The Irish Land Mapping Observatory (ILMO)- Mapping and Monitoring Land Cover, Use and Change

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Resource or Project Abstract

Although EU-wide mapping projects such as CORINE have been undertaken since the 1990s, these have proven inadequate for many national and local scale applications given their spatial resolution, restricted class categories and infrequent updating. The Irish Land Mapping Observatory (ILMO) project is part of Ireland?s response to creating a national land cover map that can be generated on an annual basis, in an objective, efficient, scalable and repeatable manner, drawing primarily on satellite imagery supplemented by ancillary field data, to populate the Ordnance Survey Ireland PRIME2 vector database. Satellite imagery have long been used to discriminate ground features on the basis of their spectral reflectance, but to take into account the dynamics of the Irish vegetation several images per year are required. To achieve this in a frequently cloud covered country, 16-day composite MODIS vegetation index images were used to separate elements on the basis of their phenological cycle. While classification using machine learning methods proved to be very successful for homogenous regions, the Irish landscape is highly fragmented and in both Longford and Sligo, problems were encountered with multiple land covers within the 250x250m pixels. Although methods for sub-pixel content retrieval were explored, illumination and geo-location instabilities contributed a significant error component to the time series and detailed land cover mapping in Ireland using currently available medium (250x250m or coarser) resolution data is not possible. To overcome the limitations on data acquisition imposed on optical data by cloud cover, synthetic aperture radar (SAR) imagery for land cover classification were also investigated. The temporal frequency of acquisitions is lower than for MODIS and only one wavelength is available but the 20m spatial resolution of ASAR and PALSAR data is far superior and imagery is reliably available as SAR wavelengths penetrate through cloud. Machine learning algorithms were used to successfully classify the SAR imagery (this time introducing an extra level of classification for grassland; wet and dry) and these maps, with their higher resolution, were used to populate the Ordnance Survey Ireland PRIME2 database. Maps for 2008 and 1992 were produced for Sligo, with an overall accuracy at 20m resolution of 91%, and of Longford with an accuracy of 96%. These land cover maps were used to estimate greenhouse gas emission/reduction profiles for crop and grasslands, with methods developed to estimate carbon stock changes for the land management and land cover and use transitions, based on existing methodologies and newly derived biomass and soil organic carbon (SOC) activity data. Transitions between improved grassland, semi-improved grassland and scrub sub-categories within the grassland remaining grassland category resulted in a large sink (sequestration) of carbon dioxide, equivalent to 0.3 to 1 t CO2 per ha per year. Based on the outputs of this project, it is recommended that high spatial resolution (better than 30m) satellite data are used for land cover mapping of Ireland, but lower spatial resolution data acquired on a shorter update cycle can be used to inform classification of more infrequently acquired imagery. Using the PRIME2 polygons as well-defined coherent objects enables a seamless land cover map to be generated, however this cannot take sub-object variation, such as strip grazing within a field, into account. Furthermore, the polygon boundaries are not updated annually so discrepancies may arise between the apparent edge of a feature and its appearance on a satellite image. Nevertheless, the combination of raster and object datasets makes it possible to perform a more complete carbon balance estimate for land use and cover transitions between two years in Ireland than is currently available.

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Contact Information for This Resource

Dr. Fiona Cawkwell
University College Cork
Environmental Scientist
Department of Geography, Western Road, University College Cork, Western Road Cork City, Ireland
Telephone: +353 (0)21 4902707
e-mail: f.cawkwell@ucc.ie

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Data, Files, Information Objects Related To This Project Resource

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Attachment Name and Download Link
Att 1    longford_modis.mpk   (1.05 Mb)
Att 2    sligo_modis.mpk   (1.64 Mb)
Att 3    SAR.mpk   (8.91 Mb)

Suggested Citation Information

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Author(s)Cawkwell, F.
Title Of WebsiteSecure Archive For Environmental Research Data
Publication InformationThe Irish Land Mapping Observatory (ILMO)- Mapping and Monitoring Land Cover, Use and Change
Name of OrganisationEnvironmental Protection Agency Ireland
Electronic Address or URL http://erc.epa.ie/safer/resource?id=269e8137-2e2c-11e6-ab63-005056ae0019
Unique Identifier269e8137-2e2c-11e6-ab63-005056ae0019
Date of AccessLast Updated on SAFER: 2017-09-26

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Cawkwell, F.   "The Irish Land Mapping Observatory (ILMO)- Mapping and Monitoring Land Cover, Use and Change". Associated datasets and digitial information objects connected to this resource are available at: Secure Archive For Environmental Research Data (SAFER) managed by Environmental Protection Agency Ireland http://erc.epa.ie/safer/resource?id=269e8137-2e2c-11e6-ab63-005056ae0019 (Last Accessed: 2017-09-26)

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Access Information For This Resource

SAFER-Data Display URL http://erc.epa.ie/safer/iso19115/display?isoID=3127
Resource KeywordsSatellite remote sensing, optical, radar, land cover, grassland, mapping, carbon budget
EPA/ERTDI/STRIVE Project Code2011-CCRP-MS-1.4
EPA/ERTDI/STRIVE Project ThemeLand-use, Soils, and Transport
Resource Availability: Any User Can Download Files From This Resource
Public-Open
Limitations on the use of this ResourceAny attached datasets, data files, or information objects can be downloaded for further use in scientific applications under the condition that the source is properly quoted and cited in published papers, journals, websites, presentations, books, etc. Before downloading, users must agree to the "Conditions of Download and Access" from SAFER-Data. These appear before download. Users of the data should also communicate with the original authors/owners of this resource if they are uncertain about any aspect of the data or information provided before further usage.
Number of Attached Files (Publicly and Openly Available for Download): 3
Project Start Date Sunday 1st April 2012 (01-04-2012)
Earliest Recorded Date within any attached datasets or digital objects Sunday 1st April 2012 (01-04-2012)
Most Recent Recorded Date within any attached datasets or digital objects Saturday 31st May 2014 (31-05-2014)
Published on SAFERThursday 9th June 2016 (09-06-2016)
Date of Last EditWednesday 15th June 2016 at 10:24:38 (15-06-2016)
Datasets or Files Updated On Wednesday 15th June 2016 at 10:22:33 (15-06-2016)

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Geographical and Spatial Information Related To This Resource

Description of Geographical Characteristics of This Project or Dataset
Tthe datasets are landcover maps of counties Sligo and Longford, the two test counties for this project, produced from different satellite imagery (MODIS-optical, and ENVISAT ASAR-radar) over different time periods

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Supplementary Information About This Resource

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Lineage information about this project or dataset
A number of projects had been undertaken by the UCC group on land cover mapping from satellite imagery, giving them a wealth of experience in both optical and radar land cover classification. The EPA have long recognised the need for reliable land cover maps of the country for a variety of policy and administrative purposes, not least carbon accounting, and therefore with the production of the Ordnance Survey PRIME2 vector database, the necessary components were available for the research project.
Supplementary Information
Other collaborators on this project:


Dr Brian Barrett

Department of Geography, University College Cork, Cork, Ireland

E-mail: bbarrett@ucc.ie



Ingmar Nitze

Department of Geography, University College Cork, Cork, Ireland

E-mail: initze@ucc.ie



Stuart Green, Dept. of Agrifood Business and Spatial Analysis

Teagasc Food Research Centre, Ashtown,

Dublin 15

Email: stuart.green@teagasc.ie


Dr Kevin Black

FERS Ltd, 117 East Courtyard, Tullyvale, Cabinteely, Dublin 18

E-mail: kevin.black@ucd.ie


Peter Hallahan

Ordnance Survey Ireland, Phoenix Park, Dublin 8

E-mail: peter.hallahan@osi.ie





The key outputs were the land cover maps for Counties Sligo and Longford, at both the 250m resolution using MODIS imagery and 20m resolution using SAR imagery, as well as a national scale map using the MODIS images. The methods developed proved the benefits offered by the PRIME2 vector database for detailed and consistent land cover mapping, which could be adopted at a national scale. Carbon stock changes were calculated for two counties, demonstrating the benefits offered by high resolution imagery. More than 10 oral presentations were given to national and international audiences, with two peer reviewed publications in international journals.


the landcover maps were generated by a classification process known as extremely randomised trees, which was found during the project to be the most robust for creating the classifications, the 250m resolution MODIS data are at classified to a general land cover equivalent to Fossitt level 1 with a distinction between improved and semi-improved grassland, the 20m SAR data, which just cover 2008, are classified to greater detail equivalent to Fossitt level 3 as a result of the higher spatial resolution


the landcover maps were generated by a classification process known as extremely randomised trees, which was found during the project to be the most robust for creating the classifications, the 250m resolution MODIS data are at classified to a general land cover equivalent to Fossitt level 1 with a distinction between improved and semi-improved grassland, the 20m SAR data, which just cover 2008, are classified to greater detail equivalent to Fossitt level 3 as a result of the higher spatial resolution
Links To Other Related Resources
  https://landmapping.wordpress.com/ilmo/ (Opens in a new window)

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