-- 
======================================================================
Alexandre dos Santos
Proteção Florestal 
IFMT - Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso
Campus Cáceres
Caixa Postal 244
Avenida dos Ramires, s/n
Bairro: Distrito Industrial 
Cáceres - MT                      CEP: 78.200-000
Fone: (+55) 65 8132-8112 (TIM)   (+55) 65 9686-6970 (VIVO)
e-mails:alexandresantosbr@yahoo.com.br 
        alexandre.santos@cas.ifmt.edu.br 
Lattes: http://lattes.cnpq.br/1360403201088680
OrcID: orcid.org/0000-0001-8232-6722 
Researchgate: https://www.researchgate.net/profile/Alexandre_Santos10                       
LinkedIn: https://br.linkedin.com/in/alexandre-dos-santos-87961635
======================================================================

### <code r>

setwd("D:/Temp")

sapply(c("raster", "sp", "ncdf4"), require, char=T)

url0  <- "https://drive.google.com/file/d/0B6tnaf2fmoCcOXhnRDIxWnM5UDA/view"

browseURL(url0) ### 266 Mb

dir(patt="\\.nc")

fn <- "Rs_daily_UT_Brazil_v2_20070101_20131231.nc"

download.file(url1, fn, mode="wb")

# nc <- nc_open(fn); names(nc[['var']])    ### inspeção de conteúdo

# r  <- raster(fn); dim(r); object.size(r) ### importará somente primeiro layer

s <- stack(fn, varname="Rs")

dim(s); print(object.size(s), units="Mb") ### 2557 layers (datas), 30.4 Mb

POI <- SpatialPoints(cbind(lon=c(-47.5,-47.5,-44.5,-40), lat=c(-18.5,-19.5,-20.5,-22)))

proj4string(POI) <- proj4string(s)

e <- extract(s, POI, method= "bilinear", df=T) #ou method="simple"

dim(e); head(e[,1:5])

e2 <- t(e[-1]) ### inverte, retirando a primeira coluna (ID)

dim(e2) ### [1] 2557    4

head(e2, 3)

#                 [,1]     [,2]      [,3] [,4]

# X2007.01.01 11.67222 12.36980  8.660182   NA

# X2007.01.02 17.28591 14.08362  9.963414   NA

# X2007.01.03 15.78652 12.72562 10.278209   NA

tail(e2, 3)

#                 [,1]     [,2]     [,3] [,4]

# X2013.12.29 23.22835 23.38377 19.95641   NA

# X2013.12.30 18.80989 21.45013 16.14789   NA

# X2013.12.31 19.01340 17.74833 20.40014   NA

### Comparação de métodos de extração (utilizando primeiro layer)

sp1 <- as(s[[1]], "SpatialPixelsDataFrame")

over(POI, sp1)[,1]

data.frame(POI@coords, 

           over = over(POI, sp1)[,1], 

           bil  = extract(s[[1]], POI, method= "bilinear", df=T)[,2],

           simp = extract(s[[1]], POI, method= "simple", df=T)[,2])

#     lon   lat      over       bil      simp

# 1 -47.5 -18.5 11.586952 11.672215 11.639958

# 2 -47.5 -19.5 12.564141 12.369798 11.964512

# 3 -44.5 -20.5  8.624653  8.660182  7.975467

# 4 -40.0 -22.0        NA        NA       NaN

### Visualizando os dois primeiros pontos

crop <- crop(s[[1]], extent(-48, -47, -20, -18))

image(crop, asp=T)

text(crop, lab=round(getValues(crop), 6), cex=.5); points(POI, pch=20, cex=2)

### over pega à esquerda, simple à direita e bilinear interpola.

### </code>