LANDSAT VS SENTINEL VS PLANET

comparison.R

library(rgee)
library(rgeeExtra)

# Roy account
ee_Initialize("roy1")

# Load Planet, Sentinel-2, and Landsat-8
# ee_utils_dataset_display(planet)
planet <- ee$ImageCollection('projects/planet-nicfi/assets/basemaps/americas')
s2 <- ee$ImageCollection$Dataset$COPERNICUS_S2_SR
l8 <- ee$ImageCollection$Dataset$LANDSAT_LC08_C02_T1_L2

# Center Map
Map$setCenter(-77.03379, -12.06716, 16)

# Define img boundaries
geom <- ee$Geometry$Point(-77.03379, -12.06716)

# get a image from a city
planet_img <- planet[[20]]
date <- ee_get_date_img(planet_img)[["time_start"]] %>% as.Date()

s2_img <- s2 %>% 
  ee$ImageCollection$filterBounds(geom$buffer(10000)) %>%
  ee$ImageCollection$filterDate(as.character(date - 100), as.character(date + 100)) %>% 
  ee$ImageCollection$filter(ee$Filter$lt('CLOUDY_PIXEL_PERCENTAGE', 1)) %>% 
  '[['(1)


l8_img <- l8 %>% 
  ee$ImageCollection$filterBounds(geom$buffer(10000)) %>%
  ee$ImageCollection$filterDate(as.character(date - 100), as.character(date + 100)) %>% 
  ee$ImageCollection$filter(ee$Filter$lt('CLOUD_COVER', 5)) %>% 
  '[['(1)

Map$setCenter(-77.02931, -12.05557, 13)
m1 <- Map$addLayer(planet_img, list(gain = 0.15, bands = list("R", "G", "B")))
m2 <- Map$addLayer(s2_img, list(max = 6000, bands = list("B4", "B3", "B2")))
m3 <- Map$addLayer(l8_img, list(max = 20000, bands = list("SR_B4", "SR_B3", "SR_B2")))
m1 | m2
m1 | m3
names(img22)