Towards Land cover Accounting and Monitoring (TaLAM) - land cover maps from satellite imagery

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Resource or Project Abstract

Ireland has a need for maps of land cover and land use to improve environmental management, policy implementation and calculations of the annual greenhouse gas budget. The currently available data for Ireland [e.g. the European Coordination of Information on the Environment (CORINE) map] have their limitations because of scale, the types of land cover classified and the update cycle. Best practice, as adopted in several European countries by 2016, is to use satellite imagery in combination with existing official mapping to be able to give every area of land a cover and use designation. The Towards Land Cover Accounting and Monitoring (TaLAM) project is part of Ireland?s response to creating a national land cover mapping programme, and aims to demonstrate how the Prime2 digital map from Ordnance Survey Ireland (OSI), can be combined with satellite imagery to produce land cover maps. Information derived from the images can be used to populate the Prime2 objects, but in upland areas there are no defined objects and one important objective of the project is to design a method that can fill in the blanks and map the land cover in these unenclosed areas. To ensure the TaLAM outputs are acceptable and useful to the professional community, a workshop was held to canvass opinion on mapping and reporting land cover change in Ireland. For enclosed ojects in Prime2, the preferred option was a minimum mapping area of 0.5 ha labelled with the percentage cover of all land cover classes within the object. For unenclosed upland regions, the preference was for the region to be broken up to create Prime2-type polygons of 2?5 ha, with all land cover classes labelled as a percentage and updated at 5-year intervals. The Suir catchment was selected as a trial area and, using a random forest classifier, very high overall accuracies (>92%) were achieved for a land cover map of enclosed areas automatically created from images acquired by NASA?s Landsat-8 satellite. Methods for classifying the upland regions focused on the Galtee Mountains, the Comeragh Mountains and Mount Brandon. It was concluded that medium spatial resolution (5?50 m) imagery acquired from optical and microwave sensors enables mapping and monitoring of upland vegetation in broad categories. However, such imagery cannot replace detailed field mapping of habitats, and the subtle differences between habitats that are sometimes required, especially by conservationists and ecologists, cannot always be distinguished, and so for detailed habitat mapping, the satellite imagery must be complemented by fieldwork. It is recommended that medium spatial resolution (5?50 m) optical and microwave satellite data are used for the land cover mapping of Ireland. The Prime2 fields integrate well with satellite imagery for creating land cover maps for enclosed areas; however, where these are not available, as in the upland areas, automatic segmentation techniques can derive land cover classes directly from the imagery. Satellite data will never entirely replace field work, and a campaign to provide field data for a national land cover map is needed. Automating the process for identifying change and updating national land cover maps remains a challenge, but with more image data available such automation will become a realistic possibility.

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Contact Information for This Resource

Dr. Fiona Cawkwell
University College Cork

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Attachment Name and Download Link
Att 1    Comeraghs_ALOS.mpk   (0.2 Mb)
Att 2    Brandon_ALOS.mpk   (0.3 Mb)
Att 3    Galtees_ALOS.mpk   (0.13 Mb)
Att 4    Suir_Landsat.mpk   (1.46 Mb)
Att 5    Suir_Landsat_1haseg.mpk   (5.24 Mb)
Att 6    Suir_Landsat_2haseg.mpk   (3.89 Mb)
Att 7    Suir_Landsat_5haseg.mpk   (2.61 Mb)

Suggested Citation Information

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Author(s)Cawkwell, F.
Title Of WebsiteSecure Archive For Environmental Research Data
Publication InformationTowards Land cover Accounting and Monitoring (TaLAM) - land cover maps from satellite imagery
Name of OrganisationEnvironmental Protection Agency Ireland
Electronic Address or URL http://erc.epa.ie/safer/resource?id=41eac02e-9585-11e8-8356-005056ae0019
Unique Identifier41eac02e-9585-11e8-8356-005056ae0019
Date of AccessLast Updated on SAFER: 2018-10-20

An example of this citation in proper usage:

Cawkwell, F.   "Towards Land cover Accounting and Monitoring (TaLAM) - land cover maps from satellite imagery". 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=41eac02e-9585-11e8-8356-005056ae0019 (Last Accessed: 2018-10-20)

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Access Information For This Resource

SAFER-Data Display URL http://erc.epa.ie/safer/iso19115/display?isoID=3159
Resource Keywordsland cover, remote sensing, Landsat, PALSAR, AVNIR, Suit, Brandon, Comeraghs, Galtees
EPA/ERTDI/STRIVE Project Code2013-SL-MS-1
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 use of the datasets provided must reference the work done by this project as Cawkwell, F., Raab, C., Barrett, B., Green, S. and Finn, J. (2017) Toward Land cover Accounting and Monitoring (TaLAM); EPA STRIVE Report 2013-SL-MS-1
Number of Attached Files (Publicly and Openly Available for Download): 7
Project Start Date Thursday 1st May 2014 (01-05-2014)
Earliest Recorded Date within any attached datasets or digital objects Saturday 1st August 2009 (01-08-2009)
Most Recent Recorded Date within any attached datasets or digital objects Friday 1st August 2014 (01-08-2014)
Published on SAFERWednesday 1st August 2018 (01-08-2018)
Date of Last EditWednesday 1st August 2018 at 13:33:51 (01-08-2018)
Datasets or Files Updated On Wednesday 1st August 2018 at 13:23:07 (01-08-2018)

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Geographical and Spatial Information Related To This Resource

Description of Geographical Characteristics of This Project or Dataset
One part of this study focuses on the River Suir catchment area (hydrometric area 16), covering parts of County Tipperary and Waterford. This includes the Comeragh Mountains and Galtee Mountains which are two of the three upland regions also studied (the other being Mount Brandon). The boundaries of the upland areas are defined as unenclosed areas of land above 150m ASL and contiguous areas of related habitats that descend below that height (as described by the National Parks and Wildlife Service).

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Supplementary Information About This Resource

In this section some supplementary information about this resource is outlined. Lineage information helps us to understand why this project was carried out, what policy or research requirements did it fulfil, etc. Lineage is important in understanding the rationale behind the carrying out of a project or the collection of a specific dataset etc. Links to web sites, applications, papers, etc are outlined to provide you with additional information or supplementary reading about the project or dataset

Lineage information about this project or dataset
This project follows on from work done on the Irish Land cover Mapping Observatory (ILMO) project by the same research team based at UCC and forms part of a larger body of work on land cover classification from satellite imagery for different habitats within Ireland. The requirement for study of the upland areas in particular stems from the large unenclosed regions within the Ordnance Survey Ireland Prime2 vector database. These areas therefore have no inherent Form and Function labels and classification from satellite imagery is one of the key methods of providing up-to-date and detailed information on the habitats within these areas. All the work done on land cover classification using satellite imagery is informing a national working group on land cover mapping at a national scale, with the methods used in accordance with current European best practice.
Supplementary Information
The land cover classes used follow those of the Fossitt habitat classification schema to level 2 or 3 as closely as possible.

The random forest classifier was used to determine the different land cover classes from the satellite imagery, with segmentation of the optical imagery using the i.segment region growing routine within GRASS. Image processing was done within ENVI, ERDAS, SARScape, ArcGIS and GRASS, and using Python libraries.

The data were saved using ArcGIS 10, however should be readable by this and later versions of ArcGIS as well as some other GIS software. The file Suir_Landsat is the pixel based classification of the Suir catchment, with the 1haseg, 2haseg and 5haseg files being the 1ha, 2ha and 5ha segmentations of the same region from the same imagery. The Comeraghs_ALOS, Galtees_ALOS and Brandon_ALOS are the optimal land cover classification of those regions using ALOS PALSAR and AVNIR data.

Two papers which contain further information are:
Barrett, B., Nitze, I., Green, S. and Cawkwell, F., 2014. Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches. Remote Sensing of Environment 154: 109?124.
Raab, C., Barrett, B., Cawkwell, F. and Green, S., 2015. Evaluation of multi-temporal and multi-sensor atmospheric correction strategies for land-cover accounting and monitoring in Ireland. Remote Sensing Letters 6(10): 784?793.

Landsat data were sourced from the USGS EarthExplorer portal, ALOS data were acquired from the European Space Agency (Cat-1 proposal ID 28407), field survey data were provided by the National Parks and Wildlife National Survey of Upland Habitats programme, the Department of Agriculture, Food and the Marine (DAFM) made data from the Forest Inventory and Planning System (FIPS) and Land Parcel Identification System (LPIS) available, and the Prime2 data were provided by Ordnance Survey Ireland (OSI).
Links To Other Related Resources
More information can be found at the project website (   https://landmapping.wordpress.com), (Opens in a new window) including the ArcGIS online maps which can be viewed at   http://ucc.maps.arcgis.com/apps/webappviewer/index.html?id=fe96fe54110b48d798bda6bcba448b16 (Opens in a new window)

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