PhenoCam "roistats" Files

Here's a jupyter notebook demonstrating how to read in and plot an "roistats" file (formerly known as an "all image" file) using R. In this case I'm using the all image file from the alligatorriver site. The all image files are in CSV format and can be read directly from the PhenoCam Network web site using a URL. To use this notebook you'll need to install the packages, ggplot2 and lubridate from CRAN.



In [4]:

    
library(ggplot2)
library(lubridate)

baseurl = 'https://phenocam.sr.unh.edu/data/archive'
sitename = 'alligatorriver'
roiname1 = 'DB_1000'

csvfile = sprintf("%s_%s_roistats.csv",sitename,roiname1)
csvurl = sprintf("%s/%s/ROI/%s",baseurl,sitename,csvfile)
df = read.csv(url(csvurl),comment.char="#",header=TRUE)
df$date = as.Date(df$date)
df$year = year(df$date)
ystart = min(df$year)
yend = max(df$year)
head(df)









    





date local_std_time doy filename solar_elev exposure mask_index gcc rcc r_mean ⋯ b_10_qtl b_25_qtl b_50_qtl b_75_qtl b_90_qtl b_95_qtl r_g_correl g_b_correl b_r_correl year

	2012-05-03                          12:01:10                            124                                 alligatorriver_2012_05_03_120110.jpg 70.15241                            NA                                  1                                   0.41935                             0.38485                             102.85102                           ⋯                                    2                                  24                                  48                                  74                                  103                                 123                                 0.98502                             0.92033                             0.93415                             2012                                
	2012-05-06                          07:31:09                            127                                 alligatorriver_2012_05_06_073109.jpg 27.97539                            NA                                  1                                   0.42260                             0.36243                              91.86082                           ⋯                                   24                                  38                                  53                                  69                                   86                                  97                                 0.98148                             0.89940                             0.93900                             2012                                
	2012-05-06                          08:01:09                            127                                 alligatorriver_2012_05_06_080109.jpg 34.05378                            NA                                  1                                   0.42547                             0.38116                              96.38509                           ⋯                                   16                                  31                                  47                                  65                                   83                                  95                                 0.98094                             0.90209                             0.93915                             2012                                
	2012-05-06                          08:31:09                            127                                 alligatorriver_2012_05_06_083109.jpg 40.10441                            NA                                  1                                   0.42459                             0.37440                              92.04720                           ⋯                                   16                                  31                                  47                                  65                                   84                                  98                                 0.97965                             0.89689                             0.93617                             2012                                
	2012-05-06                          09:01:09                            127                                 alligatorriver_2012_05_06_090109.jpg 46.07717                            NA                                  1                                   0.42391                             0.38027                              96.31717                           ⋯                                   15                                  30                                  47                                  66                                   86                                  99                                 0.98024                             0.89955                             0.93733                             2012                                
	2012-05-06                          09:31:09                            127                                 alligatorriver_2012_05_06_093109.jpg 51.90043                            NA                                  1                                   0.41835                             0.37313                              97.34223                           ⋯                                   16                                  33                                  52                                  72                                   94                                 110                                 0.98050                             0.91031                             0.94106                             2012



In [5]:

    
## combine date and local_std_time
df$datetime = with(df, as.POSIXct(paste(date,local_std_time), format="%Y-%m-%d %H:%M:%S"))



In [6]:

    
options(repr.plot.width = 8)
options(repr.plot.height = 2.5)
p = ggplot(df,aes(x=datetime,y=gcc)) + geom_point(size=0.01, shape=16, alpha=.7)
p









    



Warning message:
“Removed 1 rows containing missing values (geom_point).”



In [ ]:

date	local_std_time	doy	filename	solar_elev	exposure	mask_index	gcc	rcc	r_mean	⋯	b_10_qtl	b_25_qtl	b_50_qtl	b_75_qtl	b_90_qtl	b_95_qtl	r_g_correl	g_b_correl	b_r_correl	year
2012-05-03	12:01:10	124	alligatorriver_2012_05_03_120110.jpg	70.15241	NA	1	0.41935	0.38485	102.85102	⋯	2	24	48	74	103	123	0.98502	0.92033	0.93415	2012
2012-05-06	07:31:09	127	alligatorriver_2012_05_06_073109.jpg	27.97539	NA	1	0.42260	0.36243	91.86082	⋯	24	38	53	69	86	97	0.98148	0.89940	0.93900	2012
2012-05-06	08:01:09	127	alligatorriver_2012_05_06_080109.jpg	34.05378	NA	1	0.42547	0.38116	96.38509	⋯	16	31	47	65	83	95	0.98094	0.90209	0.93915	2012
2012-05-06	08:31:09	127	alligatorriver_2012_05_06_083109.jpg	40.10441	NA	1	0.42459	0.37440	92.04720	⋯	16	31	47	65	84	98	0.97965	0.89689	0.93617	2012
2012-05-06	09:01:09	127	alligatorriver_2012_05_06_090109.jpg	46.07717	NA	1	0.42391	0.38027	96.31717	⋯	15	30	47	66	86	99	0.98024	0.89955	0.93733	2012
2012-05-06	09:31:09	127	alligatorriver_2012_05_06_093109.jpg	51.90043	NA	1	0.41835	0.37313	97.34223	⋯	16	33	52	72	94	110	0.98050	0.91031	0.94106	2012