Dealing with Multiplatform Satellite Images
Coerce to a Data Frame
Create records object from data frame
Combine values into a vector or a list
Get/set the dates from a records or an rtoi
Loads into R a time series of images regarding an rtoi, satellite prod...
Extracts or assign the path of the database
Get the API name of a records
Get the file path of a records or an rtoi
Extract the url to download a data record
Get the slot called order from a records or an rtoi
Extract the url of the preview
Length of an object
Get the name of the object
Create a new records object
Creates a new rtoi object
Plot an rtoi object
Prints the values
Prints the credentials for the web services
Get the name of the product from a records or an rtoi
Reads an rtoi from the hard drive
A class object for satellite image metadata
Extracts the satellite records
Extracts region from an rtoi
Renames an rtoi
`rsat'
Create cloud mask from an rtoi
Computes a remote sensing index from an rtoi
Download the images from a records or an rtoi object
List the information available for an rtoi
Mosaic the tiles intersecting the region of interest
Preview a records or an rtoi object
Show the products accepted by the services
Search satellite images
Fill data gaps and smooth outliers in a time series of satellite image...
Region and Time Of Interest (rtoi)
Get the name of the satellite(s) from a records or an rtoi
Saves the credentials for the web services
Show an Object
List the variables and satellites supported by rsat
Extract or replace parts of an object
Filter the satellite records of a records or an rtoi
Testing function
Result of IMA test 1
Result of IMA test 2
Extract unique elements
Downloading, customizing, and processing time series of satellite images for a region of interest. 'rsat' functions allow a unified access to multispectral images from Landsat, MODIS and Sentinel repositories. 'rsat' also offers capabilities for customizing satellite images, such as tile mosaicking, image cropping and new variables computation. Finally, 'rsat' covers the processing, including cloud masking, compositing and gap-filling/smoothing time series of images (Militino et al., 2018 <doi:10.3390/rs10030398> and Militino et al., 2019 <doi:10.1109/TGRS.2019.2904193>).