Project

General

Profile

« Previous | Next » 

Revision b02e39a0

Added by Jim Regetz over 13 years ago

  • ID b02e39a0b4de755bb216f9272065a6d838530cc1

added R code to create various boundary assessment figures

View differences:

terrain/aspect/aspect-assessment.R
61 61
# plot latitudinal profiles of RMSE
62 62
#
63 63

  
64
# simple helper function to calculate row-wise RMSEs
65
rmse <- function(r1, r2, na.rm=TRUE) {
66
    sqrt(rowMeans(as.matrix((r1 - r2)^2), na.rm=na.rm))
64
# simple helper function to calculate row-wise RMSEs, accounting for the
65
# fact that aspect values are circular (0-360), so the difference
66
# between e.g. 5 and 355 should only be 10
67
rmse <- function(r1, r2, na.rm=TRUE, use) {
68
    diffs <- abs(as.matrix(r1) - as.matrix(r2))
69
    if (!missing(use)) diffs[!use] <- NA
70
    diffs[] <- ifelse(diffs>180, 360-diffs, diffs)
71
    sqrt(rowMeans(diffs^2, na.rm=na.rm))
67 72
}
68 73

  
69 74
par(mfrow=c(2,3), omi=c(1,1,1,1))
70 75

  
71
ylim <- c(0, 170)
76
ylim <- c(0, 100)
72 77

  
73 78
# ...with respect to ASTER
74 79
plot(lats300, rmse(s.uncor, s.aster), type="l", xlab="Latitude",
......
117 122
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="gaussian blend")
118 123
abline(v=60, col="red", lty=2)
119 124

  
125
# close pdf device driver
126
dev.off()
127

  
128
stop("not doing correlations")
120 129

  
121 130
#
122 131
# plot latitudinal profiles of correlation coefficients
......
183 192
    ylab="Correlation", ylim=ylim)
184 193
text(min(lats300), min(ylim), pos=4, font=3, labels="gaussian blend")
185 194
abline(v=60, col="red", lty=2)
186

  
187
# close pdf device driver
188
dev.off()
terrain/dem/dem-assessment.R
1
# R code to plot latitudinal profiles of mean elevation, along with both
2
# RMSE and correlation coefficients comparing fused layers with both the
3
# raw ASTER and with the Canada DEM
4
#
5
# Jim Regetz
6
# NCEAS
7
# Created on 08-Jun-2011
8

  
9
library(raster)
10

  
11
datadir <- "/home/regetz/media/temp/terrain/dem"
12

  
13
# load elevation rasters
14
d.aster <- raster(file.path(datadir, "aster_300straddle.tif"))
15
d.srtm <- raster(file.path(datadir, "srtm_150below.tif"))
16
d.uncor <- raster(file.path(datadir, "fused_300straddle.tif"))
17
d.eramp <- raster(file.path(datadir, "fused_300straddle_rampexp.tif"))
18
d.bg <- raster(file.path(datadir, "fused_300straddle_blendgau.tif"))
19
d.can <- raster(file.path(datadir, "cdem_300straddle.tif"))
20

  
21
# extract raster latitudes for later
22
lats300 <- yFromRow(d.aster, 1:nrow(d.aster))
23
lats150 <- yFromRow(d.srtm, 1:nrow(d.srtm))
24

  
25
# initialize output pdf device driver
26
pdf("elevation-assessment.pdf", height=8, width=11.5)
27

  
28

  
29
#
30
# plot latitudinal profiles of mean elevation
31
#
32

  
33
par(mfrow=c(2,2), omi=c(1,1,1,1))
34

  
35
ylim <- c(550, 575)
36

  
37
plot(lats300, rowMeans(as.matrix(d.uncor), na.rm=TRUE), type="l",
38
    xlab="Latitude", ylab="Mean elevation", ylim=ylim)
39
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="uncorrected")
40
abline(v=60, col="red", lty=2)
41
mtext(expression(paste("Latitudinal profiles of mean elevation (",
42
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
43

  
44
plot(lats300, rowMeans(as.matrix(d.can), na.rm=TRUE), type="l",
45
    xlab="Latitude", ylab="Mean elevation", ylim=ylim)
46
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="Canada DEM")
47
abline(v=60, col="red", lty=2)
48

  
49
plot(lats300, rowMeans(as.matrix(d.eramp), na.rm=TRUE), type="l",
50
    xlab="Latitude", ylab="Mean elevation", ylim=ylim)
51
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="exponential ramp")
52
abline(v=60, col="red", lty=2)
53

  
54
plot(lats300, rowMeans(as.matrix(d.bg), na.rm=TRUE), type="l",
55
    xlab="Latitude", ylab="Mean elevation", ylim=ylim)
56
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="gaussian blend")
57
abline(v=60, col="red", lty=2)
58

  
59

  
60
#
61
# plot latitudinal profiles of RMSE
62
#
63

  
64
# simple helper function to calculate row-wise RMSEs
65
rmse <- function(r1, r2, na.rm=TRUE, use) {
66
    diffs <- abs(as.matrix(r1) - as.matrix(r2))
67
    if (!missing(use)) diffs[!use] <- NA
68
    sqrt(rowMeans(diffs^2, na.rm=na.rm))
69
}
70

  
71
par(mfrow=c(2,3), omi=c(1,1,1,1))
72

  
73
ylim <- c(0, 35)
74

  
75
# ...with respect to ASTER
76
plot(lats300, rmse(d.uncor, d.aster), type="l", xlab="Latitude",
77
    ylab="RMSE", ylim=ylim)
78
lines(lats150, rmse(crop(d.uncor, extent(d.srtm)), d.srtm), col="blue")
79
legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
80
    lty=c(1, 1), bty="n")
81
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="uncorrected")
82
abline(v=60, col="red", lty=2)
83
mtext(expression(paste(
84
    "Elevation discrepancies with respect to separate ASTER/SRTM components (",
85
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
86

  
87
plot(lats300, rmse(d.eramp, d.aster), type="l", xlab="Latitude",
88
    ylab="RMSE", ylim=ylim)
89
lines(lats150, rmse(crop(d.eramp, extent(d.srtm)), d.srtm), col="blue")
90
legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
91
    lty=c(1, 1), bty="n")
92
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="exponential ramp")
93
abline(v=60, col="red", lty=2)
94

  
95
plot(lats300, rmse(d.bg, d.aster), type="l", xlab="Latitude",
96
    ylab="RMSE", ylim=ylim)
97
lines(lats150, rmse(crop(d.bg, extent(d.srtm)), d.srtm), col="blue")
98
legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
99
    lty=c(1, 1), bty="n")
100
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="gaussian blend")
101
abline(v=60, col="red", lty=2)
102

  
103
# ...with respect to CDEM
104
plot(lats300, rmse(d.uncor, d.can), type="l", xlab="Latitude",
105
    ylab="RMSE", ylim=ylim)
106
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="uncorrected")
107
abline(v=60, col="red", lty=2)
108
mtext(expression(paste(
109
    "Elevation discrepancies with respect to Canada DEM (",
110
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
111

  
112
plot(lats300, rmse(d.eramp, d.can), type="l", xlab="Latitude",
113
    ylab="RMSE", ylim=ylim)
114
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="exponential ramp")
115
abline(v=60, col="red", lty=2)
116

  
117
plot(lats300, rmse(d.bg, d.can), type="l", xlab="Latitude",
118
    ylab="RMSE", ylim=ylim)
119
text(min(lats300), max(ylim)-1, pos=4, font=3, labels="gaussian blend")
120
abline(v=60, col="red", lty=2)
121

  
122

  
123
#
124
# plot latitudinal profiles of correlation coefficients
125
#
126

  
127
# simple helper function to calculate row-wise correlation coefficients
128
corByLat <- function(r1, r2, rows) {
129
    if (missing(rows)) {
130
        rows <- 1:nrow(r1)
131
    }
132
    m1 <- as.matrix(r1)
133
    m2 <- as.matrix(r2)
134
    sapply(rows, function(row) cor(m1[row,], m2[row,],
135
        use="pairwise.complete.obs"))
136
}
137

  
138
par(mfrow=c(2,3), omi=c(1,1,1,1))
139

  
140
ylim <- c(0.99, 1)
141

  
142
# ...with respect to ASTER
143
plot(lats300, corByLat(d.uncor, d.aster), type="l", xlab="Latitude",
144
    ylab="Correlation", ylim=ylim)
145
lines(lats150, corByLat(crop(d.uncor, extent(d.srtm)), d.srtm), col="blue")
146
legend("bottomright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
147
    lty=c(1, 1), bty="n")
148
text(min(lats300), min(ylim), pos=4, font=3, labels="uncorrected")
149
abline(v=60, col="red", lty=2)
150
mtext(expression(paste(
151
    "Elevation correlations with respect to separate ASTER/SRTM components (",
152
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
153

  
154
plot(lats300, corByLat(d.eramp, d.aster), type="l", xlab="Latitude",
155
    ylab="Correlation", ylim=ylim)
156
lines(lats150, corByLat(crop(d.eramp, extent(d.srtm)), d.srtm), col="blue")
157
legend("bottomright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
158
    lty=c(1, 1), bty="n")
159
text(min(lats300), min(ylim), pos=4, font=3, labels="exponential ramp")
160
abline(v=60, col="red", lty=2)
161

  
162
plot(lats300, corByLat(d.bg, d.aster), type="l", xlab="Latitude",
163
    ylab="Correlation", ylim=ylim)
164
lines(lats150, corByLat(crop(d.bg, extent(d.srtm)), d.srtm), col="blue")
165
legend("bottomright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
166
    lty=c(1, 1), bty="n")
167
text(min(lats300), min(ylim), pos=4, font=3, labels="gaussian blend")
168
abline(v=60, col="red", lty=2)
169

  
170
# ...with respect to CDEM
171
plot(lats300, corByLat(d.uncor, d.can), type="l", xlab="Latitude",
172
    ylab="Correlation", ylim=ylim)
173
text(min(lats300), min(ylim), pos=4, font=3, labels="uncorrected")
174
abline(v=60, col="red", lty=2)
175
mtext(expression(paste(
176
    "Elevation correlations with respect to Canada DEM (",
177
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
178

  
179
plot(lats300, corByLat(d.eramp, d.can), type="l", xlab="Latitude",
180
    ylab="Correlation", ylim=ylim)
181
text(min(lats300), min(ylim), pos=4, font=3, labels="exponential ramp")
182
abline(v=60, col="red", lty=2)
183

  
184
plot(lats300, corByLat(d.bg, d.can), type="l", xlab="Latitude",
185
    ylab="Correlation", ylim=ylim)
186
text(min(lats300), min(ylim), pos=4, font=3, labels="gaussian blend")
187
abline(v=60, col="red", lty=2)
188

  
189
# close pdf device driver
190
dev.off()
191

  
terrain/flow/flow-assessment.R
1
# R code to plot latitudinal profiles of mean flow direction, along with
2
# both RMSE and correlation coefficients comparing fused layers with
3
# both the raw ASTER and with the Canada DEM
4
#
5
# Jim Regetz
6
# NCEAS
7
# Created on 08-Jun-2011
8

  
9
library(raster)
10

  
11
datadir <- "/home/regetz/media/temp/terrain/flow"
12

  
13
# create function to recode values into degrees
14
recode <- function(r) {
15
    v <- values(r)
16
    v[v==0] <- NA
17
    v[v==1] <- 0
18
    v[v==2] <- 45
19
    v[v==3] <- 90
20
    v[v==4] <- 90
21
    v[v==8] <- 135
22
    v[v==16] <- 180
23
    v[v==32] <- 225
24
    v[v==64] <- 270
25
    v[v==128] <- 315
26
    r[] <- v
27
    return(r)
28
}
29

  
30
# load flow direction rasters, recoding on the fly
31
sfd.aster <- recode(raster(file.path(datadir, "aster_300straddle_sfd.tif")))
32
sfd.srtm <- recode(raster(file.path(datadir, "srtm_150below_sfd.tif")))
33
sfd.uncor <- recode(raster(file.path(datadir, "fused_300straddle_sfd.tif")))
34
#sfd.eramp <- recode(raster(file.path(datadir, "fused_300straddle_rampexp_sfd.tif")))
35
sfd.bg <- recode(raster(file.path(datadir, "fused_300straddle_blendgau_sfd.tif")))
36
sfd.can <- recode(raster(file.path(datadir, "cdem_300straddle_sfd.tif")))
37

  
38
# extract raster latitudes for later
39
lats300 <- yFromRow(sfd.aster, 1:nrow(sfd.aster))
40
lats150 <- yFromRow(sfd.srtm, 1:nrow(sfd.srtm))
41

  
42
# initialize output pdf device driver
43
pdf("flowdir-assessment.pdf", height=8, width=11.5)
44

  
45
#
46
# plot latitudinal profiles of mean flow direction
47
#
48

  
49
par(mfrow=c(2,2), omi=c(1,1,1,1))
50

  
51
ylim <- c(80, 280)
52

  
53
plot(lats300, rowMeans(as.matrix(sfd.uncor), na.rm=TRUE), type="l",
54
    xlab="Latitude", ylab="Mean flow direction", ylim=ylim)
55
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="uncorrected")
56
abline(v=60, col="red", lty=2)
57
mtext(expression(paste("Latitudinal profiles of mean flow direction (",
58
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
59

  
60
plot(lats300, rowMeans(as.matrix(sfd.can), na.rm=TRUE), type="l",
61
    xlab="Latitude", ylab="Mean flow direction", ylim=ylim)
62
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="Canada DEM")
63
abline(v=60, col="red", lty=2)
64

  
65
#plot(lats300, rowMeans(as.matrix(sfd.eramp), na.rm=TRUE), type="l",
66
plot(lats300, rowMeans(as.matrix(sfd.can), na.rm=TRUE), type="n",
67
    xlab="Latitude", ylab="Mean flow direction", ylim=ylim)
68
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="exponential ramp")
69
text(mean(lats300), mean(ylim), pos=1, font=3, labels="(skipped)")
70
#abline(v=60, col="red", lty=2)
71

  
72
plot(lats300, rowMeans(as.matrix(sfd.bg), na.rm=TRUE), type="l",
73
    xlab="Latitude", ylab="Mean flow direction", ylim=ylim)
74
text(min(lats300), min(ylim)+0.5, pos=4, font=3, labels="gaussian blend")
75
abline(v=60, col="red", lty=2)
76

  
77

  
78
#
79
# plot latitudinal profiles of RMSE
80
#
81

  
82
# simple helper function to calculate row-wise RMSEs, accounting for the
83
# fact that flow dir values are circular (0-360), so the difference
84
# between e.g. 5 and 355 should only be 10
85
rmse <- function(r1, r2, na.rm=TRUE, use) {
86
    diffs <- abs(as.matrix(r1) - as.matrix(r2))
87
    if (!missing(use)) diffs[!use] <- NA
88
    diffs[] <- ifelse(diffs>180, 360-diffs, diffs)
89
    sqrt(rowMeans(diffs^2, na.rm=na.rm))
90
}
91

  
92
par(mfrow=c(2,3), omi=c(1,1,1,1))
93

  
94
ylim <- c(0, 100)
95

  
96
# ...with respect to ASTER
97
plot(lats300, rmse(sfd.uncor, sfd.aster), type="l", xlab="Latitude",
98
    ylab="RMSE", ylim=ylim)
99
lines(lats150, rmse(crop(sfd.uncor, extent(sfd.srtm)), sfd.srtm), col="blue")
100
legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
101
    lty=c(1, 1), bty="n")
102
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="uncorrected")
103
abline(v=60, col="red", lty=2)
104
mtext(expression(paste(
105
    "Flowdir discrepancies with respect to separate ASTER/SRTM components (",
106
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
107

  
108
#plot(lats300, rmse(sfd.eramp, sfd.aster), type="l", xlab="Latitude",
109
plot(lats300, rep(0, 300), type="n", xlab="Latitude",
110
    ylab="RMSE", ylim=ylim)
111
#lines(lats150, rmse(crop(sfd.eramp, extent(sfd.srtm)), sfd.srtm), col="blue")
112
#legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
113
#    lty=c(1, 1), bty="n")
114
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="exponential ramp")
115
text(mean(lats300), mean(ylim), font=3, labels="(skipped)")
116
#abline(v=60, col="red", lty=2)
117

  
118
plot(lats300, rmse(sfd.bg, sfd.aster), type="l", xlab="Latitude",
119
    ylab="RMSE", ylim=ylim)
120
lines(lats150, rmse(crop(sfd.bg, extent(sfd.srtm)), sfd.srtm), col="blue")
121
legend("topright", legend=c("ASTER", "SRTM"), col=c("black", "blue"),
122
    lty=c(1, 1), bty="n")
123
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="gaussian blend")
124
abline(v=60, col="red", lty=2)
125

  
126
# ...with respect to CDEM
127
plot(lats300, rmse(sfd.uncor, sfd.can), type="l", xlab="Latitude",
128
    ylab="RMSE", ylim=ylim)
129
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="uncorrected")
130
abline(v=60, col="red", lty=2)
131
mtext(expression(paste(
132
    "Flowdir discrepancies with respect to Canada DEM (",
133
    136*degree, "W to ", 96*degree, "W)")), adj=0, line=2, font=2)
134

  
135
#plot(lats300, rmse(sfd.eramp, sfd.can), type="l", xlab="Latitude",
136
plot(lats300, rep(0, 300), type="n", xlab="Latitude",
137
    ylab="RMSE", ylim=ylim)
138
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="exponential ramp")
139
text(mean(lats300), mean(ylim), font=3, labels="(skipped)")
140
#abline(v=60, col="red", lty=2)
141

  
142
plot(lats300, rmse(sfd.bg, sfd.can), type="l", xlab="Latitude",
143
    ylab="RMSE", ylim=ylim)
144
text(min(lats300), max(ylim)-5, pos=4, font=3, labels="gaussian blend")
145
abline(v=60, col="red", lty=2)
146

  
147
# close pdf device driver
148
dev.off()
terrain/slope/slope-assessment.R
61 61
#
62 62

  
63 63
# simple helper function to calculate row-wise RMSEs
64
rmse <- function(r1, r2, na.rm=TRUE) {
65
    sqrt(rowMeans(as.matrix((r1 - r2)^2), na.rm=na.rm))
64
rmse <- function(r1, r2, na.rm=TRUE, use) {
65
    diffs <- abs(as.matrix(r1) - as.matrix(r2))
66
    if (!missing(use)) diffs[!use] <- NA
67
    sqrt(rowMeans(diffs^2, na.rm=na.rm))
66 68
}
67 69

  
68 70
par(mfrow=c(2,3), omi=c(1,1,1,1))

Also available in: Unified diff