.sits_raster_api_new_rast

nrows

ncols

xmin

xmax

ymin

ymax

nlayers

Coordinate Reference System of the raster

additional parameters to be passed to raster package

Raster package internal create raster object function

internal

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Builds data cubes from collections in AWS, Brazil Data Cube, and Digital Earth Africa.
Provides different visualisation methods for image time series.
Provides smoothing methods for noisy time series.
Includes functions for smoothing based on Bayesian inference.
Enables different clustering methods, including dendrograms and self-organized maps (SOM).
Matches noiseless patterns with noisy time series using the time-weighted dynamic time warping (TWDTW) method for shape recognition.
Provides machine learning methods for time series classification, including support vector machines (SVM), random forests and deep learning.
Minimum recommended requirements: 8 GB RAM and 1 CPU dual-core.

Gilberto Camara

sits

Satellite Image Time Series Analysis for Remote Sensing Data Cubes

Rolf Simoes

Felipe Souza

Lorena Santos

Alexandre Carvalho

Pedro Andrade

Karine Ferreira

Alber Sanchez

Gilberto Queiroz

.sits_raster_api_new_rast function

Raster package internal create raster object function — .sits_raster_api_new_rast

Raster package internal create raster object function

.sits_raster_api_new_rast: Raster package internal create raster object function

Description

Usage

Arguments

Value