Land Information System (LIS)

This chapter introduces the background of the research topic, main objective, the general methodology and the significance of the project.
1.1 BACKGROUND
In an attempt to address the issue of the disorganization in the registry, the government of Uganda carried out a number of studies. The initial study proposed microfilming or scanning of the paper documents. Another, financed by USAID, recommended indexing the land records. The intention was to introduce some mechanism in the registry that would enable an expedited storage, access and retrieval of land records to enhance service delivery.
In 2010, a consortium led by IGN France International was awarded a World Bank tender for the DeSILISoR project (Design, Supply, Installation, Implementation of the Lands Information System and Securing of Land Records) for the securing of property titles through the development of a unique land information system for the 6 pilot Ministry Zonal Offices (MZOs) of Kampala, Mukono, Wakiso, Jinja, Masaka and Mbarara, Department of survey and Mapping in Entebbe and Ministry of Lands, Housing and Urban Development Headquarters. (Annual World Bank Conference on Land and Poverty,2013).
A land surveyor is required to have datum controls that he should use to control any form of survey work that were predetermined early in the 1960s under the projection of Arc 1960 UTM 36N . These controls were measured accurately using the first precise equipment in the field of the geodetic control network and using techniques such as triangulation.

1.2 PROBLEM STATEMENT
During the development of the NLIS, cartographic maps bearing plots of land in the pilot areas where scanned and georeferenced. Since the inception of the NLIS, complaints have cropped out from numerous surveyors. They claim the scanned coordinates do not tally with the actual correct coordinates on ground. This research sought to determine whether these claims were legitimate and to devise ways of how to mitigate this problem.

Figure 1. Old print of one of the land parcels in Wakiso, Busiro block 474-475 plot 1422

Figure 2.LIS scan of one of the land parcels in Wakiso, Busiro block 474-475 plot 1422
Furthermore, a number of surveyors are aligning their field work observations in the LIS so that their files are passed at the ministry thus bringing about overlapping parcels and erroneous boundaries.

1.3 MAIN OBJECTIVE
Investigating the accuracy of the scanned UTM coordinates in the new computerized National Land Information System.
1.4 SPECIFIC OBJECTIVES.
' Acquisition of cadastral surveying data for land parcels of interest..
' Using RTS controls to control the traverses for the land parcels of interest.
' Comparison of scanned coordinates with ground surveyed points.
' Devising of possible alternative procedures to mitigate discovered deviances.
1.5 GENERAL METHODOLOGY
In order to achieve the above objective the methodology below was adopted
' Acquisition of cadastral surveying data for land parcels of interest
' Boundary opening to determine the exact boundaries of the respective plots and establishing the exact positions of the mark stones of adjoining parcels.
Traversing over old marks of the respective plots which had already been surveyed and their files passed by the commissioner of land.
' Data analysis/Data processing.
' Ascertaining the coordinates of the plots of interest, drawing conclusions and suggesting recommendations according to the analysis.

1.5.1 FLOW CHART OF THEPROPOSED METHODOLOGY


1.6 CASE STUDY
My study area was Wakiso District Entebbe Municipality.
1.6.1 Geographical Scope
Wakiso is a District in central Uganda that encircles Kampala which is Uganda's capital city. The District is named after the town of Wakiso where the District head quaters are located. Wakiso lies in the central region of Uganda bordering with Nakaseke District and Luwero District to the North, Mukono district to the East, Kalangala District in lake Victoria to the South, Mpigi district to the South West and Mityana District to the North West. Wakiso district has a total area of 2704 square kilometres.
Wakiso is made up of two counties i.e. kyadonddo and Busiro counties. It also has several administrative units which include, Busukuma, Entebbe Municipality, Nabweru, Namayumba, Nansana, Nsangie.t.c
1.6.2 Entebbe Municipality, Busiro.
Entebbe is a town in central Uganda located on lake Victoria peninsula. The town was at one time the seat of government for the protectorate of Uganda prior to independence in 1962. Entebbe is the location of Entebbe International Airport and the Department of Survey and Mapping. It's situated in Wakiso district approximately 37km south west of Kampala.The study plots are plot15 (gowers road), plot6 (stevenkabuye clause), plot5 (Nakasamba road), plot18 (Air port road) of sheet number 70/4/20/SW/3&4.
1.6.3 A map of Entebbe Municipality

Figure1: a map showing a section of Entebbe municipality.

1.6.3 Subject Scope
Comparing the NLIS UTM coordinates of the respective parcels with the ground coordinates obtained and showing how much they deviate from each other in terms of coordinates, distances and areas.

1.7 SIGNIFICANCE OF THE STUDY
The significance of the study is to find out whether there are discrepancies, inconsistency, disagreements, and divergence between the LIS coordinates and the ground coordinates and devise ways of how to mitigate this problem. These discrepancies might be shown in distances, area, or even shifts of the land parcels.

CHAPTER TWO
2.0 LITERATURE REVIEW

2.1 .Land Information System (LIS) is a tool for legal, administrative and economic decision making as well as an aid for planning and development. This involves on the one hand, the database containing, spatially referenced land related data and on the other hand the procedures and techniques for systematic collection, updating, processing and distribution of the data to the end users in an efficient manner. The base of a land information system is a uniform referencing system that could facilitate in linking the different types of data within the system and with other land related datasets. The most important thing in the land information management is the quantity of the data which can be handled, the speed with which these data can be processed and the ways in which the data can be manipulated and analyzed
Dale, P. F., McLaughlin, J. D. (1988), Land information management: an introduction with
special reference to cadastral problems in third world countries Oxford: Clarendon Press. p.300.
Land Information in its most literally means all information on land like legal status, use, environmental aspects etc. On the other hand land information is sometimes set against geographic information and then has more limited meaning
The second fuzzy part of the concept of NLIS is the word 'system'. This can refer to a technical computer system but also to a system with a wider meaning: a number of organizations that work together to capture, manage, share and disseminate information on land.
Land Information challenges in Indonesia Peter Laarakkerl Suyus Windanya2 Cadastre, Land Registry and Mapping Agency, the Netherlands peter.laarakker@kadastre.nl National Land Agency, Indonesia swindanaya@bpn.go.id.
Furthermore, In Ghana its land sector agencies were presently bedeviled with poor remuneration, poor conditions of service and inadequate logistics; lack of transparency in work processes, delays and cumbersome manual procedures; poor records management; perceived corruption; mistrust on the part of customary land owners in land administration generally; lack of technical expertise in new technology available; and lack of effective collaboration and cooperation between the agencies.
In October 2003, the Government of Ghana launched the LAP to translate this policy into concrete Action i.e. , recognizing that as Ghana moved towards increasing use of digital technology and GIS systems, there was the need to design a properly structured computer-based LIS that would record basic cadastral information and better allow user access and integration within different datasets. However, it was believed that the existing agencies had to be placed under one management since they remained fragmented, ineffective and inefficient in their present operations.
Isaac Bonsu Karikari, Ghana's Land Administration Project (LAP) and Land Information Systems (LIS) Implementation.
According to Gabindadde-Musoke, in an attempt to address the issue of the disorganised registry, the government carried out a number of studies. The initial study proposed microfilming or scanning of the paper documents. Another, financed by USAID, recommended indexing the land records and setting up a process to implement the procedure.
In September 2003, a decision was taken by the Ministry of Land Housing and Urban Development to begin the implementation of computerization of the Land Registry. The aim was to address the shortcomings of the manual system, restore the integrity of the Land Registry and ensure modernization of Land Registry.
In 2002 the Government of Uganda was implementing a project known as the Second Private Sector Competitiveness Project (PSCP II) located within the Private Sector Foundation of Uganda (PSFU). The land component within the PSCP II project was worth US$ 23 million and was intended to complete the rehabilitation of damaged land records and secure them in electronic form throughout the country, Modernization of the land legislation in Uganda, MLHUD zonal offices buildings renovation etc. and was funded by the World Bank, through the Private Sector Foundation Uganda (PSFU)
Finally, in February 2010 government, through the PSFU, engaged M/s IGN France International to lead a consortium of technical experts with support from the World Bank to design, install and implement a Land Information System with the intention of addressing the shortcomings of the manual system, restoring the integrity of the Land Registry and ensuring modernization of the Land Registry operations to meet the needs of a growing economy. Friday, 31 May 2013 09:03 By Gabindadde-Musoke
NLIS was under the project called DESILISOR. (Design, Supply, Installation, Implementation of the Lands Information System and Securing of Land Records). DESILISOR project is the land information System Development project under the Ministry of Lands Housing and Urban Development which aimed at improving the tenure security through the establishment and formalizing of Land which would lead to the establishment of an efficient computerized system of Land and Title Registration and also provide coordinates on UTM.
During the LIS, there was mass rehabilitation of records, conversion from manual record management and registry operations to an Electronic Documents Management System, leading into the establishment of an efficient land records information management system. The system intends to improve the reliability and completeness of land title records and associated transactions.
Furthermore, installation of Software/Applications used in the installation of the LIS was done .i.e. GRM Registry, which is used for the processing and management of land transactions; GRM Multi-Cadaster, used for managing land parcels, creating deed plans and maps. The two applications are linked to constitute the LIS.
Scanning, digitizing and georeferencing of old sheets to get data for the system using IT equipment (Hardware and Software) procurement & delivery was done and these include computers, barcode scanners and printers.
During the computerization of the Land Registry, a number of problems were faced which include among others,
' Damaged old sheets.
' Variation in the spatial reference system
' Lack of skilled man power.
' Lack of enough equipment.
' Unregistered land parcels.
' Poor storage facilities of the land records.e.t.c
Despite of the above problems, the project was a success in Uganda in the respective Ministry Zonal Offices and apparently the NLIS coordinates are being used to carry out surveys in the country.
2.3.1 Spatial reference system
There was variation in spatial data referencing causes misalignment and displacements in spatial location of feature layers within a GIS workspace. For the datasets used in this study, variations were observed in coordinate systems, data compilation scales and datum. In general, four different coordinate systems were identified. Although variations do exist in coordinate systems, many datasets in Uganda are still based on the UTM (Zone 36N) coordinate system. This coordinate system adopted Clarke 1880 as the figure of the Earth, and Arc 1960 as the datum. The above reference system is commonly in Uganda for the reason that it has for a long time become a standard for the Department of Surveys and Mapping, the institution that is mandated to set standards for geospatial data in Uganda. However, there are plans to shift from this reference system (Arc, 1960) to WGS84 (Okia and Kitaka, 2001) because most recent spatial data such as satellite images and GPS observations are based on WGS 84 datum.
Local adjustments to the standard coordinate systems in form of constant shifts to the origin were identified in the spatial datasets. For example, UBOS and NFA have shifted the Northing Origin of their spatial datasets from 0m to 10,000,000m and 200,000m respectively. Although the problem of local shifts is easily addressed in some GIS software such as ArcGIS, this is only possible when the constants are documented and are supplied as metadata, alongside the data. However, this does not appear to be the case in Uganda, where documented metadata does not exist in many institutions. International Journal of Spatial Data Infrastructures Research, 2012, Vol.7, 488-507

2.3.2 Limitation of UTM Coordinate System for Seamless Mapping in Uganda
As already mentioned, many institutions that produce spatial data in Uganda have adopted the UTM coordinate system, because it is the standard set by the Department of Surveys and Mapping. UTM is a worldwide projection that divides the world into 60 zones and each zone is 6 degrees of longitude wide. The zones are numbered, starting from zone 1 which runs from the 180?? to the 174??W line of longitude, with numbers increasing westwards. For the northern portion of each zone, the origin is defined as 500,000mE, 0mN, while for the southern portion of the zone, the origin is defined as 500,000mE, 10,000,000mN. Although this convention is used to avoid having negative coordinates for areas south of the equator, it introduces a dual coordinate system when mapping countries such as Uganda, that fall north and south of the equator.
In order to distinguish between locations north and south of the equator, some software such as ArcGIS require that data collected from north and south of the equator should be entered as separate files. Each of the files must then be entered with a spatial reference that specifies whether the data is north or south (e.g. UTM Zone 36N and Zone 36S). On the other hand, software such as AutoCAD Map that is not sensitive to map projections, expect the data to be in consistent coordinates for seamless mapping. Obviously, the issue of map projections is a problem for both types of software, and needs to be addressed in a consistent manner.
In order to process a seamless digital map of Uganda, the immediate solution is to deduct the Northing coordinates of points in the southern hemisphere from a constant such as 10,000,000m so that all the coordinates are positive. Although a consensus had been reached at a GIS taskforce meeting (see GoU, 2001) to adopt 10,000,000m as the northing origin, this has not been implemented and institutions have continued to address the problem differently. This will therefore continue to be a major source of inconsistency, if not appropriately addressed.
International Journal of Spatial Data Infrastructures Research, 2012, Vol.7, 488-507
2.4 Traversing
Traverse is a method in the field of surveying used to establish control networks. It is also used in geodesy. Traverse networks involve placing survey stations along a line or path of travel, and then using the previously surveyed points as a base for observing the next point. Traverse networks have many advantages, including:
' Less reconnaissance and organization needed;
' While in other systems, which may require the survey to be performed along a rigid polygon shape, the traverse can change to any shape and thus can accommodate a great deal of different terrains;
' Only a few observations need to be taken at each station, whereas in other survey networks a great deal of angular and linear observations need to be made and considered;
' Traverse networks are free of the strength of figure considerations that happen in triangular systems;
' Scale error does not add up as the traverse is performed. Azimuth swing errors can also be reduced by increasing the distance between stations.
2.4.1 Types of traversing.
Frequently in surveying, engineering and geodetic science, control points (CP) are used in setting/observing distance and direction (bearings, angles, azimuths, and elevation). The CP throughout the control network may consist of monuments, benchmarks, vertical control, etc.
Open/Free
An open, or free traverse (link traverse), consists of a series of linked traverse lines which do not return to the starting point to form a polygon. Open survey is utilized in plotting a strip of land which can then be used to plan a route in road construction.
Closed
A closed traverse (polygonal, or loop traverse) is a series of linked traverse lines where the terminal point closes at the starting point. A closed traverse enables a check by plotting or computation, with any gap called the linear misclosure. When within acceptable tolerances, the misclosure can be distributed by adjusting the bearings and distances of the traverse lines using a systematic mathematical method so the adjusted measurements close. The "Bowditch rule" or "compass rule" in geodetic science and surveying assumes that linear error is proportional to the length of sides in relation to the perimeter of the traverse. Allowable misclosure is decided upon a case by case basis. The terminal (ending) point closes at the starting point.

Compound
A compound traverse is where an open traverse is linked at its ends to an existing traverse to form a closed traverse. The closing line may be defined by coordinates at the end points which have been determined by previous survey. The difficulty is, where there is linear misclosure, it is not known whether the error is in the new survey or the previous survey.
2.4.2 Instrumentation
' Total station
' Reflector prisms
' Tape measure
2.5 DATA
This is the factual information whether measurements or statistics used as a basis reasoning, discussion, research and making conclusions. There are two types of data .i.e. qualitative data and quantitative.
Qualitative data is data which is not given numerically and quantitative data is one which is numerical and is of two kinds i.e. discrete and continuous data.
We shall deal with discrete data, the discrete data takes specific numerical values for example the plot numbers, coordinates(X, Y) of my plots of interest.

'
3.0 METHODOLOGY
3.1 INTRODUCTION
This chapter introduces what was done during the execution of the project prior to its objectives.
3.2 RECONNAISANCE
A reconnaissance survey was carried out in Entebbe Municipality on the study plots.i.e. plot 15 (gowers road), plot 6 (steven kabuye clause), plot 5 (Nakasamba road), plot 18 (Air port road) of sheet number 70/4/20/SW/3&4. During the reconnaissance survey, some mark stones of the relevant plots were missing and some controls found on ground .i.e. RTS 38, RTS 39, RTS 40, RTS 41.
Table 1. controls used.
CONTROLS
Station Northing Easting
RTS41 5738.410 440256.920
RTS40 5864.960 440272.310
RTS39 6046.13 440288.87
RTS38 6273.61 440361.32

3.3 Data collection (capture)
Field data collection was carried out to ascertain the exact location of parcels of interest on ground. Ground data collection and data from secondary source i.e. data from Entebbe department of Lands and Survey was used.
3.4 Data collection methods
Both primary and secondary data collection methods were used during data collection.
Primary data: this included the data from the field. Field data collection was carried out to ascertain the exact location of points on ground.
Secondary data: this included the data from Entebbe Department of Land and Survey .i.e. the old data (coordinates) of the respective plots and the new LIS coordinates.
(See figure3 & 4 in appendix for scan of the respective plots,
Table 2. A table showing old data from the files passed at the Ministry of Land
Table 3. The LIS coordinates of the corner points of the respective point though some were missing due to the damaged sheet that was scanned and georeferenced.).
3.4.2 Primary Data
The field work was carried out in Entebbe municipality Wakiso, District. It involved traversing over old mark stones of the study plots. The fieldwork was done using a Topcon GTS 211D electronic total station observing bearings, distances and the coordinates. The standard corrections which were applied are listed in the index computations.
A traverse was opened at RTS40 raying to RTS 41 and continued to respective markstones of the respective plots which were already surveyed and their files passed by the commissioner of lands and later closed at RTS 38 raying to RTS 39.
Table 4. Datum computations
DATUM
COMPUTATION
STN N E ??N ??E BRG Distance
RTS41 5738.410 440256.920
RTS40 5864.960 440272.310 -126.55 -15.39 186 56 2 127.48

RTS39 6046.130 440288.870
RTS38 6273.610 440361.320 -227.48 -72.45 197 39 58 238.74

The areas computed from coordinates are 0.104Ha plot 15, plot 6 0.125Ha, plot 5 0.353Ha and plot 18 0.119Ha.The linear and angular misclosures are within acceptable survey limits.
3.5 Observations
From the field work observations, the collected coordinates were tallying with the old data coordinates and varied with the LIS coordinates obtained from Entebbe Department of Lands and Surveying.(see appendix table 5&6)
Furthermore, some coordinates of various plots.i.e. plot5 and plot 6 were missing in the new coordinate system due to scanning and georeferencing of old damaged sheets.
The missing coordinates were obtained by georeferencing of the old print using AutoCAD software.
3.6 Georeferencing.
This is aligning geographic data to a known coordinate system so it can be viewed, queried, and analyzed with other geographic data. Georeferencing may involve shifting, rotating, scaling, skewing and in some cases warping, rubber sheeting, or orthorectifying the data.
3.6.1 Georeferencing using AutoCAD
Using AutoCAD2009, left click insert, raster image and chose it were it was saved (figure 5)

Figure5. AutoCAD work space after left clicking the insert function

Then specified where to put the raster image in the AutoCAD drawing( figure6
.
Figure6. AutoCAD work space after specifying where to put the raster image.
Left clicked modify, 3D operation, Align. Then selected the object, selected the first alignment point on the print.i.e. One of the controls and connected it with its right point on the AutoCAD drawing. This was repeated for other controls.i.e.a minimum of three controls was used. (figure7)

Figure7. this shows the process of aligning the scanned print with respect to the controls.
AutoCAD prompted whether to align the image with respect to the drawing, entered yes and the raster image was aligned in the AutoCAD drawing which implied georeferencing was a success.( figure8)
From the figures (figure9 & 10), the observations below it were the coordinates obtained.

Figure9. working diagram after alignment

Figure10. Coordinates of the missing plots and points in the LIS were obtained from here.

Table7. Table showing georeferenced coordinates obtained.

PLOT 5
Station Northing Easting
CM1 6190.89 440153.70
CM84 6168.44 440211.02
CM3 6182.84 440216.73
CM8 6239.35 440196.62
I/0417 6245.21 440182.83
PLOT 6
Station Northing Easting
CM93 6018.77 440141.58
I/0486 6027.8 440148.2
CM500 6033.43 440152.5
CM95 6053.19 440167.15
CM90 6070.19 440140.05
CM91 6044.84 440122
CM92 6036.34 440117.27

CHAPTER FOUR
4.0 RESULTS AND ANALYSIS
4.1 INTRODUCTION:
This chapter explores the analysis of the collected data in line with the objectives set in chapter one. The data analysed was obtained from the field survey that was carried out within the study area and the data from Entebbe.
4.2 FIELD OBSERVATIONS.
ABSTRACT OF COORDINATES
STN NORTHINGS EASTINGS
I/0491 5,958.00 440,256.97
CM300 5,967.30 440,260.72
CM400 5,988.85 440,262.65
CM120 6,004.29 440,237.86
CM118 5,977.77 440,223.61
CM93 6,013.75 440,148.98
I/0486 6,023.11 440,154.97
CM500 6,028.21 440,158.17
CM95 6,048.72 440,171.00
CM90 6,064.38 440,144.88
CM91 6,038.97 440,128.97
CM92 6,029.54 440,123.06
CM1 6,183.37 440,152.78
CM2 6,158.71 440,216.82
CM3 6,177.84 440,226.41
CM8 6,239.03 440,211.85
I/0417 6,240.22 440,191.89
CM8 6,426.88 440,246.70
CM21 6,458.45 440,233.97
CM23 6,480.69 440,259.67

Figure11 shows plot 18. Green polyline indicate the drawing from the LIS coordinates and the red polyline indicate the drawing of the field observations.


Figure 11: shows the discrepancy between the NLIS scanned coordinates and the coordinates obtained after a field survey was done
Analysis
Plot18 had a shift of 5.601m to the left and its area decreased from 0.119ha to 0.115ha. The differences in coordinates are indicated below in table6.
Table 6: shows the coordinate of plot 18 in the old file, NLIS and the difference in these coordinates.
PLOT 18 OLD LIS DIFFERENCE
Station Northing Easting Northing Easting chg N chg E
CM8 6426.88 440246.70 6428.19 440240.54 -1.31 6.16
CM22 6458.45 440233.97 6469.62 440228.95 -11.18 5.03
CM23 6480.69 440259.67 6480.90 440253.08 -0.21 6.60
CM7 6439.72 440273.81 6440.10 440268.00 -0.38 5.81


Figure12 shows plot 15. Green polyline indicate the drawing from the LIS coordinates and the red polyline indicate the drawing of the field observations

Analysis
Plot15 shifted 11.5m to the right, 13.7974m upwards and its area decreased from 0.104ha to 0.095ha. The differences in coordinates are indicated below in table7.
Table7: shows the coordinate of plot 15 in the old file, NLIS and the difference in these coordinates.
PLOT15 OLD LIS DIFFERENCE
Station Northing Easting Northing Easting chg N chg E
I/0491 5958.00 440256.97 5962.16 440265.71 -4.16 -8.74
CM300 5967.30 440260.72 5970.42 440268.41 -3.12 -7.69
CM400 5988.85 440262.65 5991.85 440268.25 -3.00 -5.60
CM120 6004.29 440237.86 6007.41 440247.45 -3.12 -9.59
CM118 5977.77 440223.61 5979.78 440232.37 -2.02 -8.76



Figure13 shows plot 5. Green polyline indicate the drawing from the LIS coordinates and the red polyline indicate the drawing of the field observations.
Plot5 shifted 10.839m to the left and area decreased from 0.351ha to 0.264ha and the differences in coordinates are indicated in table8.

Table 8: shows the coordinate of plot 5 in the old file, NLIS and the difference in these coordinates
PLOT5 OLD LIS DIFFERENCE
Station Northing Easting Northing Easting chg N chg E
CM1 6183.37 440152.78 6190.89 440153.70 -7.52 -0.92
CM84 6158.71 440216.82 6168.44 440211.02 -9.73 5.80
CM3 6177.84 440226.41 6182.84 440216.73 -4.99 9.68
CM8 6239.03 440211.85 6239.35 440196.62 -0.32 15.23
I/0417 6240.22 440191.89 6245.21 440182.83 -4.99 9.05

Figure14 shows plot 6. Green polyline indicate the drawing from the LIS coordinates and the red polyline indicate the drawing of the field observations.


Figure14 shows plot 6. Green polyline indicate the drawing from the LIS coordinates and the red polyline indicate the drawing of the field observations.
Plot6 shifted 7.6835m to the left, 2.0569m upwards and area increased from 0.126ha to 0.130ha and the difference in coordinates are indicated below in table9.
Table 9: shows the coordinate of plot 6 in the old file, NLIS and the difference in these coordinates.
PLOT 6 OLD LIS DIFFERENCE
Station Northing Easting Northing Easting chg N chg E
CM93 6013.75 440148.98 6018.77 440141.58 -5.02 7.40
I/0486 6023.11 440154.97 6027.8 440148.2 -4.68 6.81
CM500 6028.21 440158.17 6033.43 440152.5 -5.21 5.65
CM95 6048.72 440171.00 6053.19 440167.15 -4.47 3.85
CM90 6064.38 440144.88 6070.19 440140.05 -5.81 4.83
CM91 6038.97 440128.97 6044.84 440122 -5.86 6.97
CM92 6029.54 440123.06 6036.34 440117.27 -6.80 5.80

CHAPTER FIVE
5.0 INTRODUCTION
This chapter includes the conclusions and recommendations prior to the research project.
5.1 Conclusions
According to the field observations, findings and data analysis of the research project, it's true that the scanned UTM coordinates of the new computerized Land Information System do not tally with the actual coordinates on ground.
The scanned coordinates have numerous shifts.i.e.to the right, left, downwards or upwards.
' Plot18 had a shift of 5.601m to the left and its area decreased from 0.119ha to 0.115ha.
' Plot15 shifted 11.5m to the right, 13.7974m upwards and its area decreased from 0.104ha to 0.095ha.
' Plot5 shifted 10.839m to the left and area decreased from 0.351ha to 0.264ha.
' Plot6 shifted 7.6835m to the left, 2.0569m upwards and area increased from 0.126ha to 0.130ha.(See table 7 in the appendix)
5.2 Recommendations
Ignoring the discrepancies and suffering the consequences.
The old prints and data should be brought back into full use during the surveys in the Ministry Zonal offices and use ground coordinates in the areas where the system has not yet been piloted.
Remapping and Resurveying of the Ministry zonal offices so that actual ground coordinates are used in the new computerized LIS system instead of the scanned UTM coordinates and Uganda at large because it's going to be piloted in other areas..
Extending more controls (RTSs) with in the Ministry Zonal offices and the whole country at large land parcel surveys are well controlled, coordinated and use the results in the system.
Further research should be done about this same area/ topic, so that more mitigation measures are brought up to cater for the discrepancies, say developing mathematical models to encounter the shifts of the land parcels.

REFFERENCES

APPENDIX

Figure3. A scan of sheet number 70/4/20/SW/3&4 which has plot 15, 6, 5.

Figure4. A scan of sheet number 70/4/20/SW/3&4 which has plot 18.
Table 2. A table showing old data from the files passed at the Ministry of Land
OLD DATA
DESN NORTHINGS EASTINGS
I/0491 5958.000 440256.970
CM300 5967.300 440260.720
CM400 5988.850 440262.650
CM120 6004.290 440237.860
CM118 5977.770 440223.610
CM93 6013.760 440148.980
I/0486 6023.120 440154.970
CM500 6028.220 440158.170
CM95 6048.730 440171.000
CM90 6064.390 440144.880
CM91 6038.980 440128.970
CM92 6029.550 440123.060
CM1 6183.380 440152.790
CM84 6158.720 440216.820
CM3 6177.850 440226.410
CM8 6239.044 440211.860
I/0417 6240.229 440191.895
CM8 6426.890 440246.720
CM22 6458.460 440234.000
CM23 6480.700 440259.700
CM7 6439.730 440273.830

Table 3. The LIS coordinates of the corner points of the respective point though some were missing due to the damaged sheet that was scanned and georeferenced.
LIS DATA
PLOT 15
Station Northing Easting
I/0491 5962.16 440265.71
CM300 5970.42 440268.41
CM400 5991.85 440268.25
CM120 6007.41 440247.45
CM118 5979.78 440232.37
PLOT 6
Station Northing Easting
CM93
I/0486
CM500
CM95
CM90
CM91
CM92
PLOT 5
Station Northing Easting
CM1
CM84 6168.44 440211.02
CM3 6182.84 440216.73
CM8 6239.35 440196.62
I/0417
PLOT 18
Station Northing Easting
CM8 6428.19 440240.54
CM22 6469.62 440228.95
CM23 6480.90 440253.08
CM7 6440.10 440268.00

Appendix of field work computations

INDEX TO COMPUTATIONS

The following are the standard corrections applied to get the final distances.


Height above sea level 1160

Mean sea level correction per 1000m -0.1816

Standard Scale Factor correction per 1000m -0.3568

Combined correction -0.5384

Multiplication factor 0.9994616

Table 4. Datum computations

DATUM
COMPUTATIONS
STN N E ??N ??E BRG Distance
RTS41 5738.410 440256.920
RTS40 5864.960 440272.310 -126.55 -15.39 186 56 2 127.48

RTS39 6046.130 440288.870
RTS38 6273.610 440361.320 -227.48 -72.45 197 39 58 238.74

Area computations

AREA COMPUTATION
PLOT 15
Station Northing Easting DIST
I/0491 5958.00 440256.97
CM300 5967.30 440260.72 -4.07E+06 10.027
CM400 5988.85 440262.65 -9.48E+06 21.636
CM120 6004.29 440237.86 -6.95E+06 29.205
CM118 5977.77 440223.61 1.16E+07 30.106
I/0491 5958.00 440256.97 8.90E+06 38.776


AREA = 0.104 Ha
AREA = 0.257 Acres

PLOT 6
Station Northing Easting DIST
CM93 6013.75 440148.98
I/0486 6023.11 440154.97 -4.08E+06 11.113
CM500 6028.21 440158.17 -2.23E+06 6.021
CM95 6048.72 440171.00 -8.95E+06 24.192
CM90 6064.38 440144.88 -7.05E+06 30.454
CM91 6038.97 440128.97 1.11E+07 29.980
CM92 6029.54 440123.06 4.11E+06 11.129
CM93 6013.75 440148.98 7.10E+06 30.348


AREA = 0.125 Ha
AREA = 0.310 Acres

Area computations

PLOT 18
Station Northing Easting DIST
CM8 6426.88 440246.70
CM22 6458.45 440233.97 -1.40E+07 34.036
CM23 6480.69 440259.67 -9.63E+06 33.987
CM7 6439.72 440273.81 1.81E+07 43.339
CM8 6426.88 440246.70 5.48E+06 29.998


AREA = 0.119 Ha
AREA = 0.295 Acres

PLOT 5
Station Northing Easting DIST
CM1 6183.37 440152.78
CM84 6158.71 440216.82 1.12E+07 68.616
CM3 6177.84 440226.41 -8.36E+06 21.399
CM8 6239.03 440211.85 -2.70E+07 62.899
I/0417 6240.22 440191.89 -6.45E+05 20.000
CM1 6183.37 440152.78 2.48E+07 68.998


AREA = 0.353 Ha
AREA = 0.873 Acres

ABSTRACT OF CO-ORDINATES

STN NORTHINGS EASTINGS
RTS40 5864.96 440272.31
I/0491 5,958.00 440,256.97
CM300 5,967.30 440,260.72
CM400 5,988.85 440,262.65
CM120 6,004.29 440,237.86
CM118 5,977.77 440,223.61
CM93 6,013.75 440,148.98
I/0486 6,023.11 440,154.97
CM500 6,028.21 440,158.17
CM95 6,048.72 440,171.00
CM90 6,064.38 440,144.88
CM91 6,038.97 440,128.97
CM92 6,029.54 440,123.06
CM1 6,183.37 440,152.78
CM2 6,158.71 440,216.82
CM3 6,177.84 440,226.41
CM8 6,239.03 440,211.85
I/0417 6,240.22 440,191.89
CM8 6,426.88 440,246.70
CM21 6,458.45 440,233.97
CM23 6,480.69 440,259.67
CM7 6,439.72 440,273.81
RTS38 6273.71 440361.22

Table5: shows how tallying was the old data to the ground data.

ABSTRACT OF CO-ORDINATES OLD DATA

STN NORTHINGS EASTINGS STN NORTHINGS EASTINGS
I/0491 5,958.00 440,256.97 I/0491 440256.970 5958.000
CM300 5,967.30 440,260.72 CM300 440260.720 5967.300
CM400 5,988.85 440,262.65 CM400 440262.650 5988.850
CM120 6,004.29 440,237.86 CM120 440237.860 6004.290
CM118 5,977.77 440,223.61 CM118 440223.610 5977.770
CM93 6,013.75 440,148.98 CM93 440148.980 6013.760
I/0486 6,023.11 440,154.97 I/0486 440154.970 6023.120
CM500 6,028.21 440,158.17 CM500 440158.170 6028.220
CM95 6,048.72 440,171.00 CM95 440171.000 6048.730
CM90 6,064.38 440,144.88 CM90 440144.880 6064.390
CM91 6,038.97 440,128.97 CM91 440128.970 6038.980
CM92 6,029.54 440,123.06 CM92 440123.060 6029.550
CM1 6,183.37 440,152.78 CM1 440152.790 6183.380
CM2 6,158.71 440,216.82 CM84 440216.820 6158.720
CM3 6,177.84 440,226.41 CM3 440226.410 6177.850
CM8 6,239.03 440,211.85 CM8 440211.860 6239.044
I/0417 6,240.22 440,191.89 I/0417 440191.895 6240.229
CM8 6,426.88 440,246.70 CM8 440246.720 6426.890
CM21 6,458.45 440,233.97 CM22 440234.000 6458.460
CM23 6,480.69 440,259.67 CM23 440259.700 6480.700
CM7 6,439.72 440,273.81 CM7 440273.830 6439.730

Table6: shows how different was the old data was to the LIS data.
GROUND DATA LIS DATA
PLOT 15 PLOT 15
Station Northing Easting Station Northing Easting
I/0491 5958.00 440256.97 I/0491 5962.16 440265.71
CM300 5967.30 440260.72 CM300 5970.42 440268.41
CM400 5988.85 440262.65 CM400 5991.85 440268.25
CM120 6004.29 440237.86 CM120 6007.41 440247.45
CM118 5977.77 440223.61 CM118 5979.78 440232.37

PLOT 6 PLOT 6
Station Northing Easting Station Northing Easting
CM93 6013.75 440148.98 CM93 6018.77 440141.58
I/0486 6023.11 440154.97 I/0486 6027.8 440148.2
CM500 6028.21 440158.17 CM500 6033.43 440152.5
CM95 6048.72 440171.00 CM95 6053.19 440167.15
CM90 6064.38 440144.88 CM90 6070.19 440140.05
CM91 6038.97 440128.97 CM91 6044.84 440122
CM92 6029.54 440123.06 CM92 6036.34 440117.27

PLOT 5 PLOT 5
Station Northing Easting Station Northing Easting
CM1 6183.37 440152.78 CM1 6190.89 440153.70
CM84 6158.71 440216.82 CM84 6168.44 440211.02
CM3 6177.84 440226.41 CM3 6182.84 440216.73
CM8 6239.03 440211.85 CM8 6239.35 440196.62
I/0417 6240.22 440191.89 I/0417 6245.21 440182.83

PLOT 18 PLOT 18
Station Northing Easting Station Northing Easting
CM8 6426.88 440246.70 CM8 6428.19 440240.54
CM22 6458.45 440233.97 CM22 6469.62 440228.95
CM23 6480.69 440259.67 CM23 6480.90 440253.08
CM7 6439.72 440273.81 CM7 6440.10 440268.00

Table7. It shows the discrepancies of the ground coordinates and the scanned UTM coordinates of the new computerized system.

Source: Essay UK - http://turkiyegoz.com/free-essays/economics/land-information-system.php


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