Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

Application of PZT and FBG impedance sensors for structural health monitoring of reinforced concrete beams strengthened with FRP composite materials

Esta Tesis tiene como objetivo principal el desarrollo de métodos de identificación del daño que sean robustos y fiables, enfocados a sistemas estructurales experimentales, fundamentalmente a las estructuras de hormigón armado reforzadas externamente con bandas fibras de polímeros reforzados (FRP). El modo de fallo de este tipo de sistema estructural es crítico, pues generalmente es debido a un despegue repentino y frágil de la banda del refuerzo FRP originado en grietas intermedias causadas por la flexión. La detección de este despegue en su fase inicial es fundamental para prevenir fallos futuros, que pueden ser catastróficos. Inicialmente, se lleva a cabo una revisión del método de la Impedancia Electro-Mecánica (EMI), de cara a exponer sus capacidades para la detección de daño. Una vez la tecnología apropiada es seleccionada, lo que incluye un analizador de impedancias así como novedosos sensores PZT para monitorización inteligente, se ha diseñado un procedimiento automático basado en los registros de impedancias de distintas estructuras de laboratorio. Basándonos en el hecho de que las mediciones de impedancias son posibles gracias a una colocación adecuada de una red de sensores PZT, la estimación de la presencia de daño se realiza analizando los resultados de distintos indicadores de daño obtenidos de la literatura. Para que este proceso sea automático y que no sean necesarios conocimientos previos sobre el método EMI para realizar un experimento, se ha diseñado e implementado un Interfaz Gráfico de Usuario, transformando la medición de impedancias en un proceso fácil e intuitivo. Se evalúa entonces el daño a través de los correspondientes índices de daño, intentando estimar no sólo su severidad, sino también su localización aproximada. El desarrollo de estos experimentos en cualquier estructura genera grandes cantidades de datos que han de ser procesados, y algunas veces los índices de daño no son suficientes para una evaluación completa de la integridad de una estructura. En la mayoría de los casos se pueden encontrar patrones de daño en los datos, pero no se tiene información a priori del estado de la estructura. En este punto, se ha hecho una importante investigación en técnicas de reconocimiento de patrones particularmente en aprendizaje no supervisado, encontrando aplicaciones interesantes en el campo de la medicina. De ahí surge una idea creativa e innovadora: detectar y seguir la evolución del daño en distintas estructuras como si se tratase de un cáncer propagándose por el cuerpo humano. En ese sentido, las lecturas de impedancias se emplean como información intrínseca de la salud de la propia estructura, de forma que se pueden aplicar las mismas técnicas que las empleadas en la investigación del cáncer. En este caso, se ha aplicado un algoritmo de clasificación jerárquica dado que ilustra además la clasificación de los datos de forma gráfica, incluyendo información cualitativa y cuantitativa sobre el daño. Se ha investigado la efectividad de este procedimiento a través de tres estructuras de laboratorio, como son una viga de aluminio, una unión atornillada de aluminio y un bloque de hormigón reforzado con FRP. La primera ayuda a mostrar la efectividad del método en sencillos escenarios de daño simple y múltiple, de forma que las conclusiones extraídas se aplican sobre los otros dos, diseñados para simular condiciones de despegue en distintas estructuras. Demostrada la efectividad del método de clasificación jerárquica de lecturas de impedancias, se aplica el procedimiento sobre las estructuras de hormigón armado reforzadas con bandas de FRP objeto de esta tesis, detectando y clasificando cada estado de daño. Finalmente, y como alternativa al anterior procedimiento, se propone un método para la monitorización continua de la interfase FRP-Hormigón, a través de una red de sensores FBG permanentemente instalados en dicha interfase. De esta forma, se obtienen medidas de deformación de la interfase en condiciones de carga continua, para ser implementadas en un modelo de optimización multiobjetivo, cuya solución se haya por medio de una expansión multiobjetivo del método Particle Swarm Optimization (PSO). La fiabilidad de este último método de detección se investiga a través de sendos ejemplos tanto numéricos como experimentales. ABSTRACT This thesis aims to develop robust and reliable damage identification methods focused on experimental structural systems, in particular Reinforced Concrete (RC) structures externally strengthened with Fiber Reinforced Polymers (FRP) strips. The failure mode of this type of structural system is critical, since it is usually due to sudden and brittle debonding of the FRP reinforcement originating from intermediate flexural cracks. Detection of the debonding in its initial stage is essential thus to prevent future failure, which might be catastrophic. Initially, a revision of the Electro-Mechanical Impedance (EMI) method is carried out, in order to expose its capabilities for local damage detection. Once the appropriate technology is selected, which includes impedance analyzer as well as novel PZT sensors for smart monitoring, an automated procedure has been design based on the impedance signatures of several lab-scale structures. On the basis that capturing impedance measurements is possible thanks to an adequately deployed PZT sensor network, the estimation of damage presence is done by analyzing the results of different damage indices obtained from the literature. In order to make this process automatic so that it is not necessary a priori knowledge of the EMI method to carry out an experimental test, a Graphical User Interface has been designed, turning the impedance measurements into an easy and intuitive procedure. Damage is then assessed through the analysis of the corresponding damage indices, trying to estimate not only the damage severity, but also its approximate location. The development of these tests on any kind of structure generates large amounts of data to be processed, and sometimes the information provided by damage indices is not enough to achieve a complete analysis of the structural health condition. In most of the cases, some damage patterns can be found in the data, but none a priori knowledge of the health condition is given for any structure. At this point, an important research on pattern recognition techniques has been carried out, particularly on unsupervised learning techniques, finding interesting applications in the medicine field. From this investigation, a creative and innovative idea arose: to detect and track the evolution of damage in different structures, as if it were a cancer propagating through a human body. In that sense, the impedance signatures are used to give intrinsic information of the health condition of the structure, so that the same clustering algorithms applied in the cancer research can be applied to the problem addressed in this dissertation. Hierarchical clustering is then applied since it also provides a graphical display of the clustered data, including quantitative and qualitative information about damage. The performance of this approach is firstly investigated using three lab-scale structures, such as a simple aluminium beam, a bolt-jointed aluminium beam and an FRP-strengthened concrete specimen. The first one shows the performance of the method on simple single and multiple damage scenarios, so that the first conclusions can be extracted and applied to the other two experimental tests, which are designed to simulate a debonding condition on different structures. Once the performance of the impedance-based hierarchical clustering method is proven to be successful, it is then applied to the structural system studied in this dissertation, the RC structures externally strengthened with FRP strips, where the debonding failure in the interface between the FRP and the concrete is successfully detected and classified, proving thus the feasibility of this method. Finally, as an alternative to the previous approach, a continuous monitoring procedure of the FRP-Concrete interface is proposed, based on an FBGsensors Network permanently deployed within that interface. In this way, strain measurements can be obtained under controlled loading conditions, and then they are used in order to implement a multi-objective model updating method solved by a multi-objective expansion of the Particle Swarm Optimization (PSO) method. The feasibility of this last proposal is investigated and successfully proven on both numerical and experimental RC beams strengthened with FRP.

Monitorización de emisiones de CO2 en un análogo natural mediante correlación con Índices de Vegetación

Entre las soluciones más satisfactorias al problema de las emisiones de CO2 está la captura y almacenamiento de este gas de efecto invernadero en reservorios profundos. Esta técnica implica la necesidad de monitorizar grandes extensiones de terreno. Utilizando una zona de vulcanismo residual, en la provincia de Ciudad Real, se han monitorizado las emisiones de CO2 utilizando imágenes de muy alta resolución espacial. Se han generado índices de vegetación, y estos se han correlacionado con medidas de contenido de CO2 del aire en los puntos de emisión. Los resultados han arrojado niveles de correlación significativos (p. ej.: SAVI = -0,93) y han llevado a descubrir un nuevo punto de emisión de CO2. Palabras clave: teledetección, CO2, vegetación, satélite Monitoring CO2 emissions in a natural analogue by correlating with vegetation indices Abstract: Among the most satisfactory solutions for the CO2 emissions problem is the capture and storage of this greenhouse gas in deep reservoirs. This technique involves the need to monitor large areas. Using a volcanic area with residual activity, in the province of Ciudad Real, CO2 emissions were monitored through very high spatial resolution imagery. Vegetation indexes were generated and correlated with measurements of the air?s CO2 content at the emission points. The results yielded significant correlation levels (e.g.: SAVI = -0.93) and led to the discovery of a new CO2 emission point. Keywords: remote sensing, CO2, vegetation, satellite.

Monitorización de emisiones de CO2 en análogos naturales de almacenamientos geológicos a través de la vegetación mediante técnicas de teledetección multiespectral

Uno de los problemas más importantes a los que se enfrenta nuestra sociedad es el de la degradación del medioambiente por la emisión de gases de efecto invernadero. La captura de CO2 en los puntos de emisión y su enterramiento mediante inyección en reservorios geológicos profundos se plantea como una solución hasta que a medio o largo plazo pueda ser mitigada la actual dependencia de la quema de combustibles fósiles. Pero la estabilidad de esos reservorios debe ser monitorizada adecuadamente. En esta tesis se ha estudiado el problema de la detección de fugas de CO2 en un análogo natural de un emplazamiento de almacenamiento profundo a través del análisis de imágenes de satélite multiespectrales. El análogo utilizado ha sido la zona de Campo de Calatrava (Ciudad Real, España), donde, por efecto de la actividad volcánica remanente, aún se pueden encontrar numerosos puntos de emisión de CO2. Se han caracterizado los puntos de emisión de CO2 identificándose dos tipologías con características y manifestaciones claramente diferenciadas: puntos de emisión húmeda o hervideros, y puntos de emisión seca o fumarolas. Para el estudio se han utilizado índices de vegetación y su relación de éstos con los contenidos atmosféricos de CO2. Se han utilizado imágenes multiespectrales de los satélites QuickBird y WorldView‐2. Se ha realizado una preselección de doce índices de vegetación especialmente adecuados para la detección de puntos de emisión de CO2. Mediante análisis y comparación de imágenes de índices de vegetación sobre puntos de emisión conocidos se ha seleccionado los cinco índices con mayor sensibilidad frente al fenómeno. Atendiendo a los principales factores condicionantes de la aparición de nuevos puntos de emisión de CO2 se ha realizado sobre las imágenes de índices de vegetación una predicción de nuevos puntos de emisión. Entre los puntos candidato se han encontrado tres nuevos puntos de emisión de CO2 no descritos previamente en la bibliografía. ABSTRACT One of the most important issues facing our society is the degradation of the environment caused by the emission of greenhouse gases. Capturing CO2 emissions, injection and burial in deep geological reservoirs is presented as a solution until the medium or long term, when the problem of the current dependence on fossil fuels burning can be mitigated. But the stability of these reservoirs should be properly monitored. In this work we study the problem of detecting CO2 leakage in a natural analogue of a deep storage site through analysis of multispectral satellite imagery. The analogue used is in the Campo de Calatrava (Ciudad Real, Spain) where, due to the remaining volcanic activity, it can still be found numerous CO2 emission points. CO2 emission points have been characterized identifying two types having distinct characteristics and effects: wet emission points or hotbeds, and dry emission points or fumaroles. For this study it has been used vegetation indices and its relationship with atmospheric CO2 contents. It has been used multispectral images from QuickBird and WorldView‐2 satellites. It has been done a preselection of twelve vegetation indices especially suitable for the detection of CO2 emission points. Using analysis and comparison of vegetation index images on real emission points it has been selected the five indexes with greater sensitivity to this phenomenon. Based upon the main factors of the emergence of new CO2 emission points it has been made a prediction of new emission points over the vegetation index images. Among the candidate points it has been found three new CO2 emission points not previously described in the literature.

Estrutura da vegetação e sua relação com a diversidade, abundância e similaridade de coleópteros bioindicadores em diferentes sistemas vegetacionais, Piracicaba, SP

A Mata Atlântica é considerada um dos biomas mais importantes do mundo devido à sua alta biodiversidade e funções ecossistêmicas. Entretanto, encontra-se fragmentada em porções de pequenas dimensões esparsas em uma matriz predominantemente agrícola, composta principalmente por extensas pastagens e monoculturas. Desse modo, os sistemas agroflorestais por apresentarem uma estrutura diferenciada dos monocultivos e similar às condições naturais, podem ser utilizados como uma alternativa para o manejo e a conservação da biodiversidade nos remanescentes florestais. A fragmentação provoca modificações no ambiente que irão refletir na perda e no deslocamento da biodiversidade, estando os insetos entre os grupos mais afetados. Uma das formas de se avaliar o estado de conservação dos fragmentos e o impacto antrópico nos sistemas vegetacionais, é estudar a presença e distribuição de organismos bioindicadores. Dentre esses, os insetos ocupam posição de destaque. Os insetos da família Scarabaeidae e da subfamília Scolytinae são bons indicadores de distúrbios, pois são muito sensíveis ás mudanças ambientais. Neste trabalho hipotetisou-se que a presença desses insetos está relacionada com a estrutura da vegetação e as condições de vida proporcionadas pelas diferentes formas de uso-da-terra. O objetivo desta pesquisa foi avaliar a diversidade de espécies, o padrão de abundância e a similaridade entre as populações de coleópteros (Scarabaeidae e Scolytinae) em diferentes sistemas vegetacionais de diferentes estruturas: i) Fragmento de floresta estacional semidecidual dividido em três áreas: beira do rio, centro e borda; ii) Sistema Agroflorestal (SAF) (interface entre o fragmento e o pasto); iii) Pasto composto de Brachiaria decumbens (L.); iv) Monocultivo de café (Coffea arábica L.); v) Monocultivo de seringueira (Hevea brasiliensis Müell. Arg.); vi) SAF de café e seringueira - todos situados numa região de domínio anterior de floresta estacional semidecidual em Piracicaba-SP. Os sistemas foram caracterizados quanto à sua estrutura e condições micrometeorológicas. Os insetos foram coletados mensalmente entre agosto/2013 e julho/2014 utilizando-se dois tipos de armadilhas: Pitfall e etanol modelo ESALQ-84. Foram coletados 1.047 espécimes distribuídos em 21 espécies da família Scarabaeidae e 1.833 indivíduos de 38 espécies da subfamília Scolytinae. A maior quantidade de espécies de Scarabaeidae foi encontrada na borda do fragmento florestal, enquanto que a maior abundância ocorreu no fragmento florestal perto do rio. A subfamília Scolytinae apresentou a maior riqueza de espécies no sistema agroflorestal misto (borda) e a maior abundância no sistema agroflorestal café-seringueira. A abundância e riqueza de espécies da família Scarabaeidae foram correlacionadas positivamente com a temperatura do ar, temperatura e umidade do solo e a precipitação. Por outro lado, a abundância e a riqueza de espécies da subfamília Scolytinae apresentaram correlação negativa com a temperatura do ar e a temperatura e umidade do solo. Ambos os grupos de insetos apresentaram a maior abundância e riqueza de espécies nas áreas com estrutura vegetacional mais complexa, sendo influenciadas pelas condições microclimáticas dentro de cada local.

Detection and mapping of burnt areas from time series of MODIS-derived NDVI data in a Mediterranean region

Moderate resolution remote sensing data, as provided by MODIS, can be used to detect and map active or past wildfires from daily records of suitable combinations of reflectance bands. The objective of the present work was to develop and test simple algorithms and variations for automatic or semiautomatic detection of burnt areas from time series data of MODIS biweekly vegetation indices for a Mediterranean region. MODIS-derived NDVI 250m time series data for the Valencia region, East Spain, were subjected to a two-step process for the detection of candidate burnt areas, and the results compared with available fire event records from the Valencia Regional Government. For each pixel and date in the data series, a model was fitted to both the previous and posterior time series data. Combining drops between two consecutive points and 1-year average drops, we used discrepancies or jumps between the pre and post models to identify seed pixels, and then delimitated fire scars for each potential wildfire using an extension algorithm from the seed pixels. The resulting maps of the detected burnt areas showed a very good agreement with the perimeters registered in the database of fire records used as reference. Overall accuracies and indices of agreement were very high, and omission and commission errors were similar or lower than in previous studies that used automatic or semiautomatic fire scar detection based on remote sensing. This supports the effectiveness of the method for detecting and mapping burnt areas in the Mediterranean region.

Effects of plant functional traits on soil stability: intraspecific variability matters

This data set describes different vegetation, soil and plant functional traits (PFTs) of 15 plant species in 30 sampling plots of an agricultural landscape in the Haean-myun catchment in South Korea. We divided the data set into two main tables, the first one includes the PFTs data of the 15 studied plant species, and the second one includes the soil and vegetation characteristics of the 30 sampling plots. For a total of 150 individuals, we measures the maximum plant height (cm) and leaf size (cm**2), which means the leaf surface area for the aboveground compartment of each individual. For the belowground compartment, we measured root horizontal width, which is the maximum horizontal spread of the root, rooting length, which is the maximum rooting depth, root diameter, which is the average root diameter of a the whole root, specific root length (SRL), which is the root length divided by the root dry mass, and root/shoot ratio, which is the root dry mass divided by the shoot dry mass. At each of the 30 studied plots, we estimated three different variables describing the vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and root density (estimated using a 30 cm x 30 cm metallic frame divided into nine 10 cm x 10 cm grids placed on the soil profile), as we calculated the total number of roots that appear in each of the nine grids and then we converted it into percentage based on the root count, following. Moreover, in each plot we estimated six different soil variables: Bulk density (g/cm**3), clay % (i.e. percentage of clay), silt % (i.e. percentage of silt), soil aggregate stability, using mean weight diameter (MWD), penetration resistance (kg/cm**2), using pocket penetrometer and soil shear vane strength (kPa).

Drivers of multi-scale plant community structure in agricultural field margins of South Korea

This data set describes the distribution of a total of 90 plant species growing on field margins of an agricultural landscape in the Haean-myun catchment in South Korea. We conducted our survey between July and August 2011 in 100 sampling plots, covering the whole catchment. In each plot we measured three environmental variables: slope, width of the field margin, and management type (i.e. "managed" for field margins that had signs of management activities from the ongoing season such as cutting or spraying herbicides and "unmanaged" for field margins that had been left untouched in the season). For the botanical survey each plot was sampled using three subplots of one square meter per subplot; subplots were 4 m apart from each other. In each subplot, we estimated three different vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and species abundance (i.e. the number of observed individuals / species). We calculated the percentage of the non-farmed habitats by creating buffer zones of 100, 200, 300, 400 and 500 m radii around each plot using data provided by (Seo et al. 2014). Non-farmed habitats included field margins, fallows, forest, riparian areas, pasture and grassland.

Low-density koala (Phascolarctos cinereus) populations in the mulgalands of south-west Queensland. IV. Abundance and conservation status

Urban encroachment on dense, coastal koala populations has ensured that their management has received increasing government and public attention. The recently developed National Koala Conservation Strategy calls for maintenance of viable populations in the wild. Yet the success of this, and other, conservation initiatives is hampered by lack of reliable and generally accepted national and regional population estimates. In this paper we address this problem in a potentially large, but poorly studied, regional population in the State that is likely to have the largest wild populations. We draw on findings from previous reports in this series and apply the faecal standing-crop method (FSCM) to derive a regional estimate of more than 59 000 individuals. Validation trials in riverine communities showed that estimates of animal density obtained from the FSCM and direct observation were in close agreement. Bootstrapping and Monte Carlo simulations were used to obtain variance estimates for our population estimates in different vegetation associations across the region. The most favoured habitat was riverine vegetation, which covered only 0.9% of the region but supported 45% of the koalas. We also estimated that between 1969 and 1995 similar to 30% of the native vegetation associations that are considered as potential koala habitat were cleared, leading to a decline of perhaps 10% in koala numbers. Management of this large regional population has significant implications for the national conservation of the species: the continued viability of this population is critically dependent on the retention and management of riverine and residual vegetation communities, and future vegetation-management guidelines should be cognisant of the potential impacts of clearing even small areas of critical habitat. We also highlight eight management implications.

Evaluation of the indirect measures of rock brittleness and fracture toughness in rock cutting

Performance prediction models for partial face mechanical excavators, when developed in laboratory conditions, depend on relating the results of a set of rock property tests and indices to specific cutting energy (SE) for various rock types. There exist some studies in the literature aiming to correlate the geotechnical properties of intact rocks with the SE, especially for massive and widely jointed rock environments. However, those including direct and/or indirect measures of rock fracture parameters such as rock brittleness and fracture toughness, along with the other rock parameters expressing different aspects of rock behavior under drag tools (picks), are rather limited. With this study, it was aimed to investigate the relationships between the indirect measures of rock brittleness and fracture toughness and the SE depending on the results of a new and two previous linear rock cutting programmes. Relationships between the SE, rock strength parameters, and the rock index tests have also been investigated in this study. Sandstone samples taken from the different fields around Ankara, Turkey were used in the new testing programme. Detailed mineralogical analyses, petrographic studies, and rock mechanics and rock cutting tests were performed on these selected sandstone specimens. The assessment of rock cuttability was based on the SE. Three different brittleness indices (B1, B2, and B4) were calculated for sandstones samples, whereas a toughness index (T-i), being developed by Atkinson et al.(1), was employed to represent the indirect rock fracture toughness. The relationships between the SE and the large amounts of new data obtained from the mineralogical analyses, petrographic studies, rock mechanics, and linear rock cutting tests were evaluated by using bivariate correlation and curve fitting techniques, variance analysis, and Student's t-test. Rock cutting and rock property testing data that came from well-known studies of McFeat-Smith and Fowell(2) and Roxborough and Philips(3) have also been employed in statistical analyses together with the new data. Laboratory tests and subsequent analyses revealed that there were close correlations between the SE and B4 whereas no statistically significant correlation has been found between the SE and T-i. Uniaxial compressive and Brazilian tensile strengths and Shore scleroscope hardness of sandstones also exhibited strong relationships with the SE. NCB cone indenter test had the greatest influence on the SE among the other engineering properties of rocks, confirming the previous studies in rock cutting and mechanical excavation. Therefore, it was recommended to employ easy-to-use index tests of NCB cone indenter and Shore scleroscope in the estimation of laboratory SE of sandstones ranging from very low to high strengths in the absence of a rock cutting rig to measure it until the easy-to-use universal measures of the rock brittleness and especially the rock fracture toughness, being an intrinsic rock property, are developed.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

Local biomass control on the composition and reactivity of particulate organic matter in aquatic environments

Freshwater ecosystems have been recognized as important components of the global carbon cycle, and the flux of organic matter (OM) from freshwater to marine environments can significantly affect estuarine and coastal productivity. The focus of this study was the assessment of carbon dynamics in two aquatic environments, namely the Florida Everglades and small prairie streams in Kansas, with the aim of characterizing the biogeochemistry of OM. In the Everglades, particulate OM (POM) is mostly found as a layer of flocculent material (floc). While floc is believed to be the main energy source driving trophic dynamics in this oligotrophic wetland, not much is known about its biogeochemistry. The objective of this study was to determine the origin/sources of OM in floc using biomarkers and pigment-based chemotaxonomy to assess specific biomass contributions to this material, on a spatial (freshwater marshes vs. mangrove fringe) and seasonal (wet vs. dry) scales. It was found that floc OM is derived from the local vegetation (mainly algal components and macrophyte litter) and its composition is controlled by seasonal drivers of hydrology and local biomass productivity. Photo-reactivity experiments showed that light exposure on floc resulted in photo-dissolution of POC with the generation of significant amounts of both dissolved OM (DOM) and nutrients (N & P), potentially influencing nutrient dynamics in this ecosystem. The bio-reactivity experiments determined as the amount and rate of CO2 evolution during incubation were found to vary on seasonal and spatial scales and were highly influenced by phosphorus limitation. Not much is known on OM dynamics in small headwater streams. The objective of this study was to determine carbon dynamics in sediments from intermittent prairie streams, characterized by different vegetation cover for their watershed (C4 grasses) vs. riparian zone (C3 plants). In this study sedimentary OM was characterized using a biomarker and compound specific carbon stable isotope approach. It was found that the biomarker composition of these sediments is dominated by higher plant inputs from the riparian zone, although inputs from adjacent prairie grasses were also apparent. Conflicting to some extent with the River Continuum Concept, sediments of the upper reaches contained more degraded OM, while the lower reaches were enriched in fresh material deriving from higher plants and plankton sources as a result of hydrological regimes and particle sorting.

Não-extensividade no contexto da atividade magnética solar: o problema da assimetria hemisférica

Solar activity indicators, each as sunspot numbers, sunspot area and flares, over the Sun’s photosphere are not considered to be symmetric between the northern and southern hemispheres of the Sun. This behavior is also known as the North-South Asymmetry of the different solar indices. Among the different conclusions obtained by several authors, we can point that the N-S asymmetry is a real and systematic phenomenon and is not due to random variability. In the present work, the probability distributions from the Marshall Space Flight Centre (MSFC) database are investigated using a statistical tool arises from well-known Non-Extensive Statistical Mechanics proposed by C. Tsallis in 1988. We present our results and discuss their physical implications with the help of theoretical model and observations. We obtained that there is a strong dependence between the nonextensive entropic parameter q and long-term solar variability presents in the sunspot area data. Among the most important results, we highlight that the asymmetry index q reveals the dominance of the North against the South. This behavior has been discussed and confirmed by several authors, but in no time they have given such behavior to a statistical model property. Thus, we conclude that this parameter can be considered as an effective measure for diagnosing long-term variations of solar dynamo. Finally, our dissertation opens a new approach for investigating time series in astrophysics from the perspective of non-extensivity.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

A Motivação do Envolvimento dos Bombeiros em Atividades de Voluntariado: um estudo de caso.

Este estudo teve como principal objetivo a análise dos fatores determinantes que levaram os bombeiros voluntários de uma corporação para a prática de voluntariado. Nesta investigação, começamos por fazer um enquadramento teórico sobre as perspetivas e tipos de motivação do voluntariado, focando-nos depois em alguns aspetos da sua prática em Portugal. A componente empírica deste estudo apoiou-se numa análise quantitativa a 92 questionários realizados a bombeiros voluntários, adaptados de um estudo realizado por Ward e Mckillop (2011) com uma escala do tipo Likert de 1 a 7 pontos. A análise da distribuição por sexo apontou uma proporção de homens superior à das mulheres (63 = 68,5% vs. 29 = 31,5%), com idades compreendidas entre os 17 e os 71 anos, sendo a média das mesmas de 37,77 anos (dp = ± 12,1). No que concerne ao estado civil, dos inquiridos (35 = 38%) são casados. Quanto à escolaridade, a moda estatística situou-se no secundário (52 = 56,5%). Os itens que compuseram a escala de motivação para o voluntariado apresentaram pontuações superiores a 4 pontos numa escala do tipo Likert de 7 pontos. A escala constituída por 17 itens relaciona os diferentes tipos de motivação, designadamente, social, interesse, prazer, material-egoísta, egoísta, altruísta, necessidade e dever moral. Estes itens foram avaliados nas seguintes variáveis: sexo, classe etária, escolaridade e antiguidade. As conclusões retiradas deste estudo revelaram, dominantemente, motivações do tipo altruísta e social, para a prática do voluntariado. Estes resultados basearam-se nos valores das significâncias estatísticas (p). Quanto à motivação dos elementos do sexo masculino e do sexo feminino, verificaram-se em ambas maiores percentagens no tipo de motivação altruísta. Na análise realizada consoante a classe etária, as respostas que obtiveram maior percentagem foram relativamente ao item altruísta. No que concerne à escolaridade, os inquiridos com ensino básico e secundário apresentaram um maior número de respostas nos itens altruísta e social. Nos licenciados o item com maior percentagem foi o dever moral. Na análise feita relativamente à interseção entre a motivação e os anos de voluntariado, obtiveram-se índices de motivação muito diferenciados, entre os quais interesse, prazer, social, egoísta, material-egoísta e necessidade. / This study aimed to the analysis of the determining factors that led the volunteer firefighters of a corporation to practice voluntary. In this investigation, we begin by making a theoretical framework on the perspectives and types of volunteer motivation, focusing us then in some aspects of their practice in Portugal. The empirical component of the study was supported on a quantitative analysis of 92 questionnaires by volunteer firefighters, adapted from a study by Ward & McKillop (2011) with a Likert scale from 1 to 7 points. The gender distribution, of the analysis indicated a ratio of greater than men to women (63 = 68.5% vs. 29 = 31.5%), aged between 17 and 71 years, and the average of 37 to 77 years (SD = ± 12.1). With regard to marital status (35 = 38%) are married. As for education, the statistical mode stood in the secondary on (52 = 56.5%). The items comprising the motivation scale for volunteering had scores greater than 4 points on a Likert scale of 7 points. The scale consists of 17 items lists the different types of motivation, namely social, interest, pleasure, material-selfish, selfish, selfless, necessity and moral duty. These items were evaluated in the following variables: gender, age group, education level and years of service. Conclusions from this study revealed mainly motivations of altruistic and social type for volunteering. These results were based on the values of statistical significance (p). Both male and female elements replied with the highest percentage for the type of altruistic motivation. In the analysis carried out according to age group, the answers with the greatest percentage were relative to the altruistic item. With regard to education respondents with elementary and high school education had a higher number of responses in altruistic and social items. At University graduate level the item with the highest percentage was the moral duty. In the analysis regarding the intersection between motivation and years of volunteering very different motivation indices were obtained including interest, pleasure, social, selfish, material-selfish and need.