.sits_s2_aws_items

a <code>character</code> representing a URL for the AWS catalog.

a <code>character</code> with the collection to be searched.

collection

a <code>character</code> with the names of the tiles.

tiles

selects images (tiles) that intersect according to the
region of interest provided. Expressed either as an <code>sfc</code> or <code>sf</code>
object from sf package, a <code>character</code> with GeoJSON following the rules
from RFC 7946, or a <code>vector</code> with bounding box named XY values in
WGS 84 ("xmin", "xmax", "ymin", "ymax").

a <code>character</code> corresponds to the initial date
when the cube will be created.

start_date

a <code>character</code> corresponds to the final date when the
cube will be created.

end_date

a <code>character</code> vector with the bands name.

bands

other parameters to be passed for specific types.

Get information from items related to Sentinel-2 in AWS

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.

.sits_s2_aws_items: Get information from items related to Sentinel-2 in AWS

Description

Usage

Arguments

Value