Difference between revisions of "ISSS608 2016-17 T3 Assign Chan En Ying Grace Methodology"

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<b>1. Read in Raster Layer (Lekagul Roadways Map)</b>  
 
<b>1. Read in Raster Layer (Lekagul Roadways Map)</b>  
<br> - It is a single layer raster file. 200x200.  
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* It is a single layer raster file. 200x200.  
<br> class      : RasterLayer  
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class      : RasterLayer  
 
<br> dimensions  : 200, 200, 40000  (nrow, ncol, ncell)
 
<br> dimensions  : 200, 200, 40000  (nrow, ncol, ncell)
 
<br> resolution  : 1, 1  (x, y)
 
<br> resolution  : 1, 1  (x, y)

Revision as of 21:00, 22 June 2018

Rose Pipits.png “Mine dear rose pipits, whence did do thou vanish?”

Background

Methodology

Did Rose Pipit kicketh the bucket?

Which song belongs to thee?

Conclusion

 


Tools

R is the primary tool used in this analysis. The following lists the packages used for the project’s scope - for data cleaning, data visualisation, geospatial analysis and audio processing.

  • R libraries
    • sp
    • rgdal
    • sf
    • raster
    • spatstat
    • maptools
    • gplots
    • ggplot2
    • ggmap
    • rasterVis
    • lattice
    • latticeExtra
    • tidyverse
    • zoo
    • tmap
    • reshape2
    • quantmod
    • ggTimeSeries
    • viridis
    • rlang
    • soundgen
    • tuneR
    • phonTools
    • seewave


Approach Taken

The following outlines the approach used for the analysis.

Step

Approach

Description

1.

Data Understanding

1. Read in Raster Layer (Lekagul Roadways Map)

  • It is a single layer raster file. 200x200.

class : RasterLayer
dimensions : 200, 200, 40000 (nrow, ncol, ncell)
resolution : 1, 1 (x, y)
extent : 0, 200, 0, 200 (xmin, xmax, ymin, ymax)
coord. ref. : NA
names : Lekagul_Roadways_2018
values : 0, 255 (min, max)


2. Find out structure of Raster Layer
Extent : 40000
CRS arguments : NA
File Size : 41078
Object Size : 14376 bytes
Layer : 1

2.

Data Cleaning

1. Import two CSV Files (Birds)

  • 2081 Training Birds (Metadata)
  • 15 Test Birds (Provided by Kasios)


2. Fix Data Quality Issues

  • Change File ID from numeric to character
  • Change coordinates to numeric
  • Change Date from Character to Date
  • Omit the two NA values for the Y coordinate.
  • Clean the Dates (All standardise to m/d/y. For missing month/year, I will replace with NA. For missing day, I will impute as 1st day of the month.)
  • Clean the Timing (Standardise all to 24 hour formatting. Use “.” instead of ":")
  • Clean the Vocalisation Type (Standardise all to lower case. For values consisting of both ‘song and call’, change to ‘call’, assumed as a sign of distress while ‘song’ is assumed as the default)
  • Clean the Quality (Recode ‘no score’ as ‘NA’)


3. Data Manipulation

  • Extract out the “Year” and “Month” from the date, as new columns
  • Create a new column for Quarter (Q1,Q2,Q3,Q4) & Season (Spring, Summer, Fall, Winter)


4. Geospatial File Compatibility

  • Convert CSV file (2081 birds) into the following:
    • spatial point data frame
    • sp format
    • shp format
    • st_read compatible format
    • readOGR compatible format
    • ppp format (for spatstat compatibility)


5. Data Overview & Exploration

  • Overlay 2081 Birds, Raster Map & Dumping Site, for an integrated overview using `plot()`
  • Use `facet_wrap` to identify location of clustering across species, across time, and across season, and by call/song


6. Segregation of Treatment & Control Groups

  • Use ‘Rose Pipits’ as Treatment Group
  • Use ‘Ordinary Snape’ and ‘Lesse Birchbeere’ as Control Groups
  • Use ‘All Birds’ as third control