Reference no: EM133675308

Report - Data Analysis in QGIS

Introduction
This is your first piece of written assessment for the unit. It tests the skills and knowledge that you have acquired in the unit within weeks 1-4. You have been introduced to the functionality of QGIS and this first assignment provides a test of your basic spatial analysis and cartography skills. Overall, it is worth 30% of the unit assessment. You have randomly been allocated one SA2 - your SA2 will be listed under Assignment 1 in the LMS.
Requirements

Overall word limit: 1200 words maximum
Submission format: Word or PDF format only
Your word count will not include any words included in tables presenting numeric outputs.

Please note that penalties are applicable for infringing these requirements - guidelines are in the unit outline for you to refer to.

Assignment brief

Based on the work completed in Weeks 2 to 4 you are to compile a short Report on Tree Canopy Cover within the Perth Metropolitan Region.
This is a short report, and you will need to be both precise and concise in reporting your findings.

Background
Based on course reading materials, together with further independent reading, provide a background section covering the importance and benefits of urban vegetation whilst identifying the characteristics of the urban environment that can influence urban vegetation. Based on the brief provided here under points 2 to 4 briefly outline the aims and objectives of this report (250 to 300 words).

Tree Canopy by Land-use
Based on the brief provided to you in Week 3 provide an analysis of the dynamics of tree canopy cover by land-use in your SA2 in comparison to tree canopy by land-use across the whole Greater Perth Region.
In class you were shown the steps required to compile tree canopy data using the land- use field called monitorcat as a land-use descriptor. For this assignment exercise you will need to complete the requisite steps to generate similar information using the field MB_cat16 as the descriptor of land-use.
To complete this exercise, you will need to generate layers that provide:
Measures of tree canopy cover and land area for your whole SA2;

Measures of tree canopy cover and land area by land-use (use the mb_cat16 field) for your SA2;
Measures of tree canopy cover and area for the region-as-a-whole; and
Measures of tree canopy cover and land area by land-use for the region-as-a-whole (use the mb_cat16 field) for your SA2;

A one-page map layout with multiple map frames that focuses on tree canopy cover and land-use for your SA2. Look to highlight overall tree canopy in your SA2 in comparison to other SA2s across the region as well as the detail of tree canopy cover and land-use in your SA2. Provide your SA2 with good spatial context and provide mapped information that you consider to be informative to your reader.
Provide a short, written analysis and discussion (300 to 400 words) comparing tree canopy cover and land-use in your SA2 area compared to the region-as-a-whole.
Consider the region as a whole and identify the important land-uses across the region in terms of land area and in terms of tree canopy cover.
Highlight and discuss tree canopy cover and land-use characteristics of your SA2 in comparison to the region as-a-whole.
Look to identify where your SA2 ranks in comparison to other SA2s in terms of overall tree canopy cover and look for trends in your land-use, socio-economic and density data that can be used to explain the tree canopy characteristics of your SA2.
Support your discussion by providing relevant graphs and tabular outputs for both your SA2 and the region as a whole, including:
Land area by land-use (in hectares and as a percentage split)*;
tree canopy cover (percentage) by land-use*; and
tree canopy cover area/non-canopy cover area (ha) by land-use*. (* make sure you include measures for the whole SA2/region).

Dwelling Density Layer Creation
As specified in section 7.2 of Lab Delta, create a layer that includes a variable that provides a measure of dwelling density in dwellings per sqkm and join the newly created layer to UF_SEIFA_SA2_2016_GPER_v2 to make a new layer.

Determinants of Tree Canopy Cover in the Perth Metropolitan Region
Also based on the work completed in Week 4 together with the inclusion of the additional variable specified in section 3 above conduct an SA2 level statistical analysis using the following independent variables that potentially explain percentage tree canopy cover:
Independent Variables:
IRSD_Score; IRSAD_Score; IEO_Score; IER_Score); population density (PopDensity_ppSQKM); and dwelling density (in dwellings per sqkm)
Dependent Variable:
TrCover_pc

Bivariate Statistical Analysis Include
A short introduction to the section providing relevant context.

A Pearson's Correlation Table incorporating all independent variables and the dependent variable.
Calculate p-values and R-squared values for all independent variables against the dependent variable.
Consider covariance between independent variables.
Provide scatter plots for all independent variables against the dependent variable.
Identify the number of SA2s that contribute to the bivariate analysis. Provide a summary and interpretation of the outputs of your statistical analysis (150 to 200 words).
Recommendations: Use the outcomes of the above analysis to recommend which of the potential explanatory variables best explain tree canopy cover at an SA2 level within the study area and that may be useful for a future broader evaluation of the determinants of tree canopy cover. When compiling your recommendations draw on relevant literature to validate your evaluation and to identify which additional independent variables you may wish include for further analysis (250 to 300 words).