Table of Contents
Description of methodology and data
Results and discussion.
Quantum Geographical Information System (QGIS) represents software that is effective in analysing the geographical information of a chosen area. It helps in editing the spatial information of a place further investigating the geographical maps. The current study will be dealing with the analysis of QGIS of the state of WA (Western Arthur) alongside analysing the background information. Lastly, the class will deal with the analysis of the particular variables based on the research question formed in the study with a suitable analysis of the data through graphs and charts.
What is the geographical features and capacity of WA?
This question will be forming the base of the study in the sections below.
QGIS is considered as a free alongside open source cross-platform indicating the analysis of the geographical information of a particular place. In the opinion of Tama and Malinowska (2018), GIS supports the actions of editing, analysing, and viewing the geospatial data of the chosen area. The main functionality of the software includes the editing of spatial information. In addition to this, it also helps in the analysis of exporting alongside composing geographical maps through vector layers and raster layers. Other than that, as pointed out by Park et al. (2019), QGIS also tends to support personal geo-databases alongside coverage, shape files and other formats. It also includes web services that include the benefits of the web map, web features, and is funded through various external sources.
Other than that, it can also be noticed that the integration of QGIS is executed through open sources that include the map server, grass GIS, Post GIS and many others. As argued by Sehra et al. (2017), the functionality of QGIS is almost similar to the applications of ArcGIS and many others. Nonetheless, it has also been noticed that the graphical represented offered by the current software is better than the other software that is available in the market for spatial or geographical analysis. Hence, it can be noticed that with the help of QGIS, analysis of a geographical location can be flawlessly executed.
The data that has been collected in the study is based on secondary data collection methods. As per the opinion of Baisantry and Saxena (2016), secondary methods collect data from different online sources. In this study, secondary data sources have been used in this study to gain several data from online journals, articles and many others. In addition to this, as per the opinion of Bolla and Djahi (2018), it also helps in collecting the data from a wide range of perspectives. The methodology that has been used in the current study includes the positivism philosophy alongside the usage of descriptive design and deductive approaches. As per the illustration of Flenniken et al. (2020), it can be analysed that a secondary collection of data that have been used in the current study provided the study with different dimensions of knowledge.
In addition to this, it can also be analysed that through secondary data, less time can be consumed for the analysis. It helps in executing the targeted goals within less timeframe. Based on this analysis, it can be reflected that through the data analysis, the geographical data of the current location that is WA can be analysed. It helped the study to give a new frame through the analysis of geographical information based on the data available in the online source. Apart from that, as the survey deals with geographical analysis; therefore, secondary data also helped in the geospatial analysis of the current location.
Based on the presented instances, it can be observed that the area of WA provided in the scheduled data includes 2832 sq km (Tama and Malinowska, 2018). Based on the presented instances, it can be reflected that the state has a small area as compared to the other countries. This also answers the question of the geographical features of WA. In this respect, it can be observed that WA is having a small area capable of consisting of a small number of people. In addition to this, the population of the place reflects 809 people. Considering the location of the state, the density of the area is also adjusted, and this answers the question of geographical features and capacity of the site.
On the other hand, it can be observed that the unemployment rate of the area is 4.18%. Keeping another pace of employment ion the different regions, it can be observed that the quality of unemployment is low that further reflects the fact that the employment rate within the area of high. This reflects the aspects that the country is well managed and is having a balanced population that can earn their livelihood prosperity. Observing both the variables of the area, it can be concluded that WA is having a minimum size of land with a minimum population and a low unemployment rate that helps the community to lead a healthy life.
The above map presented represents the different features possessed by WA within the area. It helps in reflecting the camping, photo opportunity, wildflowers, and many others. It reflects the various elements used by the people living within the region.
The above figure reflects the topographical image of WA. Most of the section, as mentioned in the model above, is highlighted with green representing forestry within the region. Hence, it can be concluded that the area works in maintaining the greenery while providing various facilities to the population.
From the above analysis, it can be reflected that QGIS of WA reflects a small area consisting of a small population and a low rate of unemployment. In addition to this, based on the geospatial reflection of the room, it can is concluded that the people living within it use high facilities and most of the area is covered with forest.
Baisantry, M. and Saxena, V., 2016, April. Removal of ladder effects by smoothening the integer format elevation layer via development of a QGIS plugin. In 2016 International Conference on Computing, Communication and Automation (ICCCA) (pp. 1054-1058). IEEE.
Bolla, M.E. and Djahi, B.S., 2018. The development of road databases and analysis of traffic accident-prone section (blacksite) based on Geographic Information System (GIS). MS&E, 403(1), p.012062.
Flenniken, J.M., Stuglik, S. and Iannone, B.V., 2020. Quantum GIS (QGIS): An introduction to a free alternative to more costly GIS platforms. EDIS, 2020(2), pp.7-7.
Park, S., Nielsen, A., Bailey, R.T., Trolle, D. and Bieger, K., 2019. A QGIS-based graphical user interfaces for application and evaluation of SWAT-MODFLOW models. Environmental Modelling & Software, 111, pp.493-497.
Sehra, S.S., Singh, J. and Rai, H.S., 2017. Assessing OpenStreetMap data using intrinsic quality indicators: an extension to the QGIS processing toolbox. Future Internet, 9(2), p.15.
Tama, A. and Malinowska, A., 2018, June. The Possibilities of Water Hazard Managements in Transformed Area with Open Geographical Information System (QGIS). In 2018 Baltic Geodetic Congress (BGC Geomatics) (pp. 344-348). IEEE.
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