“Mine dear rose pipits, whence did do thou vanish?”
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
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Approach Taken
The following outlines the approach used for the analysis.
Step
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Approach
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Description
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1.
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Data Understanding
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i. 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)
ii. Find out structure of Raster Layer
Extent : 40000
CRS arguments : NA
File Size : 41078
Object Size : 14376 bytes
Layer : 1
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2.
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Data Cleaning
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i. Import two CSV Files (Birds)
- 2081 Training Birds (Metadata)
- 15 Test Birds (Provided by Kasios)
ii. 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’)
iii. 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)
iv. Geospatial File Compatibility
- Convert CSV file (2081 birds) into the following:
a) spatial point data frame
b) sp format
c) shp format
d) st_read compatible format
e) readOGR compatible format
f) ppp format (for spatstat compatibility)
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