Overlaying a transparent map on top of another map

[gafna jeff]

Hello, 

I have two rasters. One is a continuous raster showing species richness, while the other one is a binary raster of just one plant species called Olea Africana.  I would like to plot the two maps at the same time with one transparent map (Olea africana map) overlayed on top of the other map (species richness map).

When I plot the two maps separately in ggplot2 separately, they look good. But now when I plot them together (in the last step), making Olea africana binary map transparent so as to see through to the richness map, I get a funny map. What am I doing wrong. I would appreciate your help or leads to any material. Here is my code. Attached are the richness map, Olea africana map and the funny map I get after combining the two maps

library(raster)

library(ggplot2)

library(tidyverse)

library(viridis)

library(see)

#read the overal reachness map

richness <- raster("Outputs/all_final_rasters/species/final_masked_all_richness.tif")

plot(richness)

# convert to a df for plotting in two steps,

# First, to a SpatialPointsDataFrame

mal_ras_pts <- rasterToPoints(richness, spatial = TRUE)

# Then to a 'conventional' dataframe

mal_ras_df  <- data.frame(mal_ras_pts)

rm(mal_ras_pts, richness)

names(mal_ras_df)

species_richness_df <- mal_ras_df %>%

  mutate(fct_my_richness = cut(final_masked_all_richness, breaks = 6))

names(species_richness_df)

#plot using ggplot

ggplot() +

  geom_raster(data = species_richness_df , aes(x = x, y = y, fill = fct_my_richness)) + 

  scale_fill_manual(values = rainbow(6), name = "Richness", labels = c("4-5", "6-7", "8-9", "10-11", "12-13", "14-15")) +  ggtitle("Current Richness") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + theme(plot.title=element_text(size=10)) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + coord_quickmap() + theme(legend.position = c(0.71, 0.83))  

##Read Olea africana binary raster

olea <- raster("Outputs/all_final_rasters/Current_species/masked_binary_current_species/Olea_africana.tif")

plot(olea)

# convert to a df for plotting in two steps,

# First, to a SpatialPointsDataFrame

olea_pts <- rasterToPoints(olea, spatial = TRUE)

# Then to a 'conventional' dataframe

olea_df  <- data.frame(olea_pts)

rm(olea_pts, olea)

names(olea_df)

ggplot() +

  geom_raster(data = olea_df , aes(x = x, y = y, fill = as.factor(Olea_africana), alpha = 0.2)) + scale_alpha(guide = 'none') + scale_color_manual(values=c('#999999','#E69F00')) + theme(legend.title = element_text(color = "black", size = 8), legend.text = element_text(color = "black")) + ggtitle("Olea africana") + labs(fill = "Habitat Suitability") + scale_fill_discrete(labels = c("No Habitat", "Olea africana")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + theme(plot.title=element_text(size=10)) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + coord_quickmap() + theme(legend.position = c(0.82, 0.53)) 

##combine the two maps with olea Africana map on top as transparent

ggplot() +

  geom_raster(data = species_richness_df , aes(x = x, y = y, fill = fct_my_richness)) + 

  scale_fill_manual(values = rainbow(6), name = "Richness", labels = c("4-5", "6-7", "8-9", "10-11", "12-13", "14-15")) +  ggtitle("Current Richness") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + theme(plot.title=element_text(size=10)) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + coord_quickmap() + theme(legend.position = c(0.71, 0.75))  +

geom_raster(data = olea_df , aes(x = x, y = y, fill = as.factor(Olea_africana), alpha = 0.2)) + scale_alpha(guide = 'none') + scale_color_manual(values=c('#999999','#E69F00')) + theme(legend.title = element_text(color = "black", size = 8), legend.text = element_text(color = "black")) + labs(fill = "Habitat Suitability") + scale_fill_discrete(labels = c("No Habitat", "Olea africana")) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + theme(plot.title=element_text(size=10)) + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) + coord_quickmap() + theme(legend.position = c(0.82, 0.53)) 

Regards,

Jeff

[Tom Philippi]

Jeff--

What do you want the resulting map to look like?  [That may be why no one has replied yet.]

My first idea would be the color-ramp of categorical species richness as a basemap plotted just as you do, but then black (or red) dots for just the Oleea habitat cells using 

geom_point(data = olea_df[olea_df$Olea_africana,.], aes(x = x, y = y), color = "red") +

But, actually looking at your maps of species richness and your Olea, the Olea isn't a patchy distribution but rather all but the lower right quadrant.  Thus, if the raster grid cells align, I would merge the Olea habitat as a {0,1} numeric variable (or logical) to species_richness_df, then use the value of that variable to control alpha, so alpha = 1 for the Olea habitat and alpha = .4 or so for the non-habitat, which would thus be washed out in appearance.  That would emphasize where the Olea are.

Or, you could compute a new variable junk <- fct_my_richness +  100 * Olea_africana

species and create a new color palette with the same 6 hues repeated twice, but luminosity or something else differing between the habitat and non-habitat.

If you want something else from this list, please give the ggplot2 experts an idea of what you're striving for.  

Tom

 

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[gafna jeff]

Dear Tom

Many thanks for your reply and suggestion and I really appreciate it. I want to plot two maps at the same time. The first map is the species richness map. The second map is the Olea africana map which is a binary map and should be overlaid (as a semi-transparent white overlay)  on top of the species richness map that I had earlier plotted.

Regards,

Dikko

[gafna jeff]

The main goal of my idea is the following

1 Identify area with high species richness but no Olea africana

2 identify area with low species richness and with Olea africana

3 Identify the areas with moderate species richness and with no Olea africana

On Tue, May 11, 2021 at 5:47 AM Tom Philippi <tephi...@gmail.com> wrote:

[Brandon Hurr]

Could you make a reprex? I'm happy to play around with it, but I can't because I don't have your rasters. 

I agree with what was proposed. I would keep your species richness as it is, but then apply the olea africana binary map as an alpha layer. 1 for present and 0.1 or so for not. You can still see the colors, but they would be very faint. Not sure if you can do that with rasters or not though. 

B

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[Brad Udall]

I can’t say I have much expertise with this problem, but trying to use different colors, even with transparency, seems like the wrong way to go.

You need some other way to show a second set of variables. 

How about using cross-hatching or dots for habitat suitability overlaid on top of the species richness colors?

Brad

On May 11, 2021, at 6:43 AM, Brandon Hurr <brando...@gmail.com> wrote:

Could you make a reprex? I'm happy to play around with it, but I can't because I don't have your rasters. 

I agree with what was proposed. I would keep your species richness as it is, but then apply the olea africana binary map as an alpha layer. 1 for present and 0.1 or so for not. You can still see the colors, but they would be very faint. Not sure if you can do that with rasters or not though. 

B

On Tue, May 11, 2021 at 3:32 AM gafna jeff <gafn...@gmail.com> wrote:

The main goal of my idea is the following

1 Identify area with high species richness but no Olea africana

2 identify area with low species richness and with Olea africana

3 Identify the areas with moderate species richness and with no Olea africana

On Tue, May 11, 2021 at 5:47 AM Tom Philippi <tephi...@gmail.com> wrote:

Jeff--

What do you want the resulting map to look like?  [That may be why no one has replied yet.]

My first idea would be the color-ramp of categorical species richness as a basemap plotted just as you do, but then black (or red) dots for just the Oleea habitat cells using 

geom_point(data = olea_df[olea_df$Olea_africana,.], aes(x = x, y = y), color = "red") +

But, actually looking at your maps of species richness and your Olea, the Olea isn't a patchy distribution but rather all but the lower right quadrant.  Thus, if the raster grid cells align, I would merge the Olea habitat as a {0,1} numeric variable (or logical) to species_richness_df, then use the value of that variable to control alpha, so alpha = 1 for the Olea habitat and alpha = .4 or so for the non-habitat, which would thus be washed out in appearance.  That would emphasize where the Olea are.

Or, you could compute a new variable junk <- fct_my_richness +  100 * Olea_africana

species and create a new color palette with the same 6 hues repeated twice, but luminosity or something else differing between the habitat and non-habitat.

If you want something else from this list, please give the ggplot2 experts an idea of what you're striving for.  

Tom

 

On Mon, May 10, 2021 at 12:15 AM gafna jeff <gafn...@gmail.com> wrote:

Hello, 

I have two rasters. One is a continuous raster showing species richness, while the other one is a binary raster of just one plant species called Olea Africana.  I would like to plot the two maps at the same time with one transparent map (Olea africana map) overlayed on top of the other map (species richness map).

When I plot the two maps separately in ggplot2 separately, they look good. But now when I plot them together (in the last step), making Olea africana binary map transparent so as to see through to the richness map, I get a funny map. What am I doing wrong. I would appreciate your help or leads to any material. Here is my code. Attached are the richness map, Olea africana map and the funny map I get after com<Richness map.png><Olea africana map.png><Combined map with transparency.png>bining the two maps

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[gafna jeff]

Dear Brad,

Many thanks for your time and suggestion. I really appreciate it. Yes, another option I have is using hatchings.  My idea is to use ggpattern package for hatchings. But so far I havent came across material on how this can be implemented on rasters. I have only came across materials on how it is used in bar graphs etc. Do you have any lead to materials on how hatchings are done in rasters.

Regards,

Jeff

[Brad Udall]

Jeff,

Can’t say that I do.

A quick google came up with one idea: create a new shape file for the hatchings with just lines.

That shape would be overlaid on top of the colors, but transparent I think.

One other thought….

The ggplot model is supposed to be simple conceptually.  The hatchings feel like an aesthetic, like color.  Maybe a ‘fill’ aesthetic would work somehow.

I’m reasonably certain this can be done, but that’s probably little consolation.

Brad

[Brad Udall]

Look at this:

https://coolbutuseless.github.io/2020/04/01/introducing-ggpattern-pattern-fills-for-ggplot/

[gafna jeff]

Thanks Brad. I will check this definately

[Tom Philippi]

I believe that if you want to use patterns, you need to convert your Olea raster to polygons.  If you're using sp objects, you could use something like

Olea_polys <- as(olea, "SpatialPolygonsDataFrame")

for sf objects, you can then convert that sp object to sf:

Olea_polys_sf <- st_as_sf(Olea_polys)

Note that my initial idea of using geom_point() for Olea would have given stippling (with the right point size).  I agree that hastings will be clearer than stippling, but stippling and alpha are much easier to do via ggplot.

Tom

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[gafna jeff]

Dear Tom,

Thanks for your suggestion

Jeff

[gafna jeff]

Dear all,

Am using ggpattern package to plot cross hatching of my Olea africana binary raster. My idea is to convert the raster to tibble data frame format (the format used used in ggpattern package for geom_polygon_pattern). And then plot it as hatching using geom_polygon_pattern() function. I did not use the conversion of raster to polygon approach suggested by Tom ( Olea_polys <- as(olea, "SpatialPolygonsDataFrame"))  since it limits me by not giving me the x and y which I need to plot. The binary map of Olea africana and the resultant map after cross hatching look very different. The cross hatching map is very bad. What am I doing wrong?  I would really appreciate any help or advice. Below is my code

library(raster)
library(ggplot2)
library(tidyverse)
library(viridis)
library(see)

library(ggpattern)


#read in olea africana data
olea <- raster("Outputs/all_final_rasters/Current_species/masked_binary_current_species/malaria_vector.tif")

plot(olea)

# convert to a df for plotting in two steps,
# First, to a SpatialPointsDataFrame
olea_pts <- rasterToPoints(olea, spatial = TRUE)
# Then to a 'conventional' dataframe
olea_df  <- data.frame(olea_pts)
rm(olea_pts, olea)

class(olea_df)
names(olea_df)

#Convert to tibble object or dataframe
olea_df_new<- as_tibble(olea_df)
class(olea_df_new)

olea_df_new <- olea_df_new[,-4]
names(olea_df_new)


#plot with cross hatchings
ggplot(olea_df_new, aes(x = x, y = y)) +
  geom_polygon_pattern(aes(pattern_fill = as.factor(malaria_vector)),
                       fill   = 'red',
                       colour = 'black',
                       pattern_spacing = 0.01,
                       pattern_density = 0.01,
                       pattern_colour = '#002366',
                       pattern_alpha =0.05,
                       pattern_angle = 45
  ) +
  labs(title = "") +
  coord_equal() +
  theme_bw(25) +
  theme(legend.position = 'right') +
  theme(axis.title = element_blank())

Regards,

Jeff

[Rainer Hurling]

Hi Jeff,

Am 19.05.21 um 13:41 schrieb gafna jeff:

> Dear all,
>
> Am using ggpattern package to plot cross hatching of my Olea africana
> binary raster. My idea is to convert the raster to tibble data frame
> format (the format used used in ggpattern package for
> geom_polygon_pattern). And then plot it as hatching
> using geom_polygon_pattern() function. I did not use the conversion of
> raster to polygon approach suggested by Tom ( Olea_polys <- as(olea,
> "SpatialPolygonsDataFrame"))  since it limits me by not giving me the x
> and y which I need to plot. The binary map of Olea africana and the
> resultant map after cross hatching look very different. The cross
> hatching map is very bad. What am I doing wrong?  I would really
> appreciate any help or advice. Below is my code
>
> library(raster)
> library(ggplot2)
> library(tidyverse)
> library(viridis)
> library(see)
> library(ggpattern)
>
>
> #read in olea africana data
> olea <-
> raster("Outputs/all_final_rasters/Current_species/masked_binary_current_species/malaria_vector.tif")

Didn't you forgot to attach the tif file?

Best wishes,
Rainer

>> <wwa....@gmail.com <mailto:wwa....@gmail.com>> wrote:
>>
>> Jeff,
>>
>> Can’t say that I do.
>>
>> A quick google came up with one idea: create a new
>> shape file for the hatchings with just lines.
>>
>> That shape would be overlaid on top of the colors, but
>> transparent I think.
>>
>> One other thought….
>>
>> The ggplot model is supposed to be simple
>> conceptually.  The hatchings feel like an aesthetic,
>> like color.  Maybe a ‘fill’ aesthetic would work somehow.
>>
>> I’m reasonably certain this can be done, but that’s
>> probably little consolation.
>>
>> Brad
>>
>>
>>
>>
>>> On May 11, 2021, at 8:16 AM, gafna jeff

>>>> <mailto:brando...@gmail.com>> wrote:
>>>>
>>>> Could you make a reprex? I'm happy to play
>>>> around with it, but I can't because I don't have
>>>> your rasters. 
>>>>
>>>> I agree with what was proposed. I would keep
>>>> your species richness as it is, but then apply
>>>> the olea africana binary map as an alpha layer.
>>>> 1 for present and 0.1 or so for not. You can
>>>> still see the colors, but they would be very
>>>> faint. Not sure if you can do that with rasters
>>>> or not though. 
>>>>
>>>> B
>>>>
>>>> On Tue, May 11, 2021 at 3:32 AM gafna jeff
>>>> <gafn...@gmail.com

>>>> <mailto:gafn...@gmail.com>> wrote:
>>>>
>>>> The main goal of my idea is the following
>>>>
>>>> 1 Identify area with high species richness
>>>> but no Olea africana
>>>> 2 identify area with low species richness
>>>> and with Olea africana
>>>> 3 Identify the areas with moderate species
>>>> richness and with no Olea africana
>>>>
>>>> On Tue, May 11, 2021 at 5:47 AM Tom Philippi
>>>> <tephi...@gmail.com

>>>> <mailto:ggp...@googlegroups.com>
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>>>>
>>>>
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>>>
>>
>
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[gafna jeff]

Dear Rainer,

Am sorry I forgot to attach the raster tif file. Attached is my raster

Regards

[Brandon Hurr]

Jeff, 

I couldn't get the ggpattern thing to work (weird cross hatching everywhere), but I gave my idea of an alpha layer an attempt and it's not terrible. 

library(raster)

library(see)

library(ggpattern)

library(tidyverse)

library(viridis)

#read in olea africana data

olea <- raster("~/Downloads/malaria_vector.tif")

richness <- raster("~/Downloads/final_masked_all_richness.tif")

# convert to a df for plotting in two steps,

# First, to a SpatialPointsDataFrame

olea_pts <- rasterToPoints(olea, spatial = TRUE)

richness_pts <- rasterToPoints(richness, spatial = TRUE)

# Then to a 'conventional' dataframe

olea_df  <- tibble(as.data.frame(olea_pts))

richness_df <- tibble(as.data.frame(richness_pts))

ggplot() +

geom_raster(data = richness_df , aes(x = x, y = y, fill = as.factor(final_masked_all_richness))) + 

geom_raster(data = olea_df, aes(x = x, y = y, alpha = as.factor(malaria_vector))) + scale_alpha_discrete(range = c(0, 0.5))

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[gafna jeff]

Dear Brandon,

Many thanks for this. I really appreciate. Indeed ggpattern is difficult to implement and not so many literature is available on its implementation. Probably I will switch to this transparent approach if ggpattern fails completely.

Jeff