TR32-Database: Database of Transregio 32

[1022] - Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Hasan, S., Montzka, C., Ali, M., Bogena, H., Vereecken, H., 2014. Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data. Journal of Photogrammetry and Remote Sensing, 59 - 71.
Identification
Title(s):Main Title: Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data
Description(s):Abstract: For the soil moisture retrieval from passive microwave sensors such as the ESA Soil Moisture and Ocean Salinity (SMOS) and the NASA Soil Moisture Active and Passive (SMAP) mission, a good knowledge about the vegetation characteristics is necessary. Vegetation cover is a principal factor in the attenuation, scattering and absorption of the microwave emissions from the soil; and has a direct impact on the brightness temperature by way of its canopy emissions. Here, brightness temperatures were measured at three altitudes across the TERENO (Terrestrial Environmental Observatories) site Rur catchment, Germany, to achieve a range of spatial resolutions using the airborne Polarimetric L-band Multibeam Radiometer 2 (PLMR2). The L-band Microwave Emission of the Biosphere (L-MEB) model which simulates microwave emissions from the soil–vegetation layer at L-band was used to retrieve surface soil moisture. We developed a Monte Carlo approach to simultaneously estimate soil moisture and the vegetation parameter b’ describing the relationship between τ and leaf area index (LAI). LAI was retrieved from multispectral RapidEye imagery. In this approach the plant specific vegetation parameter b’ was estimated from the lowest flight altitude data for crop, grass, coniferous forest and deciduous forest. Mean values of b’ were found to be 0.18, 0.07, 0.26 and 0.23, respectively. By assigning the estimated b’ to higher flight altitude data sets, high accuracy soil moisture retrieval was obtained with Root Mean Square Difference (RMSD) of 0.035 m3m−3 as compared to ground-based measurements.
Responsible Party
Creator(s):Author: Sayeh Hasan
Author: Carsten Montzka
Author: Muhammad Ali
Author: Heye Bogena
Author: Harry Vereecken
Publisher:Elsevier
Topic
TR32 Topic:Remote Sensing
Subject(s):CRC/TR32 Keywords: Soil Moisture
File Details
File Name:JPRS_Sayeh et al. 2014.pdf
Data Type:Text
File Size:3261 kB (3.185 MB)
Date(s):Date Submitted: 2014-09-17
Mime Type:application/pdf
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2014
Type:Article
Article Type:Journal
Source:Journal of Photogrammetry and Remote Sensing
Page Range:59 - 71
Metadata Details
Metadata Creator:Heye Bogena
Metadata Created:2014-09-17
Metadata Last Updated:2014-09-17
Subproject:C1
Funding Phase:1
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:177
Metadata Downloads:0
Dataset Downloads:4
Dataset Activity
Features