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Steven Hancock
School of Geosciences, University of Edinburgh, Edinburgh EH8 9XP, UK

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Journal article
Published: 25 October 2020 in Remote Sensing
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Stand-level maps of past forest disturbances (expressed as time since disturbance, TSD) are needed to model forest ecosystem processes, but the conventional approaches based on remotely sensed satellite data can only extend as far back as the first available satellite observations. Stand-level analysis of airborne LiDAR data has been demonstrated to accurately estimate long-term TSD (~100 years), but large-scale coverage of airborne LiDAR remains costly. NASA’s spaceborne LiDAR Global Ecosystem Dynamics Investigation (GEDI) instrument, launched in December 2018, is providing billions of measurements of tropical and temperate forest canopies around the globe. GEDI is a spatial sampling instrument and, as such, does not provide wall-to-wall data. GEDI’s lasers illuminate ground footprints, which are separated by ~600 m across-track and ~60 m along-track, so new approaches are needed to generate wall-to-wall maps from the discrete measurements. In this paper, we studied the feasibility of a data fusion approach between GEDI and Landsat for wall-to-wall mapping of TSD. We tested the methodology on a ~52,500-ha area located in central Idaho (USA), where an extensive record of stand-replacing disturbances is available, starting in 1870. GEDI data were simulated over the nominal two-year planned mission lifetime from airborne LiDAR data and used for TSD estimation using a random forest (RF) classifier. Image segmentation was performed on Landsat-8 data, obtaining image-objects representing forest stands needed for the spatial extrapolation of estimated TSD from the discrete GEDI locations. We quantified the influence of (1) the forest stand map delineation, (2) the sample size of the training dataset, and (3) the number of GEDI footprints per stand on the accuracy of estimated TSD. The results show that GEDI-Landsat data fusion would allow for TSD estimation in stands covering ~95% of the study area, having the potential to reconstruct the long-term disturbance history of temperate even-aged forests with accuracy (median root mean square deviation = 22.14 years, median BIAS = 1.70 years, 60.13% of stands classified within 10 years of the reference disturbance date) comparable to the results obtained in the same study area with airborne LiDAR.

ACS Style

Nuria Sanchez-Lopez; Luigi Boschetti; Andrew Hudak; Steven Hancock; Laura Duncanson. Estimating Time Since the Last Stand-Replacing Disturbance (TSD) from Spaceborne Simulated GEDI Data: A Feasibility Study. Remote Sensing 2020, 12, 3506 .

AMA Style

Nuria Sanchez-Lopez, Luigi Boschetti, Andrew Hudak, Steven Hancock, Laura Duncanson. Estimating Time Since the Last Stand-Replacing Disturbance (TSD) from Spaceborne Simulated GEDI Data: A Feasibility Study. Remote Sensing. 2020; 12 (21):3506.

Chicago/Turabian Style

Nuria Sanchez-Lopez; Luigi Boschetti; Andrew Hudak; Steven Hancock; Laura Duncanson. 2020. "Estimating Time Since the Last Stand-Replacing Disturbance (TSD) from Spaceborne Simulated GEDI Data: A Feasibility Study." Remote Sensing 12, no. 21: 3506.

Journal article
Published: 20 April 2020 in Remote Sensing
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The hemlock woolly adelgid (HWA; Adelges tsugae) is an invasive insect infestation that is spreading into the forests of the northeastern United States, driven by the warmer winter temperatures associated with climate change. The initial stages of this disturbance are difficult to detect with passive optical remote sensing, since the insect often causes its host species, eastern hemlock trees (Tsuga canadensis), to defoliate in the midstory and understory before showing impacts in the overstory. New active remote sensing technologies—such as the recently launched NASA Global Ecosystem Dynamics Investigation (GEDI) spaceborne lidar—can address this limitation by penetrating canopy gaps and recording lower canopy structural changes. This study explores new opportunities for monitoring the HWA infestation with airborne lidar scanning (ALS) and GEDI spaceborne lidar data. GEDI waveforms were simulated using airborne lidar datasets from an HWA-infested forest plot at the Harvard Forest ForestGEO site in central Massachusetts. Two airborne lidar instruments, the NASA G-LiHT and the NEON AOP, overflew the site in 2012 and 2016. GEDI waveforms were simulated from each airborne lidar dataset, and the change in waveform metrics from 2012 to 2016 was compared to field-derived hemlock mortality at the ForestGEO site. Hemlock plots were shown to be undergoing dynamic changes as a result of the HWA infestation, losing substantial plant area in the middle canopy, while still growing in the upper canopy. Changes in midstory plant area (PAI 11–12 m above ground) and overall canopy permeability (indicated by RH10) accounted for 60% of the variation in hemlock mortality in a logistic regression model. The robustness of these structure-condition relationships held even when simulated waveforms were treated as real GEDI data with added noise and sparse spatial coverage. These results show promise for future disturbance monitoring studies with ALS and GEDI lidar data.

ACS Style

Peter Boucher; Steven Hancock; David Orwig; Laura Duncanson; John Armston; Hao Tang; Keith Krause; Bruce Cook; Ian Paynter; Zhan Li; Arthur Elmes; Crystal Schaaf. Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation. Remote Sensing 2020, 12, 1304 .

AMA Style

Peter Boucher, Steven Hancock, David Orwig, Laura Duncanson, John Armston, Hao Tang, Keith Krause, Bruce Cook, Ian Paynter, Zhan Li, Arthur Elmes, Crystal Schaaf. Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation. Remote Sensing. 2020; 12 (8):1304.

Chicago/Turabian Style

Peter Boucher; Steven Hancock; David Orwig; Laura Duncanson; John Armston; Hao Tang; Keith Krause; Bruce Cook; Ian Paynter; Zhan Li; Arthur Elmes; Crystal Schaaf. 2020. "Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation." Remote Sensing 12, no. 8: 1304.

Accepted manuscript
Published: 18 March 2020 in Environmental Research Letters
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The Global Ecosystem Dynamics Investigation (GEDI) lidar began data acquisition from the International Space Station in March 2019 and is expected to make over 10 billion measurements of canopy structure and topography over two years. Previously, airborne lidar data with limited spatial coverage have been used to examine relationships between forest canopy structure and faunal diversity, most commonly bird species. GEDI's latitudinal coverage will permit these types of analyses at larger spatial extents, over the majority of the Earth's forests, and most importantly in areas where canopy structure is complex and/or poorly understood. In this regional study, we examined the impact that GEDI-derived Canopy Structure variables have on the performance of bird species distribution models (SDMs) in Sonoma County, California. We simulated GEDI waveforms for a two-year period and then interpolated derived Canopy Structure variables to three grid sizes of analysis. In addition to these variables, we also included Phenology, Climate, and other Auxiliary variables to predict the probability of occurrence of 25 common bird species. We used a weighted average ensemble of seven individual machine learning models to make predictions for each species and calculated variable importance. We found that Canopy Structure variables were, on average at our finest resolution of 250-m, the second most important group (32.5%) of predictor variables after Climate variables (35.3%). Canopy Structure variables were most important for predicting probability of occurrence of birds associated with Conifer forest habitat. Regarding spatial analysis scale, we found that finer-scale models more frequently performed better than coarser-scale models, and the importance of Canopy Structure variables was greater at finer spatial resolutions. Overall, GEDI Canopy Structure variables improved SDM performance for at least one spatial resolution for 19 of 25 species and thus show promise for improving models of bird species occurrence and mapping potential habitat.

ACS Style

Patrick Burns; Matthew Clark; Leonardo Salas; Steven Hancock; David Leland; Patrick Jantz; Ralph Dubayah; Scott J Goetz. Incorporating canopy structure from simulated GEDI lidar into bird species distribution models. Environmental Research Letters 2020, 15, 095002 .

AMA Style

Patrick Burns, Matthew Clark, Leonardo Salas, Steven Hancock, David Leland, Patrick Jantz, Ralph Dubayah, Scott J Goetz. Incorporating canopy structure from simulated GEDI lidar into bird species distribution models. Environmental Research Letters. 2020; 15 (9):095002.

Chicago/Turabian Style

Patrick Burns; Matthew Clark; Leonardo Salas; Steven Hancock; David Leland; Patrick Jantz; Ralph Dubayah; Scott J Goetz. 2020. "Incorporating canopy structure from simulated GEDI lidar into bird species distribution models." Environmental Research Letters 15, no. 9: 095002.

Journal article
Published: 27 February 2019 in Earth and Space Science
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NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6oS to 51.6oN) maps of forest structure and above‐ground biomass density (AGBD) during its two year mission. GEDI uses a waveform simulator for calibration of algorithms and assessing mission accuracy. This paper implements a waveform simulator, using the method proposed in Blair and Hofton (1999), and builds upon that work by adding instrument noise and by validating simulated waveforms across a range of forest types, airborne laser scanning (ALS) instruments and survey configurations. The simulator was validated by comparing waveform metrics derived from simulated waveforms against those derived from observed large‐footprint, full‐waveform lidar data from NASA's airborne Land, Vegetation, and Ice Sensor (LVIS). The simulator was found to produce waveform metrics with a mean bias of less than 0.22 m and a root mean square error of less than 5.7 m, as long as the ALS data had sufficient pulse density. The minimum pulse density required depended upon the instrument. Measurement errors due to instrument noise predicted by the simulator were within 1.5 m of those from observed waveforms and 70‐85% of variance in measurement error was explained. Changing the ALS survey configuration had no significant impact on simulated metrics, suggesting that the ALS pulse density is a sufficient metric of simulator accuracy across the range of conditions and instruments tested. These results give confidence in the use of the simulator for the pre‐launch calibration and performance assessment of the GEDI mission.

ACS Style

Steven Hancock; John Armston; Michelle Hofton; Xiaoli Sun; Hao Tang; Laura I. Duncanson; James R. Kellner; Ralph Dubayah. The GEDI Simulator: A Large‐Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions. Earth and Space Science 2019, 6, 294 -310.

AMA Style

Steven Hancock, John Armston, Michelle Hofton, Xiaoli Sun, Hao Tang, Laura I. Duncanson, James R. Kellner, Ralph Dubayah. The GEDI Simulator: A Large‐Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions. Earth and Space Science. 2019; 6 (2):294-310.

Chicago/Turabian Style

Steven Hancock; John Armston; Michelle Hofton; Xiaoli Sun; Hao Tang; Laura I. Duncanson; James R. Kellner; Ralph Dubayah. 2019. "The GEDI Simulator: A Large‐Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions." Earth and Space Science 6, no. 2: 294-310.

Research article
Published: 18 April 2017 in Methods in Ecology and Evolution
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Urban greenspace has a major impact on human health and quality of life, and thus the way in which such green infrastructure is constructed, managed and maintained is of critical importance. A range of studies have demonstrated the relationship between the areal coverage and distribution of vegetation and the provision of multiple urban ecosystem services. It is not known how sensitive findings are to the spatial resolution of the underlying data relative to the grain size of urban land cover heterogeneity. Moreover, little is known about the three‐dimensional (3D) structure of urban vegetation and delivery of services, and addressing such questions is limited by the availability of data describing canopy structure from the tree tops to the ground. Waveform airborne laser scanning (lidar) offers a new way of capturing 3D data describing vegetation structure. We generated voxels (volumetric pixels) from waveform lidar (1·5 m resolution), differentiated vegetation layers using height as a determinant, and computed statistics on surface cover, volume and volume density per stratum. We then used a range of widely available remote sensing products with varying spatial resolution (1 to 100 m) to map the same greenspace, and compared results to those from the waveform lidar survey. We focused on data from three urban zones in the UK with distinct patterns of vegetation cover. We found −3%, +7·5% and +26·1% differences in green surface cover compared with, respectively, town planning maps (<10 m resolution), national land cover maps (25 m) and European land cover maps (100 m). There were differences of −59·1%, +12·4% and −2·4% in tree cover compared with global (30 m resolution), European (25 m) and national (1 m) estimates. Waveform lidar captured sub‐canopy structure and detected empty spaces in the understorey which contributed a 16% bias in the total green volume derived from non‐waveform lidar observations. We conclude that waveform lidar has a key role to play in estimating important quantitative metrics of urban green infrastructure, which is important because urban greenspace is highly fragmented and shows high levels of spatial and volumetric heterogeneity.

ACS Style

Stefano Casalegno; Karen Anderson; Steven Hancock; Kevin J. Gaston. Improving models of urban greenspace: from vegetation surface cover to volumetric survey, using waveform laser scanning. Methods in Ecology and Evolution 2017, 8, 1443 -1452.

AMA Style

Stefano Casalegno, Karen Anderson, Steven Hancock, Kevin J. Gaston. Improving models of urban greenspace: from vegetation surface cover to volumetric survey, using waveform laser scanning. Methods in Ecology and Evolution. 2017; 8 (11):1443-1452.

Chicago/Turabian Style

Stefano Casalegno; Karen Anderson; Steven Hancock; Kevin J. Gaston. 2017. "Improving models of urban greenspace: from vegetation surface cover to volumetric survey, using waveform laser scanning." Methods in Ecology and Evolution 8, no. 11: 1443-1452.

Journal article
Published: 06 April 2017 in Scientific Reports
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The movements of organisms and the resultant flows of ecosystem services are strongly shaped by landscape connectivity. Studies of urban ecosystems have relied on two-dimensional (2D) measures of greenspace structure to calculate connectivity. It is now possible to explore three-dimensional (3D) connectivity in urban vegetation using waveform lidar technology that measures the full 3D structure of the canopy. Making use of this technology, here we evaluate urban greenspace 3D connectivity, taking into account the full vertical stratification of the vegetation. Using three towns in southern England, UK, all with varying greenspace structures, we describe and compare the structural and functional connectivity using both traditional 2D greenspace models and waveform lidar-generated vegetation strata (namely, grass, shrubs and trees). Measures of connectivity derived from 3D greenspace are lower than those derived from 2D models, as the latter assumes that all vertical vegetation strata are connected, which is rarely true. Fragmented landscapes that have more complex 3D vegetation showed greater functional connectivity and we found highest 2D to 3D functional connectivity biases for short dispersal capacities of organisms (6 m to 16 m). These findings are particularly pertinent in urban systems where the distribution of greenspace is critical for delivery of ecosystem services.

ACS Style

Stefano Casalegno; Karen Anderson; Daniel T. C. Cox; Steven Hancock; Kevin J. Gaston. Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar. Scientific Reports 2017, 7, 45571 .

AMA Style

Stefano Casalegno, Karen Anderson, Daniel T. C. Cox, Steven Hancock, Kevin J. Gaston. Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar. Scientific Reports. 2017; 7 (1):45571.

Chicago/Turabian Style

Stefano Casalegno; Karen Anderson; Daniel T. C. Cox; Steven Hancock; Kevin J. Gaston. 2017. "Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar." Scientific Reports 7, no. 1: 45571.

Journal article
Published: 15 March 2017 in IEEE Transactions on Geoscience and Remote Sensing
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A new generation of multiwavelength lidars offers the potential to measure the structure and biochemistry of vegetation simultaneously, using range resolved spectral indices to overcome the confounding effects in passive optical measurements. However, the reflectance of leaves depends on the angle of incidence, and if this dependence varies between wavelengths, the resulting spectral indices will also vary with the angle of incidence, complicating their use in separating structural and biochemical effects in vegetation canopies. The Salford Advanced Laser Canopy Analyser (SALCA) dual-wavelength terrestrial laser scanner was used to measure the angular dependence of reflectance for a range of leaves at the wavelengths used by the new generation of multiwavelength lidars, 1063 and 1545 nm, as used by SALCA, DWEL, and the Optech Titan. The influence of the angle of incidence on the normalized difference index (NDI) of these wavelengths was also assessed. The reflectance at both wavelengths depended on the angle of incidence and could be well modelled as a cosine. The change in the NDI with the leaf angle of incidence was small compared with the observed difference in the NDI between fresh and dry leaves and between leaf and bark. Therefore, it is concluded that angular effects will not significantly impact leaf moisture retrievals or prevent leaf/bark separation for the wavelengths used in the new generation of 1063- and 1545-nm multiwavelength lidars.

ACS Style

Steven Hancock; Rachel Gaulton; F. Mark Danson. Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation. IEEE Transactions on Geoscience and Remote Sensing 2017, 55, 3084 -3090.

AMA Style

Steven Hancock, Rachel Gaulton, F. Mark Danson. Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation. IEEE Transactions on Geoscience and Remote Sensing. 2017; 55 (6):3084-3090.

Chicago/Turabian Style

Steven Hancock; Rachel Gaulton; F. Mark Danson. 2017. "Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation." IEEE Transactions on Geoscience and Remote Sensing 55, no. 6: 3084-3090.

Journal article
Published: 09 February 2017 in International Journal of Environmental Research and Public Health
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Exposure to nature provides a wide range of health benefits. A significant proportion of these are delivered close to home, because this offers an immediate and easily accessible opportunity for people to experience nature. However, there is limited information to guide recommendations on its management and appropriate use. We apply a nature dose-response framework to quantify the simultaneous association between exposure to nearby nature and multiple health benefits. We surveyed ca. 1000 respondents in Southern England, UK, to determine relationships between (a) nature dose type, that is the frequency and duration (time spent in private green space) and intensity (quantity of neighbourhood vegetation cover) of nature exposure and (b) health outcomes, including mental, physical and social health, physical behaviour and nature orientation. We then modelled dose-response relationships between dose type and self-reported depression. We demonstrate positive relationships between nature dose and mental and social health, increased physical activity and nature orientation. Dose-response analysis showed that lower levels of depression were associated with minimum thresholds of weekly nature dose. Nearby nature is associated with quantifiable health benefits, with potential for lowering the human and financial costs of ill health. Dose-response analysis has the potential to guide minimum and optimum recommendations on the management and use of nearby nature for preventative healthcare.

ACS Style

Daniel Cox; Danielle F. Shanahan; Hannah L. Hudson; Richard A. Fuller; Karen Anderson; Steven Hancock; Kevin J. Gaston. Doses of Nearby Nature Simultaneously Associated with Multiple Health Benefits. International Journal of Environmental Research and Public Health 2017, 14, 172 .

AMA Style

Daniel Cox, Danielle F. Shanahan, Hannah L. Hudson, Richard A. Fuller, Karen Anderson, Steven Hancock, Kevin J. Gaston. Doses of Nearby Nature Simultaneously Associated with Multiple Health Benefits. International Journal of Environmental Research and Public Health. 2017; 14 (2):172.

Chicago/Turabian Style

Daniel Cox; Danielle F. Shanahan; Hannah L. Hudson; Richard A. Fuller; Karen Anderson; Steven Hancock; Kevin J. Gaston. 2017. "Doses of Nearby Nature Simultaneously Associated with Multiple Health Benefits." International Journal of Environmental Research and Public Health 14, no. 2: 172.

Journal article
Published: 13 January 2017 in BioScience
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Experiences of nature provide many mental-health benefits, particularly for people living in urban areas. The natural characteristics of city residents’ neighborhoods are likely to be crucial determinants of the daily nature dose that they receive; however, which characteristics are important remains unclear. One possibility is that the greatest benefits are provided by characteristics that are most visible during the day and so most likely to be experienced by people. We demonstrate that of five neighborhood nature characteristics tested, vegetation cover and afternoon bird abundances were positively associated with a lower prevalence of depression, anxiety, and stress. Furthermore, dose–response modeling shows a threshold response at which the population prevalence of mental-health issues is significantly lower beyond minimum limits of neighborhood vegetation cover (depression more than 20% cover, anxiety more than 30% cover, stress more than 20% cover). Our findings demonstrate quantifiable associations of mental health with the characteristics of nearby nature that people actually experience.

ACS Style

Daniel T. C. Cox; Danielle F. Shanahan; Hannah L. Hudson; Kate E Plummer; Gavin M. Siriwardena; Richard Fuller; Karen Anderson; Steven Hancock; Kevin J. Gaston. Doses of Neighborhood Nature: The Benefits for Mental Health of Living with Nature. BioScience 2017, 1 .

AMA Style

Daniel T. C. Cox, Danielle F. Shanahan, Hannah L. Hudson, Kate E Plummer, Gavin M. Siriwardena, Richard Fuller, Karen Anderson, Steven Hancock, Kevin J. Gaston. Doses of Neighborhood Nature: The Benefits for Mental Health of Living with Nature. BioScience. 2017; ():1.

Chicago/Turabian Style

Daniel T. C. Cox; Danielle F. Shanahan; Hannah L. Hudson; Kate E Plummer; Gavin M. Siriwardena; Richard Fuller; Karen Anderson; Steven Hancock; Kevin J. Gaston. 2017. "Doses of Neighborhood Nature: The Benefits for Mental Health of Living with Nature." BioScience , no. : 1.

Journal article
Published: 01 January 2017 in Landscape and Urban Planning
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Urban environments are expanding globally, and by 2050 nearly 70% of the world’s population will live in towns and cities, where opportunities to experience nature are more limited than in rural areas. This transition could have important implications for health and wellbeing given the diversity of benefits that nature delivers. Despite these issues, there is a lack of information on whether or how the experience of nature changes as green space becomes less available. We explore this question for residents of two case study cities of varying urban designs, sprawling (Brisbane, Australia) and compact (three English towns, U.K). Second, we examine how people’s feelings of connection to nature (measured using the Nature Relatedness scale) vary across this same gradient of nature availability. Despite climatic and cultural differences we found substantial similarities between the two locations. Lower levels of neighbourhood tree cover were associated with a reduced frequency of visits to private and public green spaces, and a similar pattern was found for the duration of time spent in private and public green spaces for Brisbane. Residents of both urban areas showed similar levels of nature relatedness, and there was a weak but positive association between tree cover and Nature Relatedness. These results suggest that regardless of the style of urban design, maintaining the availability of nature close to home is a critical step to protect people’s experiences of nature and their desire to seek out those experiences

ACS Style

D.F. Shanahan; D.T.C. Cox; Richard Fuller; Steven Hancock; Brenda Lin; Karen Anderson; R. Bush; Kevin J. Gaston. Variation in experiences of nature across gradients of tree cover in compact and sprawling cities. Landscape and Urban Planning 2017, 157, 231 -238.

AMA Style

D.F. Shanahan, D.T.C. Cox, Richard Fuller, Steven Hancock, Brenda Lin, Karen Anderson, R. Bush, Kevin J. Gaston. Variation in experiences of nature across gradients of tree cover in compact and sprawling cities. Landscape and Urban Planning. 2017; 157 ():231-238.

Chicago/Turabian Style

D.F. Shanahan; D.T.C. Cox; Richard Fuller; Steven Hancock; Brenda Lin; Karen Anderson; R. Bush; Kevin J. Gaston. 2017. "Variation in experiences of nature across gradients of tree cover in compact and sprawling cities." Landscape and Urban Planning 157, no. : 231-238.

Journal article
Published: 23 November 2016 in Scientific Reports
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Private gardens provide vital opportunities for people to interact with nature. The most popular form of interaction is through garden bird feeding. Understanding how landscape features and seasons determine patterns of movement of feeder-using songbirds is key to maximising the well-being benefits they provide. To determine these patterns we established three networks of automated data loggers along a gradient of greenspace fragmentation. Over a 12-month period we tracked 452 tagged blue tits Cyantistes caeruleus and great tits Parus major moving between feeder pairs 9,848 times, to address two questions: (i) Do urban features within different forms, and season, influence structural (presence-absence of connections between feeders by birds) and functional (frequency of these connections) connectivity? (ii) Are there general patterns of structural and functional connectivity across forms? Vegetation cover increased connectivity in all three networks, whereas the presence of road gaps negatively affected functional but not structural connectivity. Across networks structural connectivity was lowest in the summer when birds maintain breeding territories, however patterns of functional connectivity appeared to vary with habitat fragmentation. Using empirical data this study shows how key urban features and season influence movement of feeder-using songbirds, and we provide evidence that this is related to greenspace fragmentation.

ACS Style

Daniel T. C. Cox; Richard Inger; Steven Hancock; Karen Anderson; Kevin J. Gaston. Movement of feeder-using songbirds: the influence of urban features. Scientific Reports 2016, 6, 37669 .

AMA Style

Daniel T. C. Cox, Richard Inger, Steven Hancock, Karen Anderson, Kevin J. Gaston. Movement of feeder-using songbirds: the influence of urban features. Scientific Reports. 2016; 6 (1):37669.

Chicago/Turabian Style

Daniel T. C. Cox; Richard Inger; Steven Hancock; Karen Anderson; Kevin J. Gaston. 2016. "Movement of feeder-using songbirds: the influence of urban features." Scientific Reports 6, no. 1: 37669.

Journal article
Published: 11 November 2016 in Remote Sensing of Environment
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Vegetation structure controls habitat availability, ecosystem services, weather, climate and microclimate, but current landscape scale vegetation maps have lacked details of understorey vegetation and within-canopy structure at resolutions finer than a few tens of metres. In this paper, a novel signal processing method is used to correctly measure 3D voxelised vegetation cover from full-waveform ALS data at 1.5 m horizontal and 50 cm vertical resolution, including understorey vegetation and within-canopy structure. A new method for calibrating and validating the instrument specific ALS processing using high resolution TLS data is also presented and used to calibrate and validate the ALS derived data products over a wide range of land cover types within a heterogeneous urban area, including woodland, gardens and streets. This showed the method to accurately retrieve voxelised canopy cover maps with less than 0.4% of voxels containing false negatives, 10% of voxels containing false positives and a canopy cover accuracy within voxels of 24%. The method was applied across 100 km2 and the resulting structure maps were compared to the more widely used discrete return ALS and Gaussian decomposed waveform ALS data products. These products were found to give little information on the within-canopy structure and so are only capable of deriving coarse resolution, plot-scale structure metrics. The detailed 3D canopy maps derived from the new method allow landscape scale ecosystem processes to be examined in more detail than has previously been possible, and the new method reveals details about the canopy understorey, creating opportunities for ecological investigations. The calibration method can be applied to any waveform ALS instrument and processing method. All code used in this paper is freely available online through bitbucket (https://bitbucket.org/StevenHancock/voxel_lidar).

ACS Style

Steven Hancock; Karen Anderson; Mathias Disney; Kevin J. Gaston. Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar. Remote Sensing of Environment 2016, 188, 37 -50.

AMA Style

Steven Hancock, Karen Anderson, Mathias Disney, Kevin J. Gaston. Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar. Remote Sensing of Environment. 2016; 188 ():37-50.

Chicago/Turabian Style

Steven Hancock; Karen Anderson; Mathias Disney; Kevin J. Gaston. 2016. "Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar." Remote Sensing of Environment 188, no. : 37-50.

Research article
Published: 04 May 2016 in PLOS ONE
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This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding ‘scheme blocks’ framework was used to build the application (‘app’), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing–a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for ‘UAV toolkit’ (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).

ACS Style

K. Anderson; Amber Griffiths; L. Debell; Steven Hancock; James Duffy; J. D. Shutler; W. J. Reinhardt. A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones. PLOS ONE 2016, 11, e0151564 -e0151564.

AMA Style

K. Anderson, Amber Griffiths, L. Debell, Steven Hancock, James Duffy, J. D. Shutler, W. J. Reinhardt. A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones. PLOS ONE. 2016; 11 (5):e0151564-e0151564.

Chicago/Turabian Style

K. Anderson; Amber Griffiths; L. Debell; Steven Hancock; James Duffy; J. D. Shutler; W. J. Reinhardt. 2016. "A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones." PLOS ONE 11, no. 5: e0151564-e0151564.

Journal article
Published: 19 January 2016 in Landscape Ecology
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Context Urbanisation places increasing stress on ecosystem services; however existing methods and data for testing relationships between service delivery and urban landscapes remain imprecise and uncertain. Unknown impacts of scale are among several factors that complicate research. This study models ecosystem services in the urban area comprising the towns of Milton Keynes, Bedford and Luton which together represent a wide range of the urban forms present in the UK. Objectives The objectives of this study were to test (1) the sensitivity of ecosystem service model outputs to the spatial resolution of input data, and (2) whether any resultant scale dependency is constant across different ecosystem services and model approaches (e.g. stock- versus flow-based). Methods Carbon storage, sediment erosion, and pollination were modelled with the InVEST framework using input data representative of common coarse (25 m) and fine (5 m) spatial resolutions. Results Fine scale analysis generated higher estimates of total carbon storage (9.32 vs. 7.17 kg m−2) and much lower potential sediment erosion estimates (6.4 vs. 18.1 Mg km−2 year−1) than analyses conducted at coarser resolutions; however coarse-scale analysis estimated more abundant pollination service provision. Conclusions Scale sensitivities depend on the type of service being modelled; stock estimates (e.g. carbon storage) are most sensitive to aggregation across scales, dynamic flow models (e.g. sediment erosion) are most sensitive to spatial resolution, and ecological process models involving both stocks and dynamics (e.g. pollination) are sensitive to both. Care must be taken to select model data appropriate to the scale of inquiry

ACS Style

Darren R. Grafius; Ron Corstanje; Philip H. Warren; Karl L. Evans; Steven Hancock; Jim Harris. The impact of land use/land cover scale on modelling urban ecosystem services. Landscape Ecology 2016, 31, 1509 -1522.

AMA Style

Darren R. Grafius, Ron Corstanje, Philip H. Warren, Karl L. Evans, Steven Hancock, Jim Harris. The impact of land use/land cover scale on modelling urban ecosystem services. Landscape Ecology. 2016; 31 (7):1509-1522.

Chicago/Turabian Style

Darren R. Grafius; Ron Corstanje; Philip H. Warren; Karl L. Evans; Steven Hancock; Jim Harris. 2016. "The impact of land use/land cover scale on modelling urban ecosystem services." Landscape Ecology 31, no. 7: 1509-1522.

Original articles
Published: 14 January 2016 in Remote Sensing Letters
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The Salford Advanced Laser Canopy Analyser (SALCA) is a unique dual-wavelength full-waveform terrestrial laser scanner (TLS) designed to measure forest canopies. This article has two principle objectives, first to present the detailed analysis of the radiometric properties of the SALCA instrument, and second, to propose a novel method to calibrate the recorded intensity to apparent reflectance using a neural network approach. The results demonstrate the complexity of the radiometric response to range, reflectance, and laser temperature and show that neural networks can accurately estimate apparent reflectance for both wavelengths (a root mean square error (RMSE) of 0.072 and 0.069 for the 1063 and 1545 nm wavelengths, respectively). The trained network can then be used to calibrate full hemispherical scans in a forest environment, providing new opportunities for quantitative data analysis.

ACS Style

Lucy A. Schofield; Francis Danson; Neil Entwistle; Rachel Gaulton; Steven Hancock. Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks. Remote Sensing Letters 2016, 7, 299 -308.

AMA Style

Lucy A. Schofield, Francis Danson, Neil Entwistle, Rachel Gaulton, Steven Hancock. Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks. Remote Sensing Letters. 2016; 7 (4):299-308.

Chicago/Turabian Style

Lucy A. Schofield; Francis Danson; Neil Entwistle; Rachel Gaulton; Steven Hancock. 2016. "Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks." Remote Sensing Letters 7, no. 4: 299-308.

Interdisciplinary perspectives
Published: 29 November 2015 in Remote Sensing in Ecology and Conservation
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Light Detection and Ranging (LiDAR) systems are frequently used in ecological studies to measure vegetation canopy structure. Waveform LiDAR systems offer new capabilities for vegetation modelling by measuring the time‐varying signal of the laser pulse as it illuminates different elements of the canopy, providing an opportunity to describe the 3D structure of vegetation canopies more fully. This article provides a comparison between waveform airborne laser scanning (ALS) data and discrete return ALS data, using terrestrial laser scanning (TLS) data as an independent validation. With reference to two urban landscape typologies, we demonstrate that discrete return ALS data provided more biased and less consistent measurements of woodland canopy height (in a 100% tree covered plot, height underestimation bias = 0.82 m; sd = 1.78 m) than waveform ALS data (height overestimation bias = −0.65 m; sd = 1.45 m). The same biases were found in suburban data (in a plot consisting of 100% hard targets e.g. roads and pavements), but discrete return ALS were more consistent here than waveform data (sd = 0.57 m compared to waveform sd = 0.76 m). Discrete return ALS data performed poorly in describing the canopy understorey, compared to waveform data. Our results also highlighted errors in discrete return ALS intensity, which were not present with waveform data. Waveform ALS data therefore offer an improved method for measuring the three‐dimensional structure of vegetation systems, but carry a higher data processing cost. New toolkits for analysing waveform data will expedite future analysis and allow ecologists to exploit the information content of waveform LiDAR.

ACS Style

Karen Anderson; Steven L Hancock; Mathias Disney; Kevin J. Gaston. Is waveform worth it? A comparison of Li DAR approaches for vegetation and landscape characterization. Remote Sensing in Ecology and Conservation 2015, 2, 5 -15.

AMA Style

Karen Anderson, Steven L Hancock, Mathias Disney, Kevin J. Gaston. Is waveform worth it? A comparison of Li DAR approaches for vegetation and landscape characterization. Remote Sensing in Ecology and Conservation. 2015; 2 (1):5-15.

Chicago/Turabian Style

Karen Anderson; Steven L Hancock; Mathias Disney; Kevin J. Gaston. 2015. "Is waveform worth it? A comparison of Li DAR approaches for vegetation and landscape characterization." Remote Sensing in Ecology and Conservation 2, no. 1: 5-15.

Journal article
Published: 01 July 2015 in Remote Sensing of Environment
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Full waveform lidar has a unique capability to characterise vegetation in more detail than any other practical method. The reflectance, calculated from the energy of lidar returns, is a key parameter for a wide range of applications and so it is vital to extract it accurately. Fifteen separate methods have been proposed to extract return energy (the amount of light backscattered from a target), ranging from simple to mathematically complex, but the relative accuracies have not yet been assessed. This paper uses a simulator to compare all methods over a wide range of targets and lidar system parameters. For hard targets the simplest methods (windowed sum, peak and quadratic) gave the most consistent estimates. They did not have high accuracies, but low standard deviations show that they could be calibrated to give accurate energy. This may be why some commercial lidar developers use them, where the primary interest is in surveying solid objects. However, simulations showed that these methods are not appropriate over vegetation. The widely used Gaussian fitting performed well over hard targets (0.24% root mean square error, RMSE), as did the sum and spline methods (0.30% RMSE). Over vegetation, for large footprint (15m) systems, Gaussian fitting performed the best (12.2% RMSE) followed closely by the sum and spline (both 12.7% RMSE). For smaller footprints (33cm and 1cm) over vegetation, the relative accuracies were reversed (0.56% RMSE for the sum and spline and 1.37% for Gaussian fitting). Gaussian fitting required heavy smoothing (convolution with an 8m Gaussian) whereas none was needed for the sum and spline. These simpler methods were also more robust to noise and far less computationally expensive than Gaussian fitting. Therefore it was concluded that the sum and spline were the most accurate for extracting return energy from waveform lidar over vegetation, except for large footprint (15m), where Gaussian fitting was slightly more accurate. These results suggest that small footprint (≪15m) lidar systems that use Gaussian fitting or proprietary algorithms may report inaccurate energies, and thus reflectances, over vegetation. In addition the effect of system pulse length, sampling interval and noise on accuracy for different targets was assessed, which has implications for sensor design

ACS Style

Steven Hancock; John Armston; Zhan Li; Rachel Gaulton; Philip Lewis; Mathias Disney; F. Mark Danson; Alan Strahler; Crystal Schaaf; Karen Anderson; Kevin J. Gaston. Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy. Remote Sensing of Environment 2015, 164, 208 -224.

AMA Style

Steven Hancock, John Armston, Zhan Li, Rachel Gaulton, Philip Lewis, Mathias Disney, F. Mark Danson, Alan Strahler, Crystal Schaaf, Karen Anderson, Kevin J. Gaston. Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy. Remote Sensing of Environment. 2015; 164 ():208-224.

Chicago/Turabian Style

Steven Hancock; John Armston; Zhan Li; Rachel Gaulton; Philip Lewis; Mathias Disney; F. Mark Danson; Alan Strahler; Crystal Schaaf; Karen Anderson; Kevin J. Gaston. 2015. "Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy." Remote Sensing of Environment 164, no. : 208-224.

Research article
Published: 06 February 2014 in Agricultural and Forest Meteorology
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Previous studies have shown that terrestrial lidar is capable of characterising forest canopies but suggest that lidar underestimates gap fraction compared to hemispherical camera photography. This paper performs a detailed comparison of lidar to camera-derived gap fractions over a range of forest structures (in snow affected areas) and reasons for any disagreements are analysed. A terrestrial laser scanner (Leica C10 first return system) was taken to Abisko in Northern Sweden (sparse birch forests) and Sodankylä in Finland (spruce and pine forests) where five plots of varying density were scanned at each (though one Abisko plot was rejected due to geolocation issues). Traditional hemispherical photographs were taken and gap fraction estimates compared. It is concluded that, for the sites tested, the reported underestimates in gap fraction can be removed by taking partial hits into account using the return intensity. The scan density used (5–8 scans per 20 m by 20 m plot) was sufficient to ensure that occlusion of the laser beam was not significant. The choice of sampling density of the lidar data is important, but over a certain sampling density the gap fraction estimates become insensitive to further change. The lidar gap fractions altered by around 3–8% when all subjective parameters were adjusted over their complete range. The choice of manual threshold for the hemispherical photographs is found to have a large effect (up to 17% range in gap fraction between three operators). Therefore we propose that, as long as a site has been covered by sufficient scan positions and the data sampled at high enough resolution, the lidar gap fraction estimates are more stable than those derived from a camera and avoid issues with variable illumination. In addition the lidar allows the determination of gap fraction at every point within a plot rather than just where hemispherical photographs were taken, giving a much fuller picture of the canopy. The relative difference between TLS (taking intensity into account) and camera derived gap fraction was 0.7% for Abisko and −2.8% for Sodankylä with relative root mean square errors (RMSEs) of 6.9% and 9.8% respectively, less than the variation within TLS and camera estimates and so bias has been removed.

ACS Style

Steven Hancock; Richard Essery; Tim Reid; Joël Carle; Robert Baxter; Nick Rutter; Brian Huntley. Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations. Agricultural and Forest Meteorology 2014, 189-190, 105 -114.

AMA Style

Steven Hancock, Richard Essery, Tim Reid, Joël Carle, Robert Baxter, Nick Rutter, Brian Huntley. Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations. Agricultural and Forest Meteorology. 2014; 189-190 ():105-114.

Chicago/Turabian Style

Steven Hancock; Richard Essery; Tim Reid; Joël Carle; Robert Baxter; Nick Rutter; Brian Huntley. 2014. "Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations." Agricultural and Forest Meteorology 189-190, no. : 105-114.

Journal article
Published: 15 January 2014 in Journal of Climate
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Snow exerts a strong influence on weather and climate. Accurate representation of snow processes within models is needed to ensure accurate predictions. Snow processes are known to be a weakness of land surface models (LSMs), and studies suggest that more complex snow physics is needed to avoid early melt. In this study the European Space Agency (ESA)’s Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent and NASA’s “MOD10C1” snow cover products are used to assess the accuracy of snow processes within the Joint U.K. Land Environment Simulator (JULES). JULES is run “offline” from a general circulation model and so is driven by meteorological reanalysis datasets: “Princeton,” Water and Global Change–Global Precipitation Climatology Centre (WATCH–GPCC), and WATCH–Climatic Research Unit (CRU). This reveals that when the model achieves the correct peak accumulation, snow does not melt early. However, generally snow does melt early because peak accumulation is too low. Examination of the meteorological reanalysis data shows that not enough snow falls to achieve observed peak accumulations. Thus, the earlier studies’ conclusions may be as a result of weaknesses in the driving data, rather than in model snow processes. These reanalysis products “bias correct” precipitation using observed gauge data with an undercatch correction, overriding the benefit of any other datasets used in their creation. This paper argues that using gauge data to bias-correct reanalysis data is not appropriate for snow-affected regions during winter and can lead to confusion when evaluating model processes.

ACS Style

Steven Hancock; Brian Huntley; Richard Ellis; Robert Baxter. Biases in Reanalysis Snowfall Found by Comparing the JULES Land Surface Model to GlobSnow. Journal of Climate 2014, 27, 624 -632.

AMA Style

Steven Hancock, Brian Huntley, Richard Ellis, Robert Baxter. Biases in Reanalysis Snowfall Found by Comparing the JULES Land Surface Model to GlobSnow. Journal of Climate. 2014; 27 (2):624-632.

Chicago/Turabian Style

Steven Hancock; Brian Huntley; Richard Ellis; Robert Baxter. 2014. "Biases in Reanalysis Snowfall Found by Comparing the JULES Land Surface Model to GlobSnow." Journal of Climate 27, no. 2: 624-632.

Journal article
Published: 14 January 2014 in Agricultural and Forest Meteorology
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Leafless deciduous canopies in boreal regions affect the energy available for snowmelt and reduce overall surface albedo during winter, thereby exerting a strong influence on weather and climate. In this work, ground-based measurements of leafless canopy structure, including hemispherical photography, terrestrial laser scanning (TLS) and manual tree surveys were collected at 38 sites in an area of mountain birch forest in northern Sweden in March 2011 and 2012. Photo-derived sky view fraction was strongly inversely correlated (r < −0.9) to the total tree basal area in a 5 m radius around the photo site. To expand findings to wider areas, maps of canopy height for a 5 km × 3 km area were obtained from airborne lidar (ALS) data collected during summer 2005. Canopy heights derived from TLS were used to validate the ALS estimates, and simple models were developed to establish relationships between hemispherical sky view and ALS canopy height (RMSE < 5%). The models and ALS data provide useful methods for estimating canopy radiative transfer and biomass over wide areas of birch forest, despite the relatively low ALS resolution (∼1 return m−2).

ACS Style

T.D. Reid; M. Spencer; B. Huntley; S. Hancock; R.L.H. Essery; J. Carle; R. Holden; R. Baxter; Nick Rutter. Spatial quantification of leafless canopy structure in a boreal birch forest. Agricultural and Forest Meteorology 2014, 188, 1 -12.

AMA Style

T.D. Reid, M. Spencer, B. Huntley, S. Hancock, R.L.H. Essery, J. Carle, R. Holden, R. Baxter, Nick Rutter. Spatial quantification of leafless canopy structure in a boreal birch forest. Agricultural and Forest Meteorology. 2014; 188 ():1-12.

Chicago/Turabian Style

T.D. Reid; M. Spencer; B. Huntley; S. Hancock; R.L.H. Essery; J. Carle; R. Holden; R. Baxter; Nick Rutter. 2014. "Spatial quantification of leafless canopy structure in a boreal birch forest." Agricultural and Forest Meteorology 188, no. : 1-12.