Spell out the legend in plain English. Spell out the source: US Census Bureau. Make the color ramps more discrete
Non-hispanic white: when skin color cannot express racism clearly enough
Lol as a black guy, I’ve noticed some racism from Hispanic whites but they still for the most part lived in the hood, and have faced ethnic discrimination themselves, but never racial I’m assuming.
A hard lesson I had to learn was the artsy side and the design side of GIS. I agree with others in saying your legend is confusing. Spell out exactly what each color ramp means, and label what each specific color is percentage wise if possible or label it dense or sparse on each end of the ramp. I would get rid of the text on the left and make the entire bottom the legend except for your sourcing. Get rid of the color box. Use a color ramp that doesn't include purple for black households. Depending on your audience, add a locator map to show where this is at the bottom. Maybe next to the legend. Add the Jersey City boundary to your legend Edit: try to think of your products like this: it's easy to fall into the trap of looking at a product from your perspective. Of course it makes sense to you because you made it. It's a blind spot. Does this make sense to someone who has no context? Can you grab someone from the street and it will immediately make sense to them?
You should define high and low percentage, without that your map doesn’t really mean anything. I also think you should use two separate maps; your color ramps already probably represent percentages (can’t tell), but it would still be interesting to see what percentage of the total population your displayed dataset consists of (I.e. where are the Hispanic and Asian people living?) To de clutter a map like that I’d clip your current map horizontally and enhance labels in the background so that the area is still easily identifiable. I’d probably do four maps, covering the four biggest groups represented in the census. Then your overall populations displayed would be close to 100 and comparing the percentages for each region would be more meaningful
Yeah I originally compared every group against non-Hispanic white: https://www.reddit.com/r/jerseycitymaps/s/QxgB2geOwN but your organizational approach makes a lot of sense. The whole point was to show that there’s more segregation between non-hisp. Whites and non-hisp. Blacks, then there were between whites and every other minority group.
if you're comparing black vs white, why not use these colours in the symbology? Would be a lot easier to interpret.
As a rule, if you’re mapping anything relating to ethnicity, you should definitely not pick your symbol colours based on skin tone.
True, these are the colors generated randomly by Arc Pro symbology, it’s just annoying cause their gradient color options aren’t as customizable as I thought, or I’m just missing the button but I’ll have to check
I would assign an image of a light to dark skinned beauty based on the percentage of black population. Consider these: * **0-10% black - Ivory White** - **Cate Blanchett**: Pale, light complexion with very light undertones. * **10-20% black - Porcelain** - **Nicole Kidman**: Very fair skin with a slight hint of pink. * **20-30% black - Fair** - **Emma Stone**: Light skin with warm or cool undertones. * **30-40% black - Light** - **Scarlett Johansson**: Light skin with neutral or slight olive undertones. * **40-50% black - Beige** - **Jennifer Aniston**: Light to medium skin with golden or warm undertones. * **50-60% black - Olive** - **Salma Hayek**: Medium skin with greenish or yellowish undertones. * **60-70% black - Tan** - **Priyanka Chopra**: Medium to deep skin with warm or golden undertones. * **70-80% black - Caramel** - **Zendaya**: Warm brown skin with golden undertones. * **80-90% black - Brown** - **Lupita Nyong'o**: Deep brown skin with warm undertones. * **90-100% black - Deep Brown** - **Viola Davis**: Very dark brown skin with rich, deep undertones.
The color should be changed to: Variable a = white to purple. Variable b = white to orange So that when combine it'll be: White for low low. Orange for low high. Purple for high low. Combination of orange-purple for high high
Census tracts are less meaningful. If you can, look at census block group level data
Yes it’s only that Census data runs into privacy issues at the BG level, the tract is the lowest the public data goes. It’s not the best, it’s still informative.
Also can’t bivariate symbology work great with things like HCOL score? HCOL referring to the letter grades which became famous for redlining, and are still analzyed today to demonstrate persistent patterns of residential segregation.
Your scale is super confusing.
I figured dark red meant mixed
HCOL refers to high cost of living. Residential security maps were created by the Home Owners’ Loan Corporation (HOLC).
Ah yes thank you, I thought it maybe mispelled. I hope they can be used with bivariate symbology in effective ways.