Map report for unemployment at ward level in Norfolk - Research Paper Example

?Map report for unemployed Percentage male Aged 16 - 64 in Norfolk First of all, the data was downloaded from CasWeb, and then generalisation methodswere applied in order to make the maps’ appearance more efficient. The map was sited at the scale of 1:510,000. One of the tools applied for the map is smooth polygon, which improves cartographic quality and reduces the complexity of sharp angles. The other tool is known as the simplify line and is used to reduce the graphic appearance of bends without changing their original shape. Inset map at larger scale is also required to represent the small urban areas. Leader symbol was created using numeric symbols (numbers) instead of lines in order to deliver the map clearly and with less complexity. There was also the need to use Maplex toolset to have more flexibility on labels position and size. Two family fonts were used in the map i.e. Times New Roman for the title and Arial for the rest of the labels. Fitting strategy for location text is listed as follows Small polygons: curved position with low size limitation up to 6 pts Medium polygons: horizontal position with option of stuck labels when possible. Large polygons: horizontal position with option of stuck labels when possible as well as allowing the letter spacing across the polygon. And finally there was the need to use the website colorbrewer2.org in order to explore colour theory and examine different type of colours and apply the best cartographic application Methods applied Data manipulation was also required to get the percentage of males aged 16-64 whom are unemployed in Norfolk. Calculation methods ([16-17] + [18-19] + [20-24] + [25-29] + [30-44] + [45-59] + [60-67]) * ([Economic activity - males]) / ([16-17] + [18-19] + [20-24] + [25-29] + [30-44] + [45-59] + [45-59] + [65-74]) Calculate percentage ([total age from 16-64]) / ([all unemployed])*100 . Map report for unemployment at ward level in Norfolk Once more, the data was downloaded from for the same source CasWeb, and then generalisation methods were applied in order to make the maps’ appearance more efficient. Similarly, the map was sited at the scale of 1:400,000. The methods applied in this map are slightly different, but the goal should remain the same which is delivering the map in the best cartographic application. The purpose of the map is to show the total unemployment in Norfolk and the methods applied to this map as follows: Methods applied Smooth polygon to improve cartographic quality and reduce the complexity of the sharp angles. Simplify line to reduce the graphic appearance of bends. There are two types of simplify line and the one chosen for this map is bend simplify, which is more likely to have a similar view to the original shape. Dot sizes were created using the best visual appearance. Calculation was also required to establish the size of a dot (Mackay Nomograph, alignment graph) but unfortunately, it didn’t go well. Dot value was chosen by identifying the minimum and the maximum values in the table of attributes Dot placement was chosen by applying masking above the dot density map and eliminating the unsuitable areas for dots placement Data manipulation was also required to obtain the number of unemployment for both males and females in Norfolk. Map of United Kingdom to establish an overall view of where the county is exactly located. Mentioning the dot value as well as the dot size in the legend of the map is significant to gain an overall impression of the density. Map report for households with no cars in Norfolk Once again, the data was downloaded from for the same source CasWeb, and then generalisation methods were applied in order to make the maps’ appearance more efficient. The map was sited at the scale of 1:150,000. The purpose of the map is to show the lack of car ownership in Norfolk and the methods applied to this map as follows: Methods applied, strategy and techniques Inset map at larger scale to prevent the symbols from overlapping Flannery compensation noted at the map to inform the reader Inset map at large scale for urban areas to show where the points are exactly located Ensure symbolisation for inset map remains at the same scale. Omit the data from the base map to avoid clutter by exporting the data from it and adding the data as new layers. Arrange map layout by sitting guide to ensure all the layers for inset maps and everything else remain the same size or in the same line in order to make it effective Make the best use of the space by trying different page layouts. Make the map fit the purpose it was designed for Leader symbol was created using numeric symbols (numbers) instead of lines in order to deliver the map clearly and with less complexity Usages of halo masking for leader symbols in the map to improve the visual communication. Chart map of age compensation at ward level Once again, the data was downloaded from CasWeb. The map shows the age compensation in Norfolk. The generalisation methods applied to the previse maps again will be applied to this map with slightly more tools to use.The map sited at scale of 1:150,000. The first step to create the map was to distribute the age compensation to five classes and they were chosen randomly as follows: Font wise remains the same in all maps. Inset map at larger scale were also required to prevent the proportional pie graph from overlapping and again leader symbol was created using numeric symbols (numbers) instead of lines. Halo mask was also added to improve the visual appearance. Deleting the pie graph from the original base map was effective to decrease the diffusion. The page layout was created using the rulers as well as the guide in order to equalise the size for inset maps and the other layers of the map. Methods applied: Smooth polygon to improve cartographic quality and to reduce the complexity of the sharp angles. Simplify line to reduce the graphic appearance of bends, as there are two types of simplify lines. The one chosen for this map is the bend simplify, which is more likely to have a similar view to the original shape. Isopleth This map was treated differently in terms of the final output. The data set used for this map was the lake of car owner in Norfolk. The map sited at the scale of 1:510,000. There are number of steps you will need to follow in order to produce this type of map. Firstly, you have to create a feature class containing points because Interpolator only works based on a point value, and this can be done by using a tool call feature to point in arc toolbox, after which you need to find the more appropriate interpolator to use. I tested all of them and visually kriging was the most appropriate one. Moving to the cell size, 150m was considered in order to get enough accuracy as well as resolution. A map of UK was added in order to clarify to the reader the location of Norfolk County. Colour ramp was selected carefully and classified to six classifications to give the reader the ability to distinguish values. Methods applied: Feature to point Kriging interpolator Border map to clip Location map Moving to map number six, almost the same fitting strategies applied to the first map (label) are used for this map. Fitting strategy for location text is listed as follows Small polygons: curved position with low size limitation up to 6 pts. Medium polygons: horizontal position with option of stuck labels where possible. Large polygons: horizontal position with option of stuck labels where possible as well as allowing the letter spacing across the polygon. The other strategy applied for the data frame properties was the grid; I chose not to show lines or ticks in order to improve the visual appearance of the map. Inset map at larger scale was also required for urban areas. Leader symbol was created using numeric symbols (numbers) instead of lines in order deliver the map clearly and with less complexity. Halo masking for the numeric symbols was important to improve visibility. There was also the need to use Maplex toolset to have more flexibility on labels’ position and size. Methods applied: Smooth polygon to improve cartographic quality and to reduce the complexity of the sharp angles. Simplify line to reduce the graphic appearance of bends. The bend simplify was chosen for this map in order to maintain a similar view to the original shape. Maplex toolset Grids Day 1&2 Informal writing Paper map VS GPS Our first session was about the history of Malta, how it started and how it ended. Moving on to the mobile GIS, we had a briefing about all tasks we would be facing and more importantly, how we were going to tackle them. At the end of the session, we were told about the 8am workout which was not pleasant to me as I wanted to sleep one more hour, though this should not be taken as a complaint. The group was split into sub groups and the task was disclosed as GPS vs. paper map. I was happy that we would be using the GPS as this was an opportunity to perfect my skills regarding its operation. It also made us feel comfortable with the task ahead as it meant that we would not face much difficulty finding our destinations. We went out the following day as planned and after 15 minutes of waiting, we managed to get the ferry to Valletta where we were supposed to carry out the task. The most difficult part was the fact that we did not know for sure where we were going as we were only getting direction from a dot on the screen of the GPS. After managing to the 6th point, we stopped for a quick lunch after which we went back to work. However, the expedition became stressful as we headed to the 8th point for we wasted more than 20 minutes walking in the wrong direction. Lucky enough, we managed to find our way and finish the exercise successfully. The GPS is an important tool for navigation but after the completion of this task, I concluded to myself that the paper map provides higher accuracy levels than GPS because there were no visual information or landmarks to help us identify the points we were heading to in the GPS. However, it also occurred to me that combining the two together would be a better way of speeding up the process. It may also be important to observe that a GPS is disadvantageous as compared to paper maps due to its demand for power, which may act as a hindrance in the event that the power runs out. I think the purpose of today’s exercise is to Get familiar with the GPS and how to transfer the data from it to the computer Use the new technology of phones into GIS Mash-up On the second day, the activities were no different from those we had carried out the previous day. The only notable difference was the fact that the morning work out session involved a variety of exercises, which were not present on the first day. Our mash-up idea was to create a map of attraction sites in Valletta, very simple mash-up map but we decided also to map the best possible route for people with disability to walk through and be able to enjoy all the attraction. With regard to methodology, data was captured by recording our track log as well as taking photos. Street intersections on the main roads were also noted as we walked along as well as any helpful information which we found relevant to our task. Our objective was to achieve the best results without necessarily having to undergo numerous procedures that would make our work tedious and tiring. Final part of the day was to geo-tag the multimedia photographs captured using GPicSync but unfortunately, some of these photos had been misplaced in terms of storage location and therefore, we decided to conduct the operation manually; a tiring process but the results were amazing. At this stage, I can confidently say that I have gained a lot of experience in operating the GIS using different software and as such, it may be the best time to rest and study what is in for the next task. Day 3&4 Land use The idea of day three was to collect data using Trimble Juno. First task of the exercise was to make our way via public transport to Mellieha (bus 645). Upon arrival, we were given a briefing on what we were expected to capture in the area. In this context, we were supposed to study land usage as well as land cover, but the groups had to come up with various topics to aid them in developing a comprehensive report. Our group decided to classify the buildings into three categories residential, public, commercial, and under construction. Roads were to be studied into two categories i.e. side roads and main roads. The vegetation was studied under three different categories which are; small, medium and large. Initially, we decided to carry out the activity of digitizing the results as a group but after a moment we realized it was going to take us more time to complete the task and as such, we split our group into two units so as to hasten the process. It was therefore decided that one group was to carry out the process using Trimble Juno while the other group was to use the paper map provided and start collecting data in form of recording notes and taking photos. As per our expectations, we managed to cover most of the area required. The Paper map group managed to finish capturing land use cover data in very short period of time. On the fourth day, we went back to Mellieha to continue the digitising process but in a slightly different method. All the groups had to use one type of classification, which I did not know why, but it occurred to me that maybe we were to merge all the data captured to produce a land use map. We began by collecting data for the remaining areas and then walked through the area we had covered in the previous day. I guessed we were lucky because we did not have to change lots of data captured as most of the area was residential. We also decided to map all bunches as points. One of the problems we faced during the process was that, some vegetation area had no footpath or entrance and as such, we had to make use of Google map to distinguish between natural vegetation and agriculture. After this, we headed for a delicious meal in a local restaurant after which we went to the beach to join others who had retired earlier for the day. It was a happy moment as some of us played football while others went out for swimming. Things learned from exercise Trimble is not the best way to collect land use data due to the following factors: It was very hard to see the screen because of the sun glare. It takes very long to digitise a block due to the slow response of the screen touch. Trimble Juno crashed a lot. Most importantly working as group is always the best way to achieve quick results due to teamwork. Day 5&6 RTK We were the first group to experience the RTK Leica. However, we had a bit of slow start due to the signal strength although we were very close to the reference point. My assumption was that it was due to the wireless connection but however, we managed to get better signal after a while after which we started surveying the beachfront at Sliema. I was the first person from the group to experience the RTK and I found it relatively easy. It was impressing to note that the equipment contained high level of accuracy. However, we had limited time and as such, some of the members in our group did not have the chance to experience its usage. Generally, it would be true to say that the expedition offered us with an opportunity to experience mobile GIS, such that it would be easier now to apply it while writing my dissertation. GPS Assessment and wireless map It’s the last day in Malta, after brief instruction in the morning we went out to finish up with the last two tasks (GPS Assessment and wireless map). In order to accomplish the task in good time, we decided to split up into two sup groups. My colleague and I had to pick the quality of wireless in a specified area of Sliema. All we had to do was walk around every street in the specified area and record wirelesses signals using software known as the wireless agent. In the end, we managed to collect about 200 wirelesses signals, which was a great achievement for our group. It was one of the easiest tasks we had done for the entire trip. Having completed our mission in Malta, it was agreed that we would leave for UK early morning on the next day. After a morning session about the quality of GPS system and how it can be improved. The other sub group had to go and experience about the accuracy between the RTK and Trimble. Unfortunately, I did not experience the differences between the devises but from what was reported, the level of the GPS Trimble was far up to 5 meters. Reports formal writing Paper map VS GPS The aim of this report is to discuss the different approaches used in day one exercise and to answer the question; are paper maps more efficient than GPS devices. This is what I will be covering in the reports as well as their advantages and disadvantages. Paper map is the first type of navigation tool which has been used for centuries; Where as GPS is the new technology for navigation. The GPS has been in use since 1973 for military purposes to reconnaissance and surveillance by the U.S. Department of Defence and became available for civilian use in the early eighties. This system consists of 24 satellites revolving around the Earth at altitudes of approximately 20 km ASL. Advantages of paper map Paper map provides higher level of accuracy than GPS due to the visual appearance of features on the map. Following the direction in the paper map is easier than following a dot in the GPS. Paper maps do not need constant replenishment of power. Most of paper maps are free and downloadable of the internet. Paper maps can be used under any conditions as it is not affected by satellite signal strength. Disadvantages of paper map Paper map cannot be updated Paper map easily get damaged especially by environmental factors such as rain and fire Paper map does not have a compass and therefore, you will need to be experienced to locate the directions. Advantages of GPS Easy to carry and record tracks log which then can be downloaded to the personal computer and used for other purposes, even after long periods of time. Useful for water navigation since there are no landmarks in the sea. Disadvantaged of GPS The signal of GPS is not highly accurate as it can be interfered with or blocked by features such as trees, buildings. As a result an error of position can be up to 100 to 200 feet. Atmospheric conditions can also affect the GPS signal. GPS device requires a backup for batteries or a power source to keep navigating. Could end up in a dead end, due to lack of knowledge about topography, terrains and routes taken. There are number of factors affecting the accuracy of the system of GPS such as Multipath, Receiver Noise and much more. To sum up with walking around an area using a GPS device is a considerably slow process and makes a lot of errors, whereas using the GPS and paper maps together will provide enough accuracy as they can be used to back each other up in case of any failure. Therefore, using the GPS with paper map is recommendable. Melleiha Land Use Map This report is about Melleiha Land Use cover, the ideas to be mapped in this report are methods used, issues, solutions and finally produce as a group, a land use map for our area in Melleiha using the data captured in the field. The method used in this exercise was the most important. The idea was to collect as well as record information using the Trimble Juno but unfortunately, this method didn’t work out well because it was a very slow process of recording and the other reason is the limited time available. Therefore, my group and I decided to change the methods used from Trimble Juno to record information in notes and digitize the area afterward. Firstly we all agreed to use one type of geometry as well as one classification; building into five categories residential, public, commercial, abundance and under construction. Roads into two categories; side and main. Finally, vegetation was to be divided into three types of categories agriculture, abundance and natural. Using this method we managed to cover most of our area in a short period of time. The differences between the first and second days is all groups used on type of classification, which maybe later used to produce land use map for the entire area. The final part of the exercise was to transfer data captured from notes to the computer, which was quite simple and easy. A disadvantage of the methods (note) used was that some of the buildings were difficult to map. The other problem faced was that some area of visitation had no entrance or footpath, therefore a help from goggle map was required to distinguish between categories. In my opinion working as group will always overcome problems. Moreover the Trimble Juno is not the best method for digitizing due to the following factors. First, it was too difficult to distinguish between commands (point, line or polygon) in the screen because of the sun glare. Two the screen sensitivity was extremely hard to manage therefore, it took more time than expected to digitize a block. And finally it crashed often. Mash up exercise This report is about Valletta mash-up. The ideas to be mapped in this report are; methods used, issues, solution and finally to produce a mash-up map, as a group, which will contain photos, route taken and information for our area in Valletta using the data captured in the field. There have been a lot of changes in the idea since the start of this expedition. Our original idea was to map all public toilets in Valletta, but we had to abandon it after we realized on arrival that there were only two public toilets in Valletta, which could not offer much detail sufficient to complete our task. We therefore decided to venture into other ideas such as mapping all the attraction sites in the area as well as the best possible route that can be used by persons with disability to access these attraction sites. We also mapped all the benches we came across so as to give people an idea on where they can anticipate to have a rest if they opted to use our route. The methodology used involved recording street intersections and their gradients. For example: Republic Street from Archbishop to St John Street. Gradient is 1 Flat. Notes well maintained, shopping area, wide and clean, restaurant and full of tourism. This is how the street was mapped. The other method involved recording the tracks taken using both the GPS and the photos. One of the drawbacks of using these methods in some areas was that they proved tedious as there were a lot of steps to be followed and in order to avoid them a longer route had to be taken. The final part of the project is to produce the final output from the mash-up. One of the major problems we encountered in the production of the output was that some of the photos taken had been stored in wrong places, some even on the sea and in order to fix the issue it would have taken huge amounts of time. Therefore, my group and I decided to change the program used from GPicSync to other software, which would facilitate manual geo tagging. In the map, the street intersections were divided into 5 gradients and coloured differently in order to make it easy to identify the routes. Wi-Fi mapping This report is about Sliema Wi-Fi mapping. The ideas to be mapped in this report are methods used, decisions, process explanations and finally as a group to produce a Wi-Fi map which will contain graduated symbols that shows all Wi-Fi signals captured and the route taken. Wi-Fi is a mode of transferring information or data through unguided transmission, meaning that it is a wireless network. It is the most current and widely used technology in broadcasting and communication owing to the fact that it facilitates mobility as opposed to guided transmission. It has enhanced connectivity by facilitating internet connectivity on portable electronic gadgets such as laptops, mobile phones etc, which can now connect to the internet at dynamic remote locations. The task given was to use the technology of smart phones and capture Wi-Fi signals in the specified area of Sliema. Our strategy to tackle the task was quite simple and easy; all we had to do was to determine our location using a GPS and then walk in a straight line to the end of each street. The use of a smart phone that holds the program specialist (Wi-Fi Agent) in capturing the Wi-Fi signal was required for the fulfillment of this objective. One of the important steps we were required to follow was to stop the program every 20 minutes and rerun it again so as to save the portion of the work captured through out this time. In addition, we had to be prepared for any unexpected occurrences such as program failure, which would have meant more time allocation or in the worst condition, loss of data. This we came to realize as we were concluding the task after we failed to rerun the program as required, a mistake that resulted to the total crashing of the file we were working on and which turned out to be a major disappointment. The last stage was to analyse information taken from the field and then transfer it to a computer. The data was to be installed into ArcGIS and cleaned in order to show coordinate positions of each signal as well as strength and finally determine whether it was locked or free. RTK Surveying This report is about Sliema RTK Surveying. The idea to be mapped in this report consist of two parts; To produce a map of data captured from the field in ArcGIS which must be cleaned, symbolised and annotated. The other part is an assessment on the strengths and weaknesses of the RTK system. The RTK is an acronym for (Real Time Kinematic) and is mainly used in land surveying. This is a technology that came into use in the early 1990s after which it has continued to gain popularity in this field of survey. The fundamental concept behind the RTK is that you have to have a receiver base station set on a known point. Secondly, the data captured is sent to and corrected by the surveyor operating the rover unites. It is important to note that this data is sent via a wireless network. RTK system allows topographic surveying to be more efficient and accurate as such surveys have been noted to maintain a standard error ranging from approximately 0.02 to 0.05 as long as the user remains within the signal perimeter and when not, the user receives a warning on the screen when the error is more than 50 cm. Therefore, the user must record several numbers of control points in order to improve the accuracy of the rover unit. However, technology is dynamic and as such, the future of these technologies and their accuracy may improve greatly with time thus making it more efficient and dependable. The major advantage of the RTK system is repeatability. Control point. Read More