The main goal of this research was to investigate the spatial and temporal impacts of water siltation caused by Artisanal Small-scale Gold Mining (ASGM) on the underwater light field of the Tapajós River and its main tributaries (Jamanxim, Novo, Tocantinzinho, and Crepori rivers). In order to accomplish this, two fieldwork research trips were undertaken to collect data associated with water quality and radiometric data. This data provided information to quantify the underwater light field in water affected by a gradient of mining tailings intensity, clustered into five major classes ranging from 0 to 120 mg/L of total suspended solids (TSS) (Chapter 3). In general, with increased TSS from mining operations such as in the Crepori, Tocantinzinho, and Novo rivers, the scattering process prevails over absorption coefficient and, at sub-surface, scalar irradiance is reduced, resulting in a shallower euphotic zone where green and red wavelengths dominate. The effects of light reduction on the phytoplankton community was not clearly observed, which may be attributed to a low number of samples for proper comparison between impacted and non-impacted tributaries and/or to general low phytoplankton productivity in all upstream tributaries. In Chapter 4, aiming to extend the information derived from Chapter 3 over a 40-year period (1973-2012), the TSS concentration along the Tapajós River and its main tributaries was quantified based on in situ data and historical Landsat-MSS/TM/OLI data. Measurements of radiometric data were used to calibrate satellite atmospheric correction and establish an empirical relationship with TSS. The regression estimates TSS with high confidence from surface reflectance (ρ_surf (red)) up to 25%, which corresponds to approximately 110 mg.L-1. The combination of the atmospheric correction and the robust reflectance-based TSS model allowed estimation of TSS in the Tapajós River from the historical Landsat database (40 years). In Chapter 5, the role of the temporal changes of ASGM area in the water siltation over the last 40 years was investigated in four sub-basins: the Crepori, Novo, and Tocantins sub-basins (mined); and the Jamanxim sub-basin (non-mined), considering the landscape characteristics such as soil type and proximity to drainage system. ASGM areas were mapped for five annual dates (1973, 1984, 1993, 2001, and 2012) based on Landsat satellite images. Results showed that ASGM increased from 15.4 km2 in 1973, to 166.3 and 261.7 km2 in 1993 and 2012, respectively. The effects of ASGM areas on water siltation depends on several factors regarding ASGM activities, such as the type of mining, type of gold deposits, and intensity of gold mining, represented by number of miners and gold production. / Graduate / 0373 / 0768 / 0775 / lobo@uvic.ca

Global trends of transformation and loss of wetlands to other land uses has deleterious effects on surrounding ecosystems, and there is a resultant increasing need for improved mapping of wetlands. This is because wetland conservation and management depends on accurate spatial representation of these systems. Current approaches to mapping wetlands through the classification of satellite imagery typically under-represent actual wetland area, and the importance of ancillary data in improving the accuracy in mapping wetlands is recognized. This study uses likelihood estimates of wetland occurrence in KwaZulu-Natal (KZN), South Africa, using a number of environmental surrogate predictors (such as slope, rainfall, soil properties etc.). Using statistical information from a set of mutually independent environmental variables in known wetland areas, conditional probabilities were derived through a Bayesian network (BN) from which a raster layer of wetland probability was created. The layer represents the likelihood of wetlands occurring in a specific area according to the statistical conditional probability of the wetland determinants. Probability values of 80% and greater also accounted for approximately 6% of the KZN area (5 520 km²), which is substantially more than the previously documented wetland area in KZN (4% of the KZN area or 4 200 km²). Using an independent test dataset, Receiver Operating Characteristic (ROC) curves with the Area Under Curve (AUC) analysis verified that the final model output predicted wetland area well (AUC 0.853). Based on visual comparisons between the probability layer and ground verified wetland systems, it was shown that high wetland probability areas in the final output correlated well with previously highlighted major wetland and wetland-rich areas in KZN. Assessment of the final probability values indicated that the higher the probability values, the higher the accuracy in predicting wetland occurrence in a landscape setting, irrespective of the wetland area. It was concluded that the layer derived from predictor layers in a BN has the potential to improve the accuracy of the KZN wetland layer by serving as valuable ancillary data. Application of the final probability layer could extend into the development of updated spatial freshwater conservation plans, potentially predicting the historical wetland extents, and as input into the land cover classification process. Keywords: ancillary data, Bayesian network, GIS, modelling, probability, wetland mapping. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2014.

This thesis provides insight into techniques for the detection and classification of various marginal ice zone roughnesses in the southern Beaufort Sea using in situ and satellite-based microwave remote sensing. A proposed model of surface roughness shows the dependence of circular coherence, a discriminator of roughness, on the roughness and dielectrics. A relationship between ice slopes in azimuth and range direction is derived. Microwave brightness temperature of open water is significantly correlated with wave height but not with the wind speed, having the strongest correlations for the H-polarization at both 37 and 89 GHz. A modified formula for the relationship between non-dimensional form of energy and wave age at wind speeds 0−10 m/s is obtained. The brightness temperature (April−June) of sea ice at H-polarization of 89 GHz is found to decrease with increasing roughness, and is attributed to the dominant contributions from rapidly varying thermodynamic properties of snow-covered sea ice.

The middle atmosphere is a very important part of the Earth system. Until recently, we did not realize the importance of the structure of this vaporous shell and of the fundamental role it plays in both creating and sustaining life on the planet. Thanks to the development and improvement of new sounding methods and techniques, our knowledge of the composition of the atmosphere has become more detailed than ever before. We have also learned how to reveal complex interactions between different species and how they react to the incoming solar radiation. The middle part of the Earth’s atmosphere serves as a host for the Polar Mesospheric Clouds. These clouds consist of a thin layer of water-ice particles, only exsisting during the summer months and only close to the poles. There are indications that the occurrence of Polar Mesospheric Clouds may be linked to climate change. It has been pointed out that the first sightings coincide with the industrial revolution. Satellite observations have shown that Polar Mesospheric Clouds have become brighter and possibly more widely distributed during the 20th century. The clouds might therefore be suited as indicators of the variability of the climate - a good reason for studying this night-shimmering phenomena. The clouds can also be used as a proxy for middle atmospheric dynamics. In order to fully utilize Polar Mesospheric Clouds as tracers for atmospheric variability and dynamics, we need to better understand their local properties. The Optical Spectrograph and Infra-Red Imager System (OSIRIS) is one of two instruments installed on the Odin satellite. The optical spectrograph of this instrument observes sunlight scattered by the atmosphere and thus the Polar Mesospheric Clouds. This thesis deals with a tomographic technique that can reconstruct both horizontal and vertical structures of the clouds by using observations from various angles of the atmospheric region. From this information, microphysical properties such as particle sizes and number densities are obtained. The tomographic technique presented in this thesis also provides a basis for a new satellite concept - MATS. The idea behind the MATS satellite mission is to analyze wave activity in the atmosphere over a wide range of spatial and temporal scales, based on the scientific heritage from Odin/OSIRIS and the tomographic algorithms presented in this thesis. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper3: Submitted. Paper 4: Manuscript.</p>

This study has provided a landscape level estimate of leaf area index (LAI) and net primary productivity (NPP) for a temperate broadleaf forest ecosystem in south-central Indiana. The estimates were compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products LAI and NPP from both spatial and temporal perspectives. The evidence suggests that field-based estimates were poorly correlated with global MODIS data due to the simplifying assumptions of the MODIS global applicability, saturation problems of the red reflectance in highly vegetated areas, homogeneous land cover types of the study area, and other design assumptions of the field-based estimates. To improve the localized applicability of MODIS product algorithms, an empirical and localized algorithm combining in-situ measurements, the buildup of a localized biophysical model, and remote sensing-derived data were suggested for each local-scaled ecosystem. / Department of Natural Resources and Environmental Management

The goals of this project were to: (1) combine the ARC/INFO Geographic Information System (GIS) software with the TIGER data files and tree inventory data files, (2) demonstrate GIS as a tool in street tree inventory management, (3) answer a management related question, specifically the identification of dead and hazardous trees within the city, with the use of the GIS tool, and (4) prepare an article based on the project for submission to the Journal of Arboriculture.Dead and hazardous trees located along a city street are a major accident liability to a city. It is vital, for both safety and aesthetic purposes, that a community know the location of dead and hazardous trees. As a management tool the GIS can utilize the inventory data to aid the urban forester in interpreting the urban forest by identifying these tree locations. Through the use of point-in-polygon analysis and choropleth maps, these specific management concerns can be highlighted throughout the city.The power to visually demonstrate certain parts of town with higher concentrations of work needed is one way that GIS can provide the management tools necessary for better care of our urban forests. / Department of Landscape Architecture

Feedbacks between the climate system and the high-latitude carbon cycle will substantially influence the intensity of future climate change. It is therefore crucial that the net ecosystem exchange of CO2 (NEE) between the high-latitude land surface and the atmosphere is accurately quantified, where NEE refers to the difference between ecosystem respiration (R) and photosynthesis (gross ecosystem exchange, GEE): NEE=-GEE+R in umol/m^2/s. NEE can only be directly measured over areas of 1 km^2 through eddy covariance, and modeling approaches such as the Vegetation Photosynthesis Respiration Model (VPRM) are required to upscale NEE. VPRM is a remote sensing based model that calculates R as a linear function of air temperature (Ta) when air temperature is above a given threshold (Tlow), and sets respiration to a constant value when Ta<Tlow. GEE is estimated according to remote sensing observations of vegetation indices, shortwave radiation, air temperature, and soil moisture. Although in situ findings have shown that snow and Arctic species composition have a substantial influence on high-latitude NEE, model estimates of high-latitude NEE have typically been generated without Arctic-specific vegetation classes, and without using remote sensing observations to represent the effects of snow on NEE. The hypothesis driving this work was therefore that uncertainty in estimates of high-latitude NEE could be reduced by representing the influences of Arctic vegetation classes and snow. The central objectives were to determine feasible approaches for reducing uncertainty in VPRM estimates of NEE by representing the influences of snow and Arctic vegetation, create PolarVPRM accordingly, and analyze inter-annual variability in PolarVPRM estimates of high-latitude North American NEE (2001-2012). The associations between snow and NEE, and the potential to describe these influences on NEE using remote sensing observations, were examined using time lapse camera observations of snow cover area (SCA) and eddy covariance measurements of NEE from Daring Lake, Northwest Territories, Canada. Analyses indicated good agreement between SCA derived from camera, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) observations. SCA was also found to influence the timing and magnitude of NEE. MODIS SCA was therefore incorporated into VPRM, and VPRM was calibrated using eddy covariance and meteorological observations collected in 2005 at Daring Lake. VPRM was run through years 2004-2007 over both Daring Lake and Ivotuk, Alaska, USA, using four model formulations, three of which represented the effects of SCA on respiration and/or photosynthesis, and another which did not use MODIS SCA. Comparisons against eddy covariance observations indicated that uncertainty was reduced in VPRM estimates of NEE when respiration was calculated as a linear function of soil temperature when SCA>50%, and as a linear function of air temperature when SCA<50%, thereby reflecting the influence of snow on decoupling soil/air temperatures. Representing the effect of SCA on NEE therefore reduced uncertainty in VPRM estimates of NEE. In order to represent spatial variability in high-latitude estimates of NEE due to vegetation type, Arctic-specific vegetation classes were created for PolarVPRM by combining and aggregating two existing vegetation classifications: the Synergetic Land Cover Product and the Circumpolar Arctic Vegetation Map. Levene's test indicated that the PolarVPRM vegetation classes divided the pan-Arctic region into heterogeneous distributions in terms of net primary productivity, and passive microwave derived estimates of snow and growing season influences on NEE. A non-parametric statistical approach of Alternating Conditional Expectations found significant, non-linear associations to exist between passive microwave derived estimates of snow and growing season drivers of NEE. Furthermore, the shape of these associations varied according to the vegetation class over which they were examined. Further support was therefore provided to the idea that uncertainty in model estimates of NEE could be reduced by calculating snow and growing season NEE separately within each vegetation class. PolarVPRM estimates of NEE in 2001-2012 were generated at a three hourly and 1/6 x 1/4 degree resolution across polar North America (55-170 W, 55-83 N). Model calibration was conducted over three sites: Daring Lake, Ivotuk, and Atqasuk, Alaska, USA. Model validation was then conducted by comparing PolarVPRM estimates of year-round daily average NEE to non-gap-filled eddy covariance observations of daily average NEE acquired over the three calibration sites, as well as six other Arctic sites. PolarVPRM performed well over all sites, with an average mean absolute error (MAE) of 0.20 umol/m^2/s, and had diminished error rates when the influence of SCA on respiration was explicitly represented. Error analysis indicated that peak growing season GEE was underestimated at Barrow because GEE at this site showed a stronger response to the amount of incoming shortwave radiation than at the calibration site, suggesting that PolarVPRM may underestimate GEE over wetland and barren vegetated regions. Despite these uncertainties, PolarVPRM was found to generate more accurate estimates of monthly and three-hourly NEE relative to eddy covariance observations than two established models, FLUXNET Model-Tree Ensemble (MTE) and CarbonTracker. Relative to eddy covariance observations and PolarVPRM estimates, MTE tended to overestimate snow season respiration, and CarbonTracker tended to overestimate the amount of midday photosynthesis. Analysis of PolarVPRM output across North America (north of 55 N) found an increase in net annual carbon efflux over over time (2001-2012). Specifically, increased rates of respiration are estimated when soil and air temperatures are warmer. Although increases in growing season vegetation indices and air temperature enable greater photosynthetic uptake by Arctic vegetation, forests and shrublands uptake less CO2 in the middle of the growing season when air temperatures rise above the physiological optima for photosynthesis. As a result, PolarVPRM estimated a decline in net photosynthetic uptake over time. Overall, PolarVPRM output indicates that North American regions north of 55 N are losing strength as a carbon sink in response to rising air temperatures.

The atmospheric boundary layer (ABL) is the layer of air directly influenced by the Earth’s surface and is the layer of the atmosphere most important to humans as this is the air we live in. Methods for measuring the properties of the ABL include three general approaches: satellite-based, ground- based and airborne. A major research challenge is that many contemporary methods provide a restricted spatial resolution or coverage of variations of ABL properties such as how wind speed varies across a landscape with complex topography. To enhance our capacity to measure the properties of the ABL, this thesis presents a new technique that involves a small unmanned aircraft system (sUAS) equipped with a customized payload for measuring wind speed and particulate matter. The research presented herein outlines two key phases in establishing the proof-of-concept of the payload and its integration on the sUAS: (1) design and testing and (2) field demonstration. The first project focuses on measuring wind speed, which has been measured with fixed wing sUASs in previous research, but not with a helicopter sUAS. The second project focuses on the measurement of particulate matter, which is a major air pollutant typically measured with ground- based sensors. Results from both proof-of-concept projects suggest that ABL research could benefit from the proposed techniques.

In this dissertation we use digital holographic quantitative phase microscopy to observe and measure phase-only structures due to induced photothermal interactions and nanoscopic structures produced by photomechanical interactions. Our use of the angular spectrum method combined with off-axis digital holography allows for the successful hologram acquisition and processing necessary to view these phenomena with nanometric and, in many cases, subnanometric precision. We show through applications that this has significance in metrology of bulk fluid and interfacial properties. Our accurate quantitative phase mapping of the optically induced thermal lens in media leads to improved measurement of the absorption coefficient over existing methods. By combining a mathematical model describing the thermal lens with that describing the surface deformation effect of optical radiation pressure, we simulate the ability to temporally decouple the two phenomena. We then demonstrate this ability experimentally as well as the ability of digital holography to clearly distinguish the phase signatures of the two effects. Finally, we devise a pulsed excitation method to completely isolate the optical pressure effect from the thermal lensing effect. We then develop a noncontact purely optical approach to measuring the localized surface properties of an interface within a system using a single optical pressure pulse and a time-resolved digital holographic quantitative phase imaging technique to track a propagating nanometric capillary disturbance. We demonstrate the method's ability to accurately measure the surface energy of pure media and chemical monolayers formed by surfactants with good agreement to published values. We discuss the possible adaptation of this technique to applications for living biological cell membranes.

Invasive Prosopis trees pose significant threats to biodiversity and ecosystem services in the Northern Cape Province of South Africa. Several estimates have been made of the spatial extent of alien plant invasion in South Africa. The South African Plant Invaders Atlas (SAPIA) suggested that about 10 million hectares of South Africa has been invaded. However, the rate and spatial extent of Prosopis invasion has never been accurately quantified. The objective of the study is to use Remote Sensing and Geographic Information System (GIS) techniques to: (i) reveal areas susceptible to future invasion, (ii) describe the current extent and densities of Prosopis, (iii) to reveal the spatial dynamics and (iv) establish the extent of fragmentation of the natural vegetation in the Northern Cape Province. Image classification products were generated using spectral analysis of seasonal profiles, various resolution image inputs, spectral indices and ancillary data. Classification approaches varied by scene and spatial resolution as well as application of the data. Coarse resolution imagery and field data were used to create a probability map estimating the area vulnerable to Prosopis invasion using relationships between actual Prosopis occurrence, spectral response, soils and terrain unit. Multi-temporal Landsat images and a 500m x 500m point grid enabled vector analysis and statistical data to quantify the change in distribution and density as well as the spatial dynamics of Prosopis since 1974. Fragmentation and change of natural vegetation was quantified using a combined cover density class, calculating patch density per unit (ha) for each biome The extent of Prosopis cover in the Northern Cape Province reached 1.473 million hectare or 4% of the total land area during 2007. The ability of the above mentioned Remote Sensing and GIS techniques to map the extent and densities of Prosopis in the Northern Cape Province of South Africa demonstrated a high degree of accuracy (72%). While neither the image classification nor the probability map can be considered as 100% accurate representations of Prosopis density and distribution, the products provide use full information on Prosopis distribution and are a first step towards generating more accurate products. For primary invasion management, these products and the association of a small area on a map with Prosopis plants and patches, mean that the management effort and resources are efficiently focused. Further studies using hyper-spectral image analysis are recommended to improve the classification accuracy of the spatial extent and density classes obtained in this study. / Thesis (M. Environmental Science)--North-West University, Potchefstroom Campus, 2010.