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Derivation of biophysical parameters from fused remote sensing data

Dahms, Thorsten and Kumar-Babu, Dinesh and Borg, Erik and Schmidt, Marco and Conrad, Christopher (2017) Derivation of biophysical parameters from fused remote sensing data. IGARSS, 23 -28.07.2017, Dallas, Texas.

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Official URL: http://ieeexplore.ieee.org/document/8127970/


Recent launches of optical space-borne remote sensing systems with high spatial resolution, high temporal revisit frequency and constant viewing angles (e.g.: Venµs, Sentinel-2) will fortify the potential of remote sensing applications in the context of agricultural monitoring (e.g.: the derivation of biophysical parameters). The practicality of this kind of remote sensing data is limited by tile and cloud coverage. Spatial temporal image fusion techniques (e.g: STARFM) can be used to combine the data from different remote sensing sensor systems to overcome these challenges. In order to investigate the reliability of synthesized remote sensing data in agricultural monitoring, we evaluated the quality of the prediction of FPAR and LAI on maize. In this context, we used synthetic daily Landsat-like data and a RandomForest model to predict FPAR and LAI for the entire growing period in 2015. The evaluation of the biophysical time series was concluded using a weekly to bi weekly ground measurements in different phenological stages of the maize plant. The quality assessment of the entire growing period revealed the high potential of synthetic remote sensing data for agricultural monitoring. The quality of results range between R² = 0.68; RMSE = 0.79 (LAI) and R² = 0.76; RMSE = 0.12 (FPAR).

Item URL in elib:https://elib.dlr.de/115662/
Document Type:Conference or Workshop Item (Speech)
Title:Derivation of biophysical parameters from fused remote sensing data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Borg, ErikUNSPECIFIEDhttps://orcid.org/0000-0001-8288-8426
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 4374-4377
Keywords:remote sensing, biophysical Parameters, FPAR
Event Title:IGARSS
Event Location:Dallas, Texas
Event Type:international Conference
Event Dates:23 -28.07.2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
German Remote Sensing Data Center > National Ground Segment
Deposited By: Wöhrl, Monika
Deposited On:21 Nov 2017 13:35
Last Modified:29 Mar 2023 00:34

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