R/landsat.R

In hhcartr: HHCART(G) - A Reflected Feature Space for CART

#' Statlog (Landsat Satellite) Dataset.
#'
#' The database consists of the multi-spectral values of pixels in 3x3 neighbourhoods in a
#' satellite image, and the classification associated with the central pixel in each neighbourhood.
#' The aim is to predict this classification, given the multi-spectral values. In the sample
#' database, the class of a pixel is coded as a number. The Landsat satellite data is one of the
#' many sources of information available for a scene. The interpretation of a scene by integrating
#' spatial data of diverse types and resolutions including multi-spectral and radar data, maps
#' indicating topography, land use etc. is expected to assume significant importance with the
#' onset of an era characterised by integrative approaches to remote sensing (for example, NASA's
#' Earth Observing System commencing this decade). Existing statistical methods are ill-equipped
#' for handling such diverse data types. Note that this is not true for Landsat MSS data considered
#' in isolation (as in this sample database). This data satisfies the important requirements of
#' being numerical and at a single resolution, and standard maximum-likelihood classification
#' performs very well. Consequently, for this data, it should be interesting to compare the
#' performance of other methods against the statistical approach. One frame of Landsat MSS imagery
#' consists of four digital images of the same scene in different spectral bands. Two of these are
#' in the visible region (corresponding approximately to green and red regions of the visible
#' spectrum) and two are in the (near) infra-red. Each pixel is a 8-bit binary word, with 0
#' corresponding to black and 255 to white. The spatial resolution of a pixel is about 80m x 80m.
#' Each image contains 2340 x 3380 such pixels.
#'
#' The database is a (tiny) sub-area of a scene, consisting of 82 x 100 pixels. Each line of data
#' corresponds to a 3x3 square neighbourhood of pixels completely contained within the 82x100
#' sub-area. Each line contains the pixel values in the four spectral bands (converted to ASCII)
#' of each of the 9 pixels in the 3x3 neighbourhood and a number indicating the classification
#' label of the central pixel.
#'
#' @docType data
#'
#' @usage data(landsat)
#'
#' @format A data frame with 6435 rows and 36 variables:
#' \describe{
#'     \item{cols1-36}{The attributes are numerical, in the range 0 to 255.}
#'     \item{class}{Number Class 1 red soil, 2 cotton crop, 3 grey soil, 4 damp grey soil,
#'     5 soil with vegetation stubble, 6 mixture class (all types present), 7 very damp grey soil}
#' }
#'
#' @keywords datasets landsat
#'
#' @source \url{https://archive.ics.uci.edu/ml/datasets/Statlog+(Landsat+Satellite)}
"landsat"