Lake Imaging and Monitoring Aerial Drone

We describe the development of a BVLOS (Beyond Visual Line-Of-Sight) model aircraft (UAV). The broad design requirements included (i) fuselage capable of accommodating an imaging package or other instrumentation, (ii) suitability for over-lake BVLOS authorization in Switzerland, (iii) capability of land or water take-offs/landing, (iv) at least 90-min flight autonomy, (v) modularity of the imaging package and (vi) real-time IR/RGB imagery. Requirement (i) was to ensure an aircraft amenable to future developments. Requirements (ii)-(iv) were driven by the goal of improving estimates of lake surface energy fluxes, since such fluxes have a major impact on long-term lake temperatures and hence ecological status. Requirement (v), in conjunction with (i), allows the UAV to be adapted to other imaging applications. The real-time imagery requirement (vi) permits modifications of on-going missions to map areas of specific interest as they are detected. The prototype UAV produced to satisfy these characteristics was built on the twin-motor My Twin Dream (MTD) aircraft, which has a 1.8-m wing span airframe and a spacious fuselage. The legal authorization necessitated, where feasible, hardware redundancy as well as installation of a parachute system. Continuous communication between the ground station and UAV is provided by the LTE cellular telephone network. The UAV communication is handled by an on-board Linux computer, which is also responsible for control of the imagery package. The avionics involved modifications of the open-source APM autopilot software and the associated ground control station. A key modification was to support a custom-built emergency recovery system, which is triggered by loss of a heartbeat signal from the autopilot. The MTD airframe was modified to accommodate the system electronics and imaging hardware. Results from test flights over Lake Geneva demonstrate the ability of the aircraft to produce imagery data

Assessing spring phenology of a temperate woodland : a multiscale comparison of ground, unmanned aerial vehicle and Landsat satellite observations

PhD ThesisVegetation phenology is the study of plant natural life cycle stages. Plant phenological events are related to carbon, energy and water cycles within terrestrial ecosystems, operating from local to global scales. As plant phenology events are highly sensitive to climate fluctuations, the timing of these events has been used as an independent indicator of climate change. The monitoring of forest phenology in a cost-effective manner, at a fine spatial scale and over relatively large areas remains a significant challenge. To address this issue, unmanned aerial vehicles (UAVs) appear to be a potential new platform for forest phenology monitoring. The aim of this research is to assess the potential of UAV data to track the temporal dynamics of spring phenology, from the individual tree to woodland scale, and to cross-compare UAV results against ground and satellite observations, in order to better understand characteristics of UAV data and assess potential for use in validation of satellite-derived phenology. A time series of UAV data were acquired in tandem with an intensive ground campaign during the spring season of 2015, over Hanging Leaves Wood, Northumberland, UK. The radiometric quality of the UAV imagery acquired by two consumer-grade cameras was assessed, in terms of the ability to retrieve reflectance and Normalised Difference Vegetation Index (NDVI), and successfully validated against ground (0.84≤R2≥0.96) and Landsat (0.73≤R2≥0.89) measurements, but only NDVI resulted in stable time series. The start (SOS), middle (MOS) and end (EOS) of spring season dates were estimated at an individual tree-level using UAV time series of NDVI and Green Chromatic Coordinate (GCC), with GCC resulting in a clearer and stronger seasonal signal at a tree crown scale. UAV-derived SOS could be predicted more accurately than MOS and EOS, with an accuracy of less than 1 week for deciduous woodland and within 2 weeks for evergreen. The UAV data were used to map phenological events for individual trees across the whole woodland, demonstrating that contrasting canopy phenological events can occur within the extent of a single Landsat pixel. This accounted for the poor relationships found between UAV- and Landsat-derived phenometrics (R2<0.45) in this study. An opportunity is now available to track very fine scale land surface changes over contiguous vegetation communities, information which could improve characterization of vegetation phenology at multiple scales.The Science without Borders program, managed by CAPES-Brazil (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior)

Hyperspectral, thermal and LiDAR remote sensing for red band needle blight detection in pine plantation forests

PhD ThesisClimate change indirectly affects the distribution and abundance of forest insect pests and pathogens, as well as the severity of tree diseases. Red band needle blight is a disease which has a particularly significant economic impact on pine plantation forests worldwide, affecting diameter and height growth. Monitoring its spread and intensity is complicated by the fact that the diseased trees are often only visible from aircraft in the advanced stages of the epidemic. There is therefore a need for a more robust method to map the extent and severity of the disease. This thesis examined the use of a range of remote sensing techniques and instrumentation, including thermography, hyperspectral imaging and laser scanning, for the identification of tree stress symptoms caused by the onset of red band needle blight. Three study plots, located in a plantation forest within the Loch Lomond and the Trossachs National Park that exhibited a range of red band needle blight infection levels, were established and surveyed. Airborne hyperspectral and LiDAR data were acquired for two Lodgepole pine stands, whilst for one Scots pine stand, airborne LiDAR and Unmanned Aerial Vehicle-borne (UAV-borne) thermal imagery were acquired alongside leaf spectroscopic measurements. Analysis of the acquired data demonstrated the potential for the use of thermographic, hyperspectral and LiDAR sensors for detection of red band needle blight-induced changes in pine trees. The three datasets were sensitive to different disease symptoms, i.e. thermography to alterations in transpiration, LiDAR to defoliation, and hyperspectral imagery to changes in leaf biochemical properties. The combination of the sensors could therefore enhance the ability to diagnose the infection.Natural Environment Research Council (NERC) for funding this PhD program (studentship award 1368552) and providing access to specialist equipment through a Field Spectroscopy Facility loan (710.114). I would like to thank NERC Airborne Research Facility for providing airborne data (grant: GB 14-04) that made the PhD a challenge, to say the least. My sincere gratitude goes to the Douglas Bomford Trust for providing additional funds, which allowed for completion of the UAV-borne part of this research

The effects of forest degradation on arboreal apes within Sikundur, the Gunung Leuser Ecosystem, Northern Sumatra.

Tropical forests are being destroyed at a rate of 1.5 acres every second due to human activities, thereby accelerating climate change through impacts on the carbon cycle and causing the extinction of species dependent on these habitats. In the face of such immediate and globally significant issues, there is a lack of robust scientific knowledge on how tropical deforestation and degradation affects ecosystem stability and the fauna that inhabit tropical forests. As anthropogenic disturbance removes available habitat for rainforest species and degrades remaining forests, a multitude of species are threatened. There is a need to develop methods to rapidly assess tropical forest structure and relate this to habitat quality for keystone species, like primates. Only upon understanding the impacts of degradation on forests and their inhabiting animals can effective conservation methods be planned. This project aims to investigate the effects of forest degradation on primates over a large study site using innovative data collection methods, as well as enabling the identification of areas of conservation importance and the modelling of future predicted climate change effects on the well-being of primates inhabiting degraded forests, addressing the possible synergistic effects of forest degradation and climate change on primate species at a landscape scale. The findings of this project show that Sikundur in Northern Sumatra, a degraded tropical forest, is highly climatically variable. This climatic variability in turn alters how and when siamang range within the forest canopy. Due to the structural and climatic heterogeneity of the Sikundur landscape, different primate species are more abundant in different areas, with more morphologically and behaviourally specialist species dependant on specific structural elements with the forest. Although identifying historical forest degradation is problematic do to microtopography variation in Sikundur, modelling of future climate change shows that both anthropogenic disturbance and microtopographic variation may render some areas of Sikundur less suitable for primate species in the future. For species with narrower habitat requirements, climatic change is likely to have more impact, disproportionately effecting sympatric species. This thesis contains four data chapters with an introductory chapter and a discussion chapter. Chapter 1 reviews the available literature on the potential impacts of forest degradation on arboreal primates within the study site. Chapter 2 assess the effects of forest structure on microclimates within tropical rainforest canopy, with detailed recording of temperatures within the canopy. Both data collection and microclimate modelling indicate a highly diverse climate environment in the Sikundur forest canopy, with vertical temperature gradients potentially having a substantial impact on arboreal primates. Chapter 3 relates the synergistic relationship between forest degradation and microclimate on the behaviour and ranging of siamang, Symphalangus syndactylus. Results suggest that siamang are limited in their ability to behaviourally thermoregulate effectively in low cloud cover due to the limiting factors of near-exclusive arboreality and territorial defence. Chapter 4 assesses the abundance of three primate species, Thomas’s langur Presbytis thomasi, the lar gibbon Hylobates lar verstitus, and siamang, in relation to anthropogenic disturbance and forest structure at a landscape scale. In this study, the more behaviourally and ecologically specialist lar gibbons show clear habitat preferences. Thomas langur are seemingly adverse to anthropogenic disturbance whilst siamang habitat requirements, despite extensive vegetation surveys, remain unclear. Chapter 5 models the effects of future predicted climate change on the habitat suitability of siamang and Sumatran orang-utan, Pongo abelii, inhabiting the degraded forests of Sikundur. Results in this chapter indicate that areas of forest degradation and areas subject to intense solar radiation due to forest structure variation will be less suitable for arboreal primates in the future. This research contributes to a greater understanding of the effects of selective logging and climate change on tropical forests, vegetation structure and climate change on primate behaviour and ranging, and sheds light on the prospect of primate species survival in the face of anthropogenic disturbance. Additionally, it provides innovative, cost effective methods for the study of 3-dimensional forest structure and arboreal microclimate and the analytical techniques that apply these data to potential conservation actions

Refining terrestrial biosphere feedbacks to climate change through precise characterization of terrestrial vegetation

Climate change is primarily driven by the human activities of fossil fuel combustion and land use change, which together result in the emissions of greenhouse gases such as carbon dioxide (CO₂). The terrestrial biosphere currently absorbs about a third of total anthropogenic CO₂ emissions, mostly through primary production by vegetation. The continued function of vegetation as a CO₂ sink is uncertain, as climate change has the potential to enhance or restrict the carbon uptake capacity of vegetation. Uncertainty in terrestrial vegetation function in the context of climate change, due in part to a lack of precise observations of leaf biochemistry and function with which to develop models, therefore limits the confidence of climate change projections. In its entirety, this thesis examines the potential for more precise observations of leaf function and their integration across a variety of models and observational scales. The first chapter provides an introductory overview of the subsequent four chapters and how each compliments the other. The second chapter demonstrates the role of the terrestrial biosphere in influencing the relationship between temperature change and cumulative CO₂ emissions. The third chapter provides adaptations to current radiative transfer modelling approaches to improve estimations of leaf biochemical constituents. The fourth chapter applies high spatiotemporal resolution observations of leaf phenology, the timing of leaf emergence and senescence, across North America to predict species-specific leaf phenology patterns under various emissions scenarios throughout the 21st century. The fifth chapter provides an approach to detect declines in ecosystem processes such as carbon uptake using observational leaf phenology networks. These chapter results indicate that 1) uncertainty in the land-borne fraction of carbon emissions contributes largely to uncertainty in the relationship between temperature change and emissions, 2) spectral subdomains and prior estimation of leaf structure improves leaf biochemistry estimations, 3) leaf senescence timing may diverge between boreal and temperate species under a high emissions scenario, and 4) declines in vegetational carbon uptake can be accurately detected using quantitative phenocam-based indicators. The fundamental and technical insights provided through this thesis will facilitate more reliable and functionally resolved projections of terrestrial biosphere feedbacks to climate change