RGISTools: Downloading, Customizing, and Processing Time Series of Remote Sensing Data in R

02/05/2020
by   U. Pérez-Goya, et al.
0

There is a large number of data archives and web services offering free access to multispectral satellite imagery. Images from multiple sources are increasingly combined to improve the spatio-temporal coverage of measurements while achieving more accurate results. Archives and web services differ in their protocols, formats, and data standards, which are barriers to combine datasets. Here, we present RGISTools, an R package to create time-series of multispectral satellite images from multiple platforms in a harmonized and standardized way. We first provide an overview of the package functionalities, namely downloading, customizing, and processing multispectral satellite imagery for a region and time period of interest as well as a recent statistical method for gap-filling and smoothing series of images, called interpolation of the mean anomalies. We further show the capabilities of the package through a case study that combines Landsat-8 and Sentinel-2 satellite optical imagery to estimate the level of a water reservoir in Northern Spain. We expect RGISTools to foster research on data fusion and spatio-temporal modelling using satellite images from multiple programs.

READ FULL TEXT

page 7

page 10

page 13

page 21

research
07/16/2021

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks

Unprecedented access to multi-temporal satellite imagery has opened new ...
research
05/11/2019

Time delay estimation in satellite imagery time series of precipitation and NDVI: Pearson's cross correlation revisited

In order to describe more accurately the time relationships between dail...
research
02/04/2022

Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery

Our goal is to quantify whether, and if so how, spatio-temporal patterns...
research
07/03/2018

SpaceNet: A Remote Sensing Dataset and Challenge Series

Foundational mapping remains a challenge in many parts of the world, par...
research
04/11/2013

Merging Satellite Measurements of Rainfall Using Multi-scale Imagery Technique

Several passive microwave satellites orbit the Earth and measure rainfal...
research
02/20/2020

Better coverage, better outcomes? Mapping mobile network data to official statistics using satellite imagery and radio propagation modelling

Mobile sensing data has become a popular data source for geo-spatial ana...
research
06/23/2021

Sentinel-1 and Sentinel-2 Spatio-Temporal Data Fusion for Clouds Removal

The abundance of clouds, located both spatially and temporally, often ma...

Please sign up or login with your details

Forgot password? Click here to reset