| Title: | Projecting Satellite-Derived Phenology in Space | 
| Version: | 2.0.1 | 
| Date: | 2023-10-12 | 
| Maintainer: | Christian John <cjohn@ucsb.edu> | 
| Depends: | R (≥ 4.1.0) | 
| Imports: | phenex, plyr, stringr, terra, doParallel | 
| Description: | This takes in a series of multi-layer raster files and returns a phenology projection raster, following methodologies described in John (2016) https://etda.libraries.psu.edu/catalog/13521clj5135. | 
| License: | GPL-3 | 
| URL: | https://github.com/JepsonNomad/phenomap | 
| BugReports: | https://github.com/JepsonNomad/phenomap/issues | 
| RoxygenNote: | 7.1.2 | 
| NeedsCompilation: | no | 
| Packaged: | 2023-10-12 21:22:27 UTC; christianjohn | 
| Author: | Christian John [aut, cre] | 
| Repository: | CRAN | 
| Date/Publication: | 2023-10-12 22:20:09 UTC | 
Convert a series of raster files to a single phenology raster.
Description
Convert a series of raster files to a single phenology raster.
Usage
mapPheno(
  File_List = NA,
  PhenoFactor = NA,
  phase = NA,
  threshold = NA,
  year = NA,
  NDVI = NA,
  VIQ = NA,
  DOY = NA,
  PR = NA,
  SnowExtent = NA,
  verbose = FALSE
)
Arguments
| File_List | List of raster files | 
| PhenoFactor | Character string; type of dataset to analyze (e.g., "VI", "Snow") | 
| phase | Character string; name of phenophase to be measured (e.g., "greenup", "snowmelt", "senescence" or other arguments passed to phenex::phenophase()) | 
| threshold | Float threshold GWI value to be projected. Use only for VI option. | 
| year | Integer Year (YYYY) | 
| NDVI | Integer Band number of NDVI band in raster files | 
| VIQ | Integer Band number of VI Quality layer in raster files | 
| DOY | Integer Band number of Composite Day of Year layer in raster files | 
| PR | Integer Band Number of PR layer in raster files | 
| SnowExtent | Integer Band number of Maximum_Snow_Extent in raster files | 
| verbose | TRUE or FALSE (Default = FALSE) | 
Value
Raster object with extent=extent(terra::rast(File_List)[1]) and CRS = crs(terra::rast(File_List)[1]). Digital numbers are expressed as Day of Year.
Examples
## Not run: 
fpath <- system.file("extdata", package="phenomap")
File_List <- paste(fpath, list.files(path = fpath, pattern=c("TinyCrop_")), sep="/")
File_List
PhenoFactor = "VI"
phase = "greenup"
threshold = 0.5
year = 2016
NDVI = 1
VIQ = 3
DOY = 4
PR = 5
verbose = TRUE
Sample.Greenup <- mapPheno(File_List = File_List, PhenoFactor = PhenoFactor,
                           phase = phase, threshold = threshold, year = year,
                           NDVI = NDVI, VIQ = VIQ, DOY = DOY, PR = PR,
                           SnowExtent=SnowExtent,
                           verbose = verbose)
## End(Not run)
Convert a series of phenology terra::raster files to a single long-term trend terra::raster.
Description
Convert a series of phenology terra::raster files to a single long-term trend terra::raster.
Usage
mapTrend(
  File_List,
  Year_List,
  parallel = FALSE,
  n.cores = NULL,
  verbose = FALSE
)
Arguments
| File_List | List of phenology terra::raster files (i.e. those produced in 'mapPheno') | 
| Year_List | Vector of Integer Year (YYYY) with length > 5 | 
| parallel | TRUE or FALSE (Default = FALSE) if TRUE, use parallel backend through plyr::aaply | 
| n.cores | Integer number of cores to be used for parallel processing (only use if parallel = TRUE) | 
| verbose | TRUE or FALSE (Default = FALSE) | 
Value
terra::raster object with extent=ext(rast(File_List)[1]) and CRS = crs(rast(File_List)[1]). Layer 1 is the slope estimate of the linear model relating green-up timing (Day of Year) to time (Year). Layer 2 is the p-value of the slope estimate. Layer 3 is the standard error of the slope estimate. Layer 4 is the r-squared value for the linear model.
Examples
## Not run: 
fpath <- system.file("extdata", package="phenomap")
File_List.Trend <- paste(fpath, list.files(path = fpath, pattern=c("Sample_Greenup_")), sep="/")
Year_List <- 2011:2016 # Tell it what years you're using
n.cores <- 4 # Set up parallel computing
phenotrend <- mapTrend(File_List = File_List.Trend,
                             Year_List = Year_List,
                             parallel = TRUE,
                             n.cores = n.cores,
                             verbose=TRUE)
## End(Not run)