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> library(lubridate)

Attaching package: ‘lubridate’

The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

> library(plotly)
Loading required package: ggplot2

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

> library(htmlwidgets)
> library(weathermetrics) # install.packages("weathermetrics")
> library(heatindex) # install.packages("heatindex")
> 
> # Set Time-Period
> actTime = Sys.time()
> timePer = 7 * 24 * 3600
> startTime = actTime - timePer
> actYear = year(actTime)
> actMonth = month(actTime)
> lstYear = year(actTime - timePer)
> lstMonth = month(actTime - timePer) 
> # Construct paths and filenames
> # Senesecaps Description
> # 1 "2CF7F1C0532000D2" # Außenbereich Kita (zwischen Schaukel und Gerüst, hinter einer Sitzbank)
> # 2 "2CF7F1C053200114" # Baum zwischen Außenbereich Kita und Außenbereich Hort neben dem Sandkasten Kita
> # 3 "2CF7F1C0532000BD" # Außenbereich Krippe, Baum am Sandkasten Krippe
> # Sensecap Names
> s_names = c("2CF7F1C0532000D2", "2CF7F1C053200114","2CF7F1C0532000BD")
> s_labels = c("Schoenbach 1", "Schoenbach 2", "Schoenbach 3")
> path_1 = "https://saqn.geo.uni-augsburg.de"
> path_2 = "lorawan"
> path_3_y = c(lstYear, actYear)
> path_3_m = c(lstMonth, actMonth)
> 
> for(mCt in 1:length(path_3_m))
+ {
+    path_3_ym =  paste(path_3_y[mCt], formatC(path_3_m[mCt], width = 2, format = "d", flag = "0"), sep ="-")
+    print(path_3_ym)
+ for(s_name in s_names)
+ {
+   #  Sensecap Data
+   URL = paste(path_1, "/",path_2, "/",path_3_ym, "/",s_name, "_",path_3_ym, ".csv", sep = "")
+   try(download.file(URL, destfile = "download_scap.dat", method = "wget", extra = "--no-check-certificate"), silent = TRUE)
+   hdr1 = read.table("download_scap.dat", sep = ",", nrows = 1)
+   header = c(hdr1, "sc_id")
+   dF = read.table("download_scap.dat", header = FALSE, sep = ",", na.strings = c(-9999) , skip = 1)
+   dF$sc_id = s_name
+   names(dF) = header; names(dF) = trimws(names(dF), which = "left")
+   if(mCt == 1 & s_name == s_names[1])
+   {pscData = dF}else{pscData = rbind(pscData, dF)}
+ }
+ }
[1] "2026-08"
--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C0532000D2_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 409590 (400K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 12%  119M 0s
    50K .......... .......... .......... .......... .......... 25%  208M 0s
   100K .......... .......... .......... .......... .......... 37%  276M 0s
   150K .......... .......... .......... .......... .......... 50%  327M 0s
   200K .......... .......... .......... .......... .......... 62%  303M 0s
   250K .......... .......... .......... .......... .......... 75%  311M 0s
   300K .......... .......... .......... .......... .......... 87%  320M 0s
   350K .......... .......... .......... .......... ......... 100%  327M=0.002s

2026-08-20 19:26:56 (245 MB/s) - ‘download_scap.dat’ saved [409590/409590]

--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C053200114_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 127648 (125K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 40%  126M 0s
    50K .......... .......... .......... .......... .......... 80%  161M 0s
   100K .......... .......... ....                            100%  388M=0.001s

2026-08-20 19:26:56 (161 MB/s) - ‘download_scap.dat’ saved [127648/127648]

--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C0532000BD_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 329616 (322K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 15%  137M 0s
    50K .......... .......... .......... .......... .......... 31%  169M 0s
   100K .......... .......... .......... .......... .......... 46%  246M 0s
   150K .......... .......... .......... .......... .......... 62%  269M 0s
   200K .......... .......... .......... .......... .......... 77%  243M 0s
   250K .......... .......... .......... .......... .......... 93%  265M 0s
   300K .......... .......... .                               100%  222M=0.002s

2026-08-20 19:26:56 (209 MB/s) - ‘download_scap.dat’ saved [329616/329616]

[1] "2026-08"
--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C0532000D2_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 409590 (400K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 12%  211M 0s
    50K .......... .......... .......... .......... .......... 25%  225M 0s
   100K .......... .......... .......... .......... .......... 37%  310M 0s
   150K .......... .......... .......... .......... .......... 50%  314M 0s
   200K .......... .......... .......... .......... .......... 62%  289M 0s
   250K .......... .......... .......... .......... .......... 75%  314M 0s
   300K .......... .......... .......... .......... .......... 87%  317M 0s
   350K .......... .......... .......... .......... ......... 100%  292M=0.001s

2026-08-20 19:26:56 (278 MB/s) - ‘download_scap.dat’ saved [409590/409590]

--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C053200114_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 127648 (125K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 40%  230M 0s
    50K .......... .......... .......... .......... .......... 80%  278M 0s
   100K .......... .......... ....                            100%  304M=0s

2026-08-20 19:26:56 (261 MB/s) - ‘download_scap.dat’ saved [127648/127648]

--2026-08-20 19:26:56--  https://saqn.geo.uni-augsburg.de/lorawan/2026-08/2CF7F1C0532000BD_2026-08.csv
Resolving saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)... 137.250.104.17
Connecting to saqn.geo.uni-augsburg.de (saqn.geo.uni-augsburg.de)|137.250.104.17|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 329616 (322K) [text/csv]
Saving to: ‘download_scap.dat’

     0K .......... .......... .......... .......... .......... 15%  188M 0s
    50K .......... .......... .......... .......... .......... 31%  199M 0s
   100K .......... .......... .......... .......... .......... 46%  294M 0s
   150K .......... .......... .......... .......... .......... 62%  310M 0s
   200K .......... .......... .......... .......... .......... 77%  277M 0s
   250K .......... .......... .......... .......... .......... 93%  311M 0s
   300K .......... .......... .                               100%  256M=0.001s

2026-08-20 19:26:56 (252 MB/s) - ‘download_scap.dat’ saved [329616/329616]

> # Format Date and Time
> pscData$time = as.POSIXct(pscData$time, format = "%Y-%m-%dT%H:%M:%OSZ", tz = "UTC")
> pscData$time = round_date(pscData$time, "10 minutes")
> 
> # Remove duplicated DateTime entries
> if(length(which(duplicated(paste(pscData$time, pscData$sc_id))) > 0)) pscData = pscData[-which(duplicated(paste(pscData$time, pscData$sc_id))),]
> 
> # Calculate HI 
> # heat.index from weathermetrics (National Weather Service Hydrometeorological Prediction Center Web Team. Heat Index Calculator. 30 Jan 2015. http://www.wpc.ncep.noaa.gov/html/heatindex.shtml. Accessed 18 Dec 2015)
> pscData$heatIndex_01 = heat.index(t = pscData$airTemperature, rh = pscData$relativeHumidity, temperature.metric = "celsius", output.metric = NULL, round = 2)
> # heatindex from heatindex (Steadman, R. G. (1979). The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. Journal of Applied Meteorology, 18, 861-873. doi:10.1175/1520-0450(1979)018<0861:TAOSPI>2.0.CO;2)
> pscData$heatIndex_02 = heatindex(T = (pscData$airTemperature + 273.16), rh = (pscData$relativeHumidity * 0.01)) - 273.16
> # HI-Risk-Levels
> HI_Levs = c(27, 32, 39, 52)
> HI_cats = c("Caution", "Extreme Caution", "Danger", "Extreme Danger")
> HI_shapes <- lapply(HI_Levs, function(y) {
+   list(
+     type = "line",
+     x0 = 0, x1 = 1,
+     xref = "paper",
+     y0 = y, y1 = y,
+     yref = "y",
+     line = list(color = "grey60", width = 1, dash = "dot")
+   )
+ })
> HI_annotations <- lapply(seq_along(HI_Levs), function(i) {
+   list(
+     x = 1,
+     xref = "paper",
+     y = HI_Levs[i],
+     yref = "y",
+     text = paste("HI > ",HI_Levs[i],"°C : ", HI_cats[i]),
+     showarrow = FALSE,
+     xanchor = "left",
+     xshift = 8,
+     font = list(
+       size = 18,
+       color = "grey30"
+     )
+   )
+ })
> 
> 
> # Cut data to time period
> pscdata = subset(pscData, time > startTime) # Sensecap Data
> #pscdata = pscdata[order(pscdata$time),]
> 
> cl = c("#FF4500", "#CD3700", "#8B2500")
> 
> # Subplots
> # Sensecap plots
> fig_sc_temp = plot_ly(data = pscdata[pscdata$sc_id == s_names[1],], x = ~time, y = ~airTemperature, name = paste(s_labels[1], " (Ta)"), type = 'scatter', mode = 'lines', line = list(width = 3, color = cl[1])) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[2],], x = ~time, y = ~airTemperature, name = paste(s_labels[2], " (Ta)"), type = 'scatter', mode = 'lines', line = list(color = cl[2])) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[3],], x = ~time, y = ~airTemperature, name = paste(s_labels[3], " (Ta)"), type = 'scatter', mode = 'lines', line = list(color = cl[3]))
> 
> fig_sc_rhum = plot_ly(data = pscdata[pscdata$sc_id == s_names[1],], x = ~time, y = ~relativeHumidity, name = paste(s_labels[1], " (RH)"), type = 'scatter', mode = 'lines', line = list(width = 3, color = cl[1], dash = "dash")) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[2],], x = ~time, y = ~relativeHumidity, name = paste(s_labels[2], " (RH)"), type = 'scatter', mode = 'lines', line = list(color = cl[2])) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[3],], x = ~time, y = ~relativeHumidity, name = paste(s_labels[3], " (RH)"), type = 'scatter', mode = 'lines', line = list(color = cl[3])) 
> 
> fig_sc_hi_01 = plot_ly(data = pscdata[pscdata$sc_id == s_names[1],], x = ~time, y = ~heatIndex_01, name = paste(s_labels[1], " (HI)"), type = 'scatter', mode = 'lines', line = list(width = 3, color = cl[1], dash = "dot")) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[2],], x = ~time, y = ~heatIndex_01, name = paste(s_labels[2], " (HI)"), type = 'scatter', mode = 'lines', line = list(color = cl[2])) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[3],], x = ~time, y = ~heatIndex_01, name = paste(s_labels[3], " (HI)"), type = 'scatter', mode = 'lines', line = list(color = cl[3])) %>%
+   layout(
+     shapes = HI_shapes,
+     annotations = HI_annotations)
> 
> fig_sc_hi_02 = plot_ly(data = pscdata[pscdata$sc_id == s_names[1],], x = ~time, y = ~heatIndex_02, name = "IGUA - Bodenstation - HI", type = 'scatter', mode = 'lines', line = list(width = 3, color = cl[1], dash = "dot")) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[2],], x = ~time, y = ~heatIndex_02, name = "Logger - Friesenstrasse - HI", type = 'scatter', mode = 'lines', line = list(color = cl[2])) %>%
+   add_lines(data = pscdata[pscdata$sc_id == s_names[3],], x = ~time, y = ~heatIndex_02, name = "Logger - Gärtnerstrasse - HI", type = 'scatter', mode = 'lines', line = list(color = cl[3])) 
> 
> 
> # Stacked Subplots
> fig = subplot(fig_sc_temp, fig_sc_rhum, fig_sc_hi_01, nrows = 3, shareX = TRUE, margin = 0.01) %>%
+   layout(
+     title = list(
+       text = "IGUA - Physical Geography and Climate Science - Augsburg Urban Climate Network",
+       font = list(size = 24, color = "")
+       ),
+     margin = list(
+            l = 80,   # left
+            r = 40,   # right
+            t = 100,  # top
+            b = 80    # bottom
+        )
+     ,
+     plot_bgcolor='#e5ecf6', 
+     xaxis = list(
+       zerolinecolor = '#ffff', 
+       zerolinewidth = 2, 
+       gridcolor = 'ffff',
+       title = "Time"),
+     xaxis2 = list(
+       zerolinecolor = '#ffff', 
+       zerolinewidth = 2, 
+       gridcolor = 'ffff',
+       title = "Time"),
+     yaxis = list(title = list(text = "Air Temperature (°C)", font = list(size = 24, color = ""))),
+     yaxis2 = list(title = list(text = "Relative Humidity (%)", font = list(size = 24, color = ""))),
+     yaxis3 = list(title = list(text = "Heat Index (°C)", font = list(size = 24, color = ""))),
+     legend = list(font = list(size = 20))
+       )
> fig
> 
> # Export HTML
> saveWidget(fig,"Schoenbach_Sensecap_recent.html", selfcontained = F)
> #
> 
> proc.time()
   user  system elapsed 
  3.153   2.707   3.580