-
Notifications
You must be signed in to change notification settings - Fork 1
/
jemez_mask.R
254 lines (204 loc) · 7.97 KB
/
jemez_mask.R
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
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
# jemez mask data bc cant do it with python reader
# 3/22
#geolocating is right, talk to HP about it
library(plotly)
library(data.table)
library(rgdal)
library(gdalUtils)
library(sp)
library(caTools)
library(rgdal)
library(rgeos)
library(ggplot2)
library(raster)
# import DEM
jemez_DEM <-raster("/Volumes/JT/projects/uavsar/jemez/raw_data/02122020_02192020/DEM/alamos_35915_20005-003_20008-000_0007d_s01_L090HH_01.hgt.grd.tiff")
values(jemez_DEM)[values(jemez_DEM) == -10000] = NA
hist(jemez_DEM)
jemez_DEM
#bring in UAVSAR rasters
files <-list.files("/Volumes/JT/projects/uavsar/jemez/rasters/02122020_02192020/HH", full.names = TRUE)
files <-files[-4] # delete .int
files
stack_raw <-stack(files)
stack_raw # inspect
# resample the raster stack to the exact DEM resolution and extent, bc slightly off from so unknown reason (envi?)
# set extent first!
extent(stack_raw) <- extent(jemez_DEM)
stack_raw # check
stack <- resample(stack_raw, jemez_DEM, method='bilinear') #resample to dem resolution
stack #check
#pull out cor and make 0 NA
cor <-stack[[3]]
values(cor)[values(cor) == 0] = NA
plot(cor)
hist(cor)
# mask the stack with .cor
masked_stack <- mask(stack, cor, maskvalue = NA)
masked_stack
# pull out .unw for na convert
unw <-masked_stack[[4]]
values(unw)[values(unw) == 0] = NA
plot(unw)
hist(unw)
writeRaster(unw, "/Volumes/JT/projects/uavsar/jemez/anne/alamos_35915_20005.003_20008.000_0007d_s01_L090HH_01.unw.grd.tif")
# mask .cor raster .unw (takes out area where phase unwrapping algorithm breaks down)
cor_unw <-mask(cor, unw, maskvalue =NA)
plot(cor_unw)
hist(cor_unw)
#########################################################
### cor vs. unw plot
#########################################################
# dem with .unw
dem_unw <-mask(jemez_DEM, unw, maskvalue =NA)
plot(dem_unw)
hist(dem_unw)
# transform .cor and dem into df
unw_points <-as.data.frame(rasterToPoints(unw))
dem_unw_points <-as.data.frame(rasterToPoints(dem_unw))
# rename and bind columns
colnames(dem_unw_points)[3] <- "elevation" #change binded col name
colnames(unw_points)[3] <- "unwrapped_phase" #change binded col name
dem_unw_points <-cbind(dem_unw_points, unw_points$unwrapped_phase)
colnames(dem_unw_points)[4] <- "unwrapped_phase" #change binded col name
head(dem_unw_points)
#fwrite(dem_unw_points, "/Volumes/JT/projects/uavsar/jemez/dem_unw_HH_0212-0219.csv")
#dem_unw_points <-fread("/Volumes/JT/projects/uavsar/jemez/dem_unw_HH_0212-0219.csv")
#plot
theme_set(theme_light(base_size =11))
dem_unw_plot <-ggplot(dem_unw_points, aes(elevation, unwrapped_phase)) +
geom_hex(bins = 35) +
#scale_fill_viridis(option="magma")+
scale_fill_gradient(low = "grey96", high = "darkred") +
labs(title = "Jemez River Elevation vs. Unwrapped Phase 2/12-2/19 HH",
x = "Elevation (m)",
y = "Unwrapped Phase (radians)")
print(dem_unw_plot)
setwd("/Volumes/JT/projects/uavsar/jemez/scatter_plots/")
ggsave(dem_unw_plot,
file = "dem_unw_hex.png",
width = 6,
height = 4,
dpi = 400)
#########################################################
### cor vs. dem plot
#########################################################
# transform .cor and dem into df
masked_dem <-mask(jemez_DEM, cor, maskvalue = NA) # crop to slightly smaller .cor
cor_points <-as.data.frame(rasterToPoints(cor))
dem_points <-as.data.frame(rasterToPoints(masked_dem))
# rename and bind columns
colnames(dem_points)[3] <- "elevation" #change binded col name
colnames(cor_points)[3] <- "coherence" #change binded col name
cor_dem_points <-cbind(cor_points, dem_points$elevation)
colnames(cor_dem_points)[4] <- "elevation" #change binded col name
#fwrite(cor_dem_points, "/Volumes/JT/projects/uavsar/jemez/cor_dem_HH_0212-0219.csv")
cor_dem_points <-fread("/Volumes/JT/projects/uavsar/jemez/csv/cor_dem_HH_0212-0219.csv")
#plot
theme_set(theme_light(base_size =11))
p2 <-ggplot(cor_dem_points, aes(elevation, coherence)) +
geom_hex(bins = 25) +
#scale_fill_viridis(option="magma")+
scale_fill_gradient(low = "white", high = "black") +
labs(title = "Jemez River Elevation vs. Coherence 2/12-2/19 HH ",
x = "Elevation (m)",
y = "Coherence")
print(p2)
ggsave(p2,
file = "dem_cor_hex.png",
width = 6,
height = 4,
dpi = 400)
#########################################################
### cor vs. unw plot
#########################################################
# mask cor with unw
masked_cor <-mask(cor, unw, maskvalue = NA) # crop to slightly smaller .cor
plot(masked_cor)
# transform masked_cor in points
masked_cor_points <-as.data.frame(rasterToPoints(masked_cor))
# already have unw from previous work
# rename and bind columns
colnames(masked_cor_points)[3] <- "coherence" #change binded col name
unw_cor_points <-cbind(unw_points, masked_cor_points$coherence)
colnames(unw_cor_points)[4] <- "coherence" #change binded col name
#fwrite(unw_cor_points, "/Volumes/JT/projects/uavsar/jemez/unw_cor_HH_0212-0219.csv")
unw_cor_points <-fread("/Volumes/JT/projects/uavsar/jemez/unw_cor_HH_0212-0219.csv")
#plot
#theme_set(theme_light(base_size =11))
p3 <-ggplot(unw_cor_points, aes(coherence, unwrapped_phase)) +
geom_hex(bins = 25) +
#scale_fill_viridis(option="magma")+
scale_fill_gradient(low = "white", high = "darkgreen") +
scale_y_continuous(breaks = seq(-5,6,2))+
labs(title = "Jemez River Unwrapped Phase vs. Coherence 2/12-2/19 HH ",
x = "Coherence",
y = "Unwrapped Phase (radians)")+
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank())
print(p3)
ggsave(p3,
file = "unw_cor_hex.png",
width = 6,
height = 4,
dpi = 400)
#########################################################
### lon vs. unw plot
#########################################################
library(devtools)
source_gist("524eade46135f6348140")
unw_cor_points <-fread("/Volumes/JT/projects/uavsar/jemez/csv/unw_cor_HH_0212-0219.csv")
head(unw_cor_points)
colnames(unw_cor_points)[3] <- "unwrapped_phase"
unw_cor_points$graph_lon <-(unw_cor_points$x)-unw_cor_points$x[25530551]
unw_cor_points2 <-filter(unw_cor_points, unwrapped_phase >= -3, unwrapped_phase <= 5)
# plot
theme_set(theme_light(base_size =14))
p4 <-ggplot(unw_cor_points, aes(x, unwrapped_phase)) +
geom_hex(bins = 25) +
scale_fill_gradient(low = "white", high = "firebrick") +
stat_smooth_func2(geom="text",method="lm",hjust=0,parse=TRUE) +
geom_smooth(method = "lm", se = FALSE) +
#geom_abline(slope = coef(lm_fit)[[2]], intercept = coef(lm_fit)[[1]], size = 1)+
#scale_y_continuous(breaks = seq(-5,6,2))+
labs(#title = "Jemez River Unwrapped Phase vs. Longitude 2/12-2/19 HH",
x = "Longitude Change (deg)",
y = "Unwrapped Phase (radians)")+
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank())
print(p4)
ggsave(p4,
file = "unw_lon_hex_lm_labels.png",
width = 6,
height = 4,
dpi = 400)
model <- lm(unwrapped_phase ~ x, unw_cor_points)
coef(model)
#########################################################
### lon vs. elevation plot
#########################################################
cor_dem_points <-fread("/Volumes/JT/projects/uavsar/jemez/csv/cor_dem_HH_0212-0219.csv")
head(cor_dem_points)
#plot
#theme_set(theme_light(base_size =11))
p5 <-ggplot(cor_dem_points, aes(x, elevation)) +
geom_hex(bins = 25) +
#scale_fill_viridis(option="magma")+
scale_fill_gradient(low = "white", high = "goldenrod") +
labs(#title = "Jemez River Elevation (m) vs. Longitude 2/12-2/19 HH",
x = "Longitude (deg)",
y = "Elevation (m)") +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank())
print(p5)
ggsave(p5,
file = "ele_lon_hex2.png",
width = 6,
height = 4,
dpi = 400)