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Monitoring of Alpine grasslands with multitemporal optical and radar remote sensing

Greifeneder, Felix and Asam, Sarah and Castelli, Mariapina and Notarnicola, Claudia and Rossi, Mattia and Stendardi, Laura (2018) Monitoring of Alpine grasslands with multitemporal optical and radar remote sensing. International SUSALPS Conference, 18. - 20. Sep 2018, Garmisch-Partenkirchen, Deutschland.

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Abstract

The European Alps are providing important ecosystem resources such as water, food, or timber. Satellite remote sensing can act as an important data source for the observation of many parameters related to these resources, offering spatially continuous, high-resolution measurements for large areas. This talk will concentrate on the possibilities for the monitoring of Alpine grasslands with optical and radar remote sensing, which is related to several projects at the Institute of Earth Observation at Eurac Research. The aims are twofold: 1) to get a better understanding of the multitemporal remote sensing signals in relation to grassland and soil conditions in mountain areas; 2) to explore the capability to distinguish different types of grassland using multitemporal radar Images, in combination with optical images and in-situ data. The Copernicus satellites Sentinel-1 and Sentinel-2 act as the main source of information. Sentinel-1 carries a so-called Synthetic Aperture Radar sensor, which is an active sensor operating in the microwave region of the electromagnetic spectrum (C-Band). It consists of a constellation of two satellites, which produce an image of the same area every six days. In its main operational mode, Sentinel-1 generates images with an original resolution of 5 by 20 m. Due to the characteristics of an active sensor and the used wavelength, images can be acquired independent of the sun and the atmospheric conditions (i.e. clouds). The Multispectral Instrument (MSI) aboard Sentinel-2 is measuring the Earth’s reflected radiance in 13 spectral bands from the visible light to short-wave-infrared, with spatial resolutions between 10 and 60 m. The constellation of two satellites provides an image over the same area every 5 days. Studying the Sentinel-1 data, we can show that the multi-temporal SAR signal shows good potential for the monitoring of different types of crop and grasslands and the soil conditions (especially soil moisture). Optical data are required to clearly distinguish between grassland and other types of crop. Despite the limitations of SAR in mountainous Areas, due to the independence of the weather conditions it is possible to clearly detect the phenological Dynamics, as well as the time of harvest of grasslands. Overall, the combination of optical and radar imagery allows to overcome some of the limitations of the two individual sensing methods to produce more reliable observations.

Item URL in elib:https://elib.dlr.de/123056/
Document Type:Conference or Workshop Item (Speech)
Title:Monitoring of Alpine grasslands with multitemporal optical and radar remote sensing
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Greifeneder, FelixUNSPECIFIEDUNSPECIFIED
Asam, Sarahsarah.asam (at) dlr.dehttps://orcid.org/0000-0002-7302-6813
Castelli, Mariapinamariapina.castelli (at) eurac.eduUNSPECIFIED
Notarnicola, Claudiaclaudia.notarnicola (at) eurac.eduUNSPECIFIED
Rossi, Mattiamattia.rossi (at) eurac.eduUNSPECIFIED
Stendardi, LauraUNSPECIFIEDUNSPECIFIED
Date:19 September 2018
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Sentinel-1 Sentinel-2 grassland multi-temporal
Event Title:International SUSALPS Conference
Event Location:Garmisch-Partenkirchen, Deutschland
Event Type:international Conference
Event Dates:18. - 20. Sep 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Asam, Dr. Sarah
Deposited On:13 Nov 2018 11:07
Last Modified:13 Nov 2018 11:07

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