GIS Monthly Maps
Map of the Month- May 2018
Title: Fragmented farmscapes- total length (km) of shared farm boundaries per hectare by townland (RoI).
Cartographer: Stuart Green
When we talk of “farm fragmentation” we mean farmers working land that is not all in one parcel, but instead in parcels spread out over the local area, interwoven with parcels of land owned by other farmers.
Fragmentation is largely seen as a negative impact of farm efficiency and productivity. As farmers have to travel distances between parcels it increases operating costs. It inhibits improvement and development of land and the adoption of some new farm technologies. Because of this fragmented farm areas are often less improved with a higher occurrence of High Nature Value farmlands.
Farm landscapes can be fragmented for many reasons, history, demographic, topography of all three. In this month’s map, we’ve used a national farm boundary database created under the Teagasc lead, EPA funded Cosaint Project to measure the length of farm boundaries shared by two farmers. In more fragmented complex landscapes the length of shared boundary per hectare increases (imagine a chess board- if every square was owned by the same farmer, the boundary is the outside of the board, but if every square is owned by a different farmer then the shared boundary is the sum of the boundaries of all the squares on the board).
The Aran islands have the most fragmented farm landscape, whilst counties like Monahan, Roscommon, Galway and Mayo have a large share of fragmented farms. Upland commonage areas are shared but have no boundaries demarking the shared areas so come out as low. For the boundaries themselves it’s interesting to note hedgerows marking property boundaries are often older than internal field boundaries.
Data sets used: OSI Prime 2
© Ordnance Survey Ireland. All rights reserved. Licence number DOF 11/1
Map of the Month - April 2018
Title: New automatic methods to map farmland using satellites
Cartographer: Shafique Matin, Research Officer
April's map of the month illustrates how we move from pixels in a satellite image to automatically clustering pixles into discrete "objects" and being able to label those objects, its the differnce between labelling a pixel "grass" and identifying a "Improved grassland paddock" and do this routinely and automatically.
Object-based segmentation results in a quick and accurate delineation of surface features based on the four basic geometric parameters, i.e., tone, shape, size, and compactness. It takes the advantage of incorporating spatial context and mutual relationships between different objects and reduces the image noise to group contiguous pixels with similar features into one object.
Object-oriented classification is a very useful technique to classify farmland landscape with different stages of intensification due to its ability to differentiate considering its colour, texture, and shape. It also provides the opportunity to implement a ruleset to merge hedgerows, tree shadow, etc to the associated field parcels.
In a high-resolution satellite image, an intensified farmland appears bright green in colour, with a defined rectilinear boundary with sharp edges and a smooth texture. Besides, a non-intensified (semi-natural) farmland appears brownish in colour, rough-textured and often associated with rivers and forests.
The current map shows four stages of farmland mapping using object-oriented classification on high-resolution SPOT 7 satellite image of 1.5 m resolution. The radiometrically corrected image was used for a quick multiresolution segmentation that classified the image automatically into seven unsupervised classes. Finally, samples were collected for pre-defined classes which further classified the map into intensified and non-intensified farmlands and four other land cover classes.
Map of the Month - March 2018
View map: GIS Map of the Month March 2018 (PDF)
Title: Probability of finding a stonewall in Ireland
Cartographer: Stuart Green, Senior Research Officer
March’s Map of the Month is an output from our farm boundary projects.
Knowing the location, extent and type of farm boundary is important in many areas of study; landscape characterisation, biodiversity, surface water studies and many more.
Stonewalls are common in parts of Ireland and predominate over hedgerows in areas of limestone bedrock, where loose pieces of rock are found in the soil. During enclosures in earlier centuries, as these rocks were cleared from the soil they were used to form field boundaries. In other part of the country ditches and hedges are used.
Detecting stonewalls remotely is not easy, especially as in many cases they now have hedges growing alongside, or on top of. Ground observations are needed and the European Environmental Agency carries out point and transects surveys, LUCAS, of landuse and landcover every 3 years which give +5000 field boundary observations in Ireland. If we combine these with the geology map and field boundary location map we can build a probability map, interpolating between the points, which shows the percentage likelihood that a field boundary is a stone wall and not a hedgerow.
We will be using this layer in a number of ecosystem service and landscape type projects in the coming months.
Map of the Month - February 2018
View map: GIS Map of the Month February 2018 (PDF)
Title: Grass cover for Moorepark 20th February 2018
Cartographer: Richa Marwaha, Walsh Fellow
February’s Map of the Month is an output from our national grass mapping projects. This project “National farm scale estimates of grass yield using remote sensing” is developing a national model to estimate current biomass, at field scale for all grasslands in Ireland. It follows on from an earlier project that used satellite images to accurately measure grass biomass at a number of trial sites using machine learning methods.
This map of Moorepark from the 20th of February uses vegetation indices to show the relative range of grass covers between paddocks. Vegetation indices are derived from measurements of red and near infra-red light reflected from the grass in the paddocks and captured by the satellite. A value close to zero indicates no grass (bare soil), while higher values, up to 1, indicate increasing grass covers/biomass.
This map shows how new satellite data from ESA allows us to look at grass cover at paddock scale up to every 5 days. It’s this data (temporal images from Sentinel-2 and Landsat-8) that allows for mapping of biomass and observations of management.
Data sets used: ESA Sentinel 2
Map of the Month - January 2018
View map: GIS Map of the Month January 2018 (PDF)
Title: Average field sizes in Ireland, calculated per townland.
Cartographer: Dr. Jesko Zimmermann
This map uses OSI field boundary data and townland data. We calculated the average field size in townlands but we excluded those townlands that are not dominated by enclosed farm lands. These include uplands and commonage areas, raised bogs, forested areas, lakes and of course built up areas.
The map, at first glance, seems to tell a familiar story, with larger fields in the south and east, where farms are bigger and more intensive and smaller fields (in shades of green) in the north, where farms are smaller and less productive. But a closer look reveals many local details and we can see the effects of landscape, history and soil on the range of field sizes across the country and within and between neighbouring counties.
Data sets used: OSI Prime 2, EEA CORINE Land-cover 2012
© Ordnance Survey Ireland. All rights reserved. Licence number DOF 11/1
About Map of the Month
In addition to undertaking geographical analyses and producing maps for research projects, the spatial analysis lab responds to ad hoc requests for contributions. The latter may be for in-house purposes or to inform policy submissions. While dissemination is a key objective of research projects, maps produced in response to such requests rarely get a wider audience. We’ve decided that we’ll take the most interesting map we have produced in each month and to present it here to hopefully find a wider audience and promote discussion and debate on both the contribution of spatial analysis to Irish agriculture and food and on the specific maps produced.
Whilst this map can be shared please check with us before reproducing it in a publication. Many of the data sets we use are under licence with conditions attached.
For general enquiries contact Stuart Green or the author above for information on this month’s map.