Using thermal infrared (TIR) data to characterize dust storms and their sources in the Middle East

Mineral dust and aerosols can directly and indirectly influence shortwave and longwave radiative forcing. In addition, it can cause health hazards, loss of agricultural soil, and safety hazards to aviation and motorists due to reduced visibility. Previous work utilized satellite and ground-based Thermal Infrared (TIR) data to measure aerosol content in the atmosphere. This research used TIR techniques, by creating a fine-grained (2.7-45 μm) mineral spectral library, direct laboratory emission spectroscopic analysis, and spectral and image deconvolution models, to characterize both the mineral content and particle size of dust storms affecting Kuwait. These results were validated using a combination of X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) analyses that were performed on dust samples for three dust storms (May, July 2010, March 2011) from Kuwait. A combination of forward and backward Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) models were used to track air parcels arriving in Kuwait at the time of dust storm sample collection, thus testing the link to dust emitting areas or hotspots in eastern Syria and western Iraq. World soil maps and TIR analysis of surface deposits of these potential hotspots support this interpretation, and identified areas of high calcite concentration. This interpretation was in agreement with prior studies identifying calcite as the major mineral in dust storms affecting Kuwait. Spectral and image deconvolution models provided good tools in estimating mineral end members present in both dust samples and satellite plumes, but failed to identify the accurate particle size fractions present

Proceedings of the 6th International Workshop of the EARSeL Special Interest Group on Forest Fires Advances in Remote Sensing and GIS Applications in Forest Fire Management Towards an Operational Use of Remote Sensing in Forest Fire Management

During the last two decades, interest in forest fire research has grown steadily, as more and more local and global impacts of burning are being identified. The definition of fire regimes as well as the identification of factors explaining spatial and temporal variations in these fire characteristics are recently hot fields of research. Changes in these fire regimes have important social and ecological implications. Whether these changes are mainly caused by land use or climate warming, greater efforts are demanded to manage forest fires at different temporal and spatial scales. The European Association of Remote Sensing Laboratories (EARSeL)’s Special Interest Group (SIG) on Forest Fires was created in 1995, following the initiative of several researchers studying Mediterranean fires in Europe. It has promoted five technical meetings and several specialised publications since then, and represents one of the most active groups within the EARSeL. The SIG has tried to foster interaction among scientists and managers who are interested in using remote sensing data and techniques to improve the traditional methods of fire risk estimation and the assessment of fire effect. The aim of the 6th international workshop is to analyze the operational use of remote sensing in forest fire management, bringing together scientists and fire managers to promote the development of methods that may better serve the operational community. This idea clearly links with international programmes of a similar scope, such as the Global Monitoring for Environment and Security (GMES) and the Global Observation of Forest Cover/Land Dynamics (GOFC-GOLD) who, together with the Joint Research Center of the European Union sponsor this event. Finally, I would like to thank the local organisers for the considerable lengths they have gone to in order to put this material together, and take care of all the details that the organization of this event requires.JRC.H.3-Global environement monitorin

Climate Change and Environmental Sustainability- Volume 5

This volume of Climate Change and Environmental Sustainability covers topics on greenhouse gas emissions, climatic impacts, climate models and prediction, and analytical methods. Issues related to two major greenhouse gas emissions, namely of carbon dioxide and methane, particularly in wetlands and agriculture sector, and radiative energy flux variations along with cloudiness are explored in this volume. Further, climate change impacts such as rainfall, heavy lake-effect snowfall, extreme temperature, impacts on grassland phenology, impacts on wind and wave energy, and heat island effects are explored. A major focus of this volume is on climate models that are of significance to projection and to visualise future climate pathways and possible impacts and vulnerabilities. Such models are widely used by scientists and for the generation of mitigation and adaptation scenarios. However, dealing with uncertainties has always been a critical issue in climate modelling. Therefore, methods are explored for improving climate projection accuracy through addressing the stochastic properties of the distributions of climate variables, addressing variational problems with unknown weights, and improving grid resolution in climatic models. Results reported in this book are conducive to a better understanding of global warming mechanisms, climate-induced impacts, and forecasting models. We expect the book to benefit decision makers, practitioners, and researchers in different fields and contribute to climate change adaptation and mitigation

The effect of ecosystem change, restoration, and plant diversity on thermally imaged surface temperature

The objective of this dissertation was to test and quantify the hypothesis from ecosystem thermodynamics: that the surface temperature of a terrestrial ecosystem changes with the state of the ecosystem in general, and with plant species diversity in particular. Daytime surface temperature of vegetated terrestrial ecosystems has been hypothesized to decrease with increased biomass and diversity as they in turn increase transpiration, respiration, physical thermal inertia, and productivity, thereby reducing the portion of energy re-emitted as thermal radiation. The hypothesis is tested, and the results and applications are discussed, within the context of ecosystem restoration. I investigated the relationship between ecosystem surface temperature and time since restoration, type of restoration methods, and changes in ecological attributes, including plant species diversity, in two projects restoring temperate wooded ecosystems. The first restoration studied, described in Chapter 2, was a 500+ ha project restoring farmland to oak woodland, spread over 31 fields. Thermal images from 4 space-based instruments along with 12 years of in-situ sampled ecological data of the project were analyzed and compared. Significant decreases in daytime summer surface temperature (4.5 °C in 12 years), and summer diurnal temperature variation (5 °C in 8 years) over time since restorations were found. The study also found a significant relationship between increased plant species diversity and decreased surface temperature when controlling for plant cover and other vegetation attributes. Native plant species had a more pronounced relationship with surface temperature than exotic ones. The results from this study supported the hypothesis, quantified its effect, and showed how thermal imaging from space-based instruments may be used to assess the progress of restoration and the increase in species diversity. The second project studied, in Chapters 3 and 4, was of application of multiple overlapping restoration treatments to experimental plots at two former farmland sites already planted with trees, and one abandoned gravel pit. The main experimental restoration treatment was the transfer of topsoil from a donor forest. On top of the topsoil, further additions were made of woody debris, shrub plantings, and shade shelters. In-situ sampled ecological differences between experimental restoration treatments and controls were assessed in Chapter 3 and thermal differences in Chapter 4. Results from Chapter 3 indicated that most native forest plant species survived within the topsoil as it was transferred from the forest, and re-sprouted in the experimental plots on the second season after the transfer. The plant species community of topsoil recipient plots was significantly different from both recipient and donor site control plots as it contained both the transferred plant species and the species already present at the recipient sites. There was no significant effect on the plant community found from the woody debris, shrub plantings, or shade shelter treatments. Since significant ecological differences were found in Chapter 3, it would be possible to find thermal differences in the same plots in Chapter 4 if the hypothesized relationship was true. To overcome the spatial and temporal resolution limitations of space-based instruments, an Unmanned Aerial Vehicle (UAV)-borne thermal camera was utilized to image the sites four times per day over 9 days. It was found that topsoil recipient plots in the gravel pit site, as well as the smaller and flatter of the two reforestation sites, had significantly lower temperatures than controls (7.0 °C and 2.0 °C respectively) and that the difference in temperature peaked at 2 pm. In the larger and more heterogeneous reforestation site, the normalized surface temperature was only significantly lower than controls (0.7 °C) at 8 pm. There was a significant negative correlation between native forest plant species and surface temperature at all three sites. The combined evidence from the two projects studied was that temperate wooded ecosystems undergoing restoration decreased in their daytime surface temperature and diurnal temperature variation over time, and compared to controls. This decrease is partly due to increasing species diversity. These results support the existence and the direction of the hypothesized, and before this mostly untested, relationship between ecosystem change (including species diversity) and temperature. It also provides examples of the relative significance and quantity of the same relationship using more ecological, and thermal imaging, data over a longer time-span than in previous studies. Both Chapters 2 and 4 found evidence for native and later succession forest plant species having a stronger effect on surface temperature than non-native and ruderal plant species. The dissertation makes a case for thermal imaging to be used both to evaluate and monitor the progress of restoration, and to quantify the ecosystem service of thermal buffering provided by restoration. It also demonstrates the relative strengths and limitations of space-based and UAV-borne thermal imaging instruments

Atmospheric Research 2018 Technical Highlights

Atmospheric research in the Earth Sciences Division (610) consists of research and technology development programs dedicated to advancing knowledge and understanding of the atmosphere and its interaction with the climate of Earth. The Divisions goals are to improve understanding of the dynamics and physical properties of precipitation, clouds, and aerosols; atmospheric chemistry, including the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and radiative properties of Earths atmosphere and the influence of solar variability on the Earths climate. Major research activities are carried out in the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office. The overall scope of the research covers an end-to-end process, starting with the identification of scientific problems, leading to observation requirements for remote sensing platforms, technology and retrieval algorithm development; followed by flight projects and satellite missions; and eventually, resulting in data processing, analyses of measurements, and dissemination from flight projects and missions

Characterising Asteroid Spin and Surface Properties using Small-Aperture Telescopes

In this thesis, the scientific potential of small-aperture telescopes within the field of asteroid science is explored. To achieve this, the PIRATE facility (an autonomous small-aperture telescope) was used to observe a sample of near-Earth asteroids over a two-year observing campaign. Targets were selected that would allow a wide range of phase angles to be covered in order to enable characterisation of their phase curves. A range of technical optimisations are outlined, enabling routine collection of high quality data while minimising time lost due to unsuitable conditions or technical faults. An investigation into the calibration frames taken by PIRATE allowed for data reduction processes to be improved to minimise sources of noise that may impact the photometric data. Data collection processes were implemented that allow for efficient scheduling of asteroid observations, avoiding the common pitfalls when observing moving targets. A new photometric pipeline was written for observations of asteroids taken with PIRATE, along with a set of data analysis processes designed to enable spin-state modelling and phase curve extraction. The phase curves and supporting photometric data are used to provide new constraints on physical properties of the observed targets where possible. A study into biases present in asteroid phase curves due to changing viewing aspect is presented. This study shows that phase curve models fit to the data may not be single-valued when observing non-spherical asteroids over complicated viewing geometries or over multiple apparitions. The potential impacts that this may have on the interpretability of phase curve data are discussed, including the potential impact on the data presented in this thesis. Small-aperture telescopes are shown to be highly capable in enabling the collection and characterisation of asteroid light curves and phase curves. PIRATE is demonstrated to produce good quality data which is consistent with data produced independently from larger telescopes

An investigation in the use of advanced remote sensing and geographic information system techniques for post-fire impact assessment on vegetation.

2006/2007Gli incendi boschivi rappresentano uno dei maggiori problemi ambientali nella regione Mediterranea con vaste superfici colpite ogni estate. Una stima dell’impatto ambientale degli incendi (a breve e a lungo termine) richiede la raccolta di informazioni accurate post-incendio relative al tipo di incendio, all’intensità, alla rigenerazione forestale ed al ripristino della vegetazione. L’utilizzo di tecniche avanzate di telerilevamento può fornire un valido strumento per lo studio di questi fenomeni. L’importanza di queste ricerche è stata più volte sottolineata dalla Commissione Europea che si è concentrata sullo studio degli incendi boschivi ed il loro effetto sulla vegetazione attraverso lo sviluppo di adeguati metodi di stima dell’impatto e di mitigazione. Scopo di questo lavoro è la stima dell’impatto post-incendio sulla vegetazione in ambiente Mediterraneo per mezzo di immagini satellitari ad alta risoluzione, di rilievi a terra e mediante tecniche avanzate di analisi dei dati. Il lavoro ha riguardato lo sviluppo di un sistema per l’integrazione di dati telerilevati ad altissima risoluzione spaziale e spettrale. Per la stima dell’impatto a breve termine, un modello di classificazione ad oggetti è stato sviluppato utilizzando immagini Ikonos ad altissima risoluzione spaziale per cartografare il tipo di incendio, differenziando l’incendio radente dall’incendio di chioma. I risultati mostrano che la classificazione ad oggetti potrebbe essere utilizzata per distinguere con elevata accuratezza (87% di accuratezza complessiva) le due tipologie di incendio, in particolare nei boschi Mediterranei aperti. È stata inoltre valutata la capacità della classificazione ad oggetti di distinguere e cartografare tre livelli di intensità del fuoco utilizzando le immagini Ikonos e l’accuratezza del risultato è stimata all’ 83%. Per la stima dell’impatto a lungo termine, la mappatura della rigenerazione post-incendio (pino) e la ripresa della vegetazione arbustiva sono state valutate mediante tre approcci: 1) la classificazione ad oggetti di immagini ad altissima risoluzione QuickBird che ha permesso di mappare la ripresa della vegetazione e l’impatto sulla copertura a seguito dell’incendio distinguendo due livelli di intensità dell’incendio (accuratezza della classificazione 86%). 2) l’analisi statistica di dati iperspettrali rilevati in campo che ha permesso una riduzione del 97% del volume di dati e la selezione delle migliori 14 bande per discriminare l’età e le specie di pino e le 18 migliori bande per la caratterizzazione delle specie arbustive. Successivamente, i dati iperspettrali Hyperion sono stati utlizzati per mappare la rigenerazione forestale e la ripresa della vegetazione. L’accuratezza complessiva della classificazione è stata del 75.1% considerando due diverse specie di pino ed altre specie vegetali. 3) una classificazione ad oggetti che ha combinato l’analisi dei dati QuickBird ed Hyperion. Si è registrato un aumento dell’accuratezza della classificazione pari all’8.06% rispetto all’utilizzo dei soli dati Hyperion. Complessivamente, si osserva che strumenti avanzati di telerilevamento consentono di raccogliere le informazioni relative alle aree incendiate, la rigenerazione forestale e la ripresa della vegetazione in modo accurato e vantaggioso in termini di costi e tempi.Forest fires are a major environmental problem in the Mediterranean region, where large areas are affected each summer. An assessment of the environmental impact of forest fires (in the short-term and in the long-term) requires the collection of accurate and detailed post-fire information related to fire type, fire severity, forest regeneration and vegetation recovery. Advanced tools in remote sensing provide a powerful tool for the study of this phenomenon. The importance of this work was often emphasized by the European Commission, which focused on the studying of forest fires and their effect on vegetation through the development of appropriate impact assessment and mitigation methods. The aim of this study was to assess the post-fire impact on vegetation in a Mediterranean environment by employing high quality satellite and field data and by using advanced data processing techniques. The work entailed the development of a whole system integrating very high spatial and spectral resolution remotely sensed data. For short-term impact assessment, an object-oriented model was developed using very high spatial resolution Ikonos imagery to map the type of fire, namely, canopy fire and surface fire. The results showed that object-oriented classification could be used to accurately distinguish and map areas of surface and crown fire spread (overall accuracy of 87%), especially that occurring in open Mediterranean forests. Also, the performance of object-based classification in mapping three levels of fire severity by employing high spatial resolution Ikonos imagery was evaluated, and accuracy of the obtained results was estimated to be 83%. As for long-term impact assessment, the mapping of post-fire forest regeneration (pine) and vegetation recovery (shrub) was performed by following three different approaches. First, the developed object-based classification of QuickBird (very high spatial resolution) allowed post-fire vegetation recovery and survival mapping of canopy within two different fire severity levels (86% of classification accuracy). The main effect of fire has been to create a more homogeneous landscape. Second, statistical analysis of field hyperspectral data allowed a 97% reduction in data volume and recommended 14 best narrowbands to discriminate among pine trees (age and species) and 18 bands that best characterize the different shrub species. Then, hyperspectral Hyperion was employed for mapping post-fire forest regeneration and vegetation recovery. The overall classification accuracy was found to be 75.81% when mapping two different regenerated pine species and other species of vegetation recovery. Third, an object-oriented combined analysis of QuickBird and Hyperion was investigated for the same objective. An improvement in classification accuracy of 8.06% was recorded when combining both Hyperion and QuickBird imageries than by using only the Hyperion image. Overall, it was observed that advanced tools in remote sensing provided the necessary means for gathering information about the burned areas, the regenerated forests and the recovered vegetations in a successful and a timely/cost effective manner.XX Ciclo197