**GPS Equipment for Agricultural Statistics Surveys - Lessons Learned
from Fieldwork in Uganda**

J. Magezi-Apuuli, E. Menyha, E. S. K. Muwanga-Zake (Ph.D) and P.
Schøning

**Summary**

1\. One of the most important factors for production used in growing
crops, raising livestock or any other farming activity, is land. The
pattern of land-use usually varies by seasons or by different regions of
Uganda. Thus, accurate data on area used for agricultural purposes is an
important aspect of agricultural planning.

2\. In Uganda there is unfortunately no complete set of cadastral maps
and/or land registers from which area information can easily be derived.
Experience from previous agricultural censuses and surveys also reveals
that most rural holders in Uganda are not able to accurately determine
the size of their land in quantitative terms that can be used in
statistics. Therefore, when statistical surveys and censuses are
conducted, any information on the size of land has to be by some kind of
measurement.

3\. This paper discusses results from a Pilot Census of Agriculture
(PCA) in Uganda in 2003 which indicate that there is potential to use
relatively cheap Global Positioning System (GPS) equipment for measuring
of area and for geo-referencing of holdings in the context of
agricultural statistics. However, experience from the fieldwork shows
that there is need for thorough training of field staff before GPS tool
can be efficiently used. More studies are also recommended concerning
the variability and consistency of the equipment, especially where tree
cover and/or hilly areas introduce "shadow" and projection problems.

Table of contents

[1 Introduction 2](#introduction)

[2 Areas in the context of agricultural statistics
2](#areas-in-the-context-of-agricultural-statistics)

[3 Pretest of GPS in Masaka District June/July 2002
3](#pretest-of-gps-equipment-in-masaka-district-junejuly-2002)

[4 Further experimentation and fine tuning of GPS setup
4](#further-experimentation-and-fine-tuning-of-gps-setup)

[5 Testing of GPS during the Pilot Census of Agriculture, 2003
5](#testing-of-gps-during-the-pilot-census-of-agriculture-2003)

[5.1 Experimental design for measurement of areas
5](#experimental-design-for-measurement-of-areas)

[5.2 Lessons learned from the PCA 7](#lessons-learned-from-the-pca)

[5.3 Results from use of GPS and traversing during the PCA
7](#results-from-use-of-gps-equipment-and-traversing-during-the-pca)

[5.3.1 Comparative study of measurement method for Parcels
7](#comparative-study-of-measurement-method-for-parcels)

[5.3.2 Comparative study of measurement method for Plots
9](#comparative-study-of-measurement-method-for-plots)

[5.4 Results of Comparison of Time use during PCA
11](#results-of-comparison-of-time-use-during-pca)

[5.5 Comparison of costs of instruments
12](#comparison-of-costs-of-instruments)

[6 Conclusions 13](#conclusions)

[7 Further work and new possibilities for statistics
13](#further-work-and-new-possibilities-for-statistics)

# Introduction 

1\. The Uganda Government has taken strategic decisions to make poverty
eradication the over-riding objective of agricultural development
through the Plan for Modernization of Agriculture (PMA). The objective
is amongst others to give priority to agriculture as the engine for
economic growth and poverty eradication as well as to transform small
holding farmers from subsistence to producing for the market.

2\. The existing agricultural statistics system in Uganda is weak,
vulnerable and not able to meet modern user needs. Improvement or
further development of the Uganda Agricultural Statistical system is
therefore necessary.

3\. This is the background for the "Systems for Strengthening
Agricultural Statistics Project" (SSASP), a twinning project between the
Uganda Bureau of Statistics (UBOS) and Statistics Norway (SN).

4\. The overall objective of the SSASP is to strengthen the ability of
UBOS to identify the needs and then to produce and disseminate
agricultural statistics information to national and international users.
Baseline statistics and tools for monitoring effects of the
implementation of the PMA are priority objectives.

5\. The SSASP project started in 2002 and is funded by NORAD with a
total of NOK 18.5 mill over three years.

6\. Uganda Agricultural Censuses, considered as the backbone of the
agricultural statistics system, were conducted in 1963/65 and in
1990/91. UBOS is currently planning for another Census of Agriculture
and Livestock slated for 2005. As a consequence, the first 18 months of
the SSASP was mainly concentrated in preparing and conducting a Pilot
Census of Agriculture (PCA).

7\. The basic objective with the PCA is to get experiences with tools
and questionnaires, organization, economic impacts and logistics ahead
of a full Census. However in addition, the extended PCA 2003 gave
experience with, and possibilities for comparison between different
tools and methods used for area calculation, yield measurement and thus
calculation of crop production. Of which especially the latter is
regarded as a very difficult and costly task in many developing
countries.

8\. As a result of experimental design of the PCA, a simple handheld
tool for Global Positioning Systems (GPS) is tested and introduced as a
cost-efficient tool for area measurement and for geo-referencing of
holdings. Thereby UBOS has also embarked on the building of capacity for
more extensive use of Geographical Information Systems and Technology
(GIS/GIT) in the context of agricultural statistics in Uganda for the
years to come.

# Areas in the context of agricultural statistics 

1\. One of the most important factors for production used in growing
crops, raising livestock or any other farming activity, is land. The
pattern of land-use usually varies by seasons or by different regions of
the country. Thus, accurate data on area used for agricultural purposes
is an important aspect of agricultural planning.

2\. Total land operated by the holder (i.e. the agricultural holding) is
a crucial variable for the analysis of agricultural data. The area of a
holding may vary from time to time. A holder may sell or leave part of
his/her holding or he/she may buy or rent from others.

3\. At any time the holder has the option to fully or partially utilize
the holding. Thus the proportion of the holding under crop also varies
from season to season or from year to year. Since production can be
estimated as a product of Yield and Area, there is definite relationship
between area planted and amount of crop harvested. The product can
easily be computed in the case crops are grown in pure stand. The
problem is however more complex if crops are in mixed stand.

4\. Agriculture is indeed an area-based industry. Crop and forest
products is directly linked to area size and the area quality. Even
highly industrialized "zero grazing" models for animal rearing and
piggeries are in the end depending on area based crop production. Thus
accurate and timely information of agricultural areas is one of the very
core variables in all agricultural statistical censuses and surveys.

5\. Area measurement for use in traditional agricultural statistics has
a twofold objective:

-   To determine the structural changes of the agricultural holdings
    i.e. changes in total area size of the holding, size of the
    different land use categories and also to follow possible
    fragmentation or aggregation of farmland.

-   To enable for determination of the potential and actual agricultural
    production by calculation of total crop production as a function of
    yield and area

6\. Reliable estimation of annual production of food crops and other
agricultural commodities are very important, for a developing country
such as Uganda which is making serious efforts to tackle the problem of
feeding her population, diversifying her export crops and, thus, raising
the living standards of her people. Unfortunately, there have been major
methodological problems in the estimation of crop production in
developing countries, particularly in Africa.

7\. Geo referencing of agricultural holdings in the context of
agricultural statistics become relevant as Geographical Information
Systems and Tools (GIS/GIT) is widely introduced in research
institutions and civil administration planning units. Exact positioning
of holding center and even of parcels and crop-plots can be combined
with other geo referenced thematic information and digital base maps for
spatial analyses and planning.

# Pretest of GPS Equipment in Masaka District, June/July 2002

1\. In Uganda there is no complete cadastral map or land register that
includes information about holding areas. Experience from previous
surveys and censuses also reveals that most of the holders in rural
Uganda are not able to accurately determine the size of their land in
useable quantitative units. As a consequence, all information about size
of land has to be collected from scratch by measuring.

2\. Experience from area measurement during the Agricultural Censuses in
1963/65 and 1990/91, indicates that the measuring of areas by measuring
tape (or wheel) combined with compass use and traversing the perimeter
of the selected area is a fairly accurate but very time consuming
method.

The accuracy of this method however depends on the enumerators capacity
to read the compass and tape measures and also to which extent
approximation to the actual shape of the parcel or plot has to be done
-- the so called "give and take approach". Also the cost for instruments
like high quality compass and measuring tapes are considerable.

3\. On this background it was decided to look for alternative methods
for area measurements already as the pre test for the Uganda Census of
Agriculture and Livestock was conducted in Masaka district June/July
2002.

4\. As a direct consequence, two hand held GPS of the type Magellan
Meridian ([www.magellan.com](http://www.magellan.com/)) was used on
experimental basis in order for area calculation of crop-plots and
parcels as well as for geo-referencing of the holding during the
pretest.

5\. An application for automatic calculation of areas based on recording
the start position and the track-log of the perimeters was introduced.
The software was downloaded to the GPS tool by the Norwegian supplier
specially for this exercise.

6\. The GPS equipment is in principle a high precision digital watch
combined with a signal receiver. It finds longitudes and latitudes on
the earth's surface. The geographical position is found by continuously
measuring the time a signal takes from satellites in the sky to the GPS
tool on the earth surface. A obvious advantage that the GPS tool has
compared to the traversing with tape&compass is that the perimeter of
the area can be followed fairly quickly, accurately and completely.

7\. The findings of the pretest was that compared to accurate but time
consuming traversing of the same areas using compass and measuring tape,
the average of the GPS registrations seemed to be of promising accuracy.
However the variation in the repeated measurements caused some concern
at this stage. GPS based calculation of areas was during the pretest
done both by reading results from the device display directly and in
addition by downloading the track-log polygons to a GIS software for
storage, mapping and area calculations on a lap-top.

8\. The registration of holding representation point co-ordinates caused
no serious problems during the pre-test fieldwork. Several of the UBOS
staff and enumerators involved had the opportunity to learn how to use
the GPS tool.

# Further Experimentation and Fine-tuning of GPS Setup

1\. GPS tools in sufficient numbers for use in the PCA turned out
already to be available in UBOS. They were earlier procured and used in
an effort to allocate coordinates to all units in the Uganda Business
Register.

2\. The tools available were of the type Garmin 12 or Garmin 12XL. Most
of these tools already contained the necessary software to calculate
areas. Information about upgrading for area calculation software can be
found on the Garmin home pages
([www.garmin.com](http://www.garmin.com/)).

3\. In cooperation with experts from the National Biomass Study Project
and geographers within UBOS, the instruments setup were optimized for
such registrations i.e. the interval for registration recoded to the
track-log was minimized and a suitable projection and co-ordinate system
was agreed. The latter also to ensure for comparability with already
existing digital thematic maps relevant for agriculture presentations
and GIS analyses. The following setup specifications were agreed to be
used:

> **MAIN MENUE** → Setup menu → Navigation:
>
> Position frmt: hddd.ddddd ^o^
>
> Map Datum: WGS 84
>
> Units: Metric
>
> Heading: Auto E001^o^ Degrees
>
> **MAP WINDOW**
>
> 0.3 / PAN / OPT
>
> **TRACK SETUP**
>
> Record: Wrap
>
> Method: Time interval 00:00:10
>
> Track setup→Calc area
>
> Units: sq mt

4\. During this preparatory experimentation the possibility for
downloading vector data for each parcel and plot perimeter was discussed
and tested (necessary PC software can be downloaded). For practical
reasons this approach was not further followed up. Recording of parcel
and plots polygons as vector data would require advanced and expensive
systems for transferring large amounts of geographical data from the
fieldwork into UBOS storing and processing facilities. In addition, the
accuracy of the shape of the polygons registered with a handheld GPS
without any adjustments facilities or access to WAAS techniques, would
not fulfill technical requirements for use as cadastral maps. Finally
cadastral mapping was also regarded as being outside the scope of a
census of agriculture.

5\. During October/November 2003 studies of accuracy and variation of
the results of area measuring based on the use of GPS was carried out.
Initial studies with repeated GPS measuring shows a reasonable variation
around a true value accurately measured by tape and compass to 483 m^2^
illustrated as follows:

**Table 4.1. Plot area (m^2^**) measured by GPS. January 2003

  --------------------- ----------- ---- ------------ ---------------------
                                         Statistics   Std. Error

  Number of                              22           
  observations                                        

  Mean                                   474.14       5.73

  95% Confidence        Lower Bound      462.22       
  Interval for Mean                                   

                        Upper Bound      486.06       

  Median                                 482.50       

  Variance                               722.89       

  Std. Deviation                         26.89        

  Minimum                                407.00       

  Maximum                                510.00       

  Range                                  103.00       
  --------------------- ----------- ---- ------------ ---------------------

6\. As a result of the pretest and the following experimentation and
fine-tuning, it was decided to go on and to expand the experimentation
with the GPS tool during the PCA. The approach agreed for the PCA was to
traverse the perimeter of the selected areas with the GPS, conduct
readings of results of position and areas directly from the GPS display
and finally recording the data into traditional statistical
questionnaires.

# Testing of GPS during the Pilot Census of Agriculture, 2003

## Experimental design for measurement of areas

1\. The land area measured per holding selected for the PCA was limited
to that one within the selected EA and included:

-   The total area of the holding.

-   The area of agricultural parcels and plots under various crops.

-   Pasture land.

2\. The experimental design of the PCA provided for four approaches to
area estimation for three groups of holdings within each Enumeration
Area (EA). Each EA had a total of 15 holdings selected, so each of the
three randomly selected groups had 5 holdings. The experimental design
for area measurements was as follows:

(i) Holders'/respondents' eye estimates of parcel and crop plot area was
    recorded on the 5 selected holdings in Group I.

(ii) Enumerators' eye estimates of parcel and plot area was recorded on
     the 10 selected holdings in Groups II and III.

(iii) Measuring using compass and measuring tapes was recorded on the 5
      selected holdings in Group I.

(iv) Measuring by use of GPS equipment was recorded for all the 15
     holdings in the EA i.e for all the Groups I-III.

3\. A sketch map of parcels and plots for each of the fifteen holdings
in the EA had to be made in order both to plan the fioledwork, and to
enable for finding back to the holding if later visits should be
neccessary.

**Figure 5.1. The concept of parcels and crop-plots on agricultural
holdings in Uganda**

> **↑**
>
> **N**

**Parcel 1 Parcel 2**

Road to Village 3 km Ref. point Holder's house Plot 1:

> Plot 1: Banana +Yams

Farmhouse

> Plot 3: Sub-plot 1

Coffee

Plot 2:

Banana Small stream

100 m

4.The area measurements and/or estimates for both parcels and plots were
carried out in the following sequence:

-   While walking around the holding to decide on the parcel boundaries
    and the number of plots to be found on the parcel, the
    holder's/respondent's area estimate were to be recorded in the
    appropriate form for the five selected holdings for Group I.

-   The Enumerator would make his eye estimates and record it on the
    appropriate forms for the ten selected holdings in Groups II and
    III.

-   The Enumerator would take measurements using compass and measuring
    tape (traversing) on five selected holdings in Group I, and record
    the measured results (meters and degrees) for each of the sides in
    the parcel/plot that was measured. Results was then recorded
    (bearings and lengths). Thereafter, the Enumerator would calculate
    the measured area and the closing error using the programmable
    calculator and record the final results.

-   The Enumerator would do the area measurement using the GPS equipment
    for all parcels and plots in Group I --III and record it in the same
    forms.

-   Finally the Supervisor and/or the team from UBOS/MAAIF crosschecked
    some selected parcels and plots by measuring, using GPS equipment.

-   The Holders'/Respondents' eye-estimates and Enumerators'
    eye-estimates were made on different holdings to ensure independence
    of the two. Further, the actual measurements were to be carried out
    after the eye-estimates again to ensure independence. In both cases
    the eye-estimates would not be affected.

## Lessons learned from the PCA 

1\. The way the GPS equipment was set up for the PCA, the area of each
parcel and plot was calculated directly in square meters. Therefore, the
value had to be converted to hectares (by dividing by 10,000) with two
decimal places before information could be recorded in the appropriate
questionnaire. Some enumerators had problems converting from Square
Meters to Hectares. Others recorded the values in square meters directly
on the forms and this caused some confusion in the data cleaning/data
entry process.

2\. Using a hand held GPS-tool is basically not much different from
operating a cellular phone and thus possible for non-experts use.
Enumerators and supervisors were instructed in the use of GPS-tool
during the training course just before the PCA fieldwork started.

3\. During the fieldwork it turned out to be necessary to repeat and
further drill the routines for using the GPS equipment. Unfortunate
changes of the setup of the instruments accidentally occurred and had to
be corrected. However, in the end most of the enumerators managed to
record both areas and coordinates according to the instructions.

4\. Since the GPS tool is fast and easy to use compared to traversing
with tape and compass, in some cases the enumerators only conducted GPS
measurements and in spite of their instructions they did not follow up
with the requested but cumbersome traversing of the same plot. It is
also assumed that using the "high tech" GPS adds importance and status
to the enumerator's work as he/she visits the holders.

5\. During area measurement, the experience was that positioning from
between 5 to 8 satellites for each observation were received. The
expected accuracy when using a hand held GPS-tool without any
corrections based on additional fixed ground stations or WAAS techniques
is better than +/- 15 meters. This accuracy is acceptable when the
objective is to geo-reference the holding for statistical use.

6\. During the PCA fieldwork, problems were found with using the
GPS-tools on plots and parcels where the tree canopy cover is dense. In
addition, there were problems with area measuring in very steep terrains
due to the difference between actual area and horizontal projections.
Also struggling with some "shadow" effect when receiving signals from
satellites in hilly terrain caused problems. A possible improvement will
be to equip the GPS-tool with an external antenna device when used under
extreme conditions. This is possible for the GARMIN 12XL tool.

## Results from use of GPS Equipment and traversing during the PCA 

1\. The experimental design of the PCA allowed the comparison of the
results of area measured with GPS equipment, by traversing with tape and
compass and even by eye estimates by the holders and enumerators on a
large number of holdings and in different kinds of topographic and
vegetation cover.

2\. Initially problems with the level of accuracy were expected when the
objective was to measure the area of parcels and plots. Experience on
the ground, as illustrated in the table 4.1 , was however more positive.
Basically the results of GPS measurements of areas reveals variances
around the assumed most correct area figure i.e. the figure based on
accurate traversing.

### Comparative study of measurement method for Parcels

1\. The total dataset where the information about holder's and
enumerator's estimates are linked to information about parcels measured
with tape & compass and GPS comprises 1,572 parcels of which:

-   1,257 were measured by GPS equipment

-   453 were measured by traversing (tape & compass)

-   599 parcels were estimated by the holder

-   990 parcels were estimated by the enumerator.

2\. There were 430 observations where areas of parcels were measured by
both the GPS equipment and by traversing (tape & compass). A paired
T-test (see figure 5.2 and table 5.1-3) of this set of observations
reveals that [there is no statistically significant difference between
the results of the two methods concerning parcels measured during the
PCA filedwork 2003.]{.underline}

**Figure 5.2. Comparison of area measured by GPS tool and area measured
by traversing. Parcels. PCA 2003**

![](media/image1.wmf)

Table 5.1. Paired Samples Statistics of parcel areas

  ------ ------------------------- -------- ------ ----------- -----------
                                   Mean     N      Std.        Std. Error
                                                   Deviation   Mean

  Pair 1 AREA_TRAVERSING           0.3757   430    0.77711     .03748

         AREA_GPS                  0.3541   430    0.63427     .03059
  ------ ------------------------- -------- ------ ----------- -----------

Table 5.2 Paired Samples Correlations of parcel areas

  ----------- ------------------------ -------- --------------- ----------
                                       N        Correlation     Sig.

  Pair 1      AREA_TRAVERSING &        430      0.653           0.000
              AREA_GPS                                          
  ----------- ------------------------ -------- --------------- ----------

Table 5.3. Paired Samples Test of parcel areas

<table>
<colgroup>
<col style="width: 7%" />
<col style="width: 19%" />
<col style="width: 10%" />
<col style="width: 9%" />
<col style="width: 14%" />
<col style="width: 12%" />
<col style="width: 7%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 8%" />
</colgroup>
<tbody>
<tr class="odd">
<td></td>
<td></td>
<td>Paired Differences</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>T</td>
<td>Df</td>
<td><p>Sig.</p>
<p>(2-tailed)</p></td>
</tr>
<tr class="even">
<td></td>
<td></td>
<td>Mean</td>
<td>Std. Deviation</td>
<td>Std. Error Mean</td>
<td>95% Confidence Interval of the Difference</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>Lower</td>
<td>Upper</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td>Pair 1</td>
<td>AREA_TRAVERSING &amp; AREA_GPS</td>
<td>0.0215</td>
<td>0.60195</td>
<td>0.02903</td>
<td>-0.0355</td>
<td>0.0786</td>
<td>0.742</td>
<td>429</td>
<td>0.459</td>
</tr>
</tbody>
</table>

3\. Finally, a one-way ANOVA test was carried out to compare parcel
areas measured by GPS tool, or by traversing and holders estimates. A
total of 390 parcels were measured by all of these three methods. During
data collection, all measurements below 100 square metres (0.01Ha) were
rounded to 0.01Ha. So during the ANOVA, only areas larger than 0.01
hectare were included in the test. This avoids bias due to rounding of
values for the smallest areas.

4\. The results of this test is documented in table 5.4-6 below. Table
5.4 indicates that the Holders' estimates tended to be the highest,
followed by the area measurement by traversing. However, as shown in
Table 5.5, [the differences were not statistically
significant]{.underline}. [A comparison between traversing and the GPS
tool (Table 5.6) was highly non-significant. A comparison of traversing
and Holders' estimates (Table 5.6) was only statistically significant at
9% level.]{.underline}

Table 5.4. Descriptive Statistics of Parcel Areas

  ------------- ------ -------- ----------- --------- ------------ -------- ------ -------
                N      Mean     Std.        Std.      95%                   Min    Max
                                Deviation   Error     Confidence                   
                                                      Interval for                 
                                                      Mean                         

                                                      Lower Bound  Upper           
                                                                   Bound           

  1 Traversing  390    0.3866   0.80066     0.04054   0.3069       0.4663   0.02   9.45

  2 GPS         390    0.3486   0.59140     0.02995   0.2897       0.4075   0.02   5.20

  3 Holders     390    0.4955   1.19238     0.06038   0.3767       0.6142   0.01   19.02
  estimate                                                                         

  Total         1170   0.4102   0.89816     0.02626   0.3587       0.4617   0.01   19.02
  ------------- ------ -------- ----------- --------- ------------ -------- ------ -------

Table 5.5. One-Way ANOVA test. Comparison of Parcel Areas measured by
Traversing, by GPS and holders' estimates

  ---------------- ---------- ---------- ------------- ---------- ----------
                   Sum of     df         Mean Square   F          Sig.
                   Squares                                        

  Between Groups   4.532      2          2.266         2.818      .060

  Within Groups    938.490    1167       0.804                    

  Total            943.022    1169                                
  ---------------- ---------- ---------- ------------- ---------- ----------

Table 5.6. Duncan Post Hoc Test of Homogenous Subsets. Parcel Areas
measured by Traversing, by GPS and holder s' estimates

  ------------------------ --------------- --------------- ---------------
                           N               Subset for      
                                           alpha = .05     

                                           1               2

  2 GPS                    390             0.3486          

  1 Traversing             390             0.3866          0.3866

  3 Holders estimate       390                             0.4955

  Sig.                                     0.554           0.090
  ------------------------ --------------- --------------- ---------------

Means for groups in homogeneous subsets are displayed.

a Uses Harmonic Mean Sample Size = 390.000.

### Comparative study of measurement method for Plots 

1\. A one-way ANOVA test comparing plot areas measured by GPS tool,
measured by traversing and holders' estimates was also conducted. Again,
only plot areas larger than 0.01 hectares are included in the test.

2\. A total of 672 plots were measured/estimated as larger than 0.01
hectares with all the three methods. The results from this test are
documented in Tables 5.7-9 below and are similar to those for parcels.
In Table 5.7, the holders' estimate is the highest. While in Table 5.8,
the differences are only statistically significant at 9% level. In Table
5.9, the GPS tool and traversing are highly non-significant but
traversing and holders' estimates are significantly different at the 11%
level.

Table 5.7. Descriptive Statistics of Plot Areas

  -------------- ------ -------- ----------- --------- ------------ --------- ------ -------
                 N      Mean     Std.        Std.      95%                    Min    Max
                                 Deviation   Error     Confidence                    
                                                       Interval for                  
                                                       Mean                          

                                                       Lower Bound  Upper            
                                                                    Bound            

  1 Traversing   672    0.3370   1.71426     0.06613   0.2071       0.4668    0.02   28.40

  2 GPS tool     672    0.2877   1.89170     0.07297   0.1444       0.4310    0.02   35.00

  3 Holders      672    0.4915   1.70499     0.06577   0.3624       0.6206    0.01   25.60
  estimate                                                                           

  Total          2016   0.3721   1.77365     0.03950   0.2946       0.4495    0.01   35.00
  -------------- ------ -------- ----------- --------- ------------ --------- ------ -------

Table 5. 8. One-Way ANOVA test. Comparison of Plot Areas measured by
Traversing, by GPS tool and Holders' Estimates.

  ---------------- ---------- ---------- ------------- ---------- ----------
                   Sum of     df         Mean Square   F          Sig.
                   Squares                                        

  Between Groups   15.196     2          7.598         2.419      0.089

  Within Groups    6323.648   2013       3.141                    

  Total            6338.844   2015                                
  ---------------- ---------- ---------- ------------- ---------- ----------

**Table 5. 9. Duncan Post Hoc Test of Homogenous Subsets. Plot Areas
measured by Traversing, by GPS tool and Holders' Estimates**

  --------------------------- ----------- -------------- -----------------
  AREA_FOR                    N           Subset for     
                                          alpha = .05    

                                          1              2

  2 GPS Tool                  672         0.2877         

  1 Traversing                672         0.3370         0.3370

  3 Holders' estimate         672                        0.4915

  Sig. Level                              0.611          0.110
  --------------------------- ----------- -------------- -----------------

Means for groups in homogeneous subsets are displayed.

a Uses Harmonic Mean Sample Size = 672.000.

3\. The total dataset where the information about holders' and
enumerators' plot area estimates as well as crop information are linked
to information about plots measured with tape & compass and GPS tool
comprised 3,580 plots. Of these, 3,086 plots were measured by GPS tool
(GPS area \>=0.00),

1,086 plots measured by traversing (tape & compass area \>=0.00), whie
1,028 plots were estimated by the holder and finally 2,341 plot areas
were estimated by the enumerator.

4\. A total of 1,004 plots were found where area was both measured by
the GPS tool and by Traversing (measured area both for GPS tool and by
traversing \>=0). Most of the measured plots were very small and in
order to reveal possible differences between measurement of small and
larger plots, the dataset for plots was divided into 2 strata; **Stratum
1** with plot areas at least 0.5 hectares (N=70) and **Stratum 2** with
plot area size less than 0.5 hectares but more than 0.01Ha(N=934). The
results of these T-tests are presented in Tables 5.11-13 and are all not
statistically significantly different.

Table 5.11. Paired Samples Statistics of Plot Areas

  -------------- -------------- --------- --------- ------------ ---------
                                Mean      N         Std.         Std.
                                                    Deviation    Error
                                                                 Mean

  Stratum 1      Traversing     8.9251    70        14.37497     1.71814

                 GPS            7.8983    70        14.29725     1.70885

  Stratum 2      Traversing     0.1441    934       0.57584      0.01884

                 GPS            0.0894    934       0.09383      0.00307
  -------------- -------------- --------- --------- ------------ ---------

Table 5.12. Paired Samples Correlations of Plot Areas

  --------------- --------------- ------------ -------------- ------------
                                  N            Correlation    Sig.

  Stratum 1                       70           0.897          0.000

  Stratum 2                       934          0.121          0.000
  --------------- --------------- ------------ -------------- ------------

**Table 5.13. Paired samples Test of Plota Areas**

  -------------- ------------- ----------- --------- ------------ -------- ------- ------ ------------
                 Paired                                                    T       Df     Sig.
                 Differences                                                              (2-tailed)

                 Mean          Std.        Std.      95%                                  
                               Deviation   Error     Confidence                           
                                           Mean      Interval of                          
                                                     the                                  
                                                     Difference                           

                                                     Lower        Upper                   

  Stratum 1      1.0269        6.49338     0.77611   -0.5214      2.5752   1.323   69     0.190

  Stratum 2      0.0547        0.57209     0.01872   0.0180       0.0914   2.922   933    0.004
  -------------- ------------- ----------- --------- ------------ -------- ------- ------ ------------

5\. The results from the paired T-test above indicates that traversing
of the plots that are at more than 0.5 hectares, gives a slightly larger
area per plot compared to the same plot area measured by GPS equipment.
This tendency seems to be the same when plots with area size less than
0.5 hectares are measured. However, since the questionnaire only alowed
for filling in of hectares with 2 decimals, this size group of small
plots may have been disturbed by rounding-routines for the smallest
areas measured i.e. those plot areas that were less than 0.01 hectares
but rounded up and recorded as beeing equal to 0.01 hectares by the
Enumerators.

## Results of Comparison of Time use during PCA

1\. Timeuse for the different measurement methods was recorded by the
enumerator during the fieldwork of the PCA. For all observations
recorded, the average timeuse for traversing with tape and compass was
three times as long per holding as when GPS equipment was used (table
5.14).

Table 5.14. All observations of time used. Traversing, GPS tool and
Enumerators' Estimates. PCA 2003

  ----------- ---------- --------------- ------------- -------------------
                         Traversing      GPS Tool      Enumerators'
                                                       estimate

                                                       

                         Observations                  

  N           Valid      302             538           448

  N           Missing    476             240           330

                                                       

                         Minutes used                  

  Mean                   153.9           55.6          46.1

  Median                 97.0            48.0          37.5
  ----------- ---------- --------------- ------------- -------------------

2\. A subset of all observations was selected in order to compare
observations about time use on those holdings where both GPS
measurements and traversing with tape and compass was conducted. A
paired T-test for this subset of 191 holdings reveals that time use for
traversing was as much as 3 hours and 23 minutes or 3.5 times as much as
when GPS tool was used (Table 5.4.2). Therefore it can be concluded that
the GPS tool is a far more time-efficient method/tool than the tape and
compass measured in terms of average time use per holding.

Table 5.15. Comparison between time use for traversing and use of GPS.
Paired T-test Samples Statistics. PCA 2003

  ----------------- ------------ ----------------- ------------ ------------
                    Mean minutes Comparable        Standard.    Standard
                    used         observations (N)  Deviation    error for
                                                                the mean

  Traversing        203.1        191               185.4        13.4

  GPS use           57.8         191               34.1         2.5
  ----------------- ------------ ----------------- ------------ ------------

##  Comparison of costs of instruments

1\. Even simple handheld GPS tools are relatively expensive tools. The
GPS equipment model used in the PCA was a Garmin 12 channel receiver
with an approximate price of US\$150 per unit (2003 prices). During the
PCA fieldwork, three enumerators shared two GPS tools. However, with
good logistics, cost efficiency could be improved by letting even more
enumerators share the same tools.

2\. The use of batteries turned out to be high as it was agreed to
change batteries when approximately two-thirds (2/3) of the energy was
used. Since each GPS tool uses four (4) high quality AA batteries, the
costs for power supply was considerable. The reccomended batteries cost
an equivalent of US\$1.25 per pair compared to the more common ones
which cost about USCents25. Clearly, this cost could be reduced by
giving the equipment to the staff only when they are ready to carry out
the area measurements. Also use of re-chargeable batteries may reduce
the costs. The enumerators were instructed to switch off the equipment
whenever not in use. It is however, not easy to know how well they
followed this instruction.

3\. For further work it should be experimented with rechargeable
batteries as a more cost efficient option. However not all areas in
Uganda have stable power supply so recharging can give some logistical
problems.

4\. Two GPS devices were lost during the project period due to
unfortunate civil unrest in one of the enumeration areas. Such losses
and cost will have to be expected to occur even more frequently in a
full census since all districts shall be included.

5\. The price of high quality tape and compass equipment is
approximately 25 USD and 100 USD (compass including jacket)
respectively. In addition a fairly expensive programable calculator is
necessary to calculate areas captured by traversing. The total price is
therefor not so different from the price of a GPS tool. On the
otherhand, battery cost are zero for tape and compass.

# Conclusions

1\. The results from the PCA indicate that the area measurements by the
GPS equipment and those by the compass and tape are very close -- for
parcel areas there were no statistically significant diffrence between
the results of the two methods. Farmers eye-estimates of area size both
for parcels and plots and seems to overestimate the size of the areas
compared to values obtained from use of GPS and traversing technique.
Considering that the GPS equipment is much faster and that costs are
fairly comparable to those of traversing, this indicates that there is a
potential for the GPS equipment for agricultural area measurements.
However, efforts need to be made for cheaper GPS equipment and running
costs or at least more efficient use. There is also need for more
thorough training of field staff. Finally, more study is required on the
variability and consistency of the equipment under more scientifically
designed and closely supervised conditions. Special studies concerning
effects of steep slopes and under tree and cloud cover should also be
conducted.

# Further work and new possibilities for statistics

1\. Combination of digital thematic maps, digital administrative
boundaries and geo-referenced statistical information opens for spatial
analyses of data. However, before such data can be used in Geographical
Information Systems (GIS), a long process of data capture,
geo-referencing/geo-coding, scanning and digitalization is required.
Since geographical information will be found in different organizations
in Uganda, it is crucial for common use to agree upon standards and
formats.

2\. By introducing geo referencing (coordinates) and geocoding
(administrative division unit code) to statistical information of
agricultural holdings sampled during survey and censuses and at the same
time introduce similar coding for business and industry
surveys/listings, new possibilities spatial analyses of data occurs. The
statistical information can also be combined with other sources of
digitalized geographical data such as thematic maps available at the The
Uganda National Biomass Study including digital main road net, water
courses, land cover classes etc.

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