Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data
This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.
Feature
Request download
Citation
Citation Options
Identification
Title: | Main Title: Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data |
Description: | 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
Creators: | Sayeh Hasan (Author), Carsten Montzka (Author), Muhammad Ali (Author), Heye Bogena (Author), Harry Vereecken (Author) |
Publisher: | Elsevier |
Publication Year: | 2014 |
Topic
TR32 Topic: | Remote Sensing |
Related Subproject: | C1 |
Subject: | Keyword: Soil Moisture |
File Details
Filename: | JPRS_Sayeh et al. 2014.pdf |
Data Type: | Text - Article |
File Size: | 3.2 MB |
Date: | Submitted: 17.09.2014 |
Mime Type: | application/pdf |
Language: | English |
Status: | Completed |
Constraints
Download Permission: | Only Project Members |
General Access and Use Conditions: | According to the TR32DB data policy agreement. |
Access Limitations: | According to the TR32DB data policy agreement. |
Licence: | [TR32DB] Data policy agreement |
Geographic
Specific Information - Publication
Publication Status: | Published |
Review Status: | Peer reviewed |
Publication Type: | Article |
Article Type: | Journal |
Source: | Journal of Photogrammetry and Remote Sensing |
Number of Pages: | 13 (59 - 71) |
Metadata Details
Metadata Creator: | Heye Bogena |
Metadata Created: | 17.09.2014 |
Metadata Last Updated: | 17.09.2014 |
Subproject: | C1 |
Funding Phase: | 1 |
Metadata Language: | English |
Metadata Version: | V50 |
Metadata Export
Metadata Schema: |
Dataset Statistics
Page Visits: | 1122 |
Metadata Downloads: | 0 |
Dataset Downloads: | 5 |
Dataset Activity
Feature
Download
By downloading this dataset you accept the license terms of [TR32DB] Data policy agreement and TR32DB Data Protection Statement
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.