Estimation of Forest Biomass and Faraday Rotation using Ultra High Frequency Synthetic Aperture Radar

Synthetic Aperture Radar (SAR) data in the Ultra High Frequency (UHF; 300 MHz – 3 GHz)) band have been shown to be strongly dependent of forest biomass, which is a poorly estimated variable in the global carbon cycle. In this thesis UHF-band SAR data from the fairly flat hemiboreal test site Remningstorp in southern Sweden were analysed. The data were collected on several occasions with different moisture conditions during the spring of 2007. Regression models for biomass estimation on stand level (0.5-9 ha) were developed for each date on which SAR data were acquired. For L-band (centre frequency 1.3 GHz) the best estimation model was based on HV-polarized backscatter, giving a root mean squared error (rmse) between 31% and 46% of the mean biomass. For P-band (centre frequency 340 MHz), regression models including HH, HV or HH and HV backscatter gave an rmse between 18% and 27%. Little or no saturation effects were observed up to 290 t/ha for P-band. A model based on physical-optics has been developed and was used to predict HH-polarized SAR data with frequencies from 20 MHz to 500 MHz from a set of vertical trunks standing on an undulating ground surface. The model shows that ground topography is a critical issue in SAR imaging for these frequencies. A regression model for biomass estimation which includes a correction for ground slope was developed using multi-polarized P-band SAR data from Remningstorp as well as from the boreal test site Krycklan in northern Sweden. The latter test site has pronounced topographic variability. It was shown that the model was able to partly compensate for moisture variability, and that the model gave an rmse of 22-33% when trained using data from Krycklan and evaluated using data from Remningstorp. Regression modelling based on P-band backscatter was also used to estimate biomass change using data acquired in Remningstorp during the spring 2007 and during the fall 2010. The results show that biomass change can be measured with an rmse of about 15% or 20 tons/ha. This suggests that not only deforestation, but also forest growth and degradation (e.g. thinning) can be measured using P-band SAR data. The thesis also includes result on Faraday rotation, which is an ionospheric effect which can have a significant impact on spaceborne UHF-band SAR images. Faraday rotation angles are estimated in spaceborne L-band SAR data. Estimates based on distributed targets and calibration targets with high signal to clutter ratios are found to be in very good agreement. Moreover, a strong correlation with independent measurements of Total Electron Content is found, further validating the estimates

Regression-Based Retrieval of Boreal Forest Biomass in Sloping Terrain using P-band SAR Backscatter Intensity Data

A new biomass retrieval model for boreal forest using polarimetric P-band synthetic aperture radar (SAR) backscatter is presented. The model is based on two main SAR quantities: the HV backscatter and the HH/VV backscatter ratio. It also includes a topographic correction based on the ground slope. The model is developed from analysis of stand-wise data from two airborne P-band SAR campaigns: BioSAR 2007 (test site: Remningstorp, southern Sweden, biomass range: 10-287 tons/ha, slope range: 0-4 degrees) and BioSAR 2008 (test site: Krycklan, northern Sweden, biomass range: 8-257 tons/ha, slope range: 0-19 degrees). The new model is compared to five other models in a set of tests to evaluate its performance in different conditions. All models are first tested on data sets from Remningstorp with different moisture conditions, acquired during three periods in the spring of 2007. Thereafter, the models are tested in topographic terrain using SAR data acquired for different flight headings in Krycklan. The models are also evaluated across sites, i.e., training on one site followed by validation on the other site. Using the new model with parameters estimated on Krycklan data, biomass in Remningstorp is retrieved with RMSE of 40-59 tons/ha, or 22-33% of the mean biomass, which is lower compared to the other models. In the inverse scenario, the examined site is not well represented in the training data set, and the results are therefore not conclusive

Biomass Retrieval Algorithm Based on P-band BioSAR Experiments of Boreal Forest

A new biomass retrieval algorithm based on P-band multi-polarization backscatter has been developed and evaluated based on SAR and ground data over boreal forest. SAR data collections were conducted on three dates at a test site in southern Sweden (Remningstorp, biomass < 300 tons/ha; late winter to early summer 2007) and on a single date at a test site in northern Sweden (Krycklan, biomass < 200 tons/ha; fall 2008). The retrieval algorithm is a multiple linear regression model including the HV-polarized backscatter coefficient, the VV/HH backscatter ratio and the ground slope. Regression coefficients were determined from Krycklan data followed by algorithm evaluation using Remningstorp data. The results from the latter show that RMS errors vary in the range 29-42 tons/ha depending on date and stand type. The new algorithm is also compared with alternative algorithms and found to give significantly better performance. The developed model is a significant step towards an algorithm which gives consistent results across multiple sites and dates, i.e. when forest structure, topography and moisture conditions is expected to vary

Impact and modeling of topographic effects on P-band SAR backscatter from boreal forests

P-band SAR backscatter has been proven to be useful for forest biomass prediction. However, there is a need for further studies on effects of topography on P-band backscatter. In this paper, two prediction models for backscatter are evaluated, one using only biomass as predictor and one which also includes topographic corrections. Data from the BioSAR 2007 and BioSAR 2008 campaigns are used to evaluate the models. A multi-scale error model which is able to handle data from several imaging directions is used. For HH, the slope correction on stand level used in this paper is unable to correct for topographic effects. This is consistent with previous results that within stand topographic variability has a significant impact on HH P-band backscatter. For HV and VV, the model which considers topography gives lower prediction errors than the model which does not include topography. Moreover, for these polarizations topographic the correction strongly reduce the variability in backscatter measurements between imaging directions for stands with ground slopes larger than about 5 degrees

Topographic Correction for Biomass Retrieval from P-band SAR Data in Boreal Forests

The influence of the ground slope on radar backscatter has been proven to be greater for lower radar frequencies due to deeper canopy penetration. In this study, multiple heading, Pband SAR data of boreal forest in Sweden was used to find a model for topographic correction for improved biomass retrieval. Eleven models were tested and the best model was selected. The selected model was then used for biomass retrieval. Even by means of the most simplified approach, forest biomass could be established with a root-mean-square error of approximately 50 t/ha for HV and 66 t/ha for HH

Measurements of forest change using P-band SAR backscatter

Using data from the recent BioSAR 2007 and BioSAR 2010 campaigns, it has for the first time been possible to measure forest biomass change using P-band SAR data. Regression models based on backscatter change have been developed using reference data derived from high density laser scanning data. The models were evaluated for six areas with detailed in-situ measurements, for which the maximum biomass loss and growth was 30% and 20%, respectively. For the best model the coefficients of determination was 55-89%. This result suggests that not only clear cuts but also forest growth and thinning can be measured using P-band SAR backscatter

BIOSAR 2010 - A SAR campaign in support to the BIOMASS mission

The ESA funded campaign BioSAR 2010 was carried out at the forestry test site Remningstorp in southern Sweden, in support to the BIOMASS satellite mission under study. Fully polarimetric SAR data were successfully acquired at L- and P-band using ONERA's multi-frequency system SETHI. In addition with other data types gathered, e.g. LiDAR and in-situ measurements, the compiled data set will be used for analyses and comparisons with biomass estimation results obtained at the same test site in the campaign BioSAR 2007, in which DLR's E-SAR made the SAR imaging. Detection of forest changes, robustness of biomass retrieval algorithms and long-term P-band coherence will be in focus as well as cross-validations between the two SAR sensors

Cell-Mediated Immune Responses and Immunopathogenesis of Human Tick-Borne Encephalitis Virus-Infection

Tick-borne encephalitis virus (TBEV) is a flavivirus that belongs to the Flaviviridae family. TBEV is transmitted to humans primarily from infected ticks. The virus causes tick-borne encephalitis (TBE), an acute viral disease that affects the central nervous system (CNS). Infection can lead to acute neurological symptoms of significant severity due to meningitis or meningo(myelo)encephalitis. TBE can cause long-term suffering and has been recognized as an increasing public health problem. TBEV-affected areas currently include large parts of central and northern Europe as well as northern Asia. Infection with TBEV triggers a humoral as well as a cell-mediated immune response. In contrast to the well-characterized humoral antibody-mediated response, the cell-mediated immune responses elicited to natural TBEV-infection have been poorly characterized until recently. Here, we review recent progress in our understanding of the cell-mediated immune response to human TBEV-infection. A particular emphasis is devoted to studies of the response mediated by natural killer (NK) cells and CD8 T cells. The studies described include results revealing the temporal dynamics of the T cell- as well as NK cell-responses in relation to disease state and functional characterization of these cells. Additionally, we discuss specific immunopathological aspects of TBEV-infection in the CNS

Cytomegalovirus-Driven Adaptive-Like Natural Killer Cell Expansions Are Unaffected by Concurrent Chronic Hepatitis Virus Infections

Adaptive-like expansions of natural killer (NK) cell subsets are known to occur in response to human cytomegalovirus (CMV) infection. These expansions are typically made up of NKG2C+ NK cells with particular killer-cell immunoglobulin-like receptor (KIR) expression patterns. Such NK cell expansion patterns are also seen in patients with viral hepatitis infection. Yet, it is not known if the viral hepatitis infection promotes the appearance of such expansions or if effects are solely attributed to underlying CMV infection. In sizeable cohorts of CMV seropositive hepatitis B virus (HBV), hepatitis C virus (HCV), and hepatitis delta virus (HDV) infected patients, we analyzed NK cells for expression of NKG2A, NKG2C, CD57, and inhibitory KIRs to assess the appearance of NK cell expansions characteristic of what has been seen in CMV seropositive healthy individuals. Adaptive-like NK cell expansions observed in viral hepatitis patients were strongly associated with CMV seropositivity. The number of subjects with these expansions did not differ between CMV seropositive viral hepatitis patients and corresponding healthy controls. Hence, we conclude that adaptive-like NK cell expansions observed in HBV, HCV, and/or HDV infected individuals are not caused by the chronic hepatitis infections per se, but rather are a consequence of underlying CMV infection