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SC5.15

Deriving soil moisture information with optical remote sensing data in R

Soil moisture is a key variable needed for application in climatology and hydrology. Knowledge about soil moisture is important to understand the ecosystems feedback to global climate change. Remote sensing can assist with deriving spatial soil moisture data on a regular basis. Particularly, optical remote sensing can be used to estimate soil moisture with unprecedented satellite archives (>30 years of Landsat) at high spatial resolution (30 m) globally.
Optical Trapezoid Model (OPTRAM) has shown high accuracy in soil moisture estimation over mineral and organic soils. OPTRAM utilises NIR and SWIR spectral regions that are sensitive to the water content in soil and vegetation. In wetlands, OPTRAM can also be used to derive information about groundwater position. Deriving soil moisture information with OPTRAM is a complex task that requires skills in processing remote sensing images, coding and analysing spatiotemporal data.
In this workshop, we will present the workflow needed for OPTRAM calculation in open-source R software. We will guide the participants on several key points:
- sources to derive optical remote sensing data;
- spatial data wrangling;
- estimation of OPTRAM;
- plotting of spatial data;
- interpretation of results.

Public information:

We have uploaded the code and data to GitHub (you can find them following this link: https://github.com/PEATSPEC/EGU22_WTD_workshop). For the course, there is no need to install R software or download data; you will run all the code online via Binder. If you want to try Binder in advance - go to the GitHub link above and scroll down the page; at the bottom, you will see the button "launch binder" - click it. The first launch of the Binder will take up to 10 min (the second time it will be faster).
Please, take your laptops tomorrow, so we can run the code together.

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Convener: Iuliia BurdunECSECS | Co-conveners: Michel Bechtold, Viacheslav KomisarenkoECSECS

Tue, 24 May, 13:20–14:50 (CEST)

Room -2.85/86

Public information:

Session assets

Session materials

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