Steven Hancock

Doses of nearby nature simultaneously associated with multiple health benefits

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.

Quantifying Surface Reflectivity for Spaceborne Lidar via Two Independent Methods

Spaceborne differential absorption lidar has been proposed for accurate measurements of atmospheric CO2 (and surface properties). Lidar instruments typically observe the highest possible surface reflectance due to observing in the retroreflection direction (the so-called ldquohotspotrdquo) where viewed shadow is minimized. The range of observed reflectance will determine instrument dimensions and signal-to-noise ratio, but it is difficult to predict this range globally a priori. Two complementary methods are presented for estimating lidar reflectivity over a range of vegetated surface types. The first method simulates the expected response of a lidar instrument from multiangle multispectral reflectance data. The second method uses detailed 3-D vegetation structural models and Monte Carlo ray tracing to simulate the lidar signal. The simulations are used to validate the first method and assess the impact of possible instrument configurations. Both methods agree well and are robust to error in observations, with predicted lidar reflectivity (at 1570 and 2050 nm here) typically between 10% and 33% higher relative to off-nadir reflectance and ranging from 0.02 to ~ 0.7. We use the 3-D simulations to show that the impact of shifted on-off lidar pulses is not likely to be significant for accuracy of retrieved CO2, and we demonstrate that the 3-D simulation method is a flexible and powerful way of prototyping future spaceborne lidar missions.

Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation

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.

Movement of feeder-using songbirds: the influence of urban features.

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.

Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks

ABSTRACT 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.

A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones

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).

Biases in reanalysis snowfall found by comparing the JULES land surface model to GlobSnow

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 studytheEuropeanSpaceAgency(ESA)’sGlobalSnowMonitoringforClimateResearch (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,theearlierstudies’conclusions maybeasaresultofweaknessesinthedrivingdata,ratherthanin 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 thatusinggaugedatatobias-correctreanalysis dataisnotappropriateforsnow-affectedregionsduringwinter and can lead to confusion when evaluating model processes.

Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar

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.

Covariation in urban birds providing cultural services or disservices and people

We thank M. Evans and M. Gregory for their fieldwork, and J. Harris and R. Corstanje for their advice and logistical support. All authors were supported by the Fragments, Functions, Flows and Urban Ecosystem Services project, NERC grant NE/J015237/1, funded under the NERC Biodiversity and Ecosystem Service Sustainability programme. The authors declare no conflict of interest.

Extracting Tree Heights over Topography with Multi-Spectral Spaceborne Waveform Lidar

It is generally agreed that the optimal footprint size for a spaceborne lidar is 30 m. Over topography such a large footprint can blur the canopy and ground signal together preventing information extraction. Multi-spectral lidar waveforms have been simulated with Monte-Carlo ray tracing over explicit geometric forest models. A method for using multi-spectral waveform lidar to distinguish ground from canopy returns has been tested over a range of ground slopes. The results are promising, with an initial error of +/-5 m for a signal level of only 5,000 photons with noise; an easily achievable figure. The inversion algorithms completely dominate inversion errors for all cases above 10,000 signal photons.