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Spatial Analysis and Data Quality Assessment Project

Task

The tasks involved in this project are essentially practical in nature and will develop and build on the learning achieved in the module so far.

Three separate tasks are involved - the first will include sourcing data, integrating and projecting this data, performing spatial analysis operations and presenting the information in the form of maps and layouts.

The second task is a quality assessment of open source spatial data and the third is to source and work with CSO census data to explore the distribution of specific variables. Additional information sources will be utilized to explain the spatial occurrence of these variables.

 

Part (i)

The period from 1990 to 2018 witnessed rapid growth and development in Ireland especially within the counties known as the Greater Dublin Area (GDA).

Imagine you are working for a Local Authority in one of the counties in the GDA (exclude those LA areas within Dublin) and have been asked to derive and present certain information for preparation of a strategic plan for the county for the next five years.

Specifically you are tasked with quantifying and mapping changes in land-use for the following categories

Urban areas
Agricultural areas
Areas of peat bog
Select a county from the GDA (Wicklow, Kildare, Meath or Louth) and provide quantitative and map evidence of the change in each land-use category.

Use Irish Transverse Mercator (ITM) as the CRS for the project.

Part (ii) Introduction
The last decade has witnessed an increase in the number of geoportals and sources offering free-to- use open geospatial data with a corresponding growth in spatial data analysis in a wide array of social science disciplines, including public health, economics, crime, population, etc.

It is, however, of fundamental importance that the analyst is aware of the quality and utility of such data. OpenstreetMap, for example, is a widely used source of free spatial data.

The International Organization for Standardization (ISO) publishes international standards for a wide range of domains, including geographic information.

Establishes the principles for describing the quality of geographic data and specifies components for reporting quality information. It also provides an approach to organizing information about data quality.

Applicable to data producers providing quality information to describe and assess a dataset and to data users attempting to determine whether specific geographic data is of sufficient quality for their particular application.

Quality components include

Positional accuracy
Thematic accuracy
Logical consistency
Completeness
Temporal accuracy
These topics will be treated in detail in later modules but at this stage we will consider some rapid and simple methods to derive approximate estimates of the quality and utility of the open-source data as compared to the OSi national mapping.

An important aspect of such data when considering its fitness for purpose is the accuracy and completeness of the data. Studies examining such issues have been published but the assignment here is for you to make your own assessment of the quality of the data.

Task

The task is to select a suitable area of interest (for example, Wexford Town) and compare the OpenstreetMap with OSi national data in terms of accuracy and completeness.

Part (iii) 

Select two counties in Ireland, one of which is to be Dublin. 

Use the CSO Small Area statistics to show where concentrations of elderly people (over 80 years of age) are living and attempt to explain why these concentrations are present. 

Utilise alternative sources of spatial information to justify and illustrate your analysis (for example, GoogleEarth, Openstreetmap, OSi Geohive, etc). 

Demonstrate how the locations were found using Selection criteria as well as by visual analysis using various display settings (classification parameters) 

Discuss and critically analyze the parameters used - that is, the selection ranges and criteria employed (examine the different value ranges for urban and rural areas and use an appropriate range in each case).

Provide detailed listing of steps , how results were achieved for all 3 parts. 

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