Fieldwork in Human and Physical Geography: Data Collection and Analysis in Snowdonia, Study notes of Geography

Download Fieldwork in Human and Physical Geography: Data Collection and Analysis in Snowdonia and more Study notes Geography in PDF only on Docsity! The fieldwork component eduqas Context Purpose and value of fieldwork and how it relates to the course Terms Enquiry process Geographical skills The Enquiry Process 1. Context & planning – identifying/refining questions; choosing suitable locations; deciding on collection methods; risk assessments 2. Data collection – acquiring data pertinent to the investigation with an appropriate balance between primary & secondary, and quantitative & qualitative 3. Presentation & display – using appropriate methods to enable… 4. Analysis & interpretation of findings – interrogate data to identify & describe patterns, trends and relationships; apply concepts & processes to understand observed data 5. Conclusion – synthesise/summarise findings to draw conclusions relating to original questions 6. Evaluation of the whole investigation – critically reflect on every stage of the investigation to appreciate strengths & limitations; consider accuracy, validity & reliability of methodology and findings; suggest improvements for further research Planning the Snowdonia fieldwork “a eduqas Snowdonia Fieldtrip The equivalent of three days of fieldwork: 2 half days + 2 whole days Human Geography: investigations relating to: Changing Places: Re-imaging/rebranding in Blaenau Ffestiniog Importance of tourism in Betws-y-Coed Physical Geography: investigations relating to: Glaciated Landscapes – around Llyn Llydaw on Snowdon: Glacial deposition – identifying landforms in the field Periglacial slope processes – scree development Coastal Landscapes – beach management impacts at Dinas Dinlle Ecosystems at the Local Scale – sand dunes at Morfa Dinlle 1 day 1 day ½ day ½ day Data collection methods Environmental Quality Assessment – bipolar It can be difficult to decide on appropriate opposite descriptions Always make sure you have the descriptions on the correct side of the scale! Data collection methods Environmental Quality Assessment — scoring Criteria Houses — upkeep x Amount of open space x Open space — upkeep Streets — pavement quality Streets — road quality Amount of traffic Litter -— amount Mechanical noise level Public noise level Vandalism — amount Graffiti — amount Air pollution — fumes/smells Derelict x |x |x | K |K LK Tx Data collection methods Coding – for land use surveys You may need to have sub-groups in order to identify more meaningful patterns… …but having too many could make it difficult to see any patterns at all! Collecting raw data with a view to encoding later might be the best option… es oa Rie Glaciated Landscapes - 1 Are the depositional landforms around Llyn Llydaw mainly lodgement or ablation in origin? Glaciated Landscapes - 1 Are the depositional landforms around Llyn Llydaw mainly lodgement or ablation in origin? Sediment sampling – till fabric analysis You can’t measure every clast in every landform, so you will need to devise an appropriate sampling method. A useful piece of equipment would be a quadrat: How could this be used to select clasts? How many clasts should you aim to measure? What should be considered in making this decision? Measuring sediment angularity/roundness There are a number of different techniques for describing the characteristics of coarse sediment (finer sediment – sand, silt & clay – needs to be sieved). The Field Studies Council has some useful details: (https://www.geography-fieldwork.org/a-level/coasts/low-energy-coasts/data-analysis/) We’re only going to consider roundness, for which there are two main methods: Powers Index of Roundness Cailleux’s Roundness Index How could such data be presented and analysed? Powers’ Roundness https://www.researchgate.net/figure/A-new-roundness-scale-for-sedimentary-particles-after-Powers_fig4_303702743 Pro: quick and easy Con: subjective; data in categories (so less easy to process) Clast orientation How might this be measured? How could it be presented? Glaciated Landscapes - 1 Are the depositional landforms around Llyn Llydaw mainly lodgement or ablation in origin? Sediment size distribution How might this be measured? What difficulties might there be? How could these be overcome? Could this be simply assessed? If so, how? Glaciated Landscapes - 2 To what extent is the scree material at Llyn Llydaw larger at the bottom? Accurate and reliable measurements of clast size is critical for this investigation. Sampling is also needed – what might be done and how many clasts collected? Measuring coarse sediment size Techniques for measuring sediment size: https://www.geography-fieldwork.org/gcse/coasts/coastal-processes/fieldwork/ Equipment needed? Issues? Measuring coarse sediment size Measuring volume by displacement: Equipment? Issues? http://homepage.smc.edu/walker_muriel/measurements_in_the_laboratory%20Procedure.htm The Physical Fieldwork - 2 To what extent is the scree material at Llyn Llydaw greatest at the bottom? Glaciated Landscapes - 2 To what extent is the scree material at Llyn Llydaw greatest at the bottom? Chi-squared Is there a significant difference between the observed data and what would be expected (i.e. a random distribution in this case)? Hypothesis, H1 Null hypothesis, H0 Calculate chi-squared Compare value against critical values for size of data set Accept/reject null hypothesis Glaciated Landscapes - 2 To what extent is the scree material at Llyn Llydaw greatest at the bottom? Chi-squared Group the long-axis data – there should be at least 5 expected values in each class – so if you have 25 stones, have 5 classes. These are your Observed data, O. Size class 1 2 3 4 5 Row Total Top of scree slope Bottom of scree slope Column Total (Overall Total) A brief explanation about significance testing: With some statistical tests (like Chi-squared, Mann Whiney and Spearman’s Rank) it is possible that a result could have occurred by chance. Therefore it is necessary to determine what this probability is – i.e. the significance of the result. In most cases, a probability of 10% (or 0.1) that a result could have occurred by chance is considered to be too great a risk and so the null hypothesis could not be confidently rejected. The lower probability (e.g. 5% or 0.01, for example) the more significant the outcome and so the greater the confidence that rejecting the null hypothesis would be the right conclusion to draw. Coastal Landscapes To what extent has management affected coastal processes at Dinas Dinlle? Coastal Landscapes To what extent has management affected coastal processes at Dinas Dinlle? Ecosystems How typical a psammosere are the dunes at Morfa Dinlle? Expectations? A Psammosere: coastal sand dunes Ecosystems, p129, M Gillett, Hodder Education, 2005 What changes are observable as succession proceeds? Why do these change? A Psammosere: coastal sand dunes Cross section through dunes from The Functioning and Management of Psammoseres in Studland Bay, Dorset, GeoFile #710, April 2014 What changes are observable as succession proceeds? Why do these change? Ecosystems How typical a psammosere are the dunes at Morfa Dinlle? Statistics based on observations taken between 12/2015 - 10/2017 daily from 7am to 7pm local time. https://www.windfinder.com/windstatistics/foryd_bay_caernarfon Secondary data? Ecosystems How typical a psammosere are the dunes at Morfa Dinlle? https://www.windfinder.com/windstatistics/foryd_bay_caernarfon Statistics based on observations taken between 12/2015 - 10/2017 daily from 7am to 7pm local time. Ecosystems How typical a psammosere are the dunes at Morfa Dinlle? Data presentation: Kite diagrams