19 results on '"Morton, R. Daniel"'
Search Results
2. LCM2021 – The UK Land Cover Map 2021
- Author
-
Marston, Christopher G., primary, O'Neil, Aneurin W., additional, Morton, R. Daniel, additional, Wood, Claire M., additional, and Rowland, Clare S., additional
- Published
- 2023
- Full Text
- View/download PDF
3. LCM2021 – the UK Land Cover Map 2021.
- Author
-
Marston, Christopher G., O'Neil, Aneurin W., Morton, R. Daniel, Wood, Claire M., and Rowland, Clare S.
- Subjects
LAND cover ,IMAGE recognition (Computer vision) ,ENVIRONMENTAL research ,RANDOM forest algorithms ,SPATIAL resolution - Abstract
Land cover is a key environmental variable, underpinning widespread environmental research and decision making. The UK Centre for Ecology and Hydrology (UKCEH) has provided reliable land cover information since the early 1990s; this supports multiple scientific, government and commercial objectives. Recent advances in computation and satellite data availability have enabled annual UKCEH land cover maps since 2017. Here, we introduce the latest, annual UK Land Cover Map representing 2021 (LCM2021), and we describe its production and validation. LCM2021 methods replicate those of LCM2017 to LCM2020 with minor deviations in cloud-masking processes and training data sourcing to enhance accuracy. LCM2021 is based on the classification of satellite and spatial context data into 21 land cover or habitat classes, from which a product suite is derived. The production of LCM2021 involved three highly automated key stages: pre-processing of input data, image classification and production of the final data products. Google Earth Engine scripts were used to create an input data stack of satellite and context data. A set of training areas was created based on data harvested from historic UKCEH land cover maps. The training data were used to construct a random forest classifier, which yielded classified images. Compiled results were validated against 35 182 reference samples, with correspondence tables indicating variable class accuracy and an overall accuracy of 82.6 % for the 21-class data and 86.5 % at a 10-aggregated-classes level. The UK Land Cover Map product suite includes a set of raster products in various projections, thematic and spatial resolutions (10 m, 25 m and 1 km), and land–parcel or vector products. The data are provided in 21-class (all configurations) and aggregated 10-class (1 km raster products only) versions. All raster products are freely available for academic and non-commercial research. The data for Great Britain (GB) are provided in the British National Grid projection (EPSG: 27700) and the Northern Ireland (NI) data are in the TM75 Irish Grid (EPSG: 29903). Information on how to access the data is given in the "Data availability" section of the paper. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
4. On Models for Assembling Ecological Communities
- Author
-
Morton, R. Daniel, Law, Richard, Pimm, Stuart L., and Drake, James A.
- Published
- 1996
- Full Text
- View/download PDF
5. Permanence and the Assembly of Ecological Communities
- Author
-
Law, Richard and Morton, R. Daniel
- Published
- 1996
- Full Text
- View/download PDF
6. Effective management of ecological resilience – are we there yet?
- Author
-
Spears, Bryan M., Ives, Stephen C., Angeler, David G., Allen, Craig R., Birk, Sebastian, Carvalho, Laurence, Cavers, Stephen, Daunt, Francis, Morton, R. Daniel, Pocock, Michael J. O., Rhodes, Glenn, and Thackeray, Stephen J.
- Published
- 2015
7. The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England
- Author
-
Senapathi, Deepa, Carvalheiro, Luísa G., Biesmeijer, Jacobus C., Dodson, Cassie-Ann, Evans, Rebecca. L., McKerchar, Megan, Morton, R. Daniel, Moss, Ellen D., Roberts, Stuart P. M., Kunin, William E., and Potts, Simon G.
- Published
- 2015
8. LCM2021 1 - The UK Land Cover Map 2021.
- Author
-
Marston, Christopher G., O'Neil, Aneurin W., Morton, R. Daniel, Wood, Claire M., and Rowland, Clare S.
- Subjects
LAND cover ,IMAGE recognition (Computer vision) ,RANDOM forest algorithms ,SPATIAL resolution ,MAPS ,DECISION making - Abstract
Land cover is a key environmental variable, underpinning widespread environmental research and decision making. The UK Centre for Ecology and Hydrology (UKCEH) have provided reliable land cover information since the early 1990's; this supports multiple scientific, government and commercial objectives. Recent advances in computation and satellite data availability have enabled annual UKCEH land cover maps since 2017. Here we introduce the latest, annual UK Land Cover Map, representing 2021 (LCM2021) and describe its production and validation. LCM2021 methods replicate those for LCM2017 to LCM2020 with minor deviations to enhance accuracy. LCM2021 is based on the classification of satellite and spatial context data into 21 land cover/habitat classes, from which a product suite is derived. The production of LCM2021 involved three highly automated key stages: pre-processing of input data, image classification and production of the final data products. Google Earth Engine scripts were used to create an input data stack of satellite and context data. A set of training areas was created, based on data harvested from historic UKCEH land cover maps. The training data were used to construct a Random Forest classifier, which yielded classified images. Compiled results were validated against 35,182 reference samples, with correspondence tables indicating variable class accuracy and an overall accuracy of 82.6 % for the 21-class data and 86.5 % at a 10 aggregated-class level. The UK Land Cover Map product suite includes a set of raster products in various projections, thematic and spatial resolutions (10 m, 25 m and 1 km) and land-parcel/vector product. The data are provided in 21-class (all configurations) and aggregated 10-class versions (1 km raster products only). All raster products are freely available for academic and non commercial research. The data for Great Britain (GB) are provided in the British National Grid projection (https://epsg.io/27700) and the Northern Ireland (NI) data are in the TM75 Irish National Grid (https://epsg.io/29903). Information on how to access the data is given in the Data Availability section of the paper. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
9. Historical nectar assessment reveals the fall and rise of floral resources in Britain
- Author
-
Baude, Mathilde, Kunin, William E., Boatman, Nigel D., Conyers, Simon, Davies, Nancy, Gillespie, Mark A.K., Morton, R. Daniel, Smart, Simon M., and Memmott, Jane
- Subjects
United Kingdom -- Natural history ,Plants -- Forecasts and trends -- Distribution ,Market trend/market analysis ,Company distribution practices ,Environmental issues ,Science and technology ,Zoology and wildlife conservation - Abstract
There is considerable concern over declines in insect pollinator communities and potential impacts on the pollination of crops and wildflowers (1-4). Among the multiple pressures facing pollinators (2-4), decreasing floral [...]
- Published
- 2016
10. Landscape-scale drivers of pollinator communities may depend on land-use configuration
- Author
-
Gillespie, Mark A. K., primary, Baude, Mathilde, additional, Biesmeijer, Jacobus, additional, Boatman, Nigel, additional, Budge, Giles E., additional, Crowe, Andrew, additional, Davies, Nancy, additional, Evans, Rebecca, additional, Memmott, Jane, additional, Morton, R. Daniel, additional, Moss, Ellen, additional, Murphy, Mark, additional, Pietravalle, Stephane, additional, Potts, Simon G., additional, Roberts, Stuart P. M., additional, Rowland, Clare, additional, Senapathi, Deepa, additional, Smart, Simon M., additional, Wood, Claire, additional, and Kunin, William E., additional
- Published
- 2022
- Full Text
- View/download PDF
11. Supplementary material from Landscape-scale drivers of pollinator communities may depend on land-use configuration
- Author
-
Gillespie, Mark A. K., Baude, Mathilde, Biesmeijer, Jacobus, Boatman, Nigel, Budge, Giles E., Crowe, Andrew, Davies, Nancy, Evans, Rebecca, Memmott, Jane, Morton, R. Daniel, Moss, Ellen, Murphy, Mark, Pietravalle, Stephane, Potts, Simon G., Roberts, Stuart P. M., Rowland, Clare, Senapathi, Deepa, Smart, Simon M., Wood, Claire, and Kunin, William E.
- Subjects
Computer Science::Symbolic Computation - Abstract
Map of field sites, full description of derivation of explanatory variables, model coefficients and additional graphs
- Published
- 2022
- Full Text
- View/download PDF
12. Alternative Permanent States of Ecological Communities
- Author
-
Law, Richard and Morton, R. Daniel
- Published
- 1993
- Full Text
- View/download PDF
13. Historical nectar assessment reveals the fall and rise of Britain in bloom
- Author
-
Baude, Mathilde, Kunin, William E., Boatman, Nigel D., Conyers, Simon, Davies, Nancy, Gillespie, Mark A. K., Morton, R. Daniel, Smart, Simon M., and Memmott, Jane
- Subjects
Insecta ,Plant Nectar ,Species Specificity ,Medicago ,Animals ,Biodiversity ,Flowers ,Plants ,Pollination ,Grassland ,Article ,United Kingdom - Abstract
There is considerable concern over declines in insect pollinator communities and potential impacts on the pollination of crops and wildflowers. Among the multiple pressures facing pollinators, decreasing floral resources due to habitat loss and degradation has been suggested as a key contributing factor. However, a lack of quantitative data has hampered testing for historical changes in floral resources. Here we show that overall floral rewards can be estimated at a national scale by combining vegetation surveys and direct nectar measurements. We find evidence for substantial losses in nectar resources in England and Wales between the 1930s and 1970s; however, total nectar provision in Great Britain as a whole had stabilized by 1978, and increased from 1998 to 2007. These findings concur with trends in pollinator diversity, which declined in the mid-twentieth century but stabilized more recently. The diversity of nectar sources declined from 1978 to 1990 and thereafter in some habitats, with four plant species accounting for over 50% of national nectar provision in 2007. Calcareous grassland, broadleaved woodland and neutral grassland are the habitats that produce the greatest amount of nectar per unit area from the most diverse sources, whereas arable land is the poorest with respect to amount of nectar per unit area and diversity of nectar sources. Although agri-environment schemes add resources to arable landscapes, their national contribution is low. Owing to their large area, improved grasslands could add substantially to national nectar provision if they were managed to increase floral resource provision. This national-scale assessment of floral resource provision affords new insights into the links between plant and pollinator declines, and offers considerable opportunities for conservation.
- Published
- 2016
14. A method for the objective selection of landscape-scale\ud study regions and sites at the national level
- Author
-
Gillespie, Mark A. K., Baude, Mathilde, Biesmeijer, Jacobus, Boatman, Nigel, Budge, Giles E., Crowe, Andrew, Memmott, Jane, Morton, R. Daniel, Pietravalle, Stephane, Potts, Simon, Senapathi, Deepa, Smart, Simon M., and Kunin, William E.
- Abstract
1. Ecological processes operating on large spatio-temporal scales are difficult to disentangle with traditional empirical approaches. Alternatively, researchers can take advantage of ‘natural’ experiments, where experimental control is exercised by careful site selection. Recent advances in developing protocols for designing these ‘pseudo-experiments’ commonly do not consider the selection of the focal region and predictor variables are usually restricted to two. Here, we advance this type of site selection protocol to study the impact of multiple landscape scale factors on pollinator abundance and diversity across multiple regions.\ud 2. Using datasets of geographic and ecological variables with national coverage, we applied a novel hierarchical\ud computation approach to select study sites that contrast as much as possible in four key variables, while attempting to maintain regional comparability and national representativeness. There were three main steps to the protocol: (i) selection of six 100 9 100 km2 regions that collectively provided land cover representative of the national land average, (ii) mapping of potential sites into a multivariate space with axes representing four key factors potentially influencing insect pollinator abundance, and (iii) applying a selection algorithm which maximized differences between the four key variables, while controlling for a set of external constraints.\ud 3. Validation data for the site selection metrics were recorded alongside the collection of data on pollinator populations during two field campaigns. While the accuracy of the metric estimates varied, the site selection succeeded in objectively identifying field sites that differed significantly in values for each of the four key variables. Between-variable correlations were also reduced or eliminated, thus facilitating analysis of their separate effects.\ud 4. This study has shown that national datasets can be used to select randomized and replicated field sites objectively within multiple regions and along multiple interacting gradients. Similar protocols could be used for studying a range of alternative research questions related to land use or other spatially explicit environmental variables, and to identify networks of field sites for other countries, regions, drivers and response taxa in a wide range of scenarios.
- Published
- 2017
15. FORUM: Effective management of ecological resilience - are we there yet?
- Author
-
Spears, Bryan M., primary, Ives, Stephen C., additional, Angeler, David G., additional, Allen, Craig R., additional, Birk, Sebastian, additional, Carvalho, Laurence, additional, Cavers, Stephen, additional, Daunt, Francis, additional, Morton, R. Daniel, additional, Pocock, Michael J. O., additional, Rhodes, Glenn, additional, and Thackeray, Stephen J., additional
- Published
- 2015
- Full Text
- View/download PDF
16. Real World Objects in GEOBIA through the Exploitation of Existing Digital Cartography and Image Segmentation
- Author
-
Smith, Geoffrey M., primary and Morton, R. Daniel, additional
- Published
- 2010
- Full Text
- View/download PDF
17. Alternative Permanent States of Ecological Communities
- Author
-
Law, Richard and Morton, R. Daniel
- Published
- 1994
- Full Text
- View/download PDF
18. Evaluating Combinations of Temporally Aggregated Sentinel-1, Sentinel-2 and Landsat 8 for Land Cover Mapping with Google Earth Engine.
- Author
-
Carrasco, Luis, O'Neil, Aneurin W., Morton, R. Daniel, and Rowland, Clare S.
- Subjects
LAND cover ,REMOTE-sensing images ,VEGETATION mapping ,AGGREGATION (Statistics) ,DATA acquisition systems ,CLOUD computing ,TEMPORAL databases - Abstract
Land cover mapping of large areas is challenging due to the significant volume of satellite data to acquire and process, as well as the lack of spatial continuity due to cloud cover. Temporal aggregation—the use of metrics (i.e., mean or median) derived from satellite data over a period of time—is an approach that benefits from recent increases in the frequency of free satellite data acquisition and cloud-computing power. This enables the efficient use of multi-temporal data and the exploitation of cloud-gap filling techniques for land cover mapping. Here, we provide the first formal comparison of the accuracy between land cover maps created with temporal aggregation of Sentinel-1 (S1), Sentinel-2 (S2), and Landsat-8 (L8) data from one-year and test whether this method matches the accuracy of traditional approaches. Thirty-two datasets were created for Wales by applying automated cloud-masking and temporally aggregating data over different time intervals, using Google Earth Engine. Manually processed S2 data was used for comparison using a traditional two-date composite approach. Supervised classifications were created, and their accuracy was assessed using field-based data. Temporal aggregation only matched the accuracy of the traditional two-date composite approach (77.9%) when an optimal combination of optical and radar data was used (76.5%). Combined datasets (S1, S2 or S1, S2, and L8) outperformed single-sensor datasets, while datasets based on spectral indices obtained the lowest levels of accuracy. The analysis of cloud cover showed that to ensure at least one cloud-free pixel per time interval, a maximum of two intervals per year for temporal aggregation were possible with L8, while three or four intervals could be used for S2. This study demonstrates that temporal aggregation is a promising tool for integrating large amounts of data in an efficient way and that it can compensate for the lower quality of automatic image selection and cloud masking. It also shows that combining data from different sensors can improve classification accuracy. However, this study highlights the need for identifying optimal combinations of satellite data and aggregation parameters in order to match the accuracy of manually selected and processed image composites. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
19. Potential and limitation of air pollution mitigation by vegetation and uncertainties of deposition-based evaluations.
- Author
-
Nemitz E, Vieno M, Carnell E, Fitch A, Steadman C, Cryle P, Holland M, Morton RD, Hall J, Mills G, Hayes F, Dickie I, Carruthers D, Fowler D, Reis S, and Jones L
- Subjects
- Air Pollutants analysis, Air Pollutants metabolism, Air Pollution analysis, City Planning, Computer Simulation, Ecosystem, Environmental Monitoring, Humans, Models, Biological, Particulate Matter analysis, Particulate Matter metabolism, Uncertainty, United Kingdom, Air Pollution prevention & control, Trees growth & development, Trees metabolism
- Abstract
The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM
2.5 , 30% (22%) for SO2 , 24% (19%) for NH3 and 15% (13%) for O3 , compared with a desert scenario. By contrast, urban vegetation reduces average urban PM2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO2 are small, and urban tree planting is even forecast to increase urban NO2 and NO x concentrations, due to the chemical interaction with changes in BVOC emissions and O3 , but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost-benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue 'Air quality, past present and future'.- Published
- 2020
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.