On Sun, 4 Dec 2022, Nikolaos Tziokas wrote:
I have two raster layers, one coarse resolution and one fine resolution. My
goal is to extract GWR's coefficients (intercept and slope) and apply them
to my fine resolution raster.
You are making life too complicated, just use the regression.points =
argument to gwr.basic():
library(GWmodel)
library(raster)
tirs0 = terra::rast(ncols=407, nrows=342, nlyrs=1, xmin=509600,
xmax=550300, ymin=161800, ymax=196000, names=c('tirs0'),
crs='EPSG:27700')
tirs1 <- raster(tirs0)
regpoints <- as(tirs1, "SpatialPoints")
summary(regpoints)
block.data = read.csv(file = "block.data00.csv")
coordinates(block.data) <- c("x", "y")
proj4string(block.data) <- "EPSG:27700"
summary(block.data)
eq1 <- ntl ~ tirs
abw = bw.gwr(eq1, data = block.data, approach = "AIC", kernel = "tricube",
adaptive = TRUE, p = 2)
ab_gwr = gwr.basic(eq1, data = block.data, regression.points = regpoints,
bw = abw, kernel = "tricube", adaptive = TRUE, p = 2, F123.test = FALSE,
cv = FALSE)
ab_gwr
summary(ab_gwr$SDF)
The final multiplication can be done with your actual tirs raster, which
was not provided.
With the small number of input points, a geostatistical approach to
prediction would be preferable to GWR, giving well-founded prediction
standard errors.
Hope this clarifies,
Roger
I can do this easily when I perform simple linear regression. For example:
library(terra)
library(sp)
# focal terra
tirs = rast("path/tirs.tif") # fine res raster
ntl = rast("path/ntl.tif") # coarse res raster
# fill null values
tirs = focal(tirs,
w = 9,
fun = mean,
na.policy = "only",
na.rm = TRUE)
gf <- focalMat(tirs, 0.10*400, "Gauss", 11)
r_gf <- focal(tirs, w = gf, na.rm = TRUE)
r_gf = resample(r_gf, ntl, method = "bilinear")
s = c(ntl, r_gf)names(s) = c('ntl', 'r_gf')
model <- lm(formula = ntl ~ tirs, data = s)
# apply the lm coefficients to the fine res raster
lm_pred = model$coefficients[1] + model$coefficients[2] * tirs
But when I run GWR, the slope and intercept are not just two numbers (like
in linear model) but it's a range. For example, below are the results of
the GWR:
*Summary of GWR coefficient estimates*:
Min. 1st Qu. Median 3rd Qu. Max.
Intercept -1632.61196 -55.79680 -15.99683 15.01596 1133.299
tirs20 -42.43020 0.43446 1.80026 3.75802 70.987
My question is how can extract GWR model parameters (intercept and slope)
and apply them to my fine resolution raster? In the end I would like to do
the same thing as I did with the linear model, that is, *GWR_intercept +
GWR_slope * fine resolution raster*.
Here is the code of GWR:
library(GWmodel)
library(raster)
block.data = read.csv(file = "path/block.data00.csv")
#create mararate df for the x & y coords
x = as.data.frame(block.data$x)
y = as.data.frame(block.data$y)
sint = as.matrix(cbind(x, y))
#convert the data to spatialPointsdf and then to spatialPixelsdf
coordinates(block.data) = c("x", "y")#gridded(block.data) <- TRUE
# specify a model equation
eq1 <- ntl ~ tirs
dist = GWmodel::gw.dist(dp.locat = sint, focus = 0, longlat = FALSE)
abw = bw.gwr(eq1,
data = block.data,
approach = "AIC",
kernel = "tricube",
adaptive = TRUE,
p = 2,
longlat = F,
dMat = dist,
parallel.method = "omp",
parallel.arg = "omp")
ab_gwr = gwr.basic(eq1,
data = block.data,
bw = abw,
kernel = "tricube",
adaptive = TRUE,
p = 2,
longlat = FALSE,
dMat = dist,
F123.test = FALSE,
cv = FALSE,
parallel.method = "omp",
parallel.arg = "omp")
ab_gwr
You can download the csv from here
<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdrive.google.com%2Fdrive%2Ffolders%2F1V115zpdU2-5fXssI6iWv_F6aNu4E5qA7%3Fusp%3Dsharing&data=05%7C01%7CRoger.Bivand%40nhh.no%7C6855c5767a894cdb4edf08dad609d991%7C33a15b2f849941998d56f20b5aa91af2%7C0%7C0%7C638057635036324587%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ROLhw75M%2BvWhGOIT7mlyPfNZX2W0Ub4gMHgrTBVsd8A%3D&reserved=0>.
The fine resolution raster I am using:
tirs = rast(ncols=407, nrows=342, nlyrs=1, xmin=509600, xmax=550300,
ymin=161800, ymax=196000, names=c('tirs'), crs='EPSG:27700')
--
Roger Bivand
Emeritus Professor
Department of Economics, Norwegian School of Economics,
Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
e-mail: roger.biv...@nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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