R/Func_landcover.R
In SHUD-System/SHUDtoolbox: Toolbox For SHUD Model System
Defines functions
lc.GLC
lc.NLCD
lc.UMD
lc_EQ
LaiRf.GLC
LaiRf.NLCD
Documented in
LaiRf.GLC
LaiRf.NLCD
lc_EQ
lc.GLC
lc.NLCD
lc.UMD
#' Generate the default LAI and Roughness Length
#' \code{LaiRf.NLCD}
#' @param lc land classe codes
#' @param years numeric years.
#' @param class The classification of the Landuse of NLCD
#' @return Default LaiRf.NLCD parameters, a list $LAI, $RL
#' @export
#' @examples
#' lc = c(43, 23, 81, 11)
#' lr=LaiRf.NLCD(lc, years=2000:2001)
#' par(mfrow=c(2,1))
#' col=1:length(lc)
#' plot(lr$LAI, col=col, main='LAI');
#' legend('top', paste0(lc), col=col, lwd=1)
#' plot(lr$RL, col=col, main='Roughness Length');
#' legend('top', paste0(lc), col=col, lwd=1)
LaiRf.NLCD <- function(lc, years=2000){
# http://glcf.umiacs.umd.edu/data/landcover/
rltbl =matrix(c(
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112,
2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653,
1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112,
0.52, 0.52, 0.666, 0.91, 1.031, 1.044, 1.042, 1.037, 1.036, 0.917, 0.666, 0.52,
0.816, 0.8115, 0.877, 0.996, 1.0535, 1.056, 1.0575, 1.058, 1.059, 1.0025, 0.8845, 0.816,
0.7602524, 0.7551426, 0.7772204, 0.8250124, 0.846955, 0.8449668, 0.8471342, 0.8496604, 0.8514252, 0.8299022, 0.7857734, 0.7602744,
0.35090494, 0.34920916, 0.36891486, 0.40567288, 0.42336056, 0.42338372, 0.42328378, 0.42485112, 0.42631836, 0.40881268, 0.37218526, 0.35096866,
0.05641527, 0.05645892, 0.05557872, 0.05430207, 0.05425842, 0.05399002, 0.05361482, 0.0572041, 0.05892068, 0.05821407, 0.05709462, 0.05645892,
0.03699235, 0.03699634, 0.03528634, 0.03272533, 0.03272134, 0.03270066, 0.03268178, 0.03907616, 0.04149324, 0.04032533, 0.03823134, 0.03699634,
0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778,
0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778,
0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112,
0.1947138, 0.19413424, 0.20831414, 0.23348558, 0.24574614, 0.24605016, 0.24538258, 0.24630454, 0.247455, 0.23527388, 0.20963734, 0.19478494
), ncol =14, nrow=12)
laitbl = matrix(c(
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76,
5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117,
8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76,
0.52, 0.52, 0.867, 2.107, 4.507, 6.773, 7.173, 6.507, 5.04, 2.173, 0.867, 0.52,
4.64, 4.84, 5.347, 6.1, 7.4335, 8.7665, 8.833, 8.367, 7.5665, 6, 5.0135, 4.64,
5.276088, 5.528588, 6.006132, 6.4425972, 7.2448806, 8.3639474, 8.540044, 8.126544, 7.2533006, 6.3291908, 5.6258086, 5.300508,
2.3331824, 2.4821116, 2.7266101, 3.0330155, 3.8849492, 5.5212224, 6.2395131, 5.7733017, 4.1556703, 3.1274641, 2.6180116, 2.4039116 ,
0.580555, 0.6290065, 0.628558, 0.628546, 0.919255, 1.7685454, 2.5506969, 2.5535975, 1.7286418, 0.9703975, 0.726358, 0.6290065 ,
0.3999679, 0.4043968, 0.3138257, 0.2232945, 0.2498679, 0.3300675, 0.4323964, 0.7999234, 1.1668827, 0.7977234, 0.5038257, 0.4043968,
0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893,
0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893,
0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001 ,
1.2867143, 1.3945997, 1.5506977, 1.7727263, 2.5190228, 4.1367678, 5.0212291, 4.5795799, 2.8484358, 1.8856229, 1.5178736, 1.3656797
),
ncol = 14, nrow = 12)
years=sort(c(years, max(years, na.rm=TRUE)+1), decreasing = FALSE)
nlc = length(lc)
ny = length(years)
ym = rbind(expand.grid(1:12, years), c(1, max(years)+1) )
tstr = paste(ym[,2], ym[,1], '01', sep='-')
tday = zoo::as.Date(tstr)
mlai = NULL
mrl = NULL
for (i in 1:nlc){
ilc= lc[i]
lai = lc_EQ(laitbl, ilc)
rl = lc_EQ (rltbl, ilc)
mlai = cbind(mlai, lai)
mrl = cbind(mrl, rl)
}
colnames(mlai) = lc
colnames(mrl) = lc
rep.row<-function(x,n){
ret=NULL
for(i in 1:n){
ret=rbind(ret, x)
}
return(ret)
}
ts.lai = xts::as.xts(rbind(rep.row(mlai, ny), mlai[1,]), order.by =tday)
ts.rl = xts::as.xts(rbind(rep.row(mrl, ny), mrl[1,]), order.by =tday)
# ts.lai = zoo::zoo(rbind(rep.row(mlai, ny), mlai[1,]), order.by =tday)
# ts.rl = zoo::zoo(rbind(rep.row(mrl, ny), mrl[1,]), order.by =tday)
colnames(ts.lai) = paste(lc)
colnames(ts.rl) = paste(lc)
ret = list(LAI = ts.lai, RL=ts.rl, nLAI=nlc)
ret
}
#' Generate the default LAI and Roughness Length for USGS GLC
#' \code{LaiRf.GLC}
#' @param lc land classe codes
#' @param years numeric years.
#' @param if.daily whether daily output
#' @return Default LaiRf.GLC parameters, a list $LAI, $RL
#' @export
#' @examples
#' lc = 1:14
#' lr=LaiRf.GLC(lc, years=2000:2001)
#' par(mfrow=c(2,1))
#' col=1:length(lc)
#' plot(lr$LAI, col=col, main='LAI');
#' legend('top', paste0(lc), col=col, lwd=1)
#' plot(lr$RL, col=col, main='Roughness Length');
#' legend('top', paste0(lc), col=col, lwd=1)
LaiRf.GLC <- function(lc=NULL, years=2000+1:2, if.daily=FALSE){
# from UMD to GLC classification
mapid = c(1:11, 1, 12, 14, 12, 1, 13)
rep.row<-function(x,n){
for(i in 1:n){ if(i==1){ ret = x; }else{ ret=rbind(ret, x) } }
return(ret) }
rep.col<-function(x,n){
for(i in 1:n){ if(i==1){ ret = x; }else{ ret=cbind(ret, x) } }
return(ret) }
years=sort(c(years,max(years)+1))
yrlim = range(years);
ny = length(years)
t1 = as.Date(paste(yrlim[1],'-01-01',sep=''))
t2 = as.Date(paste(yrlim[2],'-12-31',sep=''))
tdaily = seq.Date(t1,t2,by=1)
DataDaily = xts::as.xts(numeric(length(tdaily)),order.by=tdaily)
DataMon = xts::apply.monthly(DataDaily,FUN=sum)
tmon =as.Date( format(time(DataMon), "%Y-%m-01"))
#tmon = time(DataMon)- days_in_month(time(DataMon))+1
nlc = length(lc)
l = matrix(0, nrow=12, ncol=nlc)
r = matrix(0, nrow=12, ncol=nlc)
lai0 = t(tsLaiRf(type=1)[mapid, ])
rl0 = t(tsLaiRf(type=2)[mapid, ])
# for (i in 1:nlc){
# l[,i] = tsLaiRf(type=1)[lc[i], ]
# r[,i] = tsLaiRf(type=2)[lc[i], ]
# }
if(is.null(lc)){ lc = 1:17}
lmat = xts::as.xts(rep.row(lai0[, lc], ny), order.by=tmon)
rmat = xts::as.xts(rep.row(rl0[, lc], ny), order.by=tmon)
colnames(lmat) = lc-1
colnames(rmat) = lc-1
ret = list('LAI'=lmat, 'RL'=rmat)
if(if.daily){
ld = NA*rep.col(DataDaily, nlc);
rd = NA*rep.col(DataDaily, nlc);
ld[time(lmat),]=lmat
rd[time(rmat),]=rmat
ld=zoo::na.approx(ld)
rd=zoo::na.approx(ld)
colnames(ld)=lc
colnames(rd)=lc
ret=list('LAI'=ld, 'RL'=rd)
}
return(ret)
}
#' Generate the default LAI and Roughness Length for UMD classification system
#' \code{tsLaiRf}
#' @param type 1: LAI, 2:RL
#' @return Default LAI and RL
#' @export
#' @examples
#' tsLaiRf(type=1)
#' tsLaiRf(type=2)
tsLaiRf <- function (type=1) {
dlai=rbind(c( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
c( 8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76),
c( 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117),
c( 8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76),
c( 0.52, 0.52, 0.867, 2.107, 4.507, 6.773, 7.173, 6.507, 5.04, 2.173, 0.867, 0.52),
c( 4.64, 4.84, 5.347, 6.1, 7.4335, 8.7665, 8.833, 8.367, 7.5665, 6, 5.0135, 4.64),
c( 5.276088, 5.528588, 6.006132, 6.4425972, 7.2448806, 8.3639474, 8.540044, 8.126544, 7.2533006, 6.3291908, 5.6258086, 5.300508),
c( 2.3331824, 2.4821116, 2.7266101, 3.0330155, 3.8849492, 5.5212224, 6.2395131, 5.7733017, 4.1556703, 3.1274641, 2.6180116, 2.4039116 ),
c( 0.580555, 0.6290065, 0.628558, 0.628546, 0.919255, 1.7685454, 2.5506969, 2.5535975, 1.7286418, 0.9703975, 0.726358, 0.6290065 ),
c( 0.3999679, 0.4043968, 0.3138257, 0.2232945, 0.2498679, 0.3300675, 0.4323964, 0.7999234, 1.1668827, 0.7977234, 0.5038257, 0.4043968),
c( 0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893),
c( 0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893),
c( 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001 ),
c( 1.2867143, 1.3945997, 1.5506977, 1.7727263, 2.5190228, 4.1367678, 5.0212291, 4.5795799, 2.8484358, 1.8856229, 1.5178736, 1.3656797)
);
drl=rbind(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
c( 1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112),
c( 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653),
c( 1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112),
c( 0.52, 0.52, 0.666, 0.91, 1.031, 1.044, 1.042, 1.037, 1.036, 0.917, 0.666, 0.52),
c( 0.816, 0.8115, 0.877, 0.996, 1.0535, 1.056, 1.0575, 1.058, 1.059, 1.0025, 0.8845, 0.816),
c( 0.7602524, 0.7551426, 0.7772204, 0.8250124, 0.846955, 0.8449668, 0.8471342, 0.8496604, 0.8514252, 0.8299022, 0.7857734, 0.7602744),
c( 0.35090494, 0.34920916, 0.36891486, 0.40567288, 0.42336056, 0.42338372, 0.42328378, 0.42485112, 0.42631836, 0.40881268, 0.37218526, 0.35096866),
c( 0.05641527, 0.05645892, 0.05557872, 0.05430207, 0.05425842, 0.05399002, 0.05361482, 0.0572041, 0.05892068, 0.05821407, 0.05709462, 0.05645892),
c( 0.03699235, 0.03699634, 0.03528634, 0.03272533, 0.03272134, 0.03270066, 0.03268178, 0.03907616, 0.04149324, 0.04032533, 0.03823134, 0.03699634),
c( 0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778),
c( 0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778),
c( 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112),
c( 0.1947138, 0.19413424, 0.20831414, 0.23348558, 0.24574614, 0.24605016, 0.24538258, 0.24630454, 0.247455, 0.23527388, 0.20963734, 0.19478494)
);
tab=switch(type,'lai'=dlai, 'rl'=drl)
return(tab)
}
#' convert equation from Univeristy of Marryland classes to NLCD classes
#' \code{lc_EQ}
#' @param dtab conversion table.
#' @param lc land classe codes in NLCD classes.
#' @return Converted values.
#' @references Lele Shu(2017), Gopal Bhatt(2012)
#' @export
lc_EQ <-function(dtab, lc){
#Source: http://www.pihm.psu.edu/EstimationofVegitationParameters.htm
lc = as.numeric(lc)
tab = matrix(c( #0, 0.00, 0, 0.00, #00
0 , 0 , 0 , 0 , # 1 0
0 , 0 , 0 , 0 , # 2 0
0 , 0 , 0 , 0 , # 3 0
0 , 0 , 0 , 0 , # 4 0
0 , 0 , 0 , 0 , # 5 0
0 , 0 , 0 , 0 , # 6 0
0 , 0 , 0 , 0 , # 7 0
0 , 0 , 0 , 0 , # 8 0
0 , 0 , 0 , 0 , # 9 0
0 , 1 , 0 , 0 , # 10 1
0 , 0.9 , 6 , 0.1 , # 11 1 Open Water
0 , 0.9 , 6 , 0.1 , # 12 1 Perennial Ice/Snow
0 , 0 , 0 , 0 , # 13 0
0 , 0 , 0 , 0 , # 14 0
0 , 0 , 0 , 0 , # 15 0
0 , 0 , 0 , 0 , # 16 0
0 , 0 , 0 , 0 , # 17 0
0 , 0 , 0 , 0 , # 18 0
0 , 0 , 0 , 0 , # 19 0
13 , 0.65 , 0 , 0 , # 20 1
13 , 0.2 , 10 , 0.8 , # 21 1 Developed, Open Space
13 , 0.35 , 10 , 0.65 , # 22 1 Developed, Low Intensity
13 , 0.65 , 10 , 0.35 , # 23 1 Developed, Medium Intensity
13 , 0.9 , 10 , 0.1 , # 24 1 Developed High Intensity
0 , 0 , 0 , 0 , # 25 0
0 , 0 , 0 , 0 , # 26 0
0 , 0 , 0 , 0 , # 27 0
0 , 0 , 0 , 0 , # 28 0
0 , 0 , 0 , 0 , # 29 0
12 , 1 , 0 , 0 , # 30 1
12 , 0.92 , 9 , 0.08 , # 31 1 Barren Land (Rock/Sand/Clay)
12 , 1 , 9 , 0 , # 32 1
0 , 0 , 0 , 0 , # 33 0
0 , 0 , 0 , 0 , # 34 0
0 , 0 , 0 , 0 , # 35 0
0 , 0 , 0 , 0 , # 36 0
0 , 0 , 0 , 0 , # 37 0
0 , 0 , 0 , 0 , # 38 0
0 , 0 , 0 , 0 , # 39 0
6 , 0.65 , 0 , 0 , # 40 1
4 , 0.6 , 10 , 0.4 , # 41 1 Deciduous Forest
2 , 0.6 , 10 , 0.4 , # 42 1 Evergreen Forest
5 , 0.6 , 10 , 0.4 , # 43 1 Mixed Forest
0 , 0 , 0 , 0 , # 44 0
0 , 0 , 0 , 0 , # 45 0
0 , 0 , 0 , 0 , # 46 0
0 , 0 , 0 , 0 , # 47 0
0 , 0 , 0 , 0 , # 48 0
0 , 0 , 0 , 0 , # 49 0
8 , 1 , 0 , 0 , # 50 1
9 , 0.4 , 10 , 0.6 , # 51 1 Dwarf Scrub
8 , 0.6 , 10 , 0.4 , # 52 1 Shrub/Scrub
0 , 0 , 0 , 0 , # 53 0
0 , 0 , 0 , 0 , # 54 0
0 , 0 , 0 , 0 , # 55 0
0 , 0 , 0 , 0 , # 56 0
0 , 0 , 0 , 0 , # 57 0
0 , 0 , 0 , 0 , # 58 0
0 , 0 , 0 , 0 , # 59 0
0 , 0 , 0 , 0 , # 60 0
0 , 0 , 0 , 0 , # 61 0
0 , 0 , 0 , 0 , # 62 0
0 , 0 , 0 , 0 , # 63 0
0 , 0 , 0 , 0 , # 64 0
0 , 0 , 0 , 0 , # 65 0
0 , 0 , 0 , 0 , # 66 0
0 , 0 , 0 , 0 , # 67 0
0 , 0 , 0 , 0 , # 68 0
0 , 0 , 0 , 0 , # 69 0
10 , 0.85 , 0 , 0 , # 70 1
10 , 0.9 , 12 , 0.1 , # 71 1 Grassland/Herbaceous
10 , 0.9 , 12 , 0.1 , # 72 1 Sedge/Herbaceous
10 , 0.9 , 12 , 0.1 , # 73 1 Lichens
10 , 0.9 , 12 , 0.1 , # 74 1 Moss
0 , 0 , 0 , 0 , # 75 0
0 , 0 , 0 , 0 , # 76 0
0 , 0 , 0 , 0 , # 77 0
0 , 0 , 0 , 0 , # 78 0
0 , 0 , 0 , 0 , # 79 0
10 , 0.9 , 0 , 0 , # 80 1
11 , 0.6 , 10 , 0.4 , # 81 1 Pasture/Hay
11 , 0.9 , 12 , 0.1 , # 82 1 Cultivated Crops
0 , 0 , 0 , 0 , # 83 0
0 , 0 , 0 , 0 , # 84 0
0 , 0 , 0 , 0 , # 85 0
0 , 0 , 0 , 0 , # 86 0
0 , 0 , 0 , 0 , # 87 0
0 , 0 , 0 , 0 , # 88 0
0 , 0 , 0 , 0 , # 89 0
8 , 0.6 , 0 , 0.4 , # 90 1 Woody Wetlands
6 , 0.6 , 0 , 0 , # 91 1
7 , 0.6 , 0 , 0 , # 92 1
6 , 0.6 , 0 , 0 , # 93 1
7 , 0.6 , 0 , 0 , # 94 1
10 , 0.8 , 0 , 0.2 , # 95 1 Emergent Herbaceous Wetlands
10 , 0.8 , 2 , 0.2 , # 96 1
10 , 0.8 , 4 , 0.2 , # 97 1
10 , 0.2 , 0 , 0.8 , # 98 1
10 , 0.2 , 0 , 0.8 ) # 99 1
, ncol=99, nrow=4)
c1= tab[2, lc]
v1 = dtab[, tab[1, lc]+1 ]
c2 = tab[4, lc]
v2 = dtab[, tab[3,lc]+1 ]
ret <- c1 * v1 + c2 * v2;
}
#' The default land cover parameters from UMD
#' \code{lc.UMD}
#' @return Default land cover parameters
#' @export
lc.UMD <- function(){
dtab = rbind(
# http://glcf.umiacs.umd.edu/data/landcover/
# Index LAIMAX RMIN RSREF ALBEDO VEGFRAC ROUGH(S/M^(1/3)) Drz SOILDGRD IMPAF
c( 1 , 0 , 0.00202546 , 13477995.32 , 0.135 , 0 , 3.5E-02 , 0.00 , 0.00 , 0.00 ), #Water
c( 2 , 10.76 , 0.00202546 , 2592000 , 0.182 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Evergreen Needleleaf
c( 3 , 5.117 , 0.00173611 , 8301077.283 , 0.213 , 0.9 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Evergreen Broadleaf
c( 4 , 10.76 , 0.00202546 , 2592000 , 0.182 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Deciduous Needleleaf
c( 5 , 7.173 , 0.00202546 , 6221002.342 , 0.236 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Deciduous Broadleaf
c( 6 , 8.833 , 0.00202546 , 4541564.403 , 0.2025 , 0.795 , 6.0E-02 , 0.60 , 0.00 , 0.00 ), #Mixed Forest
c( 7 , 8.540044 , 0.00200822 , 4837950.801 , 0.2112859 , 0.799863 , 6.0E-02 , 0.00 , 0.00 , 0.00 ), #Woodland
c( 8 , 6.2395131 , 0.00195775 , 7165420.002 , 0.25245035 , 0.801837 , 5.0E-02 , 0.40 , 0.00 , 0.00 ), #Wooded Grassland
c( 9 , 2.5535975 , 0.00202546 , 10894496.21 , 0.2495851 , 0.625005 , 4.5E-02 , 0.40 , 0.00 , 0.00 ), #Closed Shrubland
c( 10 , 1.1668827 , 0.00207025 , 12297448.88 , 0.26652016 , 0.218175 , 4.5E-02 , 0.40 , 0.00 , 0.00 ), #Open Shrubland
c( 11 , 4.782 , 0.00190972 , 8640000 , 0.28802 , 0.72552 , 4.0E-02 , 0.40 , 0.1 , 0.00 ), #Grassland
c( 12 , 4.782 , 0.00135542 , 8640000 , 0.2499162 , 0.8353665 , 4.0E-02 , 0.40 , 0.50 , 0.00 ), #Cropland
c( 13 , 0.001 , 0.00202546 , 13476983.61 , 0.23214958 , 0.07489 , 3.5E-02 , 0.05 , 0.60 , 0.00 ), #Bare Ground
c( 14 , 5.0212291 , 0.00179213 , 8397969.622 , 0.24649654 , 0.7436 , 1.0E-02 , 0.05 , 0.90 , 0.90 ) #Urban and Build
)
cn = toupper(c('INDEX', 'LAIMAX', 'RMIN', 'RSREF', 'ALBEDO',
'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
colnames(dtab) = cn
dtab = dtab[, -1 * (2:4)]
return(dtab)
}
#' Generate the default land cover parameters of NLCD classes.
#' \code{PTF.NLCD}
#' @param lc NLCD (2001 and later version) land use code.
#' @return Default land cover parameters of NLCD classes.
#' @export
lc.NLCD <- function(lc){
dtab = lc.UMD()
y= t(lc_EQ( t(dtab), lc))
y[,1] = 1:nrow(y)
colnames(y) = toupper(c('INDEX', 'ALBEDO',
'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
rownames(y)=lc
return(y)
}
#' The default land cover parameters from USGS GLC
#' \code{lc.GLC}
#' @return Default land cover parameters
#' @export
lc.GLC <- function(){
cn = toupper(c('INDEX', 'ALBEDO', 'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
mapid = c(1:11, 1, 12, 14, 12, 1, 13)
v = lc.UMD()[mapid, ]
v[, 1] = 1:nrow(v)-1
return(v)
}
SHUD-System/SHUDtoolbox documentation built on Nov. 27, 2024, 5:54 a.m.
R Package Documentation
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Defines functions lc.GLC lc.NLCD lc.UMD lc_EQ LaiRf.GLC LaiRf.NLCD
Documented in LaiRf.GLC LaiRf.NLCD lc_EQ lc.GLC lc.NLCD lc.UMD
#' Generate the default LAI and Roughness Length
#' \code{LaiRf.NLCD}
#' @param lc land classe codes
#' @param years numeric years.
#' @param class The classification of the Landuse of NLCD
#' @return Default LaiRf.NLCD parameters, a list $LAI, $RL
#' @export
#' @examples
#' lc = c(43, 23, 81, 11)
#' lr=LaiRf.NLCD(lc, years=2000:2001)
#' par(mfrow=c(2,1))
#' col=1:length(lc)
#' plot(lr$LAI, col=col, main='LAI');
#' legend('top', paste0(lc), col=col, lwd=1)
#' plot(lr$RL, col=col, main='Roughness Length');
#' legend('top', paste0(lc), col=col, lwd=1)
LaiRf.NLCD <- function(lc, years=2000){
# http://glcf.umiacs.umd.edu/data/landcover/
rltbl =matrix(c(
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112,
2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653,
1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112,
0.52, 0.52, 0.666, 0.91, 1.031, 1.044, 1.042, 1.037, 1.036, 0.917, 0.666, 0.52,
0.816, 0.8115, 0.877, 0.996, 1.0535, 1.056, 1.0575, 1.058, 1.059, 1.0025, 0.8845, 0.816,
0.7602524, 0.7551426, 0.7772204, 0.8250124, 0.846955, 0.8449668, 0.8471342, 0.8496604, 0.8514252, 0.8299022, 0.7857734, 0.7602744,
0.35090494, 0.34920916, 0.36891486, 0.40567288, 0.42336056, 0.42338372, 0.42328378, 0.42485112, 0.42631836, 0.40881268, 0.37218526, 0.35096866,
0.05641527, 0.05645892, 0.05557872, 0.05430207, 0.05425842, 0.05399002, 0.05361482, 0.0572041, 0.05892068, 0.05821407, 0.05709462, 0.05645892,
0.03699235, 0.03699634, 0.03528634, 0.03272533, 0.03272134, 0.03270066, 0.03268178, 0.03907616, 0.04149324, 0.04032533, 0.03823134, 0.03699634,
0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778,
0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778,
0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112,
0.1947138, 0.19413424, 0.20831414, 0.23348558, 0.24574614, 0.24605016, 0.24538258, 0.24630454, 0.247455, 0.23527388, 0.20963734, 0.19478494
), ncol =14, nrow=12)
laitbl = matrix(c(
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76,
5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117,
8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76,
0.52, 0.52, 0.867, 2.107, 4.507, 6.773, 7.173, 6.507, 5.04, 2.173, 0.867, 0.52,
4.64, 4.84, 5.347, 6.1, 7.4335, 8.7665, 8.833, 8.367, 7.5665, 6, 5.0135, 4.64,
5.276088, 5.528588, 6.006132, 6.4425972, 7.2448806, 8.3639474, 8.540044, 8.126544, 7.2533006, 6.3291908, 5.6258086, 5.300508,
2.3331824, 2.4821116, 2.7266101, 3.0330155, 3.8849492, 5.5212224, 6.2395131, 5.7733017, 4.1556703, 3.1274641, 2.6180116, 2.4039116 ,
0.580555, 0.6290065, 0.628558, 0.628546, 0.919255, 1.7685454, 2.5506969, 2.5535975, 1.7286418, 0.9703975, 0.726358, 0.6290065 ,
0.3999679, 0.4043968, 0.3138257, 0.2232945, 0.2498679, 0.3300675, 0.4323964, 0.7999234, 1.1668827, 0.7977234, 0.5038257, 0.4043968,
0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893,
0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893,
0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001 ,
1.2867143, 1.3945997, 1.5506977, 1.7727263, 2.5190228, 4.1367678, 5.0212291, 4.5795799, 2.8484358, 1.8856229, 1.5178736, 1.3656797
),
ncol = 14, nrow = 12)
years=sort(c(years, max(years, na.rm=TRUE)+1), decreasing = FALSE)
nlc = length(lc)
ny = length(years)
ym = rbind(expand.grid(1:12, years), c(1, max(years)+1) )
tstr = paste(ym[,2], ym[,1], '01', sep='-')
tday = zoo::as.Date(tstr)
mlai = NULL
mrl = NULL
for (i in 1:nlc){
ilc= lc[i]
lai = lc_EQ(laitbl, ilc)
rl = lc_EQ (rltbl, ilc)
mlai = cbind(mlai, lai)
mrl = cbind(mrl, rl)
}
colnames(mlai) = lc
colnames(mrl) = lc
rep.row<-function(x,n){
ret=NULL
for(i in 1:n){
ret=rbind(ret, x)
}
return(ret)
}
ts.lai = xts::as.xts(rbind(rep.row(mlai, ny), mlai[1,]), order.by =tday)
ts.rl = xts::as.xts(rbind(rep.row(mrl, ny), mrl[1,]), order.by =tday)
# ts.lai = zoo::zoo(rbind(rep.row(mlai, ny), mlai[1,]), order.by =tday)
# ts.rl = zoo::zoo(rbind(rep.row(mrl, ny), mrl[1,]), order.by =tday)
colnames(ts.lai) = paste(lc)
colnames(ts.rl) = paste(lc)
ret = list(LAI = ts.lai, RL=ts.rl, nLAI=nlc)
ret
}
#' Generate the default LAI and Roughness Length for USGS GLC
#' \code{LaiRf.GLC}
#' @param lc land classe codes
#' @param years numeric years.
#' @param if.daily whether daily output
#' @return Default LaiRf.GLC parameters, a list $LAI, $RL
#' @export
#' @examples
#' lc = 1:14
#' lr=LaiRf.GLC(lc, years=2000:2001)
#' par(mfrow=c(2,1))
#' col=1:length(lc)
#' plot(lr$LAI, col=col, main='LAI');
#' legend('top', paste0(lc), col=col, lwd=1)
#' plot(lr$RL, col=col, main='Roughness Length');
#' legend('top', paste0(lc), col=col, lwd=1)
LaiRf.GLC <- function(lc=NULL, years=2000+1:2, if.daily=FALSE){
# from UMD to GLC classification
mapid = c(1:11, 1, 12, 14, 12, 1, 13)
rep.row<-function(x,n){
for(i in 1:n){ if(i==1){ ret = x; }else{ ret=rbind(ret, x) } }
return(ret) }
rep.col<-function(x,n){
for(i in 1:n){ if(i==1){ ret = x; }else{ ret=cbind(ret, x) } }
return(ret) }
years=sort(c(years,max(years)+1))
yrlim = range(years);
ny = length(years)
t1 = as.Date(paste(yrlim[1],'-01-01',sep=''))
t2 = as.Date(paste(yrlim[2],'-12-31',sep=''))
tdaily = seq.Date(t1,t2,by=1)
DataDaily = xts::as.xts(numeric(length(tdaily)),order.by=tdaily)
DataMon = xts::apply.monthly(DataDaily,FUN=sum)
tmon =as.Date( format(time(DataMon), "%Y-%m-01"))
#tmon = time(DataMon)- days_in_month(time(DataMon))+1
nlc = length(lc)
l = matrix(0, nrow=12, ncol=nlc)
r = matrix(0, nrow=12, ncol=nlc)
lai0 = t(tsLaiRf(type=1)[mapid, ])
rl0 = t(tsLaiRf(type=2)[mapid, ])
# for (i in 1:nlc){
# l[,i] = tsLaiRf(type=1)[lc[i], ]
# r[,i] = tsLaiRf(type=2)[lc[i], ]
# }
if(is.null(lc)){ lc = 1:17}
lmat = xts::as.xts(rep.row(lai0[, lc], ny), order.by=tmon)
rmat = xts::as.xts(rep.row(rl0[, lc], ny), order.by=tmon)
colnames(lmat) = lc-1
colnames(rmat) = lc-1
ret = list('LAI'=lmat, 'RL'=rmat)
if(if.daily){
ld = NA*rep.col(DataDaily, nlc);
rd = NA*rep.col(DataDaily, nlc);
ld[time(lmat),]=lmat
rd[time(rmat),]=rmat
ld=zoo::na.approx(ld)
rd=zoo::na.approx(ld)
colnames(ld)=lc
colnames(rd)=lc
ret=list('LAI'=ld, 'RL'=rd)
}
return(ret)
}
#' Generate the default LAI and Roughness Length for UMD classification system
#' \code{tsLaiRf}
#' @param type 1: LAI, 2:RL
#' @return Default LAI and RL
#' @export
#' @examples
#' tsLaiRf(type=1)
#' tsLaiRf(type=2)
tsLaiRf <- function (type=1) {
dlai=rbind(c( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
c( 8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76),
c( 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117, 5.117),
c( 8.76, 9.16, 9.827, 10.093, 10.36, 10.76, 10.493, 10.227, 10.093, 9.827, 9.16, 8.76),
c( 0.52, 0.52, 0.867, 2.107, 4.507, 6.773, 7.173, 6.507, 5.04, 2.173, 0.867, 0.52),
c( 4.64, 4.84, 5.347, 6.1, 7.4335, 8.7665, 8.833, 8.367, 7.5665, 6, 5.0135, 4.64),
c( 5.276088, 5.528588, 6.006132, 6.4425972, 7.2448806, 8.3639474, 8.540044, 8.126544, 7.2533006, 6.3291908, 5.6258086, 5.300508),
c( 2.3331824, 2.4821116, 2.7266101, 3.0330155, 3.8849492, 5.5212224, 6.2395131, 5.7733017, 4.1556703, 3.1274641, 2.6180116, 2.4039116 ),
c( 0.580555, 0.6290065, 0.628558, 0.628546, 0.919255, 1.7685454, 2.5506969, 2.5535975, 1.7286418, 0.9703975, 0.726358, 0.6290065 ),
c( 0.3999679, 0.4043968, 0.3138257, 0.2232945, 0.2498679, 0.3300675, 0.4323964, 0.7999234, 1.1668827, 0.7977234, 0.5038257, 0.4043968),
c( 0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893),
c( 0.782, 0.893, 1.004, 1.116, 1.782, 3.671, 4.782, 4.227, 2.004, 1.227, 1.004, 0.893),
c( 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001 ),
c( 1.2867143, 1.3945997, 1.5506977, 1.7727263, 2.5190228, 4.1367678, 5.0212291, 4.5795799, 2.8484358, 1.8856229, 1.5178736, 1.3656797)
);
drl=rbind(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
c( 1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112),
c( 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653, 2.653),
c( 1.112, 1.103, 1.088, 1.082, 1.076, 1.068, 1.073, 1.079, 1.082, 1.088, 1.103, 1.112),
c( 0.52, 0.52, 0.666, 0.91, 1.031, 1.044, 1.042, 1.037, 1.036, 0.917, 0.666, 0.52),
c( 0.816, 0.8115, 0.877, 0.996, 1.0535, 1.056, 1.0575, 1.058, 1.059, 1.0025, 0.8845, 0.816),
c( 0.7602524, 0.7551426, 0.7772204, 0.8250124, 0.846955, 0.8449668, 0.8471342, 0.8496604, 0.8514252, 0.8299022, 0.7857734, 0.7602744),
c( 0.35090494, 0.34920916, 0.36891486, 0.40567288, 0.42336056, 0.42338372, 0.42328378, 0.42485112, 0.42631836, 0.40881268, 0.37218526, 0.35096866),
c( 0.05641527, 0.05645892, 0.05557872, 0.05430207, 0.05425842, 0.05399002, 0.05361482, 0.0572041, 0.05892068, 0.05821407, 0.05709462, 0.05645892),
c( 0.03699235, 0.03699634, 0.03528634, 0.03272533, 0.03272134, 0.03270066, 0.03268178, 0.03907616, 0.04149324, 0.04032533, 0.03823134, 0.03699634),
c( 0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778),
c( 0.0777, 0.0778, 0.0778, 0.0779, 0.0778, 0.0771, 0.0759, 0.0766, 0.0778, 0.0779, 0.0778, 0.0778),
c( 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112, 0.0112),
c( 0.1947138, 0.19413424, 0.20831414, 0.23348558, 0.24574614, 0.24605016, 0.24538258, 0.24630454, 0.247455, 0.23527388, 0.20963734, 0.19478494)
);
tab=switch(type,'lai'=dlai, 'rl'=drl)
return(tab)
}
#' convert equation from Univeristy of Marryland classes to NLCD classes
#' \code{lc_EQ}
#' @param dtab conversion table.
#' @param lc land classe codes in NLCD classes.
#' @return Converted values.
#' @references Lele Shu(2017), Gopal Bhatt(2012)
#' @export
lc_EQ <-function(dtab, lc){
#Source: http://www.pihm.psu.edu/EstimationofVegitationParameters.htm
lc = as.numeric(lc)
tab = matrix(c( #0, 0.00, 0, 0.00, #00
0 , 0 , 0 , 0 , # 1 0
0 , 0 , 0 , 0 , # 2 0
0 , 0 , 0 , 0 , # 3 0
0 , 0 , 0 , 0 , # 4 0
0 , 0 , 0 , 0 , # 5 0
0 , 0 , 0 , 0 , # 6 0
0 , 0 , 0 , 0 , # 7 0
0 , 0 , 0 , 0 , # 8 0
0 , 0 , 0 , 0 , # 9 0
0 , 1 , 0 , 0 , # 10 1
0 , 0.9 , 6 , 0.1 , # 11 1 Open Water
0 , 0.9 , 6 , 0.1 , # 12 1 Perennial Ice/Snow
0 , 0 , 0 , 0 , # 13 0
0 , 0 , 0 , 0 , # 14 0
0 , 0 , 0 , 0 , # 15 0
0 , 0 , 0 , 0 , # 16 0
0 , 0 , 0 , 0 , # 17 0
0 , 0 , 0 , 0 , # 18 0
0 , 0 , 0 , 0 , # 19 0
13 , 0.65 , 0 , 0 , # 20 1
13 , 0.2 , 10 , 0.8 , # 21 1 Developed, Open Space
13 , 0.35 , 10 , 0.65 , # 22 1 Developed, Low Intensity
13 , 0.65 , 10 , 0.35 , # 23 1 Developed, Medium Intensity
13 , 0.9 , 10 , 0.1 , # 24 1 Developed High Intensity
0 , 0 , 0 , 0 , # 25 0
0 , 0 , 0 , 0 , # 26 0
0 , 0 , 0 , 0 , # 27 0
0 , 0 , 0 , 0 , # 28 0
0 , 0 , 0 , 0 , # 29 0
12 , 1 , 0 , 0 , # 30 1
12 , 0.92 , 9 , 0.08 , # 31 1 Barren Land (Rock/Sand/Clay)
12 , 1 , 9 , 0 , # 32 1
0 , 0 , 0 , 0 , # 33 0
0 , 0 , 0 , 0 , # 34 0
0 , 0 , 0 , 0 , # 35 0
0 , 0 , 0 , 0 , # 36 0
0 , 0 , 0 , 0 , # 37 0
0 , 0 , 0 , 0 , # 38 0
0 , 0 , 0 , 0 , # 39 0
6 , 0.65 , 0 , 0 , # 40 1
4 , 0.6 , 10 , 0.4 , # 41 1 Deciduous Forest
2 , 0.6 , 10 , 0.4 , # 42 1 Evergreen Forest
5 , 0.6 , 10 , 0.4 , # 43 1 Mixed Forest
0 , 0 , 0 , 0 , # 44 0
0 , 0 , 0 , 0 , # 45 0
0 , 0 , 0 , 0 , # 46 0
0 , 0 , 0 , 0 , # 47 0
0 , 0 , 0 , 0 , # 48 0
0 , 0 , 0 , 0 , # 49 0
8 , 1 , 0 , 0 , # 50 1
9 , 0.4 , 10 , 0.6 , # 51 1 Dwarf Scrub
8 , 0.6 , 10 , 0.4 , # 52 1 Shrub/Scrub
0 , 0 , 0 , 0 , # 53 0
0 , 0 , 0 , 0 , # 54 0
0 , 0 , 0 , 0 , # 55 0
0 , 0 , 0 , 0 , # 56 0
0 , 0 , 0 , 0 , # 57 0
0 , 0 , 0 , 0 , # 58 0
0 , 0 , 0 , 0 , # 59 0
0 , 0 , 0 , 0 , # 60 0
0 , 0 , 0 , 0 , # 61 0
0 , 0 , 0 , 0 , # 62 0
0 , 0 , 0 , 0 , # 63 0
0 , 0 , 0 , 0 , # 64 0
0 , 0 , 0 , 0 , # 65 0
0 , 0 , 0 , 0 , # 66 0
0 , 0 , 0 , 0 , # 67 0
0 , 0 , 0 , 0 , # 68 0
0 , 0 , 0 , 0 , # 69 0
10 , 0.85 , 0 , 0 , # 70 1
10 , 0.9 , 12 , 0.1 , # 71 1 Grassland/Herbaceous
10 , 0.9 , 12 , 0.1 , # 72 1 Sedge/Herbaceous
10 , 0.9 , 12 , 0.1 , # 73 1 Lichens
10 , 0.9 , 12 , 0.1 , # 74 1 Moss
0 , 0 , 0 , 0 , # 75 0
0 , 0 , 0 , 0 , # 76 0
0 , 0 , 0 , 0 , # 77 0
0 , 0 , 0 , 0 , # 78 0
0 , 0 , 0 , 0 , # 79 0
10 , 0.9 , 0 , 0 , # 80 1
11 , 0.6 , 10 , 0.4 , # 81 1 Pasture/Hay
11 , 0.9 , 12 , 0.1 , # 82 1 Cultivated Crops
0 , 0 , 0 , 0 , # 83 0
0 , 0 , 0 , 0 , # 84 0
0 , 0 , 0 , 0 , # 85 0
0 , 0 , 0 , 0 , # 86 0
0 , 0 , 0 , 0 , # 87 0
0 , 0 , 0 , 0 , # 88 0
0 , 0 , 0 , 0 , # 89 0
8 , 0.6 , 0 , 0.4 , # 90 1 Woody Wetlands
6 , 0.6 , 0 , 0 , # 91 1
7 , 0.6 , 0 , 0 , # 92 1
6 , 0.6 , 0 , 0 , # 93 1
7 , 0.6 , 0 , 0 , # 94 1
10 , 0.8 , 0 , 0.2 , # 95 1 Emergent Herbaceous Wetlands
10 , 0.8 , 2 , 0.2 , # 96 1
10 , 0.8 , 4 , 0.2 , # 97 1
10 , 0.2 , 0 , 0.8 , # 98 1
10 , 0.2 , 0 , 0.8 ) # 99 1
, ncol=99, nrow=4)
c1= tab[2, lc]
v1 = dtab[, tab[1, lc]+1 ]
c2 = tab[4, lc]
v2 = dtab[, tab[3,lc]+1 ]
ret <- c1 * v1 + c2 * v2;
}
#' The default land cover parameters from UMD
#' \code{lc.UMD}
#' @return Default land cover parameters
#' @export
lc.UMD <- function(){
dtab = rbind(
# http://glcf.umiacs.umd.edu/data/landcover/
# Index LAIMAX RMIN RSREF ALBEDO VEGFRAC ROUGH(S/M^(1/3)) Drz SOILDGRD IMPAF
c( 1 , 0 , 0.00202546 , 13477995.32 , 0.135 , 0 , 3.5E-02 , 0.00 , 0.00 , 0.00 ), #Water
c( 2 , 10.76 , 0.00202546 , 2592000 , 0.182 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Evergreen Needleleaf
c( 3 , 5.117 , 0.00173611 , 8301077.283 , 0.213 , 0.9 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Evergreen Broadleaf
c( 4 , 10.76 , 0.00202546 , 2592000 , 0.182 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Deciduous Needleleaf
c( 5 , 7.173 , 0.00202546 , 6221002.342 , 0.236 , 0.8 , 7.0E-02 , 0.60 , 0.00 , 0.00 ), #Deciduous Broadleaf
c( 6 , 8.833 , 0.00202546 , 4541564.403 , 0.2025 , 0.795 , 6.0E-02 , 0.60 , 0.00 , 0.00 ), #Mixed Forest
c( 7 , 8.540044 , 0.00200822 , 4837950.801 , 0.2112859 , 0.799863 , 6.0E-02 , 0.00 , 0.00 , 0.00 ), #Woodland
c( 8 , 6.2395131 , 0.00195775 , 7165420.002 , 0.25245035 , 0.801837 , 5.0E-02 , 0.40 , 0.00 , 0.00 ), #Wooded Grassland
c( 9 , 2.5535975 , 0.00202546 , 10894496.21 , 0.2495851 , 0.625005 , 4.5E-02 , 0.40 , 0.00 , 0.00 ), #Closed Shrubland
c( 10 , 1.1668827 , 0.00207025 , 12297448.88 , 0.26652016 , 0.218175 , 4.5E-02 , 0.40 , 0.00 , 0.00 ), #Open Shrubland
c( 11 , 4.782 , 0.00190972 , 8640000 , 0.28802 , 0.72552 , 4.0E-02 , 0.40 , 0.1 , 0.00 ), #Grassland
c( 12 , 4.782 , 0.00135542 , 8640000 , 0.2499162 , 0.8353665 , 4.0E-02 , 0.40 , 0.50 , 0.00 ), #Cropland
c( 13 , 0.001 , 0.00202546 , 13476983.61 , 0.23214958 , 0.07489 , 3.5E-02 , 0.05 , 0.60 , 0.00 ), #Bare Ground
c( 14 , 5.0212291 , 0.00179213 , 8397969.622 , 0.24649654 , 0.7436 , 1.0E-02 , 0.05 , 0.90 , 0.90 ) #Urban and Build
)
cn = toupper(c('INDEX', 'LAIMAX', 'RMIN', 'RSREF', 'ALBEDO',
'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
colnames(dtab) = cn
dtab = dtab[, -1 * (2:4)]
return(dtab)
}
#' Generate the default land cover parameters of NLCD classes.
#' \code{PTF.NLCD}
#' @param lc NLCD (2001 and later version) land use code.
#' @return Default land cover parameters of NLCD classes.
#' @export
lc.NLCD <- function(lc){
dtab = lc.UMD()
y= t(lc_EQ( t(dtab), lc))
y[,1] = 1:nrow(y)
colnames(y) = toupper(c('INDEX', 'ALBEDO',
'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
rownames(y)=lc
return(y)
}
#' The default land cover parameters from USGS GLC
#' \code{lc.GLC}
#' @return Default land cover parameters
#' @export
lc.GLC <- function(){
cn = toupper(c('INDEX', 'ALBEDO', 'VEGFRAC', 'ROUGH', 'RZD', 'SOILDGRD', 'IMPAF') )
mapid = c(1:11, 1, 12, 14, 12, 1, 13)
v = lc.UMD()[mapid, ]
v[, 1] = 1:nrow(v)-1
return(v)
}
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