By using a multispectral image and ESRI shapefile (Point/ Line/ Polygon), a data table will be generated for classification, regression or other processing. The data table will be contained by band wise raster values and shapefile ids (User Defined).

Density, distribution function, quantile function
    and random generation for a number of univariate
    and multivariate distributions. This package implements the
    following distributions: Bernoulli, beta-binomial, beta-negative
    binomial, beta prime, Bhattacharjee, Birnbaum-Saunders,
    bivariate normal, bivariate Poisson, categorical, Dirichlet,
    Dirichlet-multinomial, discrete gamma, discrete Laplace,
    discrete normal, discrete uniform, discrete Weibull, Frechet,
    gamma-Poisson, generalized extreme value, Gompertz,
    generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t,
    Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy,
    Laplace, location-scale t, logarithmic, Lomax, multivariate
    hypergeometric, multinomial, negative hypergeometric,
    non-standard beta, normal mixture, Poisson mixture, Pareto,
    power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam,
    slash, triangular, truncated binomial, truncated normal,
    truncated Poisson, Tukey lambda, Wald, zero-inflated binomial,
    zero-inflated negative binomial, zero-inflated Poisson.

Tools to using fonts other than the standard PostScript fonts.
    This package makes it easy to use system TrueType fonts and with PDF or
    PostScript output files, and with bitmap output files in Windows. extrafont
    can also be used with fonts packaged specifically to be used with, such as
    the fontcm package, which has Computer Modern PostScript fonts with math
    symbols.

Provide estimation and data generation tools for some new multivariate frailty models.
             This version includes the gamma, inverse Gaussian, weighted Lindley, Birnbaum-Saunders,
	     truncated normal and mixture of inverse Gaussian as the distribution for the frailty terms. 
             For the basal model, it is considered a parametric approach based on the exponential, 
             Weibull and the piecewise exponential distributions as well as a semiparametric approach. 
             For details, see Gallardo and Bourguignon (2022) <doi:10.48550/arXiv.2206.12973>.