.sits_clouds_shds_estimate

cube

extent

ref_date

Vector of values for cloud detection

values

controls difference btw visible and infrared bands

controls brightness properties of cloud

controls dark property of cloud shadows.

remove influence of water in shadow detection

size of window to search for clouds near shadows

size of window of median filter to remove outliers

multicores

Estimate clouds and shadows for a CBERS AWFI image

internal

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Supports data retrieval from a web time series service (WTSS), raster bricks and cubes from the Brazilan Data Cube.
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_clouds_shds_estimate: Estimate clouds and shadows for a CBERS AWFI image

Description

Usage

Arguments

Value