rsMove (version 0.2.1)

moveCloud: moveCloud

Description

Provides historical information on cloud cover.

Usage

moveCloud(xy = xy, o.time = o.time, d.path = NULL, b.size = NULL,
  remove.file = TRUE, p.res = T)

Arguments

xy

Object of class SpatialPoints or SpatialPointsDataFrame.

o.time

Object of class Date.

d.path

Output data path for downloaded data.

b.size

Two element vector with temporal buffer size (expressed in days).

remove.file

Logical. Should the files be deleted after usage?

p.res

Should the output be ploted on screen? Default is TRUE.

Value

A list.

Details

This function makes uses daily cloud fraction data from NASA's NEO service. For each observation date (o.time), the function downloads the correspondent image and extracts the percent of cloud cover for the samples acquired at the target date. If d.path is specified, the function will look within the provided directory for the required files. If so, they won't be downloaded. If d.buffer is specified, for each date, the function will consider images before and after within a temporal buffer. d.buffer requires two elements which specify the buffer size before and after the target date. These new images will be used to report on the closest time step with the lowest possible cloud cover. The final report provides information on:

• day.cover: cloud cover for the observation date

• p.day.before: date before the obsertation date with the lowest cloud cover

• p.cover.before: cloud cover for p.day.before

• p.day.after: date after the obsertation date with the lowest cloud cover

• p.cover.after: cloud cover for p.day.after

The output will also contain a two plots with information on the distance between the observation dates and the closest date with the lowest cloud cover. The plots show the amount of samples that are covered in each of the target dates for the best dates before ($plot.before) and after ($plot.after) the observation dates.

References

https://cneos.jpl.nasa.gov/

See Also

sMoveRes tMoveRes

Examples

# NOT RUN {
 require(raster)

 # read raster data
 r <- raster(system.file('extdata', 'tcb_1.tif', package="rsMove"))

 # read movement data
 moveData <- read.csv(system.file('extdata', 'konstanz_20130804.csv', package="rsMove"))
 moveData <- SpatialPointsDataFrame(moveData[,1:2], moveData, proj4string=crs(r))

 # test function for 5, 10 20 and 30 m
 od <- as.Date(moveData@data$date)
 c.cover <- moveCloud(xy=moveData, o.time=od, d.path=".", b.size=30)

# }