Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
eval = FALSE,
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
# library(rsat)
# set_credentials("rsat.package","UpnaSSG.2021")
## ----search_review------------------------------------------------------------
# ip <- st_sf(st_as_sfc(st_bbox(c(
# xmin = -9.755859,
# xmax = 4.746094,
# ymin = 35.91557,
# ymax = 44.02201
# ), crs = 4326)))
# toi <- seq(as.Date("2021-01-10"),as.Date("2021-01-15"),1)
## -----------------------------------------------------------------------------
# db.path <- file.path(tempdir(),"database")
# ds.path <- file.path(tempdir(),"datasets")
# dir.create(db.path)
# dir.create(ds.path)
## -----------------------------------------------------------------------------
# filomena <- new_rtoi(name = "filomena",
# region = ip,
# db_path = db.path,
# rtoi_path = ds.path)
## -----------------------------------------------------------------------------
# rsat_search(region = filomena, product = c("mod09ga"), dates = toi)
## -----------------------------------------------------------------------------
# rsat_download(filomena)
## ---- eval=FALSE--------------------------------------------------------------
# rsat_mosaic(filomena)
## ---- eval=FALSE--------------------------------------------------------------
# list.files(file.path(ds.path, "filomena", "Modis/mod09ga/mosaic"), full.name = TRUE)
## -----------------------------------------------------------------------------
# plot(filomena, as.Date("2021-01-11"))
## -----------------------------------------------------------------------------
# plot(filomena, as.Date("2021-01-11"),xsize = 500, ysize = 500)
## -----------------------------------------------------------------------------
# plot(filomena,
# as.Date("2021-01-11"),
# xsize = 500,
# ysize = 500,
# band_name = c("swir1", "nir", "blue"))
## ----basic_ndsi, eval = FALSE-------------------------------------------------
# NDSI = function(green, swir1){
# ndsi <- (green - swir1)/(green + swir1)
# return(ndsi)
# }
## ----basic_variables----------------------------------------------------------
# show_variables()
## ----basic_derive, eval = FALSE-----------------------------------------------
# rsat_derive(filomena, product = "mod09ga", variable = "ndsi", fun = NDSI)
## -----------------------------------------------------------------------------
# plot(filomena,
# as.Date("2021-01-11"),
# variable = "ndsi",
# xsize = 500,
# ysize = 500,
# zlim = c(-1,1))
## ----basic_cloud, eval=FALSE--------------------------------------------------
# rsat_cloudMask(filomena)
## ----basic_ndsi_import, eval = FALSE------------------------------------------
# ndsi.img <- rsat_get_raster(filomena, "mod09ga", "ndsi")
# ndsi.img <- clamp(ndsi.img, -1, 1)
## ----basic_mask, eval = FALSE-------------------------------------------------
# clds.msk <- rsat_get_raster(filomena, "mod09ga", "CloudMask")
## ----basic_mask_resample------------------------------------------------------
# clds.msk <- resample(clds.msk, ndsi.img, method = "ngb")
## ----basic_mask_apply---------------------------------------------------------
# ndsi.filt <- ndsi.img * clds.msk
# names(ndsi.filt) <- names(clds.msk) # keep the names
## ----basic_composite----------------------------------------------------------
# snow.spain <- calc(ndsi.filt, max, na.rm = TRUE)
## ----basic_ndsi_map-----------------------------------------------------------
# library(tmap)
# tm_shape(snow.spain) + tm_raster(style = "cont")
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