parse.bits {spatialEco}R Documentation

Parse bits

Description

Returns specified bit value based on integer input

Data such as MODIS the QC band are stored in bits. This function returns the value(s) for specified bit. For example, the MODIS QC flag are bits 0-1 with the bit value 00 representing the "LST produced, good quality" flag. When exported from HDF the QC bands are often in an 8 bit integer range (0-255). With this function you can parse the values for each bit to assign the flag values.

Usage

parse.bits(x, bit, depth = 8, order = c("reverse", "none"))

Arguments

x

Integer value

bit

A single or vector of bits to return

depth

The depth (length) of the bit range, default is 8

order

c("reverse", "none") sort order for the bits

Value

a vector or data.frame of parsed interger value(s) associated with input bit

Author(s)

Jeffrey S. Evans <jeffrey_evans@tnc.org>

Examples

# Return value for bit 5 for integer value 100
parse.bits(100, 5)
 
# Return value(s) for bits 0 and 1 for integer value 100
parse.bits(100, c(0,1))

# Return value(s) for bits 0 and 1 for integer values 0-255
for(i in 0:255) { print(parse.bits(i, c(0,1))) }
 

#### Applied Example using Harmonized Landsat Sentinel-2 QC 

# Create dummy data and qc band
library(terra)
r <- rast(nrow=100, ncol=100)
  r[] <- round(runif(ncell(r), 0,1)) 
qc <- rast(nrow=100, ncol=100)
  qc[] <- round(runif(ncell(qc), 64,234)) 

# Calculate bit values from QC table
( qc_bits <- data.frame(int=0:255, 
	cloud = unlist(lapply(0:255, FUN=parse.bits, bit=1)),
	shadow = unlist(lapply(0:255, FUN=parse.bits, bit=3)),
	acloud = unlist(lapply(0:255, FUN=parse.bits, bit=2)),
	cirrus = unlist(lapply(0:255, FUN=parse.bits, bit=0)),
	aerosol = unlist(lapply(0:255, FUN=parse.bits, bit=c(7,6)))) )
		
# Query the results to create a vector of integer values indicating what to mask 
#  cloud is bit 1 and shadow bit 3	
m <- sort(unique(qc_bits[c(which(qc_bits$cloud == 1),
                           which(qc_bits$shadow == 1)
						   ),]$int))

# Apply queried integer values to mask image with QA band
qc[qc %in% m] <- NA
r <- mask(r, qc)



[Package spatialEco version 2.0-2 Index]