direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content


Using radiative transfer models for mapping soil moisture content under grassland with UAS-borne hyperspectral data
Citation key Döpper2021
Author Veronika U. Döpper and Alby Duarte Rocha and Tobias Gränzig and Birgit Kleinschmit and Michael Förster
Year 2021
ISSN 0277-786X
DOI https://doi.org/10.1117/12.2600296
Journal Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII
Abstract Soil moisture content (SMC) is a key parameter of environmental processes. Remote sensing provides effective methods for mapping SMC at different spatial resolutions. Using UAS-borne hyperspectral observations enables a SMC retrieval at sub-meter scales. Radiative transfer models (RTMs) such as ProSAIL or Scope include a SMC specific input variable and are thus a potential tool to derive SMC and avoiding extensive reference SMC measurements. The inverse application of RTMs supplies information on SMC and plant traits. Scope and ProSAIL involve SMC data of the root zone and at the surface, respectively. The combined use of both models offers the possibility to derive SMC at two vertical depths. Moreover, SMC relevant vegetation proxies such as leaf water content can be retrieved and alternatively used as indicator for SMC. Such plant traits are highest correlated to SMC at depths of major water uptake. However, their response can have a significant time-lag. We analyze the derivation of SMC at the soil surface and at the root zone using the SMC parameters within existing RTMs. As a first step, we investigate on the sensitivity of ProSAIL and Scope to their soil moisture parameters. We apply these findings on UAS-borne hyperspectral and TIR imagery acquired over a pre-alpine TERENO grassland area. The site is equipped with a SoilNet that measures SMC at different depths. Using this data, we assess the vertical extent of both soil moisture content parameters. By inverse modelling of the vegetation parameters and the use of the temporally continuous SoilNet data at root zone level, we analyze the time-lag between changes in SMC and the corresponding plant trait response to optimize the retrieval of SMC.
Bibtex Type of Publication Kleinschmit
Link to publication Download Bibtex entry

To top

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

This site uses Matomo for anonymized webanalysis. Visit Data Privacy for more information and opt-out options.

Geoinformation in Environmental Planning Lab
Office EB5
Straße des 17. Juni 145
D - 10623 Berlin
Phone: +49 (0)30 314 - 73 29 0
Fax: +49 (0)30 314 - 23 50 7