Cross-sensors analysis of multispectral Earth observation data for environmental monitoring

Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.

Development of textile wearable chemical sensors

In this elaborate, a textile-based Organic Electrochemical Transistor (OECT) was first developed for the determination of uric acid in wound exudate based on the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which was then coupled to an electrochemically gated textile transistor consisting of a composite of iridium oxide particles and PEDOT:PSS for pH monitoring in wound exudate. In that way a sensor for multiparameter monitoring of wound health status was assembled, including the ability to differentiate between a wet-dry status of the smart bandage by implementing impedance measurements exploiting the OECT architecture. Afterwards, for both wound management as well as generic health status tracking applications, a glass-based calcium sensor was developed employing polymeric ion-selective membranes on a novel architecture inspired by the Wrighton OECT configuration, which was later converted to a Proof-of-Concept textile prototype for wearable applications. Lastly, in collaboration with the King Abdullah University of Science and Technology (KAUST, Thuwal, Saudi Arabia) under the supervision of Prof. Sahika Inal, different types of ion-selective thiophene-based monomers were used to develop ion-selective conductive polymers to detect sodium ion by different methods, involving standard potentiometry and OECT-based approaches. The textile OECTs for uric acid detection performances were optimized by investigating the geometry effect on the instrumental response and the properties of the different textile materials involved in their production, with a special focus on the final application that implies the operativity in flow conditions to simulate the wound environment. The same testing route was followed for the multiparameter sensor and the calcium sensor prototype, with a particular care towards the ion-selective membrane composition and electrode conditioning protocol optimization. The sodium-selective polymer electrosynthesis was optimized in non-aqueous environments and was characterized by means of potentiostatic and potentiodynamic techniques coupled with Quartz Crystal Microbalance and spectrophotometric measurements.

Study of a pulsed LED set-up to characterise the light response of SiPM sensors for the EIC dRICH detector

L’Electron Ion Collider (EIC) è un futuro acceleratore di particelle che ha l’obiettivo di approfondire le nostre conoscenze riguardo l’interazione forte, una delle quattro interazioni fondamentali della natura, attraverso collisioni di elettroni su nuclei e protoni. L’infrastruttura del futuro detector comprende un sistema d’identificazione basato sull’emissione di luce Cherenkov, un fenomeno che permette di risalire alla massa delle particelle. Una delle configurazioni prese in considerazione per questo sistema è il dual-radiator RICH, basato sulla presenza di due radiatori all’esterno dei quali si trovano dei fotorivelatori. Un’opzione per questi sensori sono i fotorivelatori al silicio SiPM, oggetto di questo lavoro di tesi. L’obiettivo dell’attività è lo studio di un set-up per la caratterizzazione della risposta di sensori SiPM a basse temperature, illuminati attraverso un LED. Dopo un’analisi preliminare per determinare le condizioni di lavoro, si è trovato che la misura è stabile entro un errore del 3.5%.

Methodologies for attitude determination from MEMS sensors in vehicles

The focus of the thesis is the application of different attitude’s determination algorithms on data evaluated with MEMS sensor using a board provided by University of Bologna. MEMS sensors are a very cheap options to obtain acceleration, and angular velocity. The use of magnetometers based on Hall effect can provide further data. The disadvantage is that they have a lot of noise and drift which can affects the results. The different algorithms that have been used are: pitch and roll from accelerometer, yaw from magnetometer, attitude from gyroscope, TRIAD, QUEST, Magdwick, Mahony, Extended Kalman filter, Kalman GPS aided INS. In this work the algorithms have been rewritten to fit perfectly with the data provided from the MEMS sensor. The data collected by the board are acceleration on the three axis, angular velocity on the three axis, magnetic fields on the three axis, and latitude, longitude, and altitude from the GPS. Several tests and comparisons have been carried out installing the electric board on different vehicles operating in the air and on ground. The conclusion that can be drawn from this study is that the Magdwich filter is the best trade-off between computational capabilities required and results obtained. If attitude angles are obtained from accelerometers, gyroscopes, and magnetometer, inconsistent data are obtained for cases where high vibrations levels are noticed. On the other hand, Kalman filter based algorithms requires a high computational burden. TRIAD and QUEST algorithms doesn’t perform as well as filters.

RED-Bridge: A Multiprotocol Tool Prototype for IoT Sensors

The IoT is growing more and more each year and is becoming so ubiquitous that it includes heterogeneous devices with different hardware and software constraints leading to an highly fragmented ecosystem. Devices are using different protocols with different paradigms and they are not compatible with each other; some devices use request-response protocols like HTTP or CoAP while others use publish-subscribe protocols like MQTT. Integration in IoT is still an open research topic. When handling and testing IoT sensors there are some common task that people may be interested in: reading and visualizing the current value of the sensor; doing some aggregations on a set of values in order to compute statistical features; saving the history of the data to a time-series database; forecasting the future values to react in advance to a future condition; bridging the protocol of the sensor in order to integrate the device with other tools. In this work we will show the working implementation of a low-code and flow-based tool prototype which supports the common operations mentioned above, based on Node-RED and Python. Since this system is just a prototype, it has some issues and limitations that will be discussed in this work.

Development of wearable electrochemical sensors for the determination of biological analytes

Wearable biosensors are attracting interest due to their potential to provide continuous, real-time physiological information via dynamic, non-invasive measurements of biochemical markers in biofluids, such as interstitial fluid (ISF). One notable example of their applications is for glycemic monitoring in diabetic patients, which is typically carried out either by direct measurement of blood glucose via finger pricking or by wearable sensors that can continuously monitor glucose in ISF by sampling it from below the skin with a microneedle. In this context, the development of a new and minimally invasive multisensing tattoo-based platform for the monitoring of glucose and other analytes in ISF extracted through reverse iontophoresis in proposed by the GLUCOMFORT project. This elaborate describes the in-vitro development of flexible electrochemical sensors based on inkjet-printed PEDOT:PSS and metal inks that are capable of determining glucose and chloride at biologically relevant concentrations, making them good candidates for application in the GLUCOMFORT platform. In order to make PEDOT:PSS sensitive to glucose at micromolar concentrations, a biocompatible functionalization based on immobilized glucose oxidase and electrodeposited platinum was developed. This functionalization was successfully applied to bulk and flexible amperometric devices, the design of which was also optimized. Using the same strategy, flexible organic electrochemical transistors (OECTs) for glucose sensing were also made and successfully tested. For the sensing of chloride ions, an organic charge-modulated field-effect transistor (OCMFET) featuring a silver/silver chloride modified floating gate electrode was developed and tested.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Engineered Nanoparticles And Organic Matter: A Review Of The State-of-the-art.

Growth in the development and production of engineered nanoparticles (ENPs) in recent years has increased the potential for interactions of these nanomaterials with aquatic and terrestrial environments. Carefully designed studies are therefore required in order to understand the fate, transport, stability, and toxicity of nanoparticles. Natural organic matter (NOM), such as the humic substances found in water, sediment, and soil, is one of the substances capable of interacting with ENPs. This review presents the findings of studies of the interaction of ENPs and NOM, and the possible effects on nanoparticle stability and the toxicity of these materials in the environment. In addition, ENPs and NOM are utilized for many different purposes, including the removal of metals and organic compounds from effluents, and the development of new electronic sensors and other devices for the detection of active substances. Discussion is therefore provided of some of the ways in which NOM can be used in the production of nanoparticles. Although there has been an increase in the number of studies in this area, further progress is needed to improve understanding of the dynamic interactions between ENPs and NOM.

Uso de membranas de Nafion para a construção de sensores ópticos para medidas de pH

The behaviour of Nafion® polymeric membranes containing acid-base dyes, bromothymol blue (BB) and methyl violet (MV), were studied aiming at constructing an optical sensor for pH measurement. BB revealed to be inadequate for developing sensing phases due to the electrostatic repulsion between negative groups of their molecules and the negative charge of the sulfonate group of the Nafion®, which causes leaching of the dye from the membrane. On the other hand, MV showed to be suitable due to the presence of positive groups in its structure. The membrane prepared from a methanolic solution whose Nafion®/dye molar ratio was 20 presented the best analytical properties, changing its color from green to violet in the pH range from 0.6 to 3.0. The membrane can be prepared with good reproducibility, presenting durability of ca. 6 months and response time of 22 s, making possible its use for pH determination in flow analysis systems.

Polímeros biomiméticos em química analítica. Parte 1: preparo e aplicações de MIP (Molecularly Imprinted Polymers) em técnicas de extração e separação

MIPs are synthetic polymers that are used as biomimetic materials simulating the mechanism verified in natural entities such as antibodies and enzymes. Although MIPs have been successfully used as an outstanding tool for enhancing the selectivity or different analytical approaches, such as separation science and electrochemical and optical sensors, several parameters must be optimized during their synthesis. Therefore, the state-of-the-art of MIP production as well as the different polymerization methods are discussed. The potential selectivity of MIPs in the extraction and separation techniques focusing mainly on environmental, clinical and pharmaceutical samples as applications for analytical purposes is presented.

Polímeros biomiméticos em química analítica. Parte 2: aplicações de MIP (Molecularly Imprinted Polymers) no desenvolvimento de sensores químicos

The aim of this paper is the description of the strategies and advances in the use of MIP in the development of chemical sensors. MIP has been considered an emerging technology, which allows the synthesis of materials that can mimic some highly specific natural receptors such as antibodies and enzymes. In recent years a great number of publications have demonstrated a growth in their use as sensing phases in the construction of sensors . Thus, the MIP technology became very attractive as a promising analytical tool for the development of sensors.

Sensores ópticos com detecção no infravermelho próximo e médio

Optical chemical sensors with detection in the near and mid infrared region are reviewed. Fundamental concepts of infrared spectroscopy and optical chemical sensors are briefly described, before presenting some aspects on optical chemical sensors, such as synthesis of NIR and IR reagents, preparation of new materials as well as application in determinations of species of biological, industrial and environmental importance.

Construção de um calorímetro isotérmico diferencial de alta sensibilidade e baixo custo

The high cost of sensitivity commercial calorimeters may represent an obstacle for many calorimetric research groups. This work describes the construction and calibration of a batch differential heat conduction calorimeter with sample cells volumes of about 400 μL. The calorimeter was built using two small high sensibility square Peltier thermoelectric sensors and the total cost was estimated to be about US$ 500. The calorimeter was used to study the excess enthalpy of solution of binary mixtures of liquids, as a function of composition, for the following binary systems of solvents: water + 1,4-dioxane or + dimethylsulfoxide at 298,2 ± 0,5 K.

Sistema de sincronismo entre a colhedora de cana-de-açúcar e o veículo de transbordo

One of the problems found in mechanical harvest of sugar cane is the lack of synchronism between the harvest machine and the infield wagon, causing crop losses as well as operational capacity. The objective of the present research was to design a system capable of helping to synchronize the sugar cane harvest machine with the wagon. The communication between tractor and harvest machine is wireless. Two ultrasound sensors coupled to the elevator and a microprocessor manage such information, generating a correct synchronization among the machines. The system was tested in laboratory and on field performing its function adequately, maintaining the two machines in synchronization, indicating and alerting the operators their relative positions. The developed system reduced the sugar cane lost in 60 kg ha-1 comparing to the harvest with the system turned off.

Mapeamento de semeaduras de soja (Glycine max (L.)Merr.) mediante dados MODIS/Terra E TM/Landsat 5: um comparativo

The objective of this work was to compare the soybean crop mapping in the western of Parana State by MODIS/Terra and TM/Landsat 5 images. Firstly, it was generated a soybean crop mask using six TM images covering the crop season, which was used as a reference. The images were submitted to Parallelepiped and Maximum Likelihood digital classification algorithms, followed by visual inspection. Four MODIS images, covering the vegetative peak, were classified using the Parallelepiped method. The quality assessment of MODIS and TM classification was carried out through an Error Matrix, considering 100 sample points between soybean or not soybean, randomly allocated in each of the eight municipalities within the study area. The results showed that both the Overall Classification (OC) and the Kappa Index (KI) have produced values ranging from 0.55 to 0.80, considered good to very good performances, either in TM or MODIS images. When OC and KI, from both sensors were compared, it wasn't found no statistical difference between them. The soybean mapping, using MODIS, has produced 70% of reliance in terms of users. The main conclusion is that the mapping of soybean by MODIS is feasible, with the advantage to have better temporal resolution than Landsat, and to be available on the internet, free of charge.