The animation shows daily average global soil moisture, based on nearly 40 years of data from multiple satellite sensors. Blue depicts areas with high soil moisture, while brown shows low moisture – such as in deserts. Rainforests are green, while frozen soil is white. Source: TU Wien 2017.
  1. Locate the path, where your R libraries are installed.
.libPaths() 

2. Open path location and remove the related “Rcpp” libraries

3. Install the Rcpp package “freshly”

install.packages("Rcpp") # Install package again

4. Import the package to your R session.

library("Rcpp") # Install package again

Learning objectives of this topic

  • Understand, why soil moisture is an important environmental parameter.
  • Learn how soil moisture can be measured and what the physical assumptions are.
  • Work with real-life data to derive soil moisture from remotely-sensed data.

Pre Requisites


Introduction

Deforestation, desertification, urbanization, land degradation, loss of biodiversity and ecosystem functions and many more anthropogenic issues. These are all concerns which we have heard about in the media, but how do they connect to the field of remote sensing? On the basic level, identifying and monitoring these issues is possible with the help of land cover maps. Land cover maps can be used in a variety of ways, from observing the current ground conditions, to understanding how our global (or local) landscape has changed over the years. Through this lesson you will become familiar with how to differentiate between the many land cover map options to identify the best choice for your application.

Kai Heckel

Kai Heckel is a doctoral candidate at the Department for Earth Observation at Friedrich Schiller University, Jena. Areas of expertise: forest change monitoring, savanna ecosystem research, machine-learning based multi-temporal and -sensor data fusion approaches.

Dr. Marcel Urban

Dr. Marcel Urban is a postdoc at the Department for Earth Observation at Friedrich Schiller University, Jena. Areas of expertise: time series analysis, multi-scale vegetation mapping, land degradation mapping, arctic climate change research.

Dr. Carsten Pathe

Dr. Carsten Pathe is a postdoc at the Department for Earth Observation at Friedrich Schiller University, Jena. Areas of expertise: soil moisture retrieval, change detection, time series analysis, microwave imaging.