Are the NDVI frequency distributions different between the whole geography and the tourism predios?
Load libraries and set some options.
library(sf) # Simple Features for R
library(terra) # Spatial Data Analysis
library(mapview) # Interactive Viewing of Spatial Data in R
library(grateful) # Facilitate Citation of R Packages
library (ggplot2) # easy graphs in R
library(dplyr) # filter sf
options(scipen=99999)
options(max.print=99999)
options(stringsAsFactors=F)NDVI_full_montes <- rast("C:/Users/usuario/Downloads/Indice_NDVI_GeografiaMontesMaria_2023.tif")
# plot(NDVI_full_montes)predios <- st_read("C:/CodigoR/Municipios_DN/shp/predios/PrediosDNA.shp")Reading layer PrediosDNA' from data sourceC:_DN.shp’ using driver `ESRI Shapefile’ Simple feature collection with 491 features and 20 fields Geometry type: MULTIPOLYGON Dimension: XY Bounding box: xmin: -81.61475 ymin: 0.2220508 xmax: -72.04356 ymax: 11.35795 Geodetic CRS: WGS 84
slectedpredios <- predios |> filter(GEOGRAFIA=="MONTES DE MARIA")
a1 <- aggregate(NDVI_full_montes, 10) #agregate to easy viewmapview(a1) + mapview(slectedpredios)
NDVI_predios <- terra::extract(NDVI_full_montes, predios, xy=TRUE)# convert raster to dataframe
full_montes_df <- as.data.frame(NDVI_full_montes, xy = TRUE) # this works with Raster* objects as well
p<-ggplot(full_montes_df, aes(x=NDVI)) +
geom_histogram(color="black", fill="white", bins =100)
p
q<-ggplot(NDVI_predios, aes(x=NDVI)) +
geom_histogram(color="black", fill="white", bins =100)
q
pkgs <- cite_packages(output = "paragraph", out.dir = ".")
knitr::kable(pkgs)| x |
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| We used R version 4.3.2 (R Core Team 2023) and the following R packages: knitr v. 1.46 (Xie 2014, 2015, 2024), mapview v. 2.11.2 (Appelhans et al. 2023), rmarkdown v. 2.27 (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020; Allaire et al. 2024), sf v. 1.0.15 (Pebesma 2018; Pebesma and Bivand 2023), terra v. 1.7.71 (Hijmans 2024), tidyverse v. 2.0.0 (Wickham et al. 2019). |
# pkgssessionInfo()
#> R version 4.3.2 (2023-10-31 ucrt)
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#> attached base packages:
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#> other attached packages:
#> [1] dplyr_1.1.4 ggplot2_3.5.1 grateful_0.2.4 mapview_2.11.2 terra_1.7-71
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author = {},
url = {https://dlizcano.github.io/NDVIhist/},
langid = {en}
}