Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Utilizing Remote Sensing Imagery to Monitor Vegetation Change within World Heritage Sites

ABSTRACT World Heritage sites provide a glimpse into the stories and civilizations of the past. There are currently 1007 unique World Heritage properties with 779 being classified as cultural sites, 197 as natural sites, and 31 falling into the categories of both cultural and natural sites (UNESCO & World Heritage Centre, 1992-2015). However, of these 1007 World Heritage sites, at least 46 are categorized as in danger and this number continues to grow. These unique and irreplaceable sites are exceptional because of their universality. Consequently, since World Heritage sites belong to all the people of the world and provide inspiration and admiration to all who visit them, it is our responsibility to help preserve these sites. The key form of preservation involves the individual monitoring of each site over time. While traditional methods are still extremely valuable, more recent advances in the field of geographic and spatial technologies including geographic information systems (GIS), laser scanning, and remote sensing, are becoming more beneficial for the monitoring and overall safeguarding of World Heritage sites. Through the employment and analysis of more accurately detailed spatial data, World Heritage sites can be better managed. There is a strong urgency to protect these sites. The purpose of this thesis is to describe the importance of taking care of World Heritage sites and to depict a way in which spatial technologies can be used to monitor and in effect preserve World Heritage sites through the utilization of remote sensing imagery. The research conducted in this thesis centers on the Everglades National Park, a World Heritage site that is continually affected by changes in vegetation. Data used include Landsat satellite imagery that dates from 2001-2003, the Everglades' boundaries shapefile, and Google Earth imagery. In order to conduct the in-depth analysis of vegetation change within the selected World Heritage site, three main techniques were performed to study changes found within the imagery. These techniques consist of conducting supervised classification for each image, incorporating a vegetation index known as Normalized Vegetation Index (NDVI), and utilizing the change detection tool available in the Environment for Visualizing Images (ENVI) software. With the research and analysis conducted throughout this thesis, it has been shown that within the three year time span (2001-2003), there has been an overall increase in both areas of barren soil (5.760%) and areas of vegetation (1.263%) with a decrease in the percentage of areas classified as sparsely vegetated (-6.987%). These results were gathered through the use of the maximum likelihood classification process available in the ENVI software. The results produced by the change detection tool which further analyzed vegetation change correlate with the results produced by the classification method. As well, by utilizing the NDVI method, one is able to locate changes by selecting a specific area and comparing the vegetation index generated for each date. It has been found that through the utilization of remote sensing technology, it is possible to monitor and observe changes featured within a World Heritage site. Remote sensing is an extraordinary tool that can and should be used by all site managers and organizations whose goal it is to preserve and protect World Heritage sites. Remote sensing can be used to not only observe changes over time, but it can also be used to pinpoint threats within a World Heritage site. World Heritage sites are irreplaceable sources of beauty, culture, and inspiration. It is our responsibility, as citizens of this world, to guard these treasures.

Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

In situ and remote sensing signature of meddies east of the mid-Atlantic ridge

[EN] Mediterranean Water eddies (meddies) are thought to play an important climatic role. Nevertheless, their dynamics are not sufficiently known because of difficulties encountered in their observation. Though propagating below the main thermocline, a number of pieces of evidence of sea surface manifestation of meddies are collected. The present work is based on joint in situ and altimetry data analyses to prove that the meddies can be followed with remote sensing data for long periods of time. The in situ observations are based on data from an oceanographic cruise, which crossed three meddies, and reanalysis of historical data sets, including RAFOS floats paths. Suggested methodology permitted us to obtain uninterrupted tracks for several meddies for a period from several months to more than 2 years. It was found that the dynamically calm region to the north of the Azores current presents favorable conditions for meddy tracking. The meddy surface signal may become shattered and difficult to follow during interaction with a strong dynamic structures (the Azores current/surface vortexes) or peaking topography. Theoretical considerations support the observations and lead to the conclusion that the dynamic signature of meddies at the sea surface is an intrinsic property of meddy dynamics

The impact of ice crystals on radiative forcing and remote sensing of arctic boundary-layer mixed-phase clouds

This PhD thesis is embedded into the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) and investigates the radiative transfer through Arctic boundary-layer mixed-phase (ABM) clouds. For this purpose airborne spectral solar radiation measurements and simulations of the solar and thermal infrared radiative transfer have been performed. This work reports on measurements with the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer) conducted in the framework of ASTAR in April 2007 close to Svalbard. For ASTAR the SMART-Albedometer was extended to measure spectral radiance. The development and calibration of the radiance measurements are described in this work. In combination with in situ measurements of cloud particle properties provided by the Laboratoire de M¶et¶eorologie Physique (LaMP) and simultaneous airborne lidar measurements by the Alfred Wegener Institute for Polar and Marine Research (AWI) ABM clouds were sampled. The SMART-Albedometer measurements were used to retrieve the cloud thermodynamic phase by three different approaches. A comparison of these results with the in situ and lidar measurements is presented in two case studies. Beside the dominating mixed-phase clouds pure ice clouds were found in cloud gaps and at the edge of a large cloud field. Furthermore the vertical distribution of ice crystals within ABM clouds was investigated. It was found that ice crystals at cloud top are necessary to describe the observed SMART-Albedometer measurements. The impact of ice crystals on the radiative forcing of ABM clouds is in vestigated by extensive radiative transfer simulations. The solar and net radiative forcing was found to depend on the ice crystal size, shape and the mixing ratio of ice crystals and liquid water droplets.

Fast and accurate numerical solutions in some problems of particle and radiation transport: synthetic acceleration for the method of short characteristics, Doppler-broadened scattering kernel, remote sensing of the cryosphere

The aim of this work is to present various aspects of numerical simulation of particle and radiation transport for industrial and environmental protection applications, to enable the analysis of complex physical processes in a fast, reliable, and efficient way. In the first part we deal with speed-up of numerical simulation of neutron transport for nuclear reactor core analysis. The convergence properties of the source iteration scheme of the Method of Characteristics applied to be heterogeneous structured geometries has been enhanced by means of Boundary Projection Acceleration, enabling the study of 2D and 3D geometries with transport theory without spatial homogenization. The computational performances have been verified with the C5G7 2D and 3D benchmarks, showing a sensible reduction of iterations and CPU time. The second part is devoted to the study of temperature-dependent elastic scattering of neutrons for heavy isotopes near to the thermal zone. A numerical computation of the Doppler convolution of the elastic scattering kernel based on the gas model is presented, for a general energy dependent cross section and scattering law in the center of mass system. The range of integration has been optimized employing a numerical cutoff, allowing a faster numerical evaluation of the convolution integral. Legendre moments of the transfer kernel are subsequently obtained by direct quadrature and a numerical analysis of the convergence is presented. In the third part we focus our attention to remote sensing applications of radiative transfer employed to investigate the Earth's cryosphere. The photon transport equation is applied to simulate reflectivity of glaciers varying the age of the layer of snow or ice, its thickness, the presence or not other underlying layers, the degree of dust included in the snow, creating a framework able to decipher spectral signals collected by orbiting detectors.

PM(10) remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

Remote sensing of volcanic plumes using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER).

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has been used to quantify SO2 emissions from passively degassing volcanoes. This dissertation explores ASTER’s capability to detect SO2 with satellite validation, enhancement techniques and extensive processing of images at a variety of volcanoes. ASTER is compared to the Mini UV Spectrometer (MUSe), a ground based instrument, to determine if reasonable SO2 fluxes can be quantified from a plume emitted from Lascar, Chile. The two sensors were in good agreement with ASTER proving to be a reliable detector of SO2. ASTER illustrated the advantages of imaging a plume in 2D, with better temporal resolution than the MUSe. SO2 plumes in ASTER imagery are not always discernible in the raw TIR data. Principal Component Analysis (PCA) and Decorrelation Stretch (DCS) enhancement techniques were compared to determine how well they highlight a variety of volcanic plumes. DCS produced a consistent output and the composition of the plumes was easy to identify from explosive eruptions. As the plumes became smaller and lower in altitude they became harder to distinguish using DCS. PCA proved to be better at identifying smaller low altitude plumes. ASTER was used to investigate SO2 emissions at Lascar, Chile. Activity at Lascar has been characterized by cyclic behavior and persistent degassing (Matthews et al. 1997). Previous studies at Lascar have primarily focused on changes in thermal infrared anomalies, neglecting gas emissions. Using the SO2 data along with changes in thermal anomalies and visual observations it is evident that Lascar is at the end an eruptive cycle that began in 1993. Declining gas emissions and crater temperatures suggest that the conduit is sealing. ASTER and the Ozone Monitoring Instrument (OMI) were used to determine the annual contribution of SO2 to the troposphere from the Central and South American volcanic arcs between 2000 and 2011. Fluxes of 3.4 Tg/a for Central America and 3.7 Tg/a for South America were calculated. The detection limits of ASTER were explored. The results a proved to be interesting, with plumes from many of the high emitting volcanoes, such as Villarrica, Chile, not being detected by ASTER.

Observations of volcanic emissions using satellite remote sensing

Volcanoes pose a threat to the human population at regional and global scales and so efficient monitoring is essential in order to effectively manage and mitigate the risks that they pose. Volcano monitoring from space has been possible for over thirty years and now, more than ever, a suite of instruments exists with the capability to observe emissions of gas and ash from a unique perspective. The goal of this research is to demonstrate the use of a range of satellite-based sensors in order to detect and quantify volcanic sulphur dioxide, and to assess the relative performances of each sensor against one another. Such comparisons are important in order to standardise retrievals and permit better estimations of the global contribution of sulphur dioxide to the atmosphere from volcanoes for climate modelling. In this work, retrievals of volcanic sulphur dioxide from a number of instruments are compared, and the individual performances at quantifying emissions from large, explosive volcanic eruptions are assessed. Retrievals vary widely from sensor to sensor, and often the use of a number of sensors in synergy can provide the most complete picture, rather than just one instrument alone. Volcanic emissions have the ability to result significant economic loses by grounding aircraft due to the high risk associated with ash encountering aircraft. As sulphur dioxide is often easier to measure than ash, it is often used as a proxy. This work examines whether this is a reasonable assumption, using the Icelandic eruption in early 2010 as a case study. Results indicate that although the two species are for the most part collocated, separation can occur under some conditions, meaning that it is essential to accurately measure both species in order to provide effective hazard mitigation. Finally, the usefulness of satellite remote sensing in quantifying the passive degassing from Turrialba, Costa Rica is demonstrated. The increase in activity from 2005 – 2010 can be observed in satellite data prior to the phreatic phase of early 2010, and can therefore potentially provide a useful indication of changing activity at some volcanoes.

TECHNOLOGICAL ADVANCEMENT IN REMOTE SENSING AND INNOVATIVE APPLICATION TO VOLCANOLOGY

The integration of remote monitoring techniques at different scales is of crucial importance for monitoring of volcanoes and assessment of the associated hazard. In this optic, technological advancement and collaboration between research groups also play a key role. Vhub is a community cyberinfrastructure platform designed for collaboration in volcanology research. Within the Vhub framework, this dissertation focuses on two research themes, both representing novel applications of remotely sensed data in volcanology: advancement in the acquisition of topographic data via active techniques and application of passive multi-spectral satellite data to monitoring of vegetated volcanoes. Measuring surface deformation is a critical issue in analogue modelling of Earth science phenomena. I present a novel application of the Microsoft Kinect sensor to measurement of vertical and horizontal displacements in analogue models. Specifically, I quantified vertical displacement in a scaled analogue model of Nisyros volcano, Greece, simulating magmatic deflation and inflation and related surface deformation, and included the horizontal component to reconstruct 3D models of pit crater formation. The detection of active faults around volcanoes is of importance for seismic and volcanic hazard assessment, but not a simple task to be achieved using analogue models. I present new evidence of neotectonic deformation along a north-south trending fault from the Mt Shasta debris avalanche deposit (DAD), northern California. The fault was identified on an airborne LiDAR campaign of part of the region interested by the DAD and then confirmed in the field. High resolution LiDAR can be utilized also for geomorphological assessment of DADs, and I describe a size-distance analysis to document geomorphological aspects of hummock in the Shasta DAD. Relating the remote observations of volcanic passive degassing to conditions and impacts on the ground provides an increased understanding of volcanic degassing and how satellite-based monitoring can be used to inform hazard management strategies in nearreal time. Combining a variety of satellite-based spectral time series I aim to perform the first space-based assessment of the impacts of sulfur dioxide emissions from Turrialba volcano, Costa Rica, on vegetation in the surrounding environment, and establish whether vegetation indices could be used more broadly to detect volcanic unrest.

Can we infer plant facilitation from remote sensing? a test across global drylands

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant–plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant–plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. Read More: http://www.esajournals.org/doi/10.1890/14-2358.1

An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.