Microwave backscatter modeling of erg surfaces in the Sahara Desert

The Sahara Desert includes large expanses of sand dunes called ergs. These dunes are formed and constantly reshaped by prevailing winds. Previous study shows that Saharan ergs exhibit significant radar backscatter (σ°) modulation with azimuth angle (f). We use σ° measurements observed at various incidence angles and f from the NASA Scatterometer (NSCAT), the SeaWinds scatterometer, the ERS scatterometer (ESCAT), and the Tropical Rainfall Measuring Mission\u27s Precipitation Radar to model the σ° response from sand dunes. Observations reveal a characteristic relationship between the backscatter modulation and the dune type, i.e., the number and orientation of the dune slopes. Sand dunes are modeled as a composite of tilted rough facets, which are characterized by a probability distribution of tilt with a mean value, and small ripples on the facet surface. The small ripples are modeled as cosinusoidal surface waves that contribute to the return signal at Bragg angles only. Longitudinal and transverse dunes are modeled with rough facets having Gaussian tilt distributions. The model results in a σ° response similar to NSCAT and ESCAT observations over areas of known dune types in the Sahara. The response is high at look angles equal to the mean tilts of the rough facets and is lower elsewhere. This analysis provides a unique insight into scattering by large-scale sand bedforms

Global Soil Moisture Patterns Observed by Space Borne Microwave Radiometers and Scatterometers

Within the scope of the upcoming launch of a new water related satellite mission (SMOS) a global evaluation study was performed on two available global soil moisture products. ERS scatterometer surface wetness data was compared to AMSR-E soil moisture data. This study pointed out a strong similarity between both products in sparse to moderate vegetated regions with an average correlation coefficient of 0.83. Low correlations were found in densely vegetated areas and deserts. The low values in the vegetated regions can be explained by the limited soil moisture retrieval capabilities over dense vegetation covers. Soil emission is attenuated by the canopy and tends to saturate the microwave signal with increasing vegetation density, resulting in a decreased sensor sensitivity to soil moisture variations. It is expected that the new low frequency satellite mission (SMOS) will obtain soil moisture products with a higher quality in these regions. The low correlations in the desert regions are likely due to volume scattering or to the dielectric dynamics within the soil. The volume scattering in dry soils causes a higher backscatter under very dry conditions than under conditions when the sub-surface soil layers are somewhat wet. In addition, at low moisture levels the dielectric constant has a reduced sensitivity in response to changes in the soil moisture content. At a global scale the spatial correspondence of both products is high and both products clearly distinguish similar regions with high seasonal and inter annual variations. Based on the global analyses we concluded that the quality of both products was comparable and in the sparse to moderate vegetated regions both products may be beneficial for large scale validation of SMOS soil moisture. Some limitations of the studied products are different, pointing to significant potential for combining both products into one superior soil moisture data set. © The Author(s) 2008

L-Band Multi-Polarization Radar Scatterometry over Global Forests: Modelling, Analysis, and Applications

Spaceborne L-band radars have the ability to penetrate vegetation canopies over forested areas, suggesting a potential for regular and frequent global monitoring of both the vegetation state and the subcanopy soil moisture. However, L-band radar’s sensitivity to both vegetation and ground also complicates the relationship between the radar observations and the ecological and geophysical parameters. Accurate yet parsimonious forward models of the radar backscatter are valuable to building an understanding of these relationships. In the first part of this thesis, a model of L-band multi-polarization radar backscatter from forests, intended for use at regional to global spatial scales, is presented. Novel developments in the model include the consideration of multiple scattering within the dense vegetation canopy, and the application of a general model of plant allometry to mitigate the need for much intensive field data for training or over-tuning towards specific sites and tree species. Aided by our model, in the remainder and majority of the thesis, a detailed analysis and interpretation of L-band backscatter over global forests is performed, using data from the Aquarius and SMAP missions. Quantitative differences in backscatter predicted by our model due to freeze/thaw states, branch orientation, and flooding are partially verified against the data, and fitted values of aboveground-biomass and microwave vegetation optical depths are comparable to independent estimates in the literature. Polarization information is used to help distinguish vegetation and ground effects on spatial and temporal variations. We show that neither vegetation nor ground effects alone can explain spatial variations within the same land cover class. For temporal variations during unfrozen periods, soil moisture is found to often be an important factor at timescales of a week to several months, although vegetation changes remain a non-negligible factor. We report the observation of significant differences in backscatter depending on beam azimuthal angle, possibly due to plant phototropism. We also investigated diurnal variations, which have the potential to reveal signals related to plant transpiration. SMAP data from May-July 2015 showed that globally, co-polarized backscatter was generally higher at 6PM compared to 6AM over boreal forests, which is not what one might expect based on previous studies. Based on our modelling, increased canopy extinction at 6AM is a possible cause, but this is unproven and its true underlying physical cause undetermined. Finally, by making simplifying approximations on our forward model, we propose and explore algorithms for soil moisture retrieval under forest canopies using L-band scatterometry, with preliminary evaluations suggesting improved performance over existing algorithms.</p

Radar Backscatter Modeling Based on Global TanDEM-X Mission Data

Radarrückstreuung bezeichnet den Teil eines ausgesendeten elektromagnetischen Signals, der von einem Ziel am Boden wieder zurück zur Antenne gerichtet ist. Die Eigenschaften des zurückgestreuten Signals ändern sich in Abhängigkeit von Frequenz und Polarisation des Radarsignals, der Aufnahmegeometrie, sowie vom Zustand des Erdbodens und der Art der Bodenbedeckung. Informationen über das Radarrückstreuverhalten sind von höchster Wichtigkeit für die Auslegung von SAR-Missionen und werden verbreitet zur Entwicklung wissenschaftlicher Modelle genutzt, beispielsweise bei der Erforschung der Biosphäre und Kryosphäre. Hauptziel dieser Arbeit ist die Auswertung und Nutzung des globalen TanDEM-X-Datensatzes zur Modellierung der Radarrückstreuung im X-Band unter Berücksichtigung unterschiedlicher Aufnahmeparameter und Landnutzungsarten, sowie die Bereitstellung einer Reihe von globalen Rückstreumodellen, die auf aktuellen Daten basieren, für die wissenschaftliche Gemeinschaft. Es wurde ein neuer Ansatz zur statistischen Modellierung der Rückstreuinformation entwickelt, der die Qualität der zugrunde liegenden Messungen berücksichtigt. Daraus ergeben sich gewichtete polynomiale Modelle für die verschiedenen Landnutzungsarten, wie sie in der GlobCover-Karte der ESA definiert sind. Darüber hinaus wird ein eigener Validierungsansatz vorgestellt, mit zusätzlicher Betrachtung der saisonalen Variation der Rückstreuung und einer separaten Analyse des Rückstreuverhaltens des Tropischen Regenwaldes. Der nächste Schwerpunkt ist die Betrachtung des Grönländischen Eisschildes, das gekennzeichnet ist durch das Vorhandensein verschiedener Arten von Schneebedeckung, die von trockenem bis hin zu sehr feuchtem Schnee variiert. Der begrenzte Detailgrad, den die GlobCover Karte in Grönland aufweist (nur eine Klasse für das gesamte Eisschild), erlaubt dort keine verlässliche Modellierung der Rückstreuung. Diese Schwierigkeit lieferte die Motivation für die Entwicklung eines neuen Ansatzes zur Analyse des Informationsgehalts der interferometrischen TanDEM-X-Daten mit dem Ziel, unterschiedliche Schnee-Fazien mit Hilfe des sog. C-Means Fuzzy Clustering Algorithmus zu lokalisieren. Aus dieser Untersuchung konnte die Existenz von vier unterschiedlichen Klassen von Schnee-Fazien abgeleitet werden, deren Eigenschaften anschließend mit Hilfe externer Referenzdaten interpretiert wurden. Die daraus entstandene Karte wurde zur Erstellung eines einfallswinkelabhängigen Rückstreumodells genutzt, separat für jede der vier Klassen, wobei eine modifizierte Version des entwickelten Algorithmus zur Generierung globaler Rückstreumodelle eingesetzt wurde. Darüber hinaus wurde als Nebenprodukt zusätzlich die Eindringtiefe von TanDEM-X in die Eisschicht geschätzt, durch Inversion des von Weber Hoen und Zebker vorgeschlagenen "Ein-chicht Volumendekorrelationsmodells". Die Ergebnisse wurden mit dem Höhenunterschied zwischen dem globalen TanDEM-X-DEM und ICESat-Messungen verglichen. Abschließend wird ein neu entwickelter Algorithmus zur Generierung von Rückstreukarten großer Gebiete vorgestellt. Dieser erlaubt unter Verwendung von Rückstreumodellen das Angleichen der erstellten Karten anhand eines Referenzeinfallswinkels, was dann das Füllen verbleibender Lücken ermöglicht, die aufgrund fehlender Eingangsdaten vorhanden sind