In kongdd/PhenoAsync: Extract Remote Sensing Vegetation Phenology

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dir_prj <- "G:/Github/phenology/phenofit"
setwd(dir_prj)

source('inst/shiny/check_season/global.R')
source("test/stable/load_pkgs.R")
source("test/phenology_async/R/s1_materials/main_phenofit.R")
load("data_test/phenoflux115_gs.rda")

2.3 Curve fitting

test one site first

sitename <- c("AU-Stp", "IT-Noe", 'US-Syv', 'US-WCr')[1]#,"CA-Man"

d   <- df[site == sitename, .(t = date, GPP_DT, GPP_NT, w = 1)] #%T>% plotdata(365)
d$y <- rowMeans(d[, .(GPP_DT, GPP_NT)], na.rm = T)
d[y < 0, y := 0] # for GPP_NT

sp      <- st[site == sitename, ]

# parameters for season_3y
threshold_max = 0.1
nf = 1
INPUT <- get_input(df, st, sitename)

wFUN <- wTSM
i <- grep(sitename, sites)
brks2 <- brks_lst[[i]]

fit  <- curvefits(INPUT, brks2,
                  methods = c("AG", "zhang", "beck", "elmore"), #,"klos",, 'Gu'
                  debug = F, 
                  wFUN = wFUN,
                  nextent = 5, maxExtendMonth = 3, minExtendMonth = 1/3,
                  qc = as.numeric(dnew$SummaryQA), minPercValid = 0.2,
                  print = print)
fit$INPUT   <- INPUT
fit$seasons <- brks2

## check the curve fitting parameters
params <- getparam(fit)
print(str(params, 1))
print(params$AG)

## Get GOF information
stat  <- ldply(fit$fits, function(fits_meth){
    ldply(fits_meth, statistic.phenofit, .id = "flag")
}, .id = "meth")
fit$stat <- stat
print(head(stat))

# print(fit$fits$AG$`2002_1`$ws)
## visualization
# svg("Figure1_phenofit_curve_fitting.svg", 11, 7)
# Cairo::CairoPDF(file_pdf, 11, 6) #
# dev.off()
g <- plot_phenofit(fit, d, INPUT$titlestr)
grid::grid.newpage(); grid::grid.draw(g)# plot to check the curve fitting

source("test/phenology_async/R/s1_materials/main_phenofit.R")

debug <- T
if (debug){
    sites0   <- c("AU-Stp", "IT-Noe", 'US-Syv', 'US-WCr')
    subfix <- "_part"
} else {
    sites0   <- st$site
    subfix <- ""
}

file <- sprintf("Figures3_phenofit_GPPobs_v0.1.1.pdf", subfix) 
CairoPDF(file, 12, 7)
fits <- llply(sites0, get_phenofit, df, st, brks_lst, sites, wFUN = 'wTSM', 
              .progress = "text")
dev.off()
# fit <- get_phenofit(i, df, st, brks_lst, sites, 'wTSM')