-
Notifications
You must be signed in to change notification settings - Fork 2
/
D01_data_examples_slides.qmd
182 lines (95 loc) · 3.07 KB
/
D01_data_examples_slides.qmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
---
format: revealjs
output-dir: slides/
---
## {background-image="assets/landscape_bats.svg" background-size="contain"}
## Are bats in forests bigger? {background-image="assets/landscape_bats.svg" background-size="contain"}
## {background-image="assets/landscape.svg" background-size="contain"}
## Plot surverys {background-image="assets/landscape_plots.svg" background-size="contain"}
## Plot surveys {background-image="assets/landscape_one_plot.svg" background-size="contain"}
:::: {.columns}
::: {.column width="50%"}
:::
::: {.column width="50%"}
```{r d01-plotsurveys, echo = FALSE}
df = data.frame(plotID = c("F1", "F2", "A1"),
land_cover = c("forest", "forest", "arable"),
bats = c(7, 2, 4))
knitr::kable(
df, caption = 'Field survery data on a plot',
booktabs = TRUE
)
```
:::
::::
## Time Series {background-image="assets/landscape_one_plot_sensor.svg" background-size="contain"}
## Time Series {background-image="assets/landscape_one_plot_sensor.svg" background-size="contain"}
:::: {.columns}
::: {.column width="40%"}
:::
::: {.column width="60%"}
* _quasi_ continuous measurements
* measurement interval
* climate, soil, remote sensing
***
```{r d01-timeseries, echo = FALSE}
df <- data.frame(time = c("12:00", "12:15", "12:30"),
temperature = c(18.3, 18.5, 18.6))
knitr::kable(
df, row.names = FALSE
)
```
:::
::::
## Time Series
```{r d01-timeseries-vis, echo = FALSE, fig.cap="Visualization of time series data"}
library(tidyverse)
df <- read.csv(file = "data/dwd_spring_temperature.txt", skip = 1, sep = ";")
ggplot(df, aes(Jahr, Deutschland))+
geom_line()+
ylab("Temperature [°C]")+
theme_light()
```
## Species Lists {background-image="assets/landscape_one_plot.svg" background-size="contain"}
:::: {.columns}
::: {.column width="50%"}
:::
::: {.column width="50%"}
```{r d01-specieslists, echo = FALSE}
df = data.frame(species = c("Digitalis purpurea", "Galium odoratum", "Fagus Sylvatica"),
n = c("4", "25", "20"))
knitr::kable(
df, caption = 'Vegetation of F1',
booktabs = TRUE
)
```
:::
::::
## Geospatial Data
* defined by explicit location on the earth surface
* information attached to coordinates
```{r d01-geospatial, echo = FALSE}
set.seed(10)
trees = sf::st_read("data/muenster_trees.gpkg", quiet = TRUE) %>%
na.omit() %>%
slice_sample(n = 25)
knitr::kable(
sf::st_drop_geometry(trees)[1:4,], caption = 'Geospatial Data: Tree locations',
booktabs = TRUE
)
```
## Geospatial Data
```{r d01-geospatial-vis, echo = FALSE}
mapview::mapviewOptions(basemaps = c("OpenStreetMap.DE"))
mapview::mapview(trees, zcol = "species")
```
## Data for monitoring
{width = 50%}
## Other data sources
* Lab / Field experiments
* Individuum based information (e.g. traits)
* Data repositories
* Socio-Economic data (also useful for landscape ecology)
* Open Data from paper
* ...
## References