Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation

Climate change can reduce the availability of water resources in many regions, and it will affect agriculture, industry, and energy supply. Snowpack monitoring is important in water resource management as well as flood and avalanche protection. The rapid melting process due to global warming changes the snowpacks' annual statistics, including the extent, and the snow water equivalent (SWE) of seasonal snowpacks, which results in non-stationary annual statistics that should be monitored in nearly daily intervals. The development of advanced radiometric sensors capable of accurately measuring the snowpack thickness and SWE is needed for the long-term study of the snowpack parameters' statistical changes. Passive microwave radiometry provides a means for measuring the microwave emission from a scene of snow and ice. A Wideband Autocorrelation Radiometer (ac{WiBAR}) operating from 1-2~GHz measures spontaneous emission from snowpack at long wavelengths where the scattering is minimized, but the snow layer coherent effects are preserved. By using a wide bandwidth to measure the spacing between frequencies of constructive and destructive interference of the emission from the soil under the snow, it can reveal the microwave travel time through the snow, and thus the snow depth. However, narrowband radio frequency interference (RFI) in the WiBAR's frequency of operations reduces the ability of the WiBAR to measure the thickness accurately. In addition, the current WiBAR system is a frequency domain, FD-WiBAR, system that uses a field-portable spectrum analyzer to collect the data and suffers from high data acquisition time which limits its applications for spaceborne and airborne technologies. In this work, a novel frequency tunable microwave comb filter is proposed for RFI mitigation. The frequency response of the proposed filter has a pattern with many frequencies band-pass and band rejection that preserves the frequency span while reducing the RFI. Moreover, we demonstrate time-domain WiBAR, TD-WiBAR, which presented as an alternative method for FD-WiBAR, and is capable of providing faster data acquisition. A new time-domain calibration is also developed for TD-WiBAR and evaluated with the frequency domain calibration. To validate the TD-WiBAR method, simulated laboratory measurements are performed using a microwave scene simulator circuit. Then the WiBAR instrument is enhanced with the proposed comb filter and showed the RFI mitigation in time-domain mode on an instrument bench test. Furthermore, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while an incoherent radiative transfer model describes the volume scattering from the vegetation layer. We proposed a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. The proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, demonstrating the applicability of this model.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169653/1/maryamsa_1.pd

Photonic monitoring of atmospheric fauna

Insects play a quintessential role in the Earth’s ecosystems and their recent decline in abundance and diversity is alarming. Monitoring their population is paramount to understand the causes of their decline, as well as to guide and evaluate the efficiency of conservation policies. Monitoring populations of flying insects is generally done using physical traps, but this method requires long and expensive laboratory analysis where each insect must be identified by qualified personnel. Lack of reliable data on insect populations is now considered a significant issue in the field of entomology, often referred to as a “data crisis” in the field. This doctoral work explores the potential of entomological photonic sensors to unlock some of the limitations of traditional methods. This work focuses on the development of optical instruments similar in essence to lidar systems, with the goal of counting and identifying flying insects from a distance in their natural habitat. Those systems rely on the interactions between the near-infrared laser light and insects flying through the laser beam. Each insect is characterized by retrieving its optical and morphological properties, such as wingbeat frequency, optical cross sections, or depolarization ratios. This project ran in parallel a series of laboratory and field experiments. In the laboratory, prototypes were tested and used to create a database of insects’ properties. The data were used to train machine learning classifiers aiming at identifying insects from optical signals. In the case of mosquitoes, the sex and species of an unknown specimen was predicted with a 99% and 80% accuracy respectively. It also showed that the presence of eggs within the abdomen of a female mosquito could be detected from several meters away with 87% accuracy. In the field, instruments were deployed in real-world conditions for a total of 520 days over three years. More than a million insects were observed, allowing to continuously monitor their aerial density over months with a temporal resolution down to the minute. While this approach remains very new, this work demonstrated that photonic sensors could become a powerful tool to tackle the current lack of data in the field of entomology

Phytoplankton Community Composition in the Surface Ocean: Methods for Detection using Optical Measurements, Pigment Concentrations, and Flow Cytometry

Phytoplankton are microscopic photoautotrophs living in the surface ocean waters and help support all life on earth via photosynthetic production of oxygen. Thousands of species make up the bulk phytoplankton community, and the spatial and temporal distribution of different types of phytoplankton has relevance for many ocean ecosystem questions including marine food web dynamics, and carbon flux and sequestration. Methods to detect phytoplankton community composition (PCC) on the vast scale of the global ocean require estimates of PCC from remote platforms, namely earth-observing satellites. The use of satellite data to observe and interpret PCC in the surface ocean requires significant effort to develop and evaluate algorithms based on measurements made in situ; the work of this thesis contributes to that effort. Information from both global and regional (North Atlantic Ocean) datasets is applied to develop methods to estimate phytoplankton pigment concentrations, phytoplankton size classes, and diatom carbon concentrations. Optical spectra, specifically hyperspectral remote-sensing reflectance, are used in the algorithm for estimating phytoplankton pigments, which resolves the concentrations of three pigments and one pigment group (chlorophylls a, b, c, and photoprotective carotenoids). This result has implications for use with hyperspectral ocean color data measured by satellite. A novel dataset of open-ocean image-in-flow cytometry is used to evaluate and improve a commonly applied phytoplankton size class algorithm, as well as to calculate diatom carbon and develop a model to map diatom carbon using environmental parameters as model input. Biases and uncertainties in the size class algorithm are reduced by our method relative to previously published work for all three size classes (pico-, nano-, and microplankton). Diatom carbon measurements from quantitative cell imagery elucidate the variability of diatom biomass as function of chlorophyll a concentration, and this novel information enables improved methods to detect diatoms from space. The findings of this thesis are relevant to large-scale studies of ocean ecosystems and are critical for algorithm development using both current and upcoming earth-observing satellite data. Additionally, the results presented here provide tools that will benefit oceanographic research on spatial scales relevant to a changing ocean climate

GNSS reflectometry for land remote sensing applications

Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA

Aspects of in situ angular scattering measurements in contrasting waters

Rapid changes are observed in oceanic and coastal environments around the world due to global temperatures increases, ocean acidification and changing weather patterns - anthropogenic climate change. These changes have large effects on the ecosystems of the ocean. In order to understand the effects and possibly mitigate their consequences, it is necessary to increase and improve the environmental monitoring of the ocean. Optical properties of natural waters within the visible spectrum is closely linked to properties of phytoplankton, the foundation of oceanic ecosystems, as well as other particles on the micrometer and sub-micrometer scale in the water mass. Optical measurements can thus give us valuable information about the particle content of the water and the state of the ecosystem. The volume scattering function (VSF) is a fundamental optical property describing how much light is scattered by a medium and in what direction the light is scattered. In natural waters, by far most of the light is scattered in the very forward direction, which makes it technically challenging to measure the VSF. The LISST-VSF is the first commercially available instrument for field measurements of the VSF over a large angular domain. To trust the measurements, it is important to validate the performance of instrument and identify any error sources, in particular the valid range of the instrument, given that scattering coefficients of natural waters can span three orders of magnitude. In this thesis, I have characterised LISST-VSF measurements using both in situ measurements of highly contrasting water types, controlled laboratory measurements, and Monte Carlo simulations of instrument geometry. Similar aspects have been investigated for the LISST-200X, which measures the VSF at angles 0.04-13˚ at 670 nm. In Paper I, these two instruments are calibrated and validated using polymer beads and in situ measurements spanning from clear waters on the North Pole to highly turbid glacial meltwater. The measurements demonstrated that due to instrument design, the LISST-200X only gives valid scattering measurements in moderate-to-turbid waters. The LISST-VSF gives valid measurements also in clear waters (however with a loss in precision), but is limited by multiple scattering errors in more turbid waters. Multiple scattering effects on LISST-VSF measurements are investigated in detail in in Paper II and III. For this purpose, a Monte Carlo simulation was developed and validated with experimental data, and subsequently used to simulate LISST-VSF measurements with Fournier-Forand and Henyey-Greenstein phase functions. We demonstrated that the multiple scattering can yield uncertainties of 10% when the scattering coefficient is 1 m-1, which significantly restricts the accurate measurement range of LISST-VSF. LISST-200X is less affected by this error due to its shorter path length. Scattering can be an error source for other optical measurements as well. In Paper IV, we attempt to correct in situ depth profiles of absorption coefficients measured with the ac-s instrument using VSF measurements collected with the LISST-VSF in coastal waters. We show that this method does not show a clear and consistent improvement over existing methods, which are simpler to use but make strong assumptions about absorption and scattering properties. The discrepancies in the VSF correction can be attributed to several different confounding factors, such as spatial variability and multiple scattering, which are exceedingly propagated to the corrected absorption values. Nevertheless, VSF measurements are found useful to analyze the scattering error. We show that the VSF between 5-90˚ can contribute significantly to the scattering error, depending on the phase function and the reflectance efficiency of the reflective tube. Moreover, by simulating the VSF wavelength-dependency using Mie theory, we show that particle sub-populations with diameters close to the wavelength can explain why scaling the scattering error with the scattering coefficient sometimes fails.Doktorgradsavhandlin

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Nio Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans