knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
suppressMessages(library(dplyr))
suppressMessages(library(raster))
suppressMessages(library(rgdal))
suppressMessages(library(sits.prodes))
suppressMessages(library(sits.starfm))

base_path <- "/home/alber/Documents/data/experiments/prodes_reproduction"
#data("BRICK_HLS_IMAGES", package = "sits.starfm")
BRICK_HLS_IMAGES <- "/home/alber/Documents/data/experiments/prodes_reproduction/data/raster/harmonized_landsat_sentinel2/data/hls" %>%
    sits.starfm::build_hls_tibble(pattern = "*hdf$", 
                                  prodes_year_start = "-08-01")

Image documentation.

Spatial extent

img_extent <- BRICK_HLS_IMAGES %>% 
    dplyr::group_by(product, tile) %>% 
    dplyr::slice(1) %>% 
    dplyr::pull(img_extent)
map_bz <- ggplot2::ggplot(data = rnaturalearth::ne_countries(scale = "small", 
                                                             returnclass = "sf")) +
    ggplot2::geom_sf() +
    ggplot2::coord_sf(xlim = c(-74, -34), ylim = c(-34, 6), expand = FALSE) +
    ggplot2::labs(title = "HLS images.")
for (i_ext in img_extent) {
  map_bz <- map_bz + ggplot2::geom_rect(xmin = i_ext[["xmin"]], 
                                        xmax = i_ext[["xmax"]], 
                                        ymin = i_ext[["ymin"]], 
                                        ymax = i_ext[["ymax"]], 
                                        fill = NA, colour = "black", size = 1.0)
}
print(map_bz)

Temporal extent

img_date <- pdoy <- product <- sensing_date <- tile_id <- tile_product <- NULL

id_tb <- BRICK_HLS_IMAGES %>% 
    dplyr::select(tile, product) %>% 
    dplyr::distinct() %>% 
    dplyr::mutate(tile_id = as.integer(1:n()),
                  tile_product = paste(tile, product, sep = "_"))

sits.starfm:::BRICK_HLS_IMAGES %>% 
#dplyr::filter(product == "S30", tile == "T19LFJ", pyear == 2017) %>%
#View()    
    dplyr::left_join(id_tb, by = c("product", "tile")) %>% 
    dplyr::mutate(start_pyear = as.Date(paste(pyear - 1, "08", "01", sep = "-")), 
                  pdoy = as.integer(img_date - start_pyear)) %>% 
    dplyr::arrange(img_date) %>% 
    ggplot2::ggplot(ggplot2::aes(x = pdoy, y = tile_id, 
                                 color = product)) + 
    ggplot2::geom_point(size = 0.5) +
    ggplot2::labs(x = "Day of the PRODES year", y = "") +
    ggplot2::theme(axis.title.y = ggplot2::element_blank(),
                   axis.text.y = ggplot2::element_blank(),
                   axis.ticks.y = ggplot2::element_blank(), 
                   axis.text.x = ggplot2::element_text(angle = 90, hjust = 1)) + 
    ggplot2::facet_grid(tile ~ pyear) + 
    ggplot2::ggtitle("Number of HLS images")
# BRICK_HLS_IMAGES %>% 
#     dplyr::left_join(id_tb, by = c("product", "tile")) %>% 
#     dplyr::arrange(img_date) %>% 
#     ggplot2::ggplot(ggplot2::aes(x = img_date, y = tile_id, 
#                                  color = tile_product)) + 
#     ggplot2::geom_point() +
#     ggplot2::labs(x = "Image date", y = "") +
#     ggplot2::theme(axis.title.y = ggplot2::element_blank(),
#                    axis.text.y = ggplot2::element_blank(),
#                    axis.ticks.y = ggplot2::element_blank(), 
#                    axis.text.x = ggplot2::element_text(angle = 90, hjust = 1)) + 
#     ggplot2::facet_grid(tile_product ~ 1) + 
#     ggplot2::ggtitle("Number of HLS images")

Number of images

suppressWarnings(
    BRICK_HLS_IMAGES %>% 
        dplyr::group_by(product, tile, pyear) %>% 
        dplyr::summarise(n_imgs = n()) %>% 
        knitr::kable(digits = 0, row.names = TRUE, full_width = TRUE, 
                     caption = "Number of HLS images per PRODES year.") %>% 
        kableExtra::kable_styling()
)

References.



albhasan/sits.prodes documentation built on Feb. 25, 2020, 11:46 p.m.