Calculate Soil Moisture, Polynomial Fitted Curve

Prepare soil moisture grid from STR and VI images for a single date, based on polynomial function fitted to trapezoid edges.

Usage

polynomial_soil_moisture(coeffs, VI, STR)

Arguments

coeffs,

list, 6 trapezoid coefficients

VI,

terra rast, the vegetation index raster

STR,

terra rast, the STR raster

Value

rast, soil moisture grid

Note

This function is used after preparing the OPTRAM model coefficients with: optram_wetdry_coefficients. Typically a new image date, (that was not used for preparing the model), will be referenced in the img_date parameter. The resulting soil moisture raster is saved to output_dir This function implements an polynomial fitted curve, following: Ma, Chunfeng, Kasper Johansen, and Matthew F. McCabe. 2022. “Combining Sentinel-2 Data with an Optical-Trapezoid Approach to Infer within-Field Soil Moisture Variability and Monitor Agricultural Production Stages.” Agricultural Water Management 274 (December): 107942. doi:10.1016/j.agwat.2022.107942 .

Examples

img_date <- "2023-03-11"
VI_dir <- system.file("extdata", "NDVI", package = "rOPTRAM")
STR_dir <- system.file("extdata", "STR", package = "rOPTRAM")
optram_options("trapezoid_method", "polynomial")
#> 
#> Option for: trapezoid_method set to: polynomial
#> [1] "SWIR_band = 11"
#> [1] "edge_points = TRUE"
#> [1] "feature_col = ID"
#> [1] "max_cloud = 12"
#> [1] "max_tbl_size = 1e+06"
#> [1] "only_vi_str = FALSE"
#> [1] "overwrite = FALSE"
#> [1] "period = full"
#> [1] "plot_colors = no"
#> [1] "remote = scihub"
#> [1] "rm.hi.str = FALSE"
#> [1] "rm.low.vi = FALSE"
#> [1] "scm_mask = TRUE"
#> [1] "tileid = NA"
#> [1] "trapezoid_method = polynomial"
#> [1] "veg_index = NDVI"
#> [1] "vi_step = 0.005"
SM <- optram_calculate_soil_moisture(img_date,
                          VI_dir, STR_dir,
                          data_dir = tempdir())
#> Multiple tiles created: 
#> /tmp/RtmpiNiEcu/soil_moisture_2023-03-11_T36RXV.tif/tmp/RtmpiNiEcu/soil_moisture_2023-03-11_T36SXA.tif