#set projection of coordinates to lat/long
proj4string(points)<-CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")
#crs(points)<-"+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"
#tranform lat/lon to EASE-Grid 2.0 (original EASE, global cylindrical equal area, WGS84 projection)
points<-spTransform(points,CRS("+proj=cea +lat_0=0 +lon_0=0 +lat_ts=30 +ellps=WGS84 +datum=WGS84 +units=m"))
data<-as.data.frame(SMSM)
data<-unlist(data) #unlist data frame to get vector of soil moisture
data <- SpatialPointsDataFrame(points, data.frame(data)) #add soil moisture data to spatial object
###instead, used "SpatialPixelsDataFrame" with tolerance limit for irregularity
###see bottom of: http://gis.stackexchange.com/questions/79062/how-to-make-raster-from-irregular-point-data-without-interpolation
data <- SpatialPixelsDataFrame(data, tolerance = 0.000163453, data@data) # 8.17194e-05
data <- raster(data[,'data'])
plot(data)
x2 <- c(8200000)
y2 <- c(3450000)
points(x2, y2, pch=8, col="blue")
plot(yourshapefile, add = T)