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Create Scatter Plot of STR-NDVI Data Points,

Source: R/optram_wetdry_coefficients.R
plot_vi_str_cloud.Rd

Plot STR-NDVI scatterplot to show dry and wet trapezoid lines over scatterplot of multi-temporal STR and NDVI pixel values

Usage

plot_vi_str_cloud(full_df, edges_df, edge_points = FALSE)

Arguments

full_df,

data.frame of NDVI and STR pixel values

edges_df,

data.frame, points along the wet/dry edges for trapezoid

edge_points,

boolean, whether to add to the plot the linear regression points that were used to derive coefficients. default FALSE

Value

ggplot object

Note

Points in scatter plot can be colored in various ways, depending on the plot_colors option, as set in optram_options() If "plot_colors = none" all points are colored green. If "plot_colors = density" points are colored by point density on the plot. If "plot_colors = contour" points are colored green and density contour lines are overlayed If "plot_colors = feature" points are colored by some feature ID in the original AOI polygon. If "plot_colors = month" points are colored by the month of image acquisition.

Examples

aoi_name <- "Soil Moisture AOI"
optram_options("trapezoid_method", "polynomial")
#> 
#> New option for trapezoid_method applied.
#> [1] "SWIR_band = 11"
#> [1] "edge_points = TRUE"
#> [1] "feature_col = ID"
#> [1] "max_cloud = 12"
#> [1] "max_tbl_size = 1e+06"
#> [1] "period = full"
#> [1] "plot_colors = no"
#> [1] "remote = scihub"
#> [1] "rm.hi.str = FALSE"
#> [1] "rm.low.vi = FALSE"
#> [1] "trapezoid_method = polynomial"
#> [1] "veg_index = NDVI"
#> [1] "vi_step = 0.005"
full_df <- readRDS(system.file("extdata", "VI_STR_data.rds",
        package = "rOPTRAM"))
edges_df <- read.csv(system.file("extdata", "trapezoid_edges_lin.csv",
                        package = "rOPTRAM"))
pl <- plot_vi_str_cloud(full_df, edges_df)
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).

pl + ggplot2::ggtitle(paste("Trapezoid plot for:", aoi_name))
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).

pl
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> Warning: Removed 80 rows containing missing values or values outside the scale range
#> (`geom_point()`).