Saturday, November 2, 2013


Application of geospatial technologies in freshwater resource management

Ying Bo Wang1

1RMIT University, Melbourne VIC 3001, Australia

Unless otherwise indicated, diagrams included in this report were created by Ying Bo Wang, RMIT University 2013

Abstract
Freshwater is a limited resource and faces global issues arising from pollution, ever-growing consumption and climate change. To help each country manage their freshwater supply, it is important to first establish a knowledge base and subsequently, analyse the collected information. Geospatial technologies such as hydrography, Global Navigation Satellite Systems (GNSS) and satellite remote sensing are used to collect data about various water bodies while Geographic Information System (GIS) is used to store and analyse this information. This paper gives an overview of how each technology is used in freshwater management, examine its advantages and disadvantages and explore its future possibilities. While hydrography and GNSS play small but important roles in freshwater management, satellite remote sensing and GIS are critical aspects due to their irreplaceable role. No other technology currently exists that can work on such a large scale and so quickly. An underlying theme for these geospatial technologies is their need for expert users to operate. In the future, there will be an increase in user-contributed hydrography, better positioning solutions, more complete satellite imagery of Earth and better datasets to be integrated within various GIS. By giving a brief summary of each geospatial technology; this paper will contribute to future research on similar topics.

Key words: geospatial, freshwater, resource

Introduction

Freshwater is a scarce resource as it is limited. According to a report by United Nations (2012), there are 35 million cubic kilometres of freshwater on Earth, which is 2.5% of the world’s total volume of water (see Figure 1). Within that 2.5%, it is broken down into the categories of ice/snow (70%), groundwater (30%) and rivers/lakes (0.3%) (see Figure 2). Groundwater refers to groundwater basins, soil moisture, swamp water and permafrost. The report notes that the total usable freshwater for humans and the ecosystem is 200 thousand cubic kilometres. This is made up from the rivers/lakes portion and some of the groundwater.

Figure 1: Total World Water breakdown
Figure 2: Freshwater Breakdown

The importance of freshwater for human livelihood is due to its role in drinking, sanitation, agriculture, research, industry and recreation. While humans technically only need freshwater for drinking and agriculture to survive, for quality of life, the other uses of freshwater is critical too. Additionally, freshwater sources play a big role in international politics. A specific example would be a shared river between countries (see Figure 3). If country X pollutes the water upstream, country Y would have to deal with the consequences downstream. United Nations Educational, Scientific and Cultural Organization (2012) states that “148 countries include territory within one or more transboundary river basins”. A prime example of a transboundary river basin is the Nile-Kagera river (see Figure 4), which the countries of Rwanda, Burundi, the Democratic Republic of Congo, Tanzania, Kenya, Uganda, Eritrea, Ethiopia, Sudan and Egypt share.
   
Figure 3: Countries sharing a river basin.

Figure 4: Nile-Kagera River. Source: http://www.unesco-ihe.org/stories/networking-nile

The main issues for the freshwater resource are pollution and the need for a sustainable solution in the near future. Pollution refers to the act of contaminating the freshwater supply through human actions that degrade the quality of the freshwater, such that it is no longer drinkable. Pollution of freshwater has a direct impact on agriculture and subsequently, the food supply of people. This could also lead to political repercussions, in the case of shared freshwater sources between nations. The need for a sustainable solution refers to the prediction that based on current usage rates of freshwater, there will be not enough freshwater for humans. According to a report by United Nations Educational, Scientific and Cultural Organization (2012), in developing countries, up to 90% of wastewater flows untreated into their freshwater supply. In the same report, it is stated that based on current human population growth and water consumption rates, that by 2025, 1.8 billion people will be living in regions with absolute water scarcity and two-thirds of the world population could be under stress conditions. Another issue would be the effect of climate change on freshwater supplies. A warmer global average temperature could change the freshwater distribution across the world, due to change in rainfall in some areas, ice caps and permafrost melting and more snow melting from the mountaintops.

To develop a sustainable management solution to deal with these main issues, it is first necessary to collect data. After the collection of data, information on how to deal with these issues can be further derived. To collect data on water resources, geospatial technologies can be applied to great effect. Geospatial technologies used are hydrography, Global Navigation Satellite Systems (GNSS), Geographic Information System (GIS), and satellite remote sensing.

This paper will (i) give an overview of each geospatial technology; (ii) examine its benefits and limitations; and (iii) discuss its future applications.

Discussion

Hydrography
Overview
Hydrography is the science of mapping the sea floor. Hydrographic maps are produced from hydrographic surveying. Ingham (1992) states that the objective of hydrographic surveying is to represent the relief of the seabed, including all natural and man-made features. In general, there are two methods to do this; boats using sonar and airplanes using Light Detection and Ranging (LiDAR) (see Figure 5).

  
Figure 5: Sonar bathymetry (top) and Airborne LiDAR bathymetry (bottom). Source: aeromapss.com (bottom)

Figure 5 above shows the basics of using ship sonar. The hydrographic transducer, which is hung from the bottom of the boat, emits and detects the sonar the return to calculate the depth of the sea floor. On top of the ship, with a good clear view of the sky, sits the GNSS receiver, typically one that receives Global Positioning System (GPS) signals. The ship’s GPS receiver, together with a land-based base receiver, can determine the ship’s position up to 10 metres (95% of the time) (Australian Maritime Safety Authority 2007). To account for the ship’s pitch and roll, which will affect the sonar returns, accelerometers are used. Local tide tables are used to account for the influence of the tide and known reference datums are used while mapping. A computer on-board the ship will keep track of all this data.

LiDAR works on a similar principle to sonar, emitting light pulses and measuring the subsequent returns to measure distance instead of using sound. The laser scanner, which is mounted at the bottom of the aircraft, emits and detects near-infrared and green laser pulses. Modern LiDAR systems can measure up to 5 returns per pulse (Weng 2012). Green light possess a shorter wavelength, which allows it to penetrate through the water body to reach the solid seabed, while near-infrared light has a longer wavelength, which cannot penetrate the surface of the water body. The near-infrared surface return will measure the distance to the water surface while the green bottom return will measure the distance to the seabed. The difference between these two distances will be the depth of the water body at that point. Similar to ships using sonar, there are various instruments and techniques to determine and keep track of the aircraft’s position, pitch and roll.

Benefits and limitations
Through hydrography, hydrographic maps with depth soundings are produced (see Figure 6). With these maps, organizations can roughly estimate the volume of water in the waterbody. Additionally, these maps are accurate enough to be used together with other cadastral maps to determine which parts of the water body lies within which country’s borders. Hydrography can be considered a cornerstone of freshwater studies. GNSS, GIS and remote sensing are all relatively new techniques that started development post-World War 2 while hydrography has existed for much longer. A limitation of hydrography is that it is labour intensive, requiring many hours of field work and data processing for each map. The main advantage is its integration with other cartographic maps, while other digital forms of data might not be so easy.

Future applications
There will most likely be an expansion of crowd-sourced hydrographic data, where the information is volunteered by users rather than produced by a company. An example is the Teamsurv website. Like OpenStreetMap, where users volunteer their time to map streets and features, sailors can upload their sounding data to a single database while they are fishing or transporting goods. It arises due to several factors, which include cheaper technology and greater demand for more hydrographic data than professional companies can supply. An issue with crowd-sourced hydrography is the possible lack of authority and loss of accuracy. However, this could be a relative issue as not all users need high accuracy data for their purposes. The idea is to have some “poor”-quality data rather than no data at all.

Figure 6: Hydrographic map of surroundings at Headlam Point, Rakhine, Myanmar. The small numbers represent depth at that point while the curved lines are contour lines. Source: fao.org

GNSS: GPS

Overview
GNSS refers to a satellite system to determine a user’s position accurately worldwide. GPS is the system designed and operated by the United States Department of Defense. Typically, GPS Standard Positioning Service (SPS) will give a position solution with an accuracy of 15 metres. There are techniques to improve this accuracy, most common of which is differential GPS (DGPS). DGPS is commonly used to determine the boat or plane’s position in hydrography. In an ideal situation, DGPS solutions can give accuracies of up to 2 to 4 metres (Australian Maritime Safety Authority 2007).

Referring to Figure 7 below, DGPS calculates the position of the rover receiver, relative to the base receiver. Both the base and rover receivers must track the same satellites for the same time period and must remain within a certain distance with each other (usually 15 kilometres). The base receiver is usually setup on a known point. The idea is to negate the most common errors, including atmospheric error, satellite clock error and satellite orbit error. To facilitate users of DGPS, organisations and companies have setup networks of Continually Operating Reference Station (CORS). These CORS networks will function as the base receiver to the user’s rover receiver. Examples of CORS networks include Singapore Satellite Positioning Reference Network (SiReNT), Wide Area Augmentation System (WAAS) and OmniSTAR. Additionally, all GPS position solutions have a time stamp, so it is possible to measure the flow velocity of a river by attaching a buoy and allow it to drift with the river.

Figure 7: DGPS concept

Benefits and limitations
GPS is mainly used as a tool to determine position in the field, for studies involving freshwater resources. It is also used as a navigation tool. GPS is a minor technology in the study of freshwater resources as it has no direct application to manage freshwater. The main benefit of GPS is its global coverage and it operates all the time. The main limitation is that to achieve a higher accuracy using DGPS, the user will have to stay within 15 kilometres of a base station, setup on land. This means that DGPS cannot be used in remote areas with no reference station or areas far away from the coast. For example, scientists taking data at a freshwater lake in the middle of the mountains, with no reference station nearby, would have no DGPS service to determine their position. They would have to settle for the SPS solution, which gives an accuracy of roughly 15 metres.

Future applications
Figure 8: PPP concept

The next frontier for GPS techniques would be the development of real-time Precise Point Positioning (PPP). PPP uses accurate orbital data and accurate satellite clock data to build models for calculating a single receiver’s position (Witchayangkoon 2000, p2). The lone receiver can be either single- or dual-frequency, with no need for an additional receiver to be a ‘base’ station like in DGPS (see Figure 8). Currently, single-frequency PPP can achieve accuracies of several metres (Chen and Gao 2005). There are ongoing research efforts into achieving centimetre accuracy using only a lone single-frequency receiver, in real-time. If this is achieved, positional accuracy in freshwater studies will certainly improve. Currently, there are only 2 functional GNSS which are GPS and the Russian Federation’s Global Navigation Satellite System (GLONASS). In the future, additional GNSS like BeiDou Satellite Naviation System (BDS), operated by People’s Republic of China, and GALILEO, operated by The European Union, will be operational. Receivers that read these multiple GNSS signals will have an improved solution, as compared to a receiver that can only read signals from a single GNSS.

Satellite Remote Sensing

Overview
Figure 9: Passive Remote Sensing. Source: http://www.crisp.nus.edu.sg/~research/tutorial/optical.htm

Remote sensing is the science and technology of acquiring information about Earth’s surface and atmosphere using sensors aboard airborne or spaceborne platforms (Weng 2012). Satellite remote sensing is the measurement of reflected radiation, radiation that is either the Sun’s (passive) or radiation that is emitted by the satellite (active) (See Figure 9). Examples of satellites that focus on observing water bodies include Aqua, Ocean Surface Topography Mission (OSTM), Oceansat-2 and Aquaris. As water can reflect and absorb energy, remote sensing can be applied to water bodies. In Figure 10 below, it is shown that water’s reflectance is between 0.4 and 0.7 micrometre. Reflectance readings of water can be used to infer the presence of organic and/or inorganic material in the water. Water with a large amount of suspended sediment present will have a higher reflectance compared to clearer waters (University of Calgary 2013). Factors that have a direct influence of the reflectance of water include suspended sediment in water, turbulence, chlorophyll content and temperature.

By looking at the reflectance data and correlating it, users can indirectly estimate levels of organic or inorganic material. Turgeon et al. (2013) observed that they were able to correctly predict the general level of fecal contaminants 85% of the time in water. The general workflow for such a project is to (i) collect ground truth in a small area and satellite images over a large area; (ii) Use a majority of the ground truth to create a model. This model will correlate reflectance and the material you are interested in, for example: pollutants; (iii) Test the model using some of the ground truth values that were set aside at the start of the project.

Additionally, remote sensing can be used to map large bodies of water. Using satellite imagery, Peregon et al. (2009) managed to create an inventory of the wetlands of Western Siberia, as well as establish the spatial distribution of various wetland classes.

Figure 10: Spectral reflectance for vegetation, soil and water. Source: http://www.ucalgary.ca/GEOG/Virtual/Remote%20Sensing/reflectance.gif

Benefits and limitations
Before satellite remote sensing was developed, users had to solely rely on aerial photography to get a synoptic view of water bodies. Additionally, aerial photographs were analog data in the form of pictures and only had information in the visible wavelength. Remote sensing provided digital data and information outside the visible wavelength. As freshwater bodies can span dozens kilometres in length, satellite remote sensing is very useful in mapping the horizontal area of the water bodies. This gives organizations a good idea of the volume and extent of water that they are dealing with. Equally important is the use of satellite imagery to observe levels of organic and/or inorganic material in the water. Satellite remote sensing is very important to the field of freshwater studies. This is because of (i) its timely coverage, where the satellite will pass over all areas frequently; (ii) synoptic overview of the area; and (iii) efficient data acquisition, as compared to regular field work. Its main limitations are the huge expense needed to build and operate satellites and the need to have experts to interpret the raw data. Such experts need to know the theory of how remote sensing works, local knowledge of the area and knowledge of uncertainties in measurements.

Future applications
There are currently plans to launch more satellites to observe the Earth’s surface and atmosphere. They will replace the older satellites, giving equal or better spatial and spectral resolution. Examples of upcoming satellites include the ASANARO and GCOM-C1. There is also an ongoing initiative called the Global Earth Observation System of Systems (GEOSS) that combines and disseminates multiple countries’ satellite data (Normile 2004). The concept is similar to how the Internet is a network of networks, where all the information on various networks is accessed from a single entity. By pooling all this data together, the goal is to build a more complete picture of Earth. Subsequently, this gives a better observation of Earth’s freshwater supply.

Geographic Information System (GIS)

Overview
‘A geographic information system (GIS) is a computer system for capturing, storing, querying, analyzing, and displaying geospatial data.’ (Chang 2012). GIS functions as a digital framework to store and work with all the spatial and attribute data. This includes data about freshwater bodies, like location, area, depth, reflectance, temperature, flow velocity, etcetera. It can also be used to perform flood forecasting.  Liu et al. (2004) built a model that combines soil, elevation and land use data within a GIS and predicts the flood hydrograph over a river basin.

The most prominent example of GIS is the ArcGIS product from Environmental Systems Research Institute (ESRI). Besides ArcGIS, there are other GIS products in the market, some of them being freeware. Among these, MapWindow (See Figure 11) is particularly interesting as it is used by the US Environmental Protection Agency, due to its watershed analysis and modelling capabilities.

Figure 11: MapWindow GIS displaying Idaho Falls, Indiana. Source: http://mapwindow4.codeplex.com/wikipage?title=MW4GIS

Various organizations have built their own GIS to suit their needs. An example is the Australian Bureau of Meteorology’s Geofabric (See Figure 12). It is an Australia-wide GIS that combines Landsat imagery, cartographic maps, a digital elevation model (DEM) and multiple networks. One of the more interesting products from Geofabric is the Topographic Drainage Divisions and River Regions map. It shows the water drains and flows across the whole of Australia.

Figure 12: Geofabric GIS, displaying the Australian country. Source: http://mapconnect.ga.gov.au/MapConnect/Geofabric/

Benefits and limitations
Before GIS, users had to use transparency sheets and overlay them over paper maps and aerial photographs. With GIS, users could match various attributes to their spatial data, model simulations, had improved database organisation, ability to integrate other data sources easily and much faster to respond to queries and toggling of data than just using transparencies (Lyon 2003). GIS is well suited for the management of water data, as are all resources. The main limitation of GIS is its need for expert users. Users need to have basic knowledge of cartography and the ability to integrate various data sets, which may not have the same format or coordinate system. Local expert knowledge of the area is not necessary but would be very helpful.

Future applications
The next phase for GIS would be moving from the desktop environment to a cloud-based environment. This means that the GIS would not be installed on the desktop directly; rather the users would access the GIS through the Internet. An example would be ArcGIS Online. Users can create maps and do basic analysis on ESRI’s servers without the need to install ArcGIS. In the future, a complete GIS with advanced analysis capabilities could be available. In addition, more and better quality datasets could be integrated into existing GIS. This could improve the accuracy of the analysis operations within GIS. An example would be Geofabric’s plans to replace their 9-second DEM with a 1-second DEM. This improved DEM would lead to the borders of the Topographic Drainage Divisions and River Regions map to be more accurately defined.


Conclusion
With pollution, ever-growing consumption of freshwater and climate change, there is a strong need for sustainable management of every country’s freshwater supply. Geospatial technologies can be used to help achieve this purpose. They can collect, store, display and help analyse the freshwater data. As such technology becomes cheaper, there will be a lower barrier, allowing more users to use geospatial technologies to manage their freshwater resource. Another geospatial technology that was not covered in great detail is aerial photography.


References
Australian Maritime Safety Authority 2007, Differential Global Positioning System (DGPS) Fact Sheet, viewed 01 Nov 2013, http://www.amsa.gov.au/forms-and-publications/Fact-Sheets/DGPS_Fact_Sheet.pdf

Chang, Kang-tsung 2012, Introduction to Geographic Information Systems, 6th edition, McGraw Hill, New York

Chen, K and Gao, Y 2005, ‘Real-time precise point positioning using single frequency data.’ Proceedings of ION GNSS-2005, pp.1514-1523.

Ingham AE (eds) 1992, Hydrography for the surveyor and engineer, 3rd edn, Blackwell Scientific Publication, Oxford, Boston

Liu, YB, Smedt, FHD, Hoffman, L & Pfister, L 2004, ‘Parameterization using Arcview GIS in medium and large watershed modelling‘, GIS and Remote Sensing in Hydrology, Water Resources and Environment (Proceedings of ICGRHWE held at the Three Gorges Dam, China, Sep 2003), IAHS Publ. 289, Wallingford.

Lyon, John G. 2003, GIS for Water Resources and Watershed Management, 1st Edition, Taylor & Francis, New York

Normile, D 2004, ‘Summit pledges global data sharing.(Earth Observation)(Global Earth Observation System of Systems)’, Science, vol. 304(5671), pp. 661(1).

Peregon, A, Maksyutov, S & Yamagata, Y 2009, 'An image-based inventory of the spatial structure of West Siberian wetlands', Environmental Research Letters, vol. 4, no. 4, viewed 01 Nov 2013, http://iopscience.iop.org/1748-9326/4/4/045014/fulltext/

Turgeon, P, Michel, P, Levallois, P, Ravel, A, Archambault, M, Lavigne, M, Kotchi, SO and Brazeau, S 2013, ‘Assessing and monitoring agroenvironmental determinants of recreational freshwater quality using remote sensing’, Water Science & Technology, vol. 67, no. 7, pp. 1503-1511.

United Nations 2012, United Nations Environment Programme 2012 Annual Report, viewed 01 Nov 2013, http://www.unep.org/pdf/UNEP_ANNUAL_REPORT_2012.pdf

United Nations Educational, Scientific and Cultural Organization 2012, World Water Development Report (WWDR4), 4th Edition, viewed 01 Nov 2013, http://unesdoc.unesco.org/images/0021/002156/215644e.pdf
University of Calgary 2013, Water and Remote Sensing, viewed 01 Nov 2013, http://www.ucalgary.ca/GEOG/Virtual/Remote%20Sensing/rswater.html

Weng, Q 2012, An introduction to contemporary remote sensing, 1st edn, McGraw-Hill, New York

Witchayangkoon, B 2000 ‘Elements of GPS precise point positioning’, PhD dissertation, University of Maine, United States.

Precise Point Positioning and its implications

Ying Bo Wang1
1RMIT University, Melbourne VIC 3001, Australia
Unless otherwise indicated, diagrams included in this report were created by Ying Bo Wang, RMIT University 2013

Introduction
In the past, Point Positioning and Differential DGPS positioning have been predominantly used for mapping and geodetic positioning respectively. However, a relatively new technique referred to as Precise Point Positioning (PPP) has been introduced and promises to improve and replace Point Positioning (Holden 2013b). This paper aims to investigate this claim as well as PPP’s effects on DGPS usage. It will (i) go through key concepts behind Point Positioning, DGPS and PPP and (ii) compare PPP against Point Positioning and DGPS.
The techniques in this report are described in the context is in the United States Department of Defense’s Global Positioning System (GPS). However, the key concepts behind each technique can be applied to GLONASS, GALILEO or any other Global Navigation Satellite System (GNSS).

Point Positioning
Point Positioning is the basic way of determining a receiver’s position through use of the C/A (Course/Acquisition) code and the broadcast navigation message. The broadcast message contains the GPS date and time, the broadcast ephemeris and the almanac. Hofmann-Wellenhof, Lichtenegger and Walse (2008) state that the almanac is to help the receiver acquire the satellite while the broadcast ephemeris is to compute a reference orbit for the satellites. It requires a minimum of 4 satellites to generate 4 different pseudo-ranges to the receiver. This is represented by Figure 1 below. From there, the position of the receiver (X, Y, Z coordinates) will be calculated with a horizontal accuracy of approximately 10 metres.

Figure 1: Point Positioning using 4 satellites
The main limitation of Point Positioning is its poor accuracy, due to not accounting for the receiver clock error, satellite clock error, satellite orbit error and atmospheric errors. This makes it unsuitable for applications that require very accurate positions, like cadastral surveys. The advantages are that it only requires tracking a single frequency, L1 for GPS signals, and a low-cost handheld GPS unit. The position solution is also very quickly derived, making it real-time.

Differential Positioning using PRN code (DGPS)
Holden (2013a) asserts that “DGPS” is differential positioning using pseudo-random (PRN) code while “Differential Positioning” refers to differential positioning using carrier signals. The focus in this report will be DGPS.
DGPS calculates the position of one receiver, termed the rover, relative to another receiver, termed the base. The base receiver is set up on a point with known coordinates, like a survey mark. Knowing the true coordinates, the base receiver will then apply corrections to the rover receiver (Australian Maritime Safety Authority 2013). These corrections remove the receiver clock error and atmospheric errors, bringing the horizontal accuracy of measurements to 2-3 metres. Both receivers must track the same satellites during this time and must not be separated by more than 10 kilometres.

Figure 2: Key concept behind DGPS
Holden (2013) states that DGPS can be applied to either static receivers, whose data is differentially post-processed, or in-motion receivers, whose differential corrections are applied real-time. To facilitate DGPS, various companies and government agencies have set up Continually Operating Reference Systems (CORS). CORS is a network of GNSS receivers that are in a fixed location, and function as base receivers. Users would acquire the CORS data for the base station that suits their survey, and differentially process with their rover measurements (Holden 2013).
The main limitation of DGPS is that it requires 2 separate receivers at 2 different locations, where one location is a point with known coordinates. This could be an issue in areas with low number of established survey marks. These 2 receivers must also be tracking the same satellites for the same time period. If either of the 2 receivers loses the satellite signal, the rover’s position for that time epoch cannot be differentially processed.


Precise Point Positioning (PPP)
PPP uses accurate orbital data and accurate satellite clock data to build models for calculating a single receiver’s position (Witchayangkoon 2000, p2). The lone receiver can be either single- or dual-frequency, with no need for an additional receiver to be a ‘base’ station. This is illustrated below in Figure 3.

Figure 3: Key Concept behind PPP
Using precise International GPS Service (IGS) orbit and clock products, Kouba and Héroux (2001) found that global centimetre-level accuracy was possible with a dual-frequency lone receiver. The overall process can be illustrated below in Figure 4. A similar accuracy can also be achieved in real-time, with a dual-frequency lone receiver (Chen 2004).

Figure 4: PPP workflow
The main difference between single- and dual-frequency PPP is the fact that single-frequency PPP does not account for ionospheric effect. This traditionally results in single-frequency PPP to achieve an accuracy of several meters while dual-frequency having centimetre accuracy (Chen and Gao 2005). There are several ongoing research efforts into achieving centimetre accuracy using only a lone single-frequency receiver, in real-time. When this is achieved, the effect could be as significant as when United States turned off Selective Availability in May 2000 (Holden 2013).

Analysis
Currently, most asset mapping GPS surveys use the DGPS technique along with a lone single-frequency receiver. The DGPS technique will provide the required accuracy with an acceptable amount of cost. Even with PPP refined to real-time centimetre-level accuracy, the field work for asset mapping would remain the same. The user would still have to go into the field to collect data with a single-frequency lone receiver. The key difference is that now, the user could conduct the survey almost anywhere in the world, without regard to where the base station is. Another important advantage is that PPP’s position solutions are referred to a global reference frame, as compared to being relative to the local base station (Gao 2006).
If and when high-accuracy real-time single-frequency PPP is achieved, DGPS use could be reduced. This is because PPP does not require a base station and if the base station is a CORS network, the user need not pay for the base station data. However, as suggested by Bisnath and Gao (2008), since DGPS and PPP function independently, they could serve as mutual integrity checkers. Additionally, in urban areas where CORS networks and other base stations are already well-established, DGPS might still be used. In this way, DGPS would still serve a purpose, albeit maybe a reduced one.  In remote areas lacking CORS networks, PPP would probably be the preferred technique as no base station would be required.
Rizos et al. (2012) argues that since CORS networks provide a large role in providing the corrections required to achieve real-time centimetre-level PPP results, the need for CORS networks will not disappear. This could mean that in the future, within urban environments, PPP would be used to complement the DGPS technique instead of replacing it.
Once real-time single-frequency PPP is achieved, it seems that PPP would replace Point Positioning. This is due to PPP providing a more accurate position solution than Point Positioning with no obvious disadvantages.

Conclusion
Point Positioning uses C/A code to determine the receiver’s position. It includes receiver clock error, satellite clock error, satellite orbit error and atmospheric errors. DGPS accounts for these errors by having 2 separate receivers tracking the same satellites. PPP uses precise clock/orbit data along with a single receiver to obtain similar accuracy to DGPS. PPP would not completely replace DGPS as the CORS network is still important, especially in urban environments. PPP will provide a better position solution than Point Positioning in nearly all circumstances. With real-time high-accuracy PPP, asset mapping GPS surveys would no longer be restricted to always being within 15 kilometres of a base station.

References
Australian Maritime Safety Authority 2013, ‘Differential Global Positioning System’, viewed 02 Oct 2013, http://www.amsa.gov.au/navigation/services/dgps/
Bisnath, S & Gao, Y 2008 ‘Current State of Precise Point Positioning and Future Prospects and Limitations’ Observing our Changing Earth International Association of Geodesy Symposia, vol. 133, pp.615-623.
Chen, K 2004, ‘Real-Time Precise Point Positioning and Its Potential Applications’, Proceedings of ION GNSS-2004, pp. 1844-1854.
Chen, K and Gao, Y 2005, ‘Real-time precise point positioning using single frequency data.’ Proceedings of ION GNSS-2005, pp.1514-1523.
Gao, Y 2006 ‘Precise Point Positioning and Its Challenges, Aided-GNSS and Signal Tracking’ GNSS Solutions, November/December 2006, viewed 02 Oct 2013, http://www.insidegnss.com/auto/NovDec06GNSSSolutions.pdf
Hofmann-Wellenhof, B, Lichtenegger, H & Wasle, E 2008, ‘GNSS – Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and more’ 1st Edn, Springer-Verlag Wien, Austria.
Holden, L 2013a, ‘GNSS III’ Lecture Notes, GEOM 2066, RMIT, Australia.
Holden, L 2013b, ‘Postgraduate extra assessment’ Assignment Handout, GEOM 2066, RMIT, Australia.
Kouba, J and Héroux, P 2001, ,Precise point positioning using IGS orbit and clock products.’, GPS solutions, Vol 5, no. 2, pp. 12-28.
Rizos, C, Janssen, V, Roberts, C & Grinter, T 2012 ‘Precise Point Positioning: Is the era of differential GNSS positioning drawing to an end?’, Proceedings of FIG Working Week 2012, 6-10 May 2012, Rome, Italy
Witchayangkoon, B 2000 ‘Elements of GPS precise point positioning’, PhD dissertation, University of Maine, United States.

Management and inventory of control points using Geographic Information System

Ying Bo Wang1

1RMIT University, Melbourne VIC 3001, Australia

Abstract
Surveying companies traditionally store their control point data in separate files and only access this information based on what the staff has remembered about them. GIS provides a potential solution by providing a framework for users to access their past control points in a geospatial context, along with attribute data. This application has been applied to Singapore. Two different pre-existing data sets were used; one is a road network shapefile that functions as a basemap in the GIS while the other is a Microsoft Excel file that provides the attribute data for the control points. Overlaid on top of the road network is a point shapefile that locates where each group of control points are. With this application, users are able to quickly and accurately find control points of interest, with little degradation over time. This application shows how GIS could possibly be used in the more general area of asset management, especially assets with a spatial component.

Keywords: Singapore, Control Point, Geographic Information System, Geospatial, Asset Management, GIS, ArcGIS

Introduction

In the surveying industry, it is important to know where the previously established control points around a job site are, as it would allow surveyors to use these control points to do their surveys without the need to setup new ones. This will lead to a reduction of pre-survey work and would expedite the surveying workflow. In Singapore, this is especially critical as the land area is only 714.3 square kilometres for the entire country (Land Transport Authority 2013). For companies that have done years of surveying work, an overlap of a new job site with old job sites is practically a given.

In the past, the method to store and retrieve information regarding the location of the control points was done by pure rote memorisation. Over the years however, it is difficult to remember all the jobs performed at various locations around the country. This is further exacerbated by the fact that there will be turnover in staff, which inevitably leads to loss of such information. This has led to cases where the field surveyors have forgotten or remembered wrongly where their old control points were and they have had to create new control points, only to find their old control points afterwards. This was a case of wasted man-hours and resources that a company, J K Foo Consortium Pte Ltd., wanted to address.

Geographic Information Systems (GIS) is appropriate in this situation as all the control points have an inherent location. In fact, all the control points have coordinates in the SVY21 co-ordinate system, making it simple to place them on the same layer. While all the control points are on the same layer, it is easy to locate the control points of interest (those near the current job site) by eye. Everything up to this point could still be done with a paper map. But a GIS provides additional functions not possible with a paper map. GIS allows attribute data to be attached to the spatial data. This allows the user to perform spatial or logical queries to return the control points the user requires.

The purpose of this assignment is to discuss the utilisation of GIS to manage surveying control points. The application chosen is an ArcMap Document (.mxd) file that contains two layers, a shapefile layer that contains all the jobs and a basemap layer. The product is a shapefile layer created and accessed using ArcGIS. The shapefile could also be read with other free GIS, like Quantum GIS (QGIS) or ArcReader. This shapefile contains the jobs’ locations that a surveying company undertook in its years of business in Singapore. Each job entry in the shapefile would be given a coordinate from a representative control point. Further exploration of a particular entry would lead to additional information related to the job. This was accomplished with hyperlinks in the shapefile. This assignment also looks at the methodology to produce products needed and discusses the limitations of such an application.

Material and Methods

Data
The data set used consists of a basemap shapefile and a Microsoft Excel document. The shapefile contains the street network of Singapore, dated around 1997. It had no attribute data, just a collection of lines. This data was produced and owned by J K Foo Consortium Pte Ltd as a product of one of their past jobs for Singapore Land Transport Authority. The road network was produced in SVY21 coordinate system. Heywood, Cornelius and Carver (2006) state that ‘The purpose for which a spatial data set has been created will influence the quality and spatial detail provided by the data set.’ As this shapefile only consists of the road network, it did not cover the forested areas, nature reserves, water bodies, airports and military camps of Singapore. Thankfully, as Singapore was highly urbanised, with public roads covering roughly 5 kilometres per square kilometre of the land area, this was not a big impediment (Land Transport Authority 2013). This road network shapefile, shown below in Figure 2, was used as a basemap layer of Singapore. Users are expected to be able to identify the various addresses of Singapore through their knowledge of the road network shape. This could be supplemented by using a road directory map book.

Alternatively, it was considered to buy an updated vector shapefile of the roads from Singapore Land Transport Authority or Singapore Land Authority. It was also possible to buy a raster layer of Singapore. Other data sources considered include satellite images and aerial photographs. However, these options were mooted by the company as they felt the road network they possessed, combined with their expert local knowledge and the onemap.sg website, was sufficient to locate all locations in Singapore. The company felt there was no need to spend additional resources to procure a more complete basemap.

The Microsoft Excel document was the surveying company’s file that contains all the necessary attribute data related to their jobs. This includes Job Number, Lot Number, Road Name, Client, and etcetera. This document will provide the attribute data that will be linked to the spatial locations of each job location.

Methodology
The company only had one copy of ArcMap 10.0 that can create and edit the shapefile and attributes. ArcReader, a free version of ArcMap, was used by other members of the company to view the application. This meant that after every new edit of the job shapefile, the user would have to publish a new Published Map Documents (.pmf) file for use with ArcReader.

Figure 1: Concept behind application

The road network shapefile was originally designed for viewing in ArcView3.1. Some steps were taken in ArcCatalog to ensure the road network shapefile could be used in ArcMap 10.0. This road network layer would be used as the basemap. Next, a new vector point shapefile was created to display the locations of each job, as well as list out the various attributes associated with each job. Each record was located on the basemap and given a Job Number attribute. Conceptually, this is shown above in Figure 1. Following that, a join operation was performed in ArcMap to link the Microsoft Excel file with the spatial locations of the jobs. The key used to join them was the Job Number field.

The data model used in this application was a vector shapefile. Chang (2012) states that discrete spatial features are represented as points, lines and polygons using points with x-, y-coordinates in the vector data model. The data generated in this application were discrete points with coordinates, which makes it suitable for the vector data model. The alternative would be to use a raster layer. If a raster layer was used, it would bring up several issues. Firstly, the spatial resolution of each cell in the raster layer would have to be determined. This presents its own questions as how to handle multiple jobs within the same cell. Secondly, each time the raster layer had to updated, the user would have to locate the correct cell, and then edit the raster data in a different window. Overall, a vector data model is easier and more efficient for this application as the data is discrete in nature.

Additionally, a Hyperlink attribute was added to the Job Location shapefile. This would allow any user to access additional information related to the job. Finally, when the user was satisfied with editing, he/she would create a .pmf file to be distributed among the company’s internal server for all employees of the company to view the application on ArcReader. The final application displayed would be similar to Figure 2 below.
 Figure 2: Road network of Singapore with example control points, displayed in ArcMap 10.0

Results

Upon opening the application, any user would be able to locate his/her new job site and recognise which of the old job sites nearby could be of help to him/her. LeBoeuf, Dobbins and Abkowitz (2003) had asserted that ‘certain relationships and operational trends are more easily conveyed in a geographic context than in a traditional tabular format’. In this case, a field surveyor not familiar with the area could look at the map and visually identify locations, rather than using text addresses that held no significance to the surveyor. Information about the old job sites could be found out by using the Identify tool in ArcReader. The user could also drag a box around multiple features to obtain their attribute information.


Figure 3: Identify window for a job entry in ArcReader

The user could also perform a search or a logical/spatial query to return the jobs he/she was interested in. This was done using the Find tool. Specifically, the most common query is to perform a search in the Road Name field of the control point layer. The user would put in a search that would return all job entries that matched the road name the user typed. From there, the user would be able to zoom in to the location of interest. A similar query could be done in the other fields, assuming the user had expert knowledge on what was required. The user could also input a specific X, Y coordinate and pan to that location to search for nearby jobs.

Additionally, the user could use the Hyperlinks tool to link to folders on the company’s servers. This allowed the user to jump to the folder containing a list of coordinates of all the control points used for this particular job, control point sketches, photographs and related documents for the job.

Discussion

With the current application, users can find, identify and use hyperlinks to job locations of interest. This must all be done at a local workstation. The next step would be to develop a mobile product, such that users can access this application even out in the field. Within the ArcGIS 10 System, there is the ArcGIS Server product that could be utilised for this purpose. Alternatively, an offline product could also be developed, so that field surveyors need not have internet connection to access this information. With a wide-screen tablet, it should be feasible to use this application on the move.

To add context to the map, it would be useful to have other thematic layers. This could be an elevation raster layer, a vegetation cover layer or a buildings layer. The elevation layer would be a Digital Elevation Model (DTM) or a Triangulated Irregular Network (TIN). It would provide slope and aspect of the land. The vegetation layer would show where the forests and nature reserves are. The buildings layer would contain polygons representing buildings with a height value attribute for each polygon. All these additional layers would help the field surveyor to plan his survey.

With the current extent of technology, GIS is the premier method, with regard to time and cost, to manage large amounts of spatial data. Within this application, GIS will consolidate the company’s knowledge about control points and would be able to disseminate this information to multiple users with little downtime. The disadvantages of using GIS in this case would be (i) its dependence on Intranet availability; users must be connected to the company’s servers to use Hyperlinks, and (ii) a technological divide; some users might not know or like using a digital service for their needs.

Additionally, it is possible to map directly all the control points. This way, users would directly see all the control points, instead of needing to open a list of coordinates and place the multiple control points manually. However, with multiple control points per job, this would increase the work needed to update the shapefile each time. Generally, the control points are not too far from the job site itself, so it is a minor concern and not considered worth the extra effort.

Conclusions

The application developed is able to find, identify and use hyperlinks for jobs of interest. From there, the user can quickly find more information relating to the control points. Cheng and Phillips (2011) assert that GIS is capable of presenting geo-referenced information which firms can utilise for more informed decisions. This GIS application accomplished that, helping the company’s management to decide whether it was necessary to create new control points or just use the existing control points. Its main disadvantages are the Intranet requirement and users’ lack of knowledge or reluctance to use this application. Possible future improvements to this application include an offline mobile version and additional thematic layers.

Acknowledgement
The author acknowledges J K Foo Consortium Pte Ltd for their input and advice in developing the application. The author also acknowledges Ms Gita Pupedis on her thoughtful comments on this assignment.

References
Chang, K 2012, ‘Introduction to geographic information systems’, 6th edn, McGraw-Hill, New York, USA.

Cheng, L & Phillips, J 2011, ‘Geographic information system applications in supply chains’, International Journal of Business Research, vol. 11.5, p131-136.

Heywood, D, Cornelius, S & Carver, S 2006 ‘An introduction to geographical information systems’, 3rd edn, Prentice-Hall, Harlow, UK.

Land Transport Authority 2013 ‘Singapore Land Transport Statistics in Brief 2013’, viewed 23 Sep 2013, http://www.lta.gov.sg/content/dam/ltaweb/corp/PublicationsResearch/files/FactsandFigures/Stats_in_Brief_2013.pdf

LeBoeuf, EJ, Dobbins, JP & Abkowitz, MD 2003 ‘Development of a GIS-based Spill Management Information System. Phase I: Proof of Principle Approach for the Cheatham Reach’, Vanderbilt University—Civil and Environmental Engineering, Nashville, TN.

Monday, October 14, 2013

Comparison of the BBC’s Domesday Project and its contemporary equivalents
Ying Bo Wang1
1RMIT University, Melbourne VIC 3001, Australia
Unless otherwise indicated, diagrams included in this report were created by Ying Bo Wang, RMIT University 2013

Abstract
The Domesday Project in 1986 is an interesting work. It is often described as being 10 years too early for its time. It can be described as a Geographic Information System that combines attribute and spatial data over the whole of the United Kingdom. The techniques and methods used in the Domesday Project have an influence on today’s mapping products. This paper compares contemporary mapping applications with the ones in the Domesday Project and examines how the techniques employed have changed. The ideas powering the features of the Domesday Project are still in use today, just that the graphics and user interface is different. Additionally, users today prefer to search for individual sections of information on their own through the internet, rather than buying and using a packaged product like the Domesday Project.

Keywords: Domesday Project, contemporary, mapping

Contents
  • Introduction
  • Hardware
    • Comparison of Hardware
  • Software
    • Comparison for National Disc
    • Comparison for Community Disc
  • Conclusions
  • References

Introduction
The original Domesday Book was compiled by the order of King William I of England in 1086, to perform an extensive survey covering much of England (Rhind, Armstrong & Openshaw 1988). The term ‘Domesday’ is an alias for the word ‘Doomsday’, as the survey results were treated as accurate at the time it was compiled. This provided a sense of finality to some individuals, hence the term ‘Doomsday’. The British Broadcasting Corporation (BBC)’s Domesday Project in 1986 was meant to be a massive update to the original Domesday Book. It was released on the 900th anniversary of the original Domesday Book. From just a data standpoint, it comprised of large amounts of text, journal articles, photographs, official statistics data, animated video with sound, satellite images, aerial photographs and topographic maps (Maguire 1989). This data was meant to be released to the public.

In terms of scope, it was an incredible multimedia project that was essentially an expensive time capsule of what it was like in Great Britain during that time period. Additionally, its data was planned to be of use to lawmakers, geographers, students and businessmen. Until its revival through Domesday Reloaded in 2011, no other organisation has attempted a public project of this scale. To appreciate what was done in the Project, it is vital to review its components and compare it with what is typical for the average person in the United Kingdom.

This paper will (i) compare contemporary equivalent products (within Great Britain) with BBC’s Domesday Project and (ii) analyse whether the techniques and methodologies have changed between 1986 and 2013. The comparison will take into account both hardware and software differences.

Hardware
The Domesday Project had the following pieces of hardware (See Figure 1):
  1. Acorn BBC Master micro-computer programmed on BCPL
  2. Phillips LaserVision Player
  3. Cathode Ray Tube (CRT) Colour monitor
  4. Trackerball
  5. Two 12 inch Domesday LaserDiscs (LD)
The Domesday LDs would be played on the Phillips LaserVision Player. The Phillips machine takes commands from the Acorn micro-computer and trackerball, which are manipulated by the user. The output is then displayed on a colour monitor (See Figure 2).

Figure 1: Domesday Machine. Left to right: Phillips LaserVision player, Colour Monitor, Acorn Microcomputer & Trackerball. Source: www.bbc.co.uk


Figure 2: Overview of hardware used in Domesday Project

Comparison of Hardware
The modern equivalents of the Domesday Project hardware can be summarised by Table 1 below:
1986 (Domesday Project)
2013
Laser Discs
CD/DVD/Cloud Storage
LaserDisc Player
CD/DVD Player or None
Micro-computer
Personal Computers (PC)
CRT Colour Monitor
Liquid Crystal Display (LCD) Monitor
Table 1: Hardware comparisons between 1986 and 2013

Each of the LaserDiscs used for the Project held roughly 110,000 still images and 600 megabytes (MB) (Goddard and Armstrong 1986). Today, compact discs (CD) can hold up to 700 MB while DVDs (Digital Versatile Discs or Digital Video Disc) can hold up to 17080 MB. The difference in capacity and physical size of the disc means that no new products are recorded on LaserDiscs anymore. Moreover, as more and more data centres are being setup, corporations and organisations are exploring the idea of cloud storage. This removes the need for physical media, enabling users to directly download the data they need from the Internet. As a direct consequence, the LaserDisc Players have been replaced by CD or DVD players. For users of cloud storage, they would not need to use players of any kind.

The micro-computer and the language the software was coded in were getting obsolete to the point that the number of users was quickly dwindling. This is mainly due much faster processor speed (2MHz to 2GHz) and larger memory (128kB to 3GB) of the newer PCs. The CRT colour monitor used has been replaced by LCD monitors. This is mainly due to the smaller physical size and energy efficiency of LCD monitors, compared to CRT monitors. In summary, this meant that all the hardware used for the Domesday Project was rendered obsolete by today’s standards in computing. No company would produce such hardware on a commercial scale anymore.

Software
The two Domesday Discs contain a total of “30 million words, 21 000 files of spatial (or mappable) digital data, 24 000 Ordnance Survey topographic maps, statistical tabulations and time series, picture libraries and TV film clips” (Rhind, Armstrong & Openshaw 1988). This is further elaborated in Figure 3 below.

Figure 3: Overview of content in Community Disc and National Disc. Source: BBC Enterprise.

Comparison for National Disc
The modern equivalents of the National Disc can be summarised by Table 2 below:
1986 (Domesday Project)
2013
Keyword Search
Google, Yahoo, Bing search engines
Photographs
Flickr
Videos
Youtube
Interactive Dataset Graphics
GIS, ArcGIS Online, QGIS
Database in spatial form
GIS, ArcGIS Online, QGIS
Text (Authoritative)
Google Scholar, Project Gutenburg, online journals
Table 2: National Disc comparison between 1986 and 2013

Both Domesday discs could be navigated by use of keyword searching. This has been expanded upon by modern-day equivalents such as Google, Yahoo and Bing search engines. Users that searched the national disc to find photographs and videos, now go to the Internet to use Flickr and Youtube respectively. To get scholarly articles, newspaper articles and government reports, a user would now search for them on Google Scholar, Project Gutenburg or other online journals. For interactive dataset graphics as well as the ability to associate attribute data to spatial data, users today will typically use one of the Geographic Information System softwares. Examples include ArcGIS Online, Quantum GIS (QGIS) or GRASS GIS.

Comparison for Community Disc
The modern equivalents of the Community Disc can be summarised by Table 3 below:
1986 (Domesday Project)
2013
Ordnance Survey Maps
Ordnance Survey Database(ordnancesurvey.cok.uk)
Information and Opinions by Community
Yelp!, Tripadvisor, blogs, forums
Pictures within maps
Google Earth, Google Streetview
‘Scalable’ maps
Google Maps, Bing Maps
Aerial Photographs
Online Archives (English-heritage.org.uk)
Satellite Images
Google Earth
‘Surrogate walk’
Google Streetview
Table 3: Community Disc comparison between 1986 and 2013

The Ordnance Survey Maps and Aerial Photographs on the LaserDisc can now be found on the online Ordnance Survey repository and an online archive (English-heritage.org.uk) respectively. Satellite images of the United Kingdom can now be viewed using Google Earth. The way the LaserDisc took to the idea of ‘scalable’ maps was to use analogue images in a hierarchical order. Starting at the smallest scale are the satellite images, before ‘zooming in’ to ordnance survey maps, small scale aerial photographs, large scale aerial photographs, and amateur photographs at street level, in that order respectively. This is replaced by using Google Maps, Bing Maps or OpenStreetMap. The idea of ‘surrogate walks’ was a sort of virtual reality. By interacting with icons, the user could zoom in to that location and navigate the area by viewing still photographs at a street level. This has been expanded upon in Google Streetview.

In summary, for authoritative sources of information like scholarly articles, ordance survey maps or aerial photographs, organisations have opted to store the information on their servers, allowing users to download what information they need for a fee. For community information, blogs and cloud data have taken over with Flickr, Youtube, blogs and forums. All this information, authoritative or community, is accessed through the Internet with keyword searches. In 1986, the Domesday Project gave a packaged product for the user to explore the contents. Today, the user searches for particular sections of information he needs.

Conclusions
The main technological catalyst for this project was the invention of the LaserDisc, and commercial computers able to handle them. However, the problem arises when the BBC designed the hardware to be integral to the Domesday Project. This meant that without the hardware, which was rapidly turning obsolete, there was no way to read the Domesday Discs. This factor along with underestimating the costs for the Domesday Project effectively killed any chance for the Domesday Project to be widely adopted.

Another problem was for users who needed up-to-date exact information. Due to the data being stored on physical media, this made any update difficult. To perform an update, the BBC would have to issue new LaserDiscs to their customers each time. This meant the data on the discs quickly lost currency. This is compared to information found on the Internet, where the user could get the most up-to-date information.

The main reason why no other organisation has done a similar project in contemporary times is probably because users only want to view bits of information they need at that time. Users prefer not to buy and search through a packaged product like the Domesday Project. To do another similar project today, a company would hire individuals to assemble the various components mainly from the internet and write the information onto a DVD.

The methods and techniques used to gather authoritative data for the Domesday Project are still the same as what is used today. This includes satellite images, aerial photographs, scholarly articles and surveys. For community data, this has changed to crowdsourcing from the Internet. Examples include blogs and forums. The ideas behind the individual products of the Domesday Project are still healthy today. The presentation is just different as compared to the past. For example, scalable maps in the Domesday Project are now replicated in Google Earth. This is mainly due to advancement of technology. As long as technology keeps evolving, the method of presenting spatial data will also continue to change. For example, the idea of a ‘Surrogate walk’ itself is a successor to Aspen Movie Map created by the American University MIT in 1978. This makes ‘Surrogate walk’ and Aspen Movie Map ancestors to the modern Google Streetview.

References:

Goddard, J & Armstrong, P 1986, ‘The 1986 Domesday Project’, Transactions of the Institute of British Geographers, New Series, Vol.11, Issue 3, pp. 290-295

Rhind, D, Armstrong, P & Openshaw, S 1988, ‘The Domesday machine: a nationwide geographical information system’, The Geographical Journal, Vol. 154, Issue 1, pp. 56-68

Maguire, D J 1989, ‘The Domesday interactive videodisc system in geography teaching’, Journal of Geography in Higher Education, Vol.13, Issue 1, pp.55-68

Openshaw, S, Rhind, D & Goddard, J 1986, ‘Geography, geographers and the BBC Domesday project’, Area, Vol.18, Issue 1, pp.9-13