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This doctoral thesis presents the first work on the extent, spatial dynamics, and long-term trends of the giant kelp (Macrocystis pyrifera) ecosystem in southern South America and sub-Antarctic latitudes. This work was based on an interdisciplinary approach of remote sensing using satellite images, unmanned aerial vehicles (UAV), geographical information systems, underwater exploration, and a collection of historical sources and secondary information from international collaborations. The first research paper of this thesis (Chapter 3) presents a mapping methodology of giant kelp derived from filtering values from the satellite Sentinel-2. This method was validated with secondary sources (previous kelp surveys) and primary sources of data, such as detailed orthomosaics made with UAV. Because of the high overall accuracy of this method, it was possible to map and measure the surface of the complete distribution of the giant kelp ecosystem by ecoregion and province. The second paper (Chapter 4) is based on the mapping methodology from Chapter 3, developing a spatial analysis of the sub-Antarctic kelp from South America, Falkland Islands (Malvinas) and South Georgia to understand the abiotic patterns that could predict the typical size of a giant kelp forest. Additionally, these patterns were compared in a temporal analysis stretching as far back as the 19th century to assess the persistence of this ecosystem. The results of this paper indicate that sub-Antarctic giant kelp is one of the least modified and most persistent marine ecosystems on Earth. Chapter 5 analyses the spatial distribution of marine sea surface temperature (SST) heatwaves and marine cold spells in the Channels and Fjords ecoregion in past decades, with a focus on understanding the climatological trends as they can affect giant kelp ecosystems. This paper established that, in contrast to the main global trend pointing towards SST warming, the frequency of marine cold spells in the nearshore coastlines of southernmost South America has in fact increased in the decade of 2010. We identified two main mechanisms as possible causes for this trend: increased frequency of storms driven by the Antarctic Circumpolar Current and glacier melting in the Patagonian fjords. Cold waters favour the persistence of giant kelp and associated biodiversity, hence the lack of SST warming highlights the region as a potential refugium for the ecosystem. However, more studies are needed to understand these new dynamics, and we conclude the paper with a summary of potential stressors to giant kelp ecosystems in the study area. Finally, Chapter 6 provides an overview of the main findings of this thesis and recommendations for future research, highlighting the need for further interdisciplinary studies on the Magellanic marine province as a climatic refugium for the giant kelp ecosystem.

This DPhil is motivated by the impact that public data can have on the practise of sustainable finance. Disclosure guidance for environmental information is increasingly being used to compel companies to better manage their environmental risk exposure and environmental impacts. Data-driven technologies can 'unravel' company information related to environmental risk and are changing the information asymmetries between company managers, their investors, and society. Three novel and rigorous data science papers have been prepared which provide new access to company environmental risk information. The first paper develops a global inventory of photovoltaic solar energy facilties using machine learning and earth observation and then uses this dataset to assess land cover impacts due to renewable energy siting decisions. The second paper develops asset-level data arrangements of the coal, oil, and gas supply chains, and identifies concentrations of environmental transition risk in the complex network topology. The third paper advances earth observation and computer vision technical methods, assessing the power of these techniques for producing company asset-level data even with limited training data. In developing these papers, this DPhil has identified the opportunities and limits that technology might have in the provision of information for public and private governance of environmental risk and impact. These limits add clarity to the role that policy must play in meeting the diverse information needs of both company shareholders and stakeholders. A discussion chapter provides commentary on these limits; on how the needs of both shareholders and stakeholders can be met with company risk disclosure at the asset-level; and how innovation might be fostered in markets for environmental information. Policy recommendations are summarised and an agenda for further research is provided.

A steadily increasing number of studies have indicated the multidimensional relationships between exposure to greenspace and human health. These previous studies applied diverse, spatially explicit methods and datasets when measuring and modelling greenspace exposure. However, they often did not consider the key underlying principles of geospatial science, such as spatial scale. Potential uncertainties regarding the estimation of greenspace exposure and modelling relationships between greenspace and human health are inherent in such studies. Therefore, research to investigate the spatial dimensions (e.g., scale, data, methods) of exposure to greenspace is warranted. Previous studies measuring greenspace exposure have usually only considered individual exposure types (i.e., availability, accessibility, and visibility). Consequently, there are no existing methodological approaches that standardise and harmonise these three individual metrics to produce a composite estimate of aggregate greenspace exposure. Additional research is essential to develop metrics for greenspace exposure that can reduce the multiplicity of current heterogeneous approaches to greenspace exposure estimation. The four papers foundational to this thesis encompass different methodological approaches and used diverse spatial data to address existing challenges in greenspace exposure assessment. Greater Manchester in the UK was used as the case study area. However, the methods are intended to be transferable to other urban areas. The first paper provides a systematic review of the spatial dimensions considered in previous studies evaluating the associations between greenspace and human health. These preceding studies used a wide range of spatial data, scales of analysis, and buffer distances, resulting in the likelihood that their results were vulnerable to scale effects. Furthermore, these studies represented a heterogeneous collection of study designs. Such heterogeneity of study design may have caused ambiguities in understanding the associations between greenspace and health amongst existing studies. There is a need for new methodological solutions to overcome the existing challenges. The second paper investigated the scale effects inherent in three commonly used metrics of greenspace availability exposure (i.e., NDVI, leaf area index, and land use land cover). Applying lacunarity analysis, this paper identifies the scale sensitivity and the upper limit of the acceptable scale range beyond which these greenspace metrics are vulnerable to scale effects. Using lacunarity weightings, this study also provides a new methodological solution for measuring greenspace availability exposure that combines multiple, properly weighted metrics to reduce the scaling effect. This novel metric offers a unique solution for measuring greenspace availability at high resolutions, independent of scale. The third paper provides an innovative methodological approach to modelling eye-level greenspace visibility using a fusion of digital elevation and land use-land cover data. This study applied a classic viewshed analysis for visibility assessment to more than 86 million observer locations to achieve high resolution and granularity in eye-level exposure assessment. This paper also explores the differences between eye-level and top-down exposure metrics, and the results showed that these two exposure measures are complementary but distinct from one another. The fourth paper develops and evaluates a new methodological approach to measuring greenspaces accessibility at a high spatial resolution. This novel methodological approach allows the availability, accessibility, and visibility metrics of greenspace exposure to be combined to produce a composite greenspace exposure index (CGEI). This CGEI, in turn, introduces the possibility of standardising and harmonising greenspace exposure estimates. The paper also applies the newly developed exposure metrics to investigate variations in greenspace exposure in relation to socioeconomic inequalities and years of potential life lost (YPLL) at the neighbourhood scale. The results of this research indicate the composite greenspace exposure metric is a superior metric for green space exposure estimation and is better at explaining the variability in YPLL compared to any given single exposure metric. It also further supports previous research findings that greenspace exposure spatially co-varies with socioeconomic inequalities and that increased exposure to greenspace is significantly associated with lower YPLL. Overall, this thesis suggests that future studies should critically consider spatial dimensions in the context of exposure assessment. Further studies are required to continue to improve the current understanding of the relationships between greenspace exposure and health.

Dust is a critical component of the Earth System. The central and western Sahara (CWS) is the dustiest place on Earth during the northern hemisphere summer. Understanding patterns and causes of spatial and temporal variability of dust presence here is essential for its reliable simulation in numerical models of weather and climate. Four papers in this thesis contribute to that objective, utilising a combination of high temporal resolution satellite data and global atmospheric reanalyses for June – August 2004 – 2010 inclusive. The first paper develops an objective dust detection scheme for the CWS using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI), which are available every 15 minutes around the clock. These data have shed valuable insight on CWS dust processes, but their subjective application has to date limited their range of applications. The SEVIRI dust flag (SDF) developed here is evaluated against other widely used surface and satellite derived indicators of dustiness and it is found to reliably detect the presence of moderate-heavy dust loadings. The distribution of dust each summer is presented, revealing a high degree of interannual variability in overall dust coverage. The second paper utilises SDF to create an objective, high spatial resolution dust source map, based on the automated tracking of individual dust plumes. The most active sources are associated predominantly with palaeo-lakes and outwash plains, typically around the Saharan mountains. There is a clear intraseasonal progression of active source areas, controlled by regional climatology. The tracking scheme describes the transport trajectory of dust events following their initiation and the spatial association with deep convection at this time, revealing a clear regional divide in the relative importance of known meteorological mechanisms that drive dust emission from the dominant sources. The third paper uses an unsupervised clustering algorithm to classify maps of daily dust presence frequency and identify patterns of intraseasonal variability in CWS dust coverage. The resulting idealised dust states vary according to frequency of dust occurrence and its location, demonstrating a clear progression in preferred dust location from June – August and preferred state transitions from one day to the next. High daily dust occurrence frequency corresponds to an advanced West African Monsoon flow and low daily dust occurrence frequency corresponds to a Harmattan-dominated CWS. The overall location of the dust is linked to the location of the Sahara Heat Low, which changes as the summer progresses. The final paper addresses interannual variability in summertime dust presence frequency by comparing the 2 years with highest (2005) and lowest (2008) dust presence. The key difference is the occurrence of 3 multi-day periods in 2005 characterised by anomalously high dust presence. Case study comparison with the 3 periods of highest dust presence in 2008 identifies the anticyclonic circulation of the midtroposphere as a key control on dust duration over the CWS, dictating whether emitted dust is efficiently transported away from the CWS or whether it remains in suspension over the region for prolonged periods of time, up to several days in the anomalously dusty periods of 2005.

The goal of quantifying the woody cover and biomass of tropical savannas, woodlands and forests using satellite data is becoming increasingly important, but limitations in current scientific understanding reduce the utility of the considerable quantity of satellite data currently being collected. The work contained in this thesis reduces this knowledgegap, using new field data and analysis methods to quantify changes using optical, radar and LiDAR data. The first paper shows that high-resolution optical data (Landsat & ASTER) can be used to track changes in woody vegetation in the Mbam Djerem National Park in Cameroon. The method correlates a satellite-derived vegetation index with field-measured canopy cover, and the paper concludes that forest encroached rapidly into savanna in the region from 1986-2006. Using the same study area, but with radar remote sensing data from 1996 and 2007 (ALOS PALSAR & JERS-1), the second paper shows that radar backscatter correlates well with field-measured aboveground biomass (AGB). This dataset confirms the woody encroachment within the park; however, in a larger area around the park, deforestation dominates. The AGB-radar relationships described above are expanded in the next paper to include field plots from Budongo Forest (Uganda), the Niassa Reserve (north Mozambique), and the Nhambita Community Project (central Mozambique). A consistent AGB-radar relationship is found in the combined dataset, with the RMSE for predicted AGB values for a site increasing by <30 %, compared with a site-specific equation, when using an AGB-radar equation derived from the three other sites. The study of the Nhambita site is extended in the following paper to assess the ability of radar to detect change over short time periods in this environment, as will be needed for REDD (Reducing Emissions from Deforestation and Degradation). Using radar mosaics from 2007 and 2009, areas known (from detailed ground data) to have been degraded decreased in AGB in the radar change detection, whereas areas of agroforestry and forest protection showed small increases.