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Update index.Rmd #3

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smnotaro
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Super cool stuff that you've worked on! I can't wait to see what your finished product is!

I choosed 9 sites as training sites (Si polar swath"I00831006"; Lyot crater"V00823007"; Cerberus fossae"V00825005";Echus chasma"I00839002"; Sinus Meridiana west"I00849005"; Syrtis Major"I00853002"; Ophir planum"I00864002"; Marte vallis"I00868006; Eastern Meridiani"I00836002").
For each training site, I downloaded and used Raster data. Those data are Visible and infrared data in the “.TIFF” format and are combination of different band (9 0R 10 bands according to Mars Odysee website) and each band is showing data in a specific wavelength. I also downloaded Earth data from Landsat to show how I am applying what is done on Earth to Mars.After downloading Earth data, I resized some of them so that all images will have the same size and I then added them together to create a metadata containing all information from each site. For Mars, I don't need to resize any of the images because they all have the same size.I finally used the band ratio combination to determine the presence, abundance and distribution of water, water ice, ice or volatiles materials in each site I choose as training site and from there I was able to see which sites could be selected as the best future landing/mining sites.
I chose 9 sites as training sites (Si polar swath"I00831006"; Lyot crater"V00823007"; Cerberus fossae"V00825005";Echus chasma"I00839002"; Sinus Meridiana west"I00849005"; Syrtis Major"I00853002"; Ophir planum"I00864002"; Marte vallis"I00868006; Eastern Meridiani"I00836002").
For each training site, I downloaded and used Raster data. Those data are Visible and infrared data in the “.TIFF” format and are combination of different band (9 0R 10 bands according to Mars Odysee website) and each band is showing data in a specific wavelength. I also downloaded Earth data from Landsat to show how I am applying what is done on Earth to Mars. After downloading Earth data, I resized some of them so that all images will have the same size and I then added them together to create a metadata containing all information from each site. For Mars, I don't need to resize any of the images because they all have the same size.I finally used the band ratio combination to determine the presence, abundance and distribution of water, water ice, ice or volatiles materials in each site I chose as training site and from there I was able to see which sites could be selected as the best future landing/mining sites.
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The last sentence is a run-on sentence that I could not figure out how to fix. So just adjust this sentence a bit to make it easier to read.


# Data and Results
## PART1: Selection of thhe landing/mining sites

The goal here is to detect the site where we could have more water/ water ice/ volatiles materials. I applied some corrections to satelitte images I downloaded. For question of time I will only show what I did in only one site here but all sites I selected to be future landing/mining site are shown later in the second part of this project.
The goal here is to detect the site where we could have more water/water ice/volatiles materials. I applied some corrections to satelitte images I downloaded. For question of time I will only show what I did in only one site here but all sites I selected to be future landing/mining site are shown later in the second part of this project.
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In your second sentence, maybe just quickly say what those corrections are.

@@ -51,7 +51,7 @@ Band4 <- ("B05.tif")
Band5 <- ("B06.tif")
Band6 <- ("B07.tif")
Band7 <- ("B08.tif")

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Maybe mention why there's B and B .tif files? Unless I missed it, I'm not sure what these different files mean.

@@ -65,7 +65,7 @@ band9 <- ("b09.tiff")



```{r, message=F, warning=F}
```{r, message=F, warning=F}
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I got an error on this line that said when I tried to buildthe website:
Error in .rasterObjectFromFile(x, band = band, objecttype = "RasterLayer", :
Cannot create a RasterLayer object from this file. (file does not exist)
Calls: ... raster -> raster -> .local -> .rasterObjectFromFile
Execution halted

Exited with status 1.

Therefore, your script sadly isn't reproducible yet.

@@ -118,10 +118,10 @@ res(band5) # Size find is 20x20
res(band6) # Size find is 20x20
res(band7) # Size find is 10x10
res(band8) # Size find is 10x10
res(band9) # Size find is 10x10
res(band9) # Size find is 10x10
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This is all so interesting how you did each step.

```{r}
image1 <- stack(Band2, Band3, Band7) #Here is how it works for Landsat data on Earth
#image1 <- stack(band4, band5, band6)
#image1 <- stack(band4, band5, band6) #Clear specification of what this line is for and why it was commented out
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You nicely specified in the lines above and below what they were for, but if you used a comment to specify whey you commented out line 143, that would be helpful.

@@ -181,6 +181,7 @@ plotRGB(image2, r = 4, g = 3, b = 2, axes = TRUE,
stretch = "lin", main = "True Color Composite")
box(col="white")
```

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@smnotaro smnotaro Nov 24, 2020

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I think adding an extra line here will make it so ###FALSE COLOR doesn't show up next to the image in the html view.

@@ -196,21 +197,22 @@ par(col.axis="white",col.lab="white",tck=0)
plotRGB(image2, r = 5, g = 4, b = 3, axes = TRUE, stretch = "lin", main = "False Color Composite")
box(col="white")
```

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I think adding an extra line here will make it so ###Indices of WATER doesn't show up next to the image in the html view.

x = " ",
y = " ") +
scale_fill_gradient(high = "#CEE50E",
low = "#087F28",
name = "Water or Water ice or Volatiles materials")
low = "#087F28",
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The colors go from the darkest color being the smallest value and the lightest color being the largest value, which is backwards in how most humans understand colors and values. Unless there is a reason for this being opposite, I think you should switch the colors to go from lightest for smallest value to darkest for largest value. I couldn't recreate your script since it won't load past the third chunk, so I think this is the spot in your script to change your colors. I apologize if this is the wrong spot.

x = " ",
y = " ") +
scale_fill_gradient(high = "#CEE50E",
low = "#087F28",
name = "Water or Water ice or Volatiles materials")
low = "#087F28",
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Same suggestion as my last suggestion where the colors should be flip flopped in order. 0 is usually the lightest value you see in a figure.

@@ -266,7 +268,7 @@ library(threejs)
```

##Results2
I firstly prepared and loaded the data and then with the package called "streejs" I plot the exact locations of landing and mining sites on the Martian global map. I created a cvs file where I stored the latitudes and logitude of the future landing and mining sites selested and call that file in R.
I first prepared and loaded the data and then with the package called "threejs." I then plotted the exact locations of landing and mining sites on the Martian global map. Also, I created a cvs file where I stored the latitudes and logitude of the future landing and mining sites selested and call that file in RStudio.
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I think you meant to say threejs? If not, I'm not sure where streejs came from.

@@ -291,7 +293,7 @@ globejs(img = "C:/Users/Owner/Desktop/sare backup/c/user hadar/Desktop/GEO511/T

# Conclusions

From all sites I selected as training sites I choosed 9 sites as training sites (Si polar swath"I00831006"; Lyot crater"V00823007"; Cerberus fossae"V00825005";Echus chasma"I00839002"; Sinus Meridiana west"I00849005"; Syrtis Major"I00853002"; Ophir planum"I00864002"; Marte vallis"I00868006; Eastern Meridiani"I00836002"), Meridiana west seems to be the best one. The band ratio combination is used to determine the presence, abundance and distribution of water, water ice, ice or volatiles materials in each site before selecting some specific spots within Meridiana west as future landing/mining site.This is done using R language meaning that R is a suitable tool offering the user the choice to manipulate the data in the way he or she wants as well as to perfom diverses task on Earth and in space. R is definitely a great too that can help explorers, planetary scientists to overcome some difficulties they could not handle with other softwares.
From all sites I selected as training sites I chose 9 sites as training sites (Si polar swath"I00831006"; Lyot crater"V00823007"; Cerberus fossae"V00825005";Echus chasma"I00839002"; Sinus Meridiana west"I00849005"; Syrtis Major"I00853002"; Ophir planum"I00864002"; Marte vallis"I00868006; Eastern Meridiani"I00836002"), Meridiana west seems to be the best one. The band ratio combination is used to determine the presence, abundance and distribution of water, water ice, ice or volatiles materials in each site before selecting some specific spots within Meridiana west as future landing/mining site. This was done using R language, therefore, R is a suitable tool that offers the user the choice to manipulate the data in a way he/she/they want as well as to perfom diverses task on Earth and in space. RStudio is definitely a great too that can help explorers and planetary scientists to overcome some difficulties they could not handle with other software.
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Saying he/she/they is more inclusive to non-binary people.

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