EFFICIENT AND FAST PRODUCTION OF CADASTRAL

EFFICIENT AND FAST PRODUCTION OF CADASTRAL MAPS IN ETHIOPIA
Thomas Dubois
International Cadastral Mapping Adviser, REILA project
NIRAS Finland Oy
[email protected]
Paper prepared for presentation at the
“2016 WORLD BANK CONFERENCE ON LAND AND POVERTY”
The World Bank - Washington DC, March 14-18, 2016
Copyright 2016 by author(s). All rights reserved. Readers may make verbatim copies of this
document for non-commercial purposes by any means, provided that this copyright notice
appears on all such copies.
Abstract
Ethiopia is estimated to have 50 million parcels. Of these, only a fraction are registered in any kind of
cadastral register. The rest of the parcels can only be distinguished by informal agreements between the
land holders in the country. The effects of this are numerous land conflicts and a high tenure insecurity. It
has been shown by many international studies that the introduction of a cadastral system generally gives a
greatly improved tenure security. In real terms, a cadastral register can therefore mean less conflicts,
increased food production and an improved environmental protection. It also empowers women and
increases gender equality.
The Responsible and Innovative Land Administration (REILA) project is a cooperation between the
Finnish and Ethiopian governments. It is implemented by the consultant company NIRAS and has been
active since 2011. Its main focus has been to support the development and performance of rural cadastral
mapping in Ethiopia.
This paper will explain how the REILA project recently has effectivized the mapping process to greatly
minimize the time and effort needed to produce the cadastral maps. This is done with a method that is
easy to teach and that can be performed by using only open source softwares.
Key Words:
Land administration, Cadastre, Ethiopia, Parcel maps, Efficient production
2
Table of Contents
1
Introduction ........................................................................................................................................... 4
1.1
The General Cadastral Situation in Ethiopia ................................................................................. 4
1.2
The REILA Project ....................................................................................................................... 5
1.3
Cooperations ................................................................................................................................. 6
1.4
Field Surveying Methods .............................................................................................................. 6
1.5
Imagery-based Field Surveying of Parcels ................................................................................... 7
1.6
Editing and Printing of Imagery-based Field Data ....................................................................... 7
1.7
Information About the Author ...................................................................................................... 8
1.8
Acknowledgements ....................................................................................................................... 8
2
General Description of the Workflow ................................................................................................... 9
3
Production of Field Maps.................................................................................................................... 11
4
Field Work .......................................................................................................................................... 14
5
Office Editing...................................................................................................................................... 16
5.1
Scanning and Georeferencing ..................................................................................................... 16
5.2
Quality Control ........................................................................................................................... 18
6
Public Display and Additional Editing ............................................................................................... 20
7
Printing of Parcel Maps....................................................................................................................... 21
8
Handover and Maintenance ................................................................................................................ 22
9
Possible Future Improvements ............................................................................................................ 23
10
Conclusions ..................................................................................................................................... 26
11
Table of Figures .............................................................................................................................. 27
3
1 Introduction
1.1 The General Cadastral Situation in Ethiopia
In Ethiopia, it is estimated that there are approximately 50 million parcels. Of these, only a fraction are
registered in any kind of cadastral register. The rest of the parcels can only be distinguished by informal
agreements between the land holders in the country. The effects of this are numerous land conflicts and a
high tenure insecurity, which have the result that the land holders use the land in a very short term
perspective. It has been shown by many international studies that the introduction of a cadastral system
gives a greatly improved tenure security. In real terms, a cadastral register can therefore mean less
conflicts, increased food production and an improved environmental protection. Since it is made
mandatory by law to register also the spouse in joint (family) holderships, it also empowers women and
increases gender equality. To complete a modern digital cadastre that covers the whole country has
therefore been high on the agenda for the Ethiopian government on both national and regional level.
The scale of this task means that any improvement in the production speed is of utmost importance. It
should be mentioned that parcels are held (not owned) from the Government of Ethiopia by the land
holders through a lease system that normally spans between 25 and 99 years, depending on the type of
holdership. In addition, holding of land without time limit exists in rural areas for peasants and
pastoralists. In some areas, registration of the parcel attributes (land holder names, land use, parcel ID
etc) have been performed. This is titled First level registration, and does not include the measurement of
the parcel boundaries. However, it has been found that there is an urgent need of a Second level
registration, which includes the registration of the parcel boundaries. The main use of the geographical
features of the parcels are general planning, valuation, land disputes and reallocation.
Figure 1. The regions of Ethiopia.
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The country is divided into administrational units at four levels: Region, Zone, Woreda (“district”) and
Kebele (“sub-district”). Parcel IDs are created by using codes (numbers or letters separated by slashes) for
the four administrational units, followed by either a Holding and Parcel ID, or only a Parcel ID (this
differs between the regions). E.g. in the Benishangul-Gumuz region, a full parcel ID could be
06/02/02/14/1502.
1.2 The REILA Project
The Responsible and Innovative Land Administration (REILA) project is a cooperation between the
Finnish and Ethiopian governments, and has been active since August 2011. Its main focus has been to
support the development and performance of rural cadastral mapping in Ethiopia. The project will finish
in June 2016, but different extension possibilities are now evaluated. REILA involves the following
Ethiopian institutions:

The Ministry of Agriculture and Natural Resource, Land Administration and Use Directorate
(MoARD-LAUD).

The Ethiopian Mapping Agency (EMA).

The Amhara Bureau of Rural Land Administration and Use (BoRLAU).

The Benishangul-Gumuz Bureau of Environment, Forestry and Land Administration (BoEFLA).

In addition, the Information Network Security Agency (INSA) is an indirect beneficiary of the
project.
One of the main tasks of the REILA project is to establish a cadastral system in its focus areas. Initially
this included the Amhara and Benishangul-Gumuz regions. However, REILA was given the
responsibility by the Ethiopian Ministry of Agriculture and Natural Resource to evaluate imagery based
cadastral mapping in different geographical and cultural environments using different methods
countrywide. This expanded the activities to the Oromia, SNNP and Tigray regions. This task resulted in
reports, seminars and an Operations Manual, as well as valuable experience for the project staff and its
counterparts.
Among other project activities, the following can be mentioned.

Supporting the acquisition of aerial and satellite imagery that covers parts of Amhara and
Benishangul-Gumuz, e.g. by assisting the planning and performance of ground control point
surveying.

Establishing of a TVET Land Administration education in Assosa, Benishangul-Gumuz.
5

Establishment of a new geodetic national zero-order reference network in cooperation with EMA.

Establishment of a new National Rural Land Administration Information System (NRLAIS) in
cooperation with mainly EMA, MoARD-LAUD and INSA.

Capacity building through cooperation with universities inside (e.g. Bahir Dar University) and
outside (e.g. ITC Holland) of Ethiopia.

Arrangement of seminars and study visits (e.g. to Holland, Germany, Rwanda and Finland) for
persons with key positions in the mentioned Ethiopian counterpart organizations.

Presentations and publications of documents at e.g. World Bank- and FIG events.
1.3 Cooperations
Except cooperation with the mentioned counterpart institutions, the following programmes/projects can
be mentioned:

Land Investment for Transformation (LIFT). This six-year DFID-funded project started 2014 and
focuses on the issuance of second level certification in Ethiopia. The cooperation between REILA
and LIFT is mainly through sharing of experience and planning of related cadastral activities.

Sustainable Land Management Programme (SLMP). This programme is mainly carried out by
MoARD-LAUD. The cooperation with REILA has included sharing of staff and experiences.
1.4 Field Surveying Methods
Since around 10 years, different mapping methods have been tested in Ethiopia to evaluate which method
that is most suitable for rural cadastral mapping. The traditional ground surveying techniques (using total
station or precision GPS) are in many cases expensive and difficult to teach in a short time. They are very
accurate though, so they are preferred in infrastructure and (peri)-urban mapping. The handheld GPS is
comparatively inexpensive and easy to use, but has a problem with random inaccuracy when used outside
North America, Europe and Eastern Asia. However, for navigation purposes in the field work, it is a very
useful tool. Satellite and aerial image techniques are comparatively inexpensive and accurate, easy to
teach and have seen a rapid development the recent years. The accuracy and resolution of the imagery
have been drastically improved the recent years, and are suitable for rural cadastral mapping nowadays.
For these reasons, imagery based rural second level registration was selected as the main cadastral
mapping method of the REILA project.
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1.5 Imagery-based Field Surveying of Parcels
The images are printed out and brought to the field for identification of the parcel boundaries. The parcel
borders are confirmed at the location of the parcel by the land holder, neighbors and a Land
Administration Committee member (the legal representative). The borders are then simply drawn with a
pen directly on the image printout. This method is proved to be very successful, since it is fast, easy to
teach and has an accuracy (normally 1-2 m) that fits the purpose for rural cadastral mapping. It also has a
high acceptance from the land holders, since they can easily verify that the parcel borders are correctly
demarcated on the image printout by comparing the drawn border lines with features (e.g. roads, trees) in
the image printout.
1.6 Editing and Printing of Imagery-based Field Data
The office part of the process involves scanning and referencing of the printed image which includes the
drawn border lines, followed by digitization of the borders in a GIS software. Until recently, this process
had several bottlenecks. The production of the image printouts took a long time, involving the creation of
an atlas of images covering the selected sub-district.
The recent development of the methodology now means that the process has an improved quality control
and greatly reduces the time needed to produce the map printouts needed for the work. This is all done
based on open source software, mainly using the latest version of the Quantum GIS (QGIS) software. By
using a combination of built-in functions in the mentioned software, an atlas consisting of hundreds of
field maps can now automatically be produced in a few hours, using digital orthophotos as the main
resource. The parcel map production is even more improved, with functions that automatically creates a
parcel map atlas in a pdf file containing all parcel maps. For each individual parcel map it automatically
links in the attribute information about the parcel and the land holder, finds an appropriate zoom level for
the parcel size and adds the map to the pdf file. The user can then simply print the whole file to produce
the maps in one step. Both the map generation and the printing can be performed in one day for a subdistrict, which typically consists of 5.000-6.000 parcels. With the previous method, this typically took 4-5
weeks of full time work for one person.
Other improvements include an effective quality control which can be fully performed within the QGIS
software. The quality control includes topology checking, detection of outlying attribute values as well as
detection of duplicate parcel IDs.
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1.7 Information About the Author
The author of this document, Thomas Dubois holds an M. Sc. in Surveying (specializing on Geodesy and
GIS) from the Royal Inst. of Technology (KTH) in Stockholm, Sweden, and is a permanent employee of
the consultant company NIRAS. He is the International Cadastral Mapping Adviser in REILA since the
beginning of the project, and is stationed as a component team leader in Bahir Dar, Amhara region.
1.8 Acknowledgements
The author wishes to thank all staff working within REILA and NIRAS as well as all staff and
managements within the Ethiopian and Finnish counterpart organizations for their invaluable contribution
to the development of the methods described in this document.
8
2 General Description of the Workflow
This document will focus on the technical parts of the project methodology. However, to give the full
picture of the implementation of the second level registration in the project areas, the major steps are
listed here.
In the preparatory phase activities that form the basis of the certification should be conducted. These
include:

Selection of a kebele (sub-district) where the second level registration will be performed.

Training of trainers and operation managers.

Recruitment and training of contractual staff.

Strengthen/establish and train Kebele Land Administration Committee members.

Update the registry from the 1st level registration (parcel attributes, e.g. land holder names, land
use), if it exists.

Verify the current extents of the kebele boundary.

Settle as many conflicting interests/disputes as possible.

Perform procurement and setting up of all the necessary equipment and materials.

Public Information and Awareness (PIA) creation for different target groups (e.g. decision
makers, land holders).

Arrangement of transportation facilities.

Preparing and printing of field maps and different field registration forms.
The field work can be divided into two separate parts:

Surveying and mapping of the land parcel boundaries.

Adjudication - identification, assessment, and verification of the legal holders, the legal rights and
encumbrances for each parcel.
The following are the major activities performed at the office level:

Scan and geo-reference the printed out field maps including parcel borders demarcated with a
pen.

Digitize parcel boundaries.

Construct and fill in the parcel attribute table.

Scan all existing records and field registration forms.
9

Perform quality control of all the information.

Print out the information for Public Display. During this, the land holders verify their registered
boundaries and parcel attributes.

Make corrections of the information following the Public Display.

Produce a map for each parcel.

Prepare for the transition to the maintenance phase, so that the cadastre can be continuously
updated easily.
Figure 2. A farmer is participating in the measurements of his parcel.
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3 Production of Field Maps
The first step is the acquisition of the imagery. One source is Satellite images that are normally ordered
from a digital image provider (e.g. Digital Globe). Another option is to use Aerial images. These require
thorough preparations (e.g. planning and acquiring airborne photogrammetry equipment), but will give a
higher resolution and avoids large displacements in the image due to incorrect compensation of
displacements caused by the terrain undulation. The development of enhanced and accurate global terrain
models has limited the effects of this error also for the satellite images.
When the images are received, an area to be mapped has to be selected. In the REILA case, this is
normally a kebele (sub-district). The approximate boundaries of the selected kebele then have to be
obtained. These are used to select the parts of the images that will be printed out.
By using the approximate boundary of the selected kebele, imagery is made available for the field map
production. The selection is normally done by opening the image database and the kebele boundary in the
QGIS software.
Figure 3. Kebele boundaries are used to select images.
The image contrast, brightness and saturation are adjusted individually to enhance the image details. The
kebele boundary is then adjusted after discussions with local Land Administration experts. If a detail in
the image (e.g. a river) is known to be the exact boundary, the borders are adjusted to fit that feature.
11
By using the QGIS Vector tools, a buffer zone with a distance of e.g. 1500 m is then created around the
given boundary. This zone will be used later to create additional field maps on demand if the approximate
boundary is not covering the actual kebele borders.
In QGIS, a rectangular vector grid is created with a suitable dimension to cover the whole kebele
including the buffer zone. Each rectangle gets a dimension to fit the selected map scale (normally 1:1000
or 1:2000) and paper size (normally A3 or A2). The initial point in the grid (upper left corner) gets
coordinates rounded off to even 100-values to enable an identical position of the coordinate grid lines on
each field map (the grid coordinates will of course be different for different maps).
By using Spatial query functions, two layers of rectangles are created. The first contains all rectangles
that are on or inside the kebele boundary. The second layer contains all remaining rectangles that are on
or inside the buffer zone.
Figure 4. Grid rectangles for field map creation in the kebele and the buffer zone.
The layer with the grid inside the kebele boundary is then used in the QGIS Print composer as the Atlas
Generation Coverage layer. By using a predefined Composer Template, the field maps are harmonized,
and it is simple to fill in the needed information (e.g. the kebele name, image acquisition date etc) by
using existing and formatted labels in the template. The Atlas Generation function will generate one pdf
file that contains all field maps inside the kebele. The maps are automatically numbered in a sequence
from 1 and up. The field maps can then conveniently be printed out from e.g. Adobe Reader with the
selected paper format.
12
Figure 5. An example of an A3 sized field map.
After this, the maps in the buffer zone layer are generated into a pdf file (but not printed). These maps are
also numbered from 1 and up but beginning with the letter ‘A’ (for Additional) to distinguish them from
the maps inside the kebele. An Overview map is also produced in the QGIS Print Composer (using a
separate template), displaying the numbers of each field map from both the kebele- and buffer series.
In case the real kebele boundary is found to exceed the area covered by the printed out maps, additional
maps can conveniently be printed out simply by finding the numbers of the needed additional maps in the
overview. Since they are all prepared in a pdf file, individual maps can then quickly be printed out. This
also assures that a minimum of paper and toner is used, since additional maps are only printed on demand.
Figure 6. Example of an overview map (left) and an enlargement (right) to display the sheet numbers.
13
4 Field Work
Since the technical aspects are the focus of this document, the field work is only briefly described. The
prerequisites are the following:

A Public Information and Awareness campaign has to be performed in the location of interest.

If a first level cadastral register (parcel attributes) exists, it should be updated with current
information from recent land administration activities (e.g. from inheritance, subdivision etc).

A field team has to be in place, consisting of a surveyor (to draw the boundaries on the field
map), a field registrar (to register all parcel attributes (land holder name, parcel ID etc), a team
leader (to control the acquired field data and to plan the team activities and write reports), and
finally a Land Administration Committee member, who is the legal representative from the
kebele.

Equipment has to be available, consisting of a selection of field maps (covering the area to be
visited the coming days), field registration forms, clipboards, bags, stationery, 50 m measurement
tape, ruler and a handheld GPS. A means of transportation (normally a car) also has to be
available.
The team leader and the committee member plan the daily activities and make sure that the land holders
are present when the team moves systematically from parcel to parcel. The land holder points out
boundary features (e.g. roads) and the indicated borders are drawn in the image. The parcel ID is then
written in the middle of the parcel to enable identification during the digitizing process. After the parcel is
demarcated and all data is collected, the field form is signed by the land holder, team leader and
committee member.
Figure 7. A field team during the demarcation of a parcel (left), and an example of a parcel demarcated in the field map.
14
The measurement tape is used if a border corner cannot be seen in the field map image. In these cases, the
distance is measured to an object that can be identified both in the image and on the ground. The distance
is converted to the map scale, and by using a ruler, the correct place can be located in the image. In case
the direction is uncertain, two or more additional measurements are performed in the same way to obtain
the location through intersection. The handheld GPS is only used for navigation purposes and for tasks
with a lower accuracy demand (like the demarcation of the kebele boundary).
Figure 8. Example of the use of a 50 m tape and a ruler to demarcate hidden parcel corners.
The land holder is asked to present any documentation that shows that he/she is the legal holder. If a first
level registration exists in the area, it is normally a holding- or parcel registry book that has been issued to
the farmer previously by the Woreda (district) Land Administration office.
Regarding field forms, two main possibilities exist. If there is an existing database with updated parcel
attributes, the data can be printed out and brought to the field. The field registrar will then correct any
erroneous information and simply confirm correct information. This will normally increase the speed
since less writing is needed, but can be limited by uncertainties and errors in the printed out database
information. The second option is to use blank field registration forms and create a new database. This is
preferable if any exiting cadastral information is limited or untrustable. The advantage with the second
option is also that it is possible to create a ‘tailor-made’ structure with desired contents. This is of special
importance when the new national rural cadastral methodology (NRLAIS) is developed.
When a field map is completed, it should be delivered to the office without delay. The field crew then
continues until the kebele is completed. They can then move to the next kebele and start there if all
preparations are done.
15
5 Office Editing
5.1 Scanning and Georeferencing
When the field maps are delivered to the office, they are first scanned with an appropriate scanner. For A3
size maps, a simple A3 scanner will perform the task.
To reference the scanned image, the Georeferencing function in QGIS is used. To perform this, nine
evenly distributed grid crosses from the printed coordinate grid are selected. The comparatively high
number of points is chosen to ensure that any grosserror is easily detected, and to be able to find local
deformations in the map (e.g. due to folding damages). Each grid cross is zoomed in and digitized,
followed by the entering of the grid cross coordinates, which are printed in the margins of the field maps.
If any large residuals appear (larger than 3 pixels), all grid gross demarcations and entered coordinates are
checked. If physical deformations of the map are found to be the reason, the map is re-scanned with
additional pressure put on it to flatten it out. Minor errors have been found to be the consequence of
folding the map, so this should be avoided.
Figure 9. Selected (circled) grid crosses for georeferencing (left) and a digitized grid cross center (right).
When the georeferencing is satisfactory, the new referenced image is added to the main view in QGIS. A
simple way to check the quality of the georeferenced image is to compare it to a reference grid (with the
same grid interval as the field maps) that can be generated in QGIS. Any deviations are then clearly
visible if the scanned map- and reference grid are deviating from each other.
16
Figure 10. Acceptable accuracy (left) and not acceptable (right), when the reference grid line is completely outside the image
grid.
If the referencing quality is acceptable, the digitizing of the parcels can start. A polygon layer with a
predefined attribute table is created for the purpose of gathering the parcel information. The digitizing is
done by choosing the polygon tool and then carefully clicking on each border corner that is demarcated
with a pen in the field. For curved borders a sufficient number of points are digitized to represent the
boundary well.
A new function that speeds up the parcel digitizing is the Autotrace function. When demarcating the
borders of the neighbor to an existing parcel, it is enough to click at both common corners of the existing
parcel. The function will then trace and snap on all points between the selected corners of the existing
parcel. In the figure below, a new parcel (shown in red) is attached to point A and B. The existing points
in between are snapped to automatically.
A
B
Figure 11. The Autotrace function. Automatic point snapping is made from A to B for the new parcel.
17
A very convenient feature in QGIS is the style files. They can be created as templates, and by activating a
style file for a certain layer, all colors, line widths etc are set to the predefined style. The advantage of this
is that the graphic display of different layer categories (grids, parcels, boundaries etc) can be harmonized
and is also very quick to implement.
5.2 Quality Control
To avoid gaps, overlaps and invalid parcel geometries, the QGIS Topology checker is used. This function
should be regularly used during the parcel digitizing to avoid topology errors.
A
B
C
Figure 12. An example of overlaps (A), gaps (B) and invalid geometries (C, the parcel border is crossing itself).
The attributes are first checked by sorting each column in the table. For values, errors are then found by
looking at the top and bottom of each column if the erroneous input has an extreme value (e.g. a team
number that is higher than the number of teams). Also text columns can be checked by sorting them and
then scrolling through them. Since they are sorted, misspellings are easily found.
By using the function Select features by using an expression, it is also possible to detect duplicate parcel
IDs, since they should have unique values.
Figure 13. Detection of duplicate parcel IDs.
18
If several data encoders are digitizing the same kebele, it is important to coordinate and supervise the
digitizing, since topology errors will occur when files from different encoders are joined together. One
person will then be responsible to create on é final file containing the whole kebele (sub-district).
The quality control is also performed by re-checking the information in selected parcels. When the
digitizing is complete and the quality control is finished, the Final kebele boundary is demarcated. It is of
utmost importance to take regular backups throughout the process.
19
6 Public Display and Additional Editing
Even if the quality control in the field and in the office is rigorous, misunderstandings in the field and
undetected errors will remain. To detect these errors and to enable transparency in the registration, a
Public Display map is printed out and displayed in the kebele for a certain amount of time (e.g. one
month). It is then possible for each land holder to verify that the boundaries of his/her own parcel(s), as
well as others in the kebele (sub-district), are correct.
In addition, the collected attributes of each parcel are printed out and displayed, and a field team is
stationed at the selected site in the kebele throughout the display period. Each land holder must now
verify that the border- and attribute information are correct. The task of the field team is to collect the
signatures and note any incorrect data that is found. They also guide the land holders so that they find
their parcels in the kebele map and the attribute tables.
Figure 14. A land holder is shown the location of her parcel on the public display map.
When the display period is over, the errors that were found are corrected in the office. If necessary, field
visits have to be performed to sort out any problems that cannot be solved in the office. It should be noted
however, that it is not possible to achieve a successful and correct registration of 100% of the parcels in a
kebele. Land disputes and complicated editing errors has to be put in the maintenance list so that the
second level certification can take place for the completed majority of the parcels in the kebele.
20
7 Printing of Parcel Maps
One major bottleneck in the second level certification process was the creation of the individual parcel
maps. The procedure was to manually panorate the Print Composer view in QGIS and adjust the zoom
level to find a suitable scale for the parcel. The attribute data (e.g. parcel ID, land holder name) then had
to be manually copied from the attribute table into the parcel map, after which it could be printed. This
was a tedious process that took 5-10 minutes per map. With a normal volume of 5.000 parcels for a
kebele (sub-district), this took several weeks to perform. The use of map templates and the atlas function
dramatically reduced the time and effort to generate the parcel maps, by using the following steps:

The shapefile containing the parcels is selected for the atlas grid generation.

The map is set to be Controlled by atlas, and to use a range of Predefined scales. This will enable
the software to automatically find an appropriate scale and position for each map depending on
the parcel size and location.

The attribute information for the current parcel is obtained by adding a table with a link to the
desired column in the attribute table, and selecting Current atlas feature as the source.

After entering the common information for all parcels (e.g. kebele name, date of printing) in the
predefined labels in the template, a pdf file can be generated. If Single file export is selected, the
result will be one pdf file containing all parcels in ID or land holder name order.


The parcel maps in the pdf file can then be printed out in sequence or by selecting individual
maps in e.g. Acrobat Reader.
The main remaining bottleneck is the needed signatures and stamps on each map. It is under
investigation if this could be simplified (e.g. by including scanned signatures) in a way that is
supported by the legislation and trusted by the land holders.
Figure 15. An example of a parcel map.
21
8 Handover and Maintenance
When all parcel maps are finished, the whole work including the digital cadastre files, maps, field forms
and backups should be taken care of by the implementing organization. In the REILA case, this is
normally the Woreda, which is an administrational unit on district level, normally containing 10-50
kebeles (sub-districts).
Among the most important parts and the greatest risks of the whole project is the maintenance. If proper
routines are not followed and the cadastre is not properly and regularly updated, the whole work may
have to be repeated after some years. Many changes have then occurred due to e.g. inheritance and
infrastructural development. Ethiopia has started an enormous task which is of utmost importance to
finish as soon as possible. Therefore, huge resources in manpower and equipment are needed for the
continuous mapping of new areas. It is then a risk that the maintenance is partly neglected due to lack of
resources. To distribute them so that the maintenance can still be performed is therefore of highest
importance for the future use and reliability of the cadastre.
To support the maintenance, it is important to ensure that the updating routines are initiated immediately
after delivery and included as a part of the daily work for the land administration staff in the woredas and
kebeles. Capacity building is also very important, since staff turnover might mean that a knowledge gap
suddenly appears when no one at the land administration office can handle a certain part of the production
chain.
22
9 Possible Future Improvements
When the production chain is created, it is important not to be locked to a certain software or data format,
since this might mean that new methods or softwares cannot be implemented. It is also important to be
attentive to any technical developments within land administration, since technical innovations can
further effectivize the process. In the methodology presented in this document, some possible future
improvements can be mentioned:
The georeferencing module that is used now in QGIS is generalized to work for all normal types of
georeferencing, with different number of points and point distributions. The module is therefore not ideal
for the specific use of referencing the field maps with nine grid crosses. In the present module, it is
necessary to input the coordinates of each of the nine grid crosses, and also to zoom in and out to find
them. Since the printed coordinate grid on the scanned field maps have a regular grid cross distribution
and scale, it would be enough to indicate the position in the image and enter the coordinates for the upper
left and lower right grid crosses and finally give the grid interval. The software could calculate the
location of the remaining seven points in the ground coordinate system. It could then make an
approximate zoomed in display on each point (since their approximate locations are known) to simplify
the digitizing of the exact position of each grid cross. This would make the georeferencing remarkably
quicker and more fail-safe (since fewer coordinates are entered) for the specific purpose of referencing
field maps.
Figure 16. An illustration of zoomed in grid crosses in a possible future georeferencing module.
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One of the most time consuming parts of the office process is the digitizing of parcels. It is somewhat
simplified by the previously mentioned Autotrace function, but in most cases it still needs the manual
digitizing of each parcel corner. The regular checking of topology errors is also time consuming.
To use some kind of automatic line extraction in images have been investigated on several occasions, but
there are a limited number of free softwares that can perform the process (Incscape and WinTopo are
among the few). If the landscape is free of trees, flat and dominated by a checkerboard of parcels used for
agriculture, most borders that are visible in the image are also the real boundaries, and the extracted lines
cold then simplify the work. However, in many areas trees are used for border demarcation, and together
with other natural features like rivers and gullies, they will generate a large number of erroneous borders
if an automatic line tracing function is used. This demands extensive and time consuming editing, and
also demands experienced users.
An approach that might be promising in the future is to use a type of semi-automatic line tracing. This
method begins with the assumption that the field maps are scanned, and that all parcel borders are
demarcated with a pen. Every parcel corner that is shared with another parcel is called a node. In the
example in the following figure, they are labeled A to E for the parcel 1101/04. Between the nodes, there
is normally a need to digitize a number of points to follow the border shape. With semi-automatic tracing,
the function would start with digitizing the nodes A and B only. The function first retrieves information
about the pen color (with a certain tolerance) where the nodes are digitized. The function can then try to
create a straight line from A in the attempt to connect to B, following the color of the pen line. When the
line turns (no more pen color in that direction), a border point is automatically created, and a new straight
line is started from there. Finally, after creating more border points, the function will in most cases find B
and the border section between A and B is automatically completed.
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A
E
D
A
C
B
B
Figure 17. Nodes labeled A-E in a parcel (left), semi-automatic line tracing between nodes (right).
After the A-B section is completed, the node C is digitized and automatically connected to B through
additional border points. The process is repeated until the whole parcel is demarcated. In case the line
passes through e.g. a tree shadow with the same color as the pen, some manual digitizing is needed.
However, for most parcels only the border nodes need to be digitized, which significantly speeds up the
process. If a neighboring parcel is digitized using the same nodes as a finished parcel, the function can reuse the calculated border points between the nodes so that gaps and overlaps are avoided.
Handheld GPS equipment’s suffer at present from random inaccuracy that can reach up to 10 meters in
some cases when used in Ethiopia. The main reason for this is that it is not possible to receive any
correction signals in this country that are otherwise found in Europe (EGNOS) or North America
(WAAS). If a similar signal world start to be transmitted with a range including Ethiopia, the errors
would be greatly reduced and the handheld GPS could then be much more suitable for some tasks within
cadastral mapping.
Satellite images might have a problem with displacements of details in areas with steep terrain with many
natural breaklines. The main reasons for this is that a terrain model is used to compensate for these
displacements caused by the perspective from the satellite. If the terrain model is not accurate enough,
displacement errors in the final picture will occur. However, the international terrain models are
continuously improved, and if future terrain models go down to around meter accuracy, satellite images
will compete on almost equal terms with aerial images, since the image resolution is already at around 30
cm for e.g. the new satellite WorldView 3.
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10 Conclusions
This document describes how the REILA project has developed simple, fast and efficient methods to
perform cadastral mapping in Ethiopia.
In general, the recent developments of the cadastral mapping process have greatly reduced time and effort
needed to produce the cadastral register in an Ethiopian kebele (sub-district). Previously, it was a tedious
operation to print out field- and parcel maps, but due to developments of the methodology it is now a very
fast and automated process, which is performed with open-source software (Quantum GIS).
The quality control of geographical and attribute data for the parcels has been simplified by the use of
topology checking functions for the parcel boundaries and sorting of individual columns in the attribute
table.
One of the major threats to a developed cadastral database is when the maintenance of the register is not
handled properly. It is therefore of great importance to support that resources are set aside for this.
Capacity building to avoid problems during staff turnover is also a major issue.
Future technical developments will certainly allow an even faster, flexible and reliable methodology. It is
therefore important to monitor the development of software and equipment and update the procedures
regularly.
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11 Table of Figures
Figure 1. The regions of Ethiopia. ................................................................................................................ 4
Figure 2. A farmer is participating in the measurements of his parcel. ...................................................... 10
Figure 3. Kebele boundaries are used to select images. .............................................................................. 11
Figure 4. Grid rectangles for field map creation in the kebele and the buffer zone. ................................... 12
Figure 5. An example of an A3 sized field map. ........................................................................................ 13
Figure 6. Example of an overview map (left) and an enlargement (right) to display the sheet numbers. .. 13
Figure 7. A field team during the demarcation of a parcel (left), and an example of a parcel demarcated in
the field map. .............................................................................................................................................. 14
Figure 8. Example of the use of a 50 m tape and a ruler to demarcate hidden parcel corners. ................... 15
Figure 9. Selected (circled) grid crosses for georeferencing (left) and a digitized grid cross center (right).
.................................................................................................................................................................... 16
Figure 10. Acceptable accuracy (left) and not acceptable (right), when the reference grid line is
completely outside the image grid. ............................................................................................................. 17
Figure 11. The Autotrace function. Automatic point snapping is made from A to B for the new parcel. .. 17
Figure 12. An example of overlaps (A), gaps (B) and invalid geometries (C, the parcel border is crossing
itself). .......................................................................................................................................................... 18
Figure 13. Detection of duplicate parcel IDs. ............................................................................................. 18
Figure 14. A land holder is shown the location of her parcel on the public display map. .......................... 20
Figure 15. An example of a parcel map. ..................................................................................................... 21
Figure 16. An illustration of zoomed in grid crosses in a possible future georeferencing module. ............ 23
Figure 17. Nodes labeled A-E in a parcel (left), semi-automatic line tracing between nodes (right). ........ 25
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