The Dot Sampling Method
March 29, 2016
KAMIKURA, Kenji
Senior Statistician
Statistics Department
MAFF Japan

Preface
Concerning agricultural production survey, it is common to ask farmers to getdata of planted area, namely through interpersonal hearing method. This
hearing method is popular in many countries such as developing countries, but it
has a week point that you cannot evaluate a validity of the data, as you get thedata through hearing from persons without any evidence. It has been often
happened that such data doesn’t show the real situation. As for the frequency ofplanted area surveys in one year, the reality is that many of you cannot conduct
them even once a year, though you should do several times a year. Under thesesituations, with the advent of Google Earth, the Dot Sampling method has beendeveloped and you have been able to estimate a plated area of certain crops
simply and efficiently in a target area. In order to carry out the Dot Sampling
Method, the Excel Macros have been developed and anybody can conduct thesurvey easily. Though area survey has long been a big obstacle to implement
production survey so far, the Dot Sampling Method has removed the obstacle allat once.
Area Survey with the Dot Sampling method has characteristics such that its
survey object is not a person but a land, it doesn’t require population
composition, as well as it is easier to be conducted and non-sampling errors
hardly occur, as it is not a variable survey but an attribute survey.
Also, the Dot Sampling Method widely exhibits its power in not only in an area
survey but also other surveys such as a yield survey.

This document has compiled the essence related to the development of the
Dot Sampling Method taken from domestic and foreign books, magazines,
documents for meetings, training materials for government staff from various
countries. This document aims to provide every person with an opportunity toknow the Dot Sampling Method. Moreover, we expect that readers of thisdocument understand the power of the Dot Sampling Method and discover lotsof possibilities the Dot Sampling Method has.
We are delighted if this document is useful for you to study methodologies ofstatistical surveys or disseminate survey methods through international
technical cooperation.

Contents
Preface
Contents

Chapter 1

Dot Sampling Method

1.1

Concept of the Dot Sampling Method……………………………… １

1.2

Examples of what you can do with the developed Excel

Macros
1.2.1 Putting any number of dots on a target region……………………… 2
1.2.2 Putting any number of dots on rice fields in a target region……… 2
1.2.3 Using it as a two-dimensional ruler to measure area ……………… 2
1.3

Characteristics of the Dot Sampling Method

1.3.1 It is an efficient and powerful method based on traditional
theory…………………………………………………………………………… 3
1.3.2 To be applicable to both attribute and variable survey………………5
1.3.3 To be applicable to minor crops ………………………………………… 6
1.3.4 To be applicable to mix crops …………………………………………… 6
1.3.5 To be applicable to dyke survey ………………………………………… 6
1.3.6 To be applicable to complicated geography or slope …………………7
1.3.7 To require small number of enumerators, even unskilled ones…… 7
1.3.8 To be conducted repeatedly any times a year………………………… 7
1.3.9 To have possibility to further develop in the future ………………… 7

Chapter 2

2.1

Area Survey Using the Dot Sampling Method

Concept of area survey…………………………………………………… 9

2.2 Procedure of survey
2.2.1 Step1 To put sample dots on Google Earth …………………………… 10i2.2.2 Step2 Preparatory survey on Google Earth …………………………… 12
2.2.3 Step3 Field survey…… ………………………………………………………13
2.2.4 Step4 Estimation of area…………………………………………………… 13
2.3 Procedure of survey for the second time …………………………… 14
2.4 Size of the sample required for the Dot Sampling
Method…………………………………………………………………………… 14
2.5 Way of involvement by statistical organizations in surveys……18
2.6 Examples: results of preparatory surveys on Google Earth
2.6.1 Preparatory survey, Thailand………………………………………………18
2.6.2 Preparatory survey, Lao PDR……………………………………………… 20
2.6.3 Prefecture survey, East Timor …………………………………………… 20
2.７ Area Survey using the Method as a two-dimensional ruler……21

Chapter 3

Yield Survey Using the Dot Sampling Method

3.1 Application of the Dot Sampling Method to yield survey ……… 23
3.2 Procedure of survey
3.2.1 Step1 Selection of sample spots for crop cutting …………………… 24
3.2.2 Step2 Crop cutting, threshing, drying, weighing …………………… 25
3.2.3 Step3 Estimation of average yield/ha in a target region…………… 26

Chapter 4

Examples of Rice Production Survey
Using the Dot Sampling Method

4.1 Planted area survey… ………………………………………………………27
4.2 Yield survey …………………………………………………………………… 29
4.3 Production survey ……………………………………………………………30

ii

Chapter 5

Mystery of the Dot Sampling Method

5.1 Better precision than theoretical precision ………………………… 31
5.2 Sampling survey or measuring survey ……………………………… 33

Chapter 6

Dissemination of the Dot Sampling Method
and Similar Methods Overseas

6.１ Situation of similar methods overseas ……………………………… 34
6.２ Dissemination of the Dot Sampling Method in international
technical cooperation activities ………………………………………… 35

Chapter 7

Frequently Asked Questions
on the Dot Sampling method………… 37

Afterword …………………………………………………………………………… 41

Reference …………………………………………………………………………… 42iii

Chapter 1

Dot Sampling Method

Detailed and specific explanation on the Dot Sampling Method is given inchapter 2 and after. In this chapter you learn at first the concept of the Dot
Sampling Method. And then you learn both the basic functions of Excel Macrosdeveloped for efficiently conducting surveys using the Dot Sampling Method andthe various characteristics of the Dot Sampling Method.

1.1 Concept of the Dot Sampling Method
In this document, the Dot Sampling Method is defined as a method that puts
dots randomly on a map and survey the dot itself or plots near the dot.
Originally, the Dot Sampling Method has started as “the method which
conducts attribute surveys by counting dots,” but in this document the Dot
Sampling Method includes “the method which conducts variable surveys neardots.”In a case that the Dot Sampling Method is applied to rice planted area survey,
you put dots at regular intervals on the map of Google Earth and you estimate
total area of rice planted field in a target region from sharing rate of dots whichfall on rice planted spots.
In another case that you select crop cutting fields and spots based on
locations of dots, you can estimate the yield easily as the fields have been
already selected by the probability proportional to rice planted area.
The reason why the name of the Dot Sampling Method include “sample” isthat dots themselves on the map are thought to be sample spots. Please notethat samples are not extracted from a population which has been compiled
before conducting surveys like prevailing methods, such as area frame method.

Note: Attribute survey method is also the method for opinion poll.
Regarding opinion poll, you ask selected sample person if he or she
supports the cabinet or not in order to estimate a cabinet support
1

rate nationwide. In the same way, regarding area survey using the
Dot Sampling method, you ask selected sample dot if it is fallen on
rice planted spot or not in order to estimate a rice planted area ratenationwide.

1.2

Examples of what you can do with the developed Excel Macros

Before taking up the main subject of the Dot Sampling method, we will
mention following three activities which you can conduct with the Excel Macro.
You can put sample dots at equal intervals in a grid pattern only by inputting six
values into the Excel Macro.
1.2.1 Putting any number of dots on a target region
You can put dots of any number in any place on Google Earth by putting 6
values in the Excel Macro. For instance, you can put 1,000 dots in a country on
Google Earth by inputting data of total land area, 1,000 as the number of dots
and range of rectangle covering the country into Excel Macro.

1.2.2 Putting any number of dots on rice fields in a target region
You can put 200 dots on rice fields of 400km2 in a prefecture by inputting
400km2 of total area or rice fields, 200 dots and range of rectangle covering theprefecture into Excel Macro.

1.2.3 Using it as a two-dimensional ruler to measure area
You can put a dot every 0.01km2 on Google Earth by inputting data of
0.01km2 as area, one as number of dots and range of a target region into Excel
Macro. Thus you can estimate area by counting the number of dots fallen on
concerning region.

Note 1: Concerning 1.2.3, you can call this method a two-dimensional ruler
by measuring area by counting the number of dots, while normal ruler2

is called one-dimensional rules by measuring length by counting

thenumber of divisions. This method is as same as dot grid method which
has already been adopted as dot grid plate for measuring area.
Note 2: Six values are as follows:# Values to determine number of dots per area
1) Any area (square measure)2) Number of dots putting in the area of 1)# Values to determine a range of rectangle for putting dots
3) Any latitude on the north of the northernmost of a target region4) Any longitude on the west of the westernmost of a target region5) Any latitude on the south of the southernmost of a target region6) Any longitude on the east of the easternmost of a target region
Note 3: A shape of range where dots are put is rectangle surrounded by
input latitudes and longitudes while dots of any number are put intarget area on Google Earth
Note 4: The Excel Macro for the Dot Sampling Method is available to anybody.
For those who want to get the Excel Macro files, please make contact
with Kenji Kamikura (kkamikura@hotmail.com).

1.3

Characteristics of the Dot Sampling Method

1.3.1 It is an efficient and powerful method based on traditional
TheoryThe Dot Sampling Method is one of traditional survey methods. With the
Method, you can conduct surveys efficiently. The Method has been thought to bea suitable method for crop production survey because of reasons below.
1) You don’t need to prepare for listing of target population from which you'll
extract your sample,
2) Sample dots are selected by probability proportional to size of each field,33) You can conduct area survey easily as it is an attribution method,4) You can easily conduct compilation, estimation and calculation of precision,5) Non-sampling error hardly happens.
But it was difficult to put the Method into practice, as it was almost impossible
to get a map which enables you to put any number of dots with any intervals on
the map and to prepare for guide maps for guiding enumerators to sample dots
which are necessary for practicing the Method. However, the advent of Google
Earth has made it possible to carry out those activities. In addition, in order to
conduct field survey, with Google Earth you have only to visit to the sample dots
which are thought to have fallen on cultivated land, as you can check the land
usages of sample dots on computer’s screen such as forest, lake, building, road,and so on. Even if there are 10,000 sample dots, the number of sample dots forfield survey can be reduced to 500 dots when the cultivated land ratio is five
percent. You can say that old traditional survey method was reborn as a powerfuland new method linking with latest information technology.

Note: There are some statisticians, saying almost the same idea as the Dot
Sampling method.
One is Frank Yates, statistician, England, who says in his book
“Sampling Methods for Censuses and Surveys, 1949” as follows:# If we have areas demarcated on a map, such as fields, and a point
is located at random on the map, the probabilities of the point
falling within the boundaries of the different fields are clearly
proportional to the areas of the field. Consequently, areas can beselected at random with probabilities proportional to their size by
the simple procedure of taking random points on the map.”(35p)# All that is required for acreage is to determine the proportion ofpoints which fall in areas of the given type. The method is therefore
particularly attractive when carrying out surveys of the areas ofcrops, etc., by aerial survey, since it avoids all the measurements of4

area which would be required if an ordinary random sample ofareas were taken.（p35）
Another one is Kei Takeuchi, statistician, Japan, who says in his book
written in 2010, as follows.
# As the number of dots N increases, dots scatter all over the innerpart of a square and finally scatter thoroughly in a uniform manner.
If you write a figure of S square units within a square of 1 squareunit, 𝑁𝑛 becomes almost equal to S no matter what kind of figure it is,when the number of dots within the figure is n.(69p)# It is rather difficult to measure each area of every rice fields andtotal the area of respective rice fields in a certain map when there arelots of rice fields in various sizes. Better simple way is that estimatingarea by counting the number of dots fallen on rice fields after putting
lots of dots randomly inside the map. If the number of dots whichhave fallen on rice fields is n out of N dots, total area of rice fields inthe map is estimated𝑛𝑁of area of the map.(70p)

1.3.2 To be applicable to both attribute and variable survey
The Dot Sampling Method is applicable to both attribute and variable survey.
You can conduct attribute survey if you check whether sample dot is fallen on
rice plated spot or not and calculate the ratio of the number of sample dots onrice planted spot to number of total sample dots. The Random Digit Dialing
method used for opinion poll and the method for election exit survey is attributesurvey.
You can conduct variable survey when you weigh the rice harvested from a
spot around a sample dot, utilizing the nature of dot which is selected byprobability proportional to size.

51.3.3 To be applicable to minor crops
Even an area of minor crops can be grasped, as sample dots are selected inproportional to planted area. Every dot has same probability, so the appearance
ratio of each crop is to be proportional to its planted area. Regarding the numberof necessary sample dots, it can be calculated according to required precision.

1.3.4 To be applicable to mix crops
With area survey using the Dot Sampling Method, you don’t need special
correspondence for mixed crops.
There are two types of mixed crops. One is more than one crops are planted
randomly in one spot. Another one is more than one crops are planted separately
in a field.
For instance, in case when maize and soybean areplanted randomly in afield, you count maize as well as soybean, namely, planted area are counted twotimes.
In case when more than one crop are planted separately, you just count acrop of the spot which the dot falls on.

Note: As planted area are decided in an above mentioned way, please notethat you need to conduct crop cutting in a normal method focusing ona said crop when sample spot for crop cutting falls on a spot wheremore than one crop are planted randomly. In this way, you canestimate a production of said crop in a target area as follows:(average yield in the target area) x (planted area in the target area)

1.3.5 To be applicable to dyke survey
With the Dot Sampling Method, you can estimate both planted area excluding
dyke and area of dyke separately. This is because sample dots are selected byprobability proportionate to size of planted area and area of dyke. Therefore you
don’t need to conduct dyke survey separately.
6Note: In many cases, results of planted area survey often include dyke.
Therefore, crop production is apt to be overestimated when you
estimate production with yield multiplied by area. In this case you needto estimate production by using either area without dyke or yieldcalculated with dyke.

1.3.6 To be applicable to complicated geography or slope
At the field survey, you only identify whether said crop is planted or not. You
don’t measure area. So, it doesn’t matter if the geography is complicated. On asloped area, angle of slope doesn’t affect the results, as sample dots are put
according to area of projection plane.

1.3.7 To require small number of enumerators, even unskilled ones
With the Dot Sampling Method, you need small number of enumerators. Only
one person can conduct field survey, because you do not need to measure area.
Even unskilled ones can conduct a survey, because what you need to do is only
identify an attribution of sample dots, for instance identify if rice is planted or not(See 2.2).

1.3.8 To be conducted repeatedly any times a year
If you fix sample dots for several years, you can conduct surveys with the Dot
sampling Method repeatedly any times a year, as you only need to visit same
sample dots that you visited previous time without finding out where to visit (See
2.3).

1.3.9 To have possibility to further develop in the future
You can say that the Dot Sampling Method is a simple but profound methodwith possibility to further develop in the future.
The Dot Sampling Method has a possibility to have affinity with drone. It is7expected that drone would take pictures of spots of sample dots automatically byletting a drone read coordinates of latitude and longitude of sample dots. Thus
you might be able to conduct field survey on a desk.
The Dot Sampling Method has a possibility of development from the view
point of actual measurement nature which the Dot Sampling Method possesses.
Functions which Google Earth being equipped with, such as time slider andmeasurement of area, might have possibility to develop more efficient survey
with the Dot Sampling Method.
Thus, there seems to be possibilities to develop a system of crop production
survey which is suitable for new age together with past experience and newtechnology as well as knowledge of mathematics.

8

Chapter 2 Area Survey Using the Dot Sampling Method
In this chapter, concerning area survey using the Dot Sampling method, welearn concept of area survey and procedure of survey as well as procedure ofsurvey for the second time which is much easier than the survey in the first time,
size of the sample required for the Dot Sampling Method and a way of
involvement by statistical organizations in surveys. And also we look at three
examples of preparatory surveys on Google Earth. In addition, we learn the way
to use the Dot Sampling Method as a two dimensional ruler or a ruler formeasuring area.

2.1 Concept of area survey
The basic idea of the Dot Sampling Method is, for instance, as being describedin Chapter 1, you put n sample dots in a target area and count the number ofsample dots which fall on rice planted spots. If the number of dots which falls on
rice planted spots is 𝑛1 , then you estimate rice planted area（𝑇̂）by multiplying
area of the target region (W) by the ratio（𝑝̂ ＝𝑛𝑛1）. Please note that with the Dot
Sampling Method, you put sample dots systematically in a grid pattern which iseasy to manage dots and generates more precise results than putting them insimple random way.

Note 1: Estimation formula is as follows:
Rice planted area𝑛𝑇̂ = 𝑛1 × 𝑊 = 𝑝̂ 𝑊

Standard error

SE = √ 𝑛𝑝̂×𝑞̂

when 𝑞̂ = 1 − 𝑝̂

Note 2: CV for estimated value is as follows:
Coefficient of variation𝑆𝐸

CV= 𝑝̂

2.2 Procedure of survey
There are following 4 procedures for area survey using the Dot Sampling
9

Method.
Step 1 is to extract sample dots. You decide the number of sample dots, input
density of sample dots (values of area and number of dots) and values of latitude
and longitude which decide a range of target area into the table on Excel sheet.
Click buttons according to the instruction on the sheet. Sample dots will be
displayed on Google Earth.
Step 2 is examining attributions of sample dots on Google Earth. You
categorize attributions of sample dots into cultivated land and others such as
forest, river, road, building which you clearly don’t need to visit for a field survey.
Thus sample dots are classified into two categories, one is sample dots which
you need to conduct field survey to examine their attribution and another issample dots which you don’t need to conduct field survey.
Step 3 is conducting field survey to visit sample dots and examine their
attributions. In the case of rice planted area survey, you check whether rice isplanted or not at a spot of each sample dot.
Step 4 is estimating area.
The following are the details of 4 procedures in the case of a rice planted area
survey as an example.

2.2.1 Step 1

To put sample dots on Google Earth

In order to put sample dots on Google Earth you use Excel Macro which has
been developed for putting them efficiently.
Before starting you prepare a computer with Google Earth, three Excel Macrofiles of LL Sheet for the dot sampling、LL Table Maker、Save Range As KML File.
First, you open the file of LL Sheet for the dot sampling and input anappropriate file name for saving, following six values from 1) to 6).
1) Area of target region2) The number of sample dots putting in the target region3) Any latitude on the north of the northernmost of a target region4) Any longitude on the west of the westernmost of a target region105) Any latitude on the south of the southernmost of a target region6) Any longitude on the east of the easternmost of a target region
Concerning the value of area of target region of 1) such as a countries landarea, you can get it from administrative data or other sources.
You need to calculate the necessary number of sample dots for inputting
value of 2). The way of the calculation is described in 2.4.
You need to use decimal degrees for inputting latitude and longitude from 3)to 6) which you can get Google Earth or other sources.

Note1: A purpose of inputting values of 1) and 2) is to determine dot density
or number of dots per area.
Note2: Values from 3) to 6) determine a rectangle shape of range for putting
dots which covers all area of target region. Values of 3) and 4) provide
coordinates of northwest starting point of systematic sampling andvalues of 5) and 6) provide coordinates just before southeast ending
point.
Note3: Dots are put into rectangle form in a range surrounded by input
latitude and longitude.
Note4: The number of dots which are fallen in target region defined in 1) isalmost as same as the number of dots defined in 2) with highprobability, though it depend on the starting point of systematic
sampling.

Suppose you would like to put 100 sample dots in Tsubameshi, Niigata
Prefecture, you open a file “LL Sheet for the dot sampling” and input 6 values asfollows:
You enter Tsubameshi as a name of the file in cell (1). You enter 110.94 asarea of Tsubameshi in cell (2). You enter 100 as the number of sample dots incell (3). You put 37.73 as latitude on the north of the northernmost of a target
region in cell (4). You enter 138.78 as longitude on the west of the westernmost11

of a target region in cell (5). You enter 37.59 as latitude on the south of thesouthernmost of a target region in cell (6). You enter 138.98 as longitude on theeast of the easternmost of a target region in cell (7).

LL Sheet for the dot sampling
T-1 Basic data to generate sample dots (Sampling Design)
Size of the Target
Starting point Starting point Finishing point Finishing point
Target area
Sample sizearea km2(latitude)(longitude)(latitude)(longitude)
(1)

(2)

Tsubameshi(3)

110.94

(4)

100

(5)

37.73

(6)

138.78(7)

37.59

138.981-(1) Click here to check data in T-1 table

2. Sampling based on the "Sampling design"
2-(1) Click here to complete T-2 table

2-(2) Click here to make a KML file

After finishing filling in cells, you click on the buttons according to instructions.
“LL Table Maker” file and “Save Range As KML” file starts automatically followed
by appearance of a table “Sample dots (Coodinate Values)” and Google Earthstarts automatically. Finally Sample dots will appear on Google Earthautomatically.

2.2.2 Step２ Preparatory survey on Google Earth
Preparatory survey is conducted on Google Earth. You examine attribution ofeach sample dot on Google Earth and distinguish sample dots which possibly
have fallen on cultivated land and you need to visit for a field survey from sample
dots which clearly have fallen on forest, river, road, building and you don’t needto visit for a field survey. In addition at this stage survey you could examine land
usage in target area.
According to the results of preparatory survey for Tsubameshi described in
2.2.1, cultivated land is estimated 6,000ha which may be more than actual value,
as it includes all sample dots which have possibility to have fallen on cultivatedland. In order to get final estimation, you have to conduct field survey to12examine actual attributions of sample dots as described in 2.2.3.
Results of Step 2（Preparatory Survey on Google Earth)category

sampe dpts

share (%)

estimation (ha)cultivated land andunclear usage

53

54

6,000

dyke

6

6

679

non-cultibated
land

39

40

4,415

Total

98

100

11,0942.2.3 Step3 Field survey
Step 3 is conducting field survey to visit sample dots which you are to visit asa result of step2 and examine their attributions.
Before visiting fields, you need to print out guide maps which enumerators
bring to lead them to the fields. If computer or smartphone are available, you
could send KML file, which you made in step1, to enumerators. Enumerators
open KML files which could lead them to the fields on Google Earth.
Enumerators visit sample dots which has been categorized to be visited forfield survey in step 2 and examine attributions of the sample dots. In the case ofrice planted area survey, enumerators check whether rice is planted or not at aspot of each sample dot.
In the case of Tsubameshi mentioned in step2, you need to visit 53 sample
dots to examine their attributions, as 53 dots have been categorized dots to bevisited for field survey.
As explained in 2.3, please note that you visit only 43 dots at the second
survey instead of 53 dots, if 10 dots out of 53 dots are classified to
non-cultivated area as a result of field survey.

2.2.4 Step４

Estimation of area

Please see estimation formula shown in 2.1. You can estimate rice planted13area by area of target area times a ratio of 𝑛1 to n when n is total number ofsample dots in target area and 𝑛1 is the number of dots which fall on rice
planted spot.

2.３ Procedure of survey for the second time
You can conduct a second survey and after more efficiently than first survey,
as explained below.
Firstly, as you can use same sample dots which you used at a previous survey,
you don’t need to select sample dots thereafter and what you need to do is only
to examine attribution of sample dots without selecting new sample dots.
Secondly, you can visit only sample dots which have fallen on cultivated land
to examine attribution of dots, as you already know which sample dots havefallen on non-cultivated land from the first survey.
Also, it is easy to conduct planted area survey several times a year because ofreasons above.

2.４ Size of the sample required for the Dot Sampling Method
The number of sample dots required for the preparatory survey mentioned instep 2 for the area survey using the Dot Sampling Method is calculated with two
factors: aimed precision and population coefficient of variation.

(𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝐶𝑉)2

The number of necessary sample dots＝（𝑎𝑖𝑚𝑒𝑑 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛)2（𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛)2＝（𝑎𝑖𝑚𝑒𝑑 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑒𝑟𝑟𝑜𝑟)2

Note: Though you cannot get a value of population p at the time of survey,
population CV can be estimated using results of past survey or pretest.

Please note that necessary number of sample dots is for the preparatory
survey explained in 2.2.2. The number of sample dots for field survey is less than14

that for preparatory survey, which has been categorized to be visited for fieldsurvey in step 2
The next table shows the necessary number of sample dots for preparatory
survey calculated by the formula above as well as the theoretical number ofsample dots for field survey calculated by the formula “the number of sample𝑝dots for preparatory survey x 100” by values of p and CV. Please note that as thevalue of p become smaller, the number of necessary sample dots for preparatory
survey increases sharply but the number of necessary sample dots for fieldsurvey increases not so sharply. This is one of characteristics of the Dot Sampling
Method. You can keep high precision with small number of sample dots for fieldsurvey.

Note1: In the next table, the number of necessary sample dots for fieldsurvey is a theoretical value for the number of sample dots which fallon rice planted spots in case of, for instance, rice planted area survey.
At the time of actual field survey, you need to visit all sample dots
which have possibilities to fall on rice planted spots, so the number ofwhich is somewhat more than theoretical value.
Note2: In the case of preparatory survey in Tsubameshi shown in Step2, just
100 Sample dots have been distributed in Tsubameshi. But now, let’s
make a sampling design for the survey, looking at the next table.
According to the past survey, share of rice planted area in Tsubameshi
is 40 %, so the number of necessary sample dots for preparatory
survey is 150 according to the next table. And the theoretical numberof necessary sample dots for field survey is 60 according to the nexttable, but actually you have to visit somewhat more than 60 sample
dots, as you have to visit every sample dots which has been
categorized to have possibility to be fallen on rice planted spot.
Note3: You could calculate the actual number of sample dots for field survey
with some of prior information. If you get prior information that share15

of rice field excluding dyke in Tsubameshi is 50 %, you calculate thenumber of sample dots which are possibly on rice planted area is 75
out of 150 sample dots. Thus, if you have got prior information, you
can calculate both the number of necessary sample dots for
preparatory survey and the approximate actual number of sample
dots for field survey, which is one of the advantages of the Dot
Sampling Method.

16

Number of Necessary Sample Dots by Aimed Precisionin case of Preparatory Survey and Field Survey

Share
of
rice plantedarea
in a target
regionAimed Precision
CV = 3%

Preparatory
surveyAimed Precision
CV = 5%Preparatory
surveyField
surveyAimed Precision
CV = 10%Preparatory
surveyField
surveyField
surveyp%
1

110,000

1,100

39,600

396

9,900

99

2

54,444

1,089

19,600

392

4,900

98

3

35,926

1,078

12,933

388

3,233

97

4

26,667

1,067

9,600

384

2,400

96

5

21,111

1,056

7,600

380

1,900

95

6

17,407

1,044

6,267

376

1,567

94

7

14,762

1,033

5,314

372

1,329

93

8

12,778

1,022

4,600

368

1,150

92

9

11,235

1,011

4,044

364

1,011

91

10

10,000

1,000

3,600

360

900

90

20

4,444

889

1,600

320

400

80

30

2,593

778

933

280

233

70

40

1,667

667

600

240

150

60

50

1,111

556

400

200

100

50

60

741

444

267

160

67

40

70

476

333

171

120

43

30

80

278

222

100

80

25

20

90

123

111

44

40

11

10

Note: Calculation fomulas are as follows:𝑛

Sample size for Preparatory Survey =

𝑝 𝑛
𝑛

𝑝
𝑝
× 1−
1
1
=
𝑝
×
1
1

𝑝

=

𝑛

𝑝× 1
𝑝×

−𝑝
1

Number of dots for Field Survey = Sample size for Preparatory Survey ×

17

𝑝
1

2.５ Way of involvement by statistical organization in surveys
Before you conduct a rice planted area survey in your country, you need todecide which organization is to conduct surveys in your government according to
the situation of your government.
Main activities for each organization to do are as follows:(Step1) 1) To put sample dots on Google Earth(Step2) 2) To conduct preparatory survey(Step3) 3) To send hard copies of maps to show sample dots or to send KML
files to put sample dots on Google Earth to enumerators
4) To visit sample dots, check whether rice is planted or not at a spotof each sample dot and report its number5) To compile results of field survey(Step4) 6) To estimate rice planted area
(Other) 7) To manage samples such as replace sample dots periodically
Activities from 1) to 3) and from 5) to 7) may be carried out by a central
organization or a local organization. Activity 2) may be carried out by a localorganization more efficiently than by a central organization, as a localorganization has much more information than a central organization. Activity 4)
is to be carried out by enumerators or a local organization.

2.６ Examples: results of preparatory surveys on Google Earth
You can carry out preparatory surveys for any countries, as preparatory
survey can be carried out on Google Earth. In this section, we learn results of
preparatory surveys conducted for three countries. Please note that these areresults of preparatory surveys, so no field surveys have been carried out yet tovisit and check sample dots to identify the planted crops for getting results.

2.6.１ Preparatory survey, Thailand
In order to study to see if the Dot Sampling Method is useful, preparatory
survey for rice field area in Thailand was conducted in 2013.
18

On Google Earth 999 sample dots were put in Thailand. The number ofsample dots which may have fallen on rice field was 184. The number of sample
dots which may have fallen on dyke was 31. So the number of sample dots whichwere necessary for conducting field survey, was 215 or 184+31.
If you calculate rice field area from the results of the preparatory survey as anexperiment, rice field area including dyke is calculated to be 11,043,000 ha, as
the ratio of rice field is 21.5 % and national land area is 51,312,000ha. However,official statistics shows rice field area including dyke is 10,400,000ha in 2011.
You cannot compare the results of preparatory survey with that of official
statistics as preparatory survey has examined only spots which have possibilityof rice field and you need to conduct field survey to visit each sample dot toestimate area. However, official statistics which Thai government has estimatedusing lots of monetary resources, 10,400,000ha, is similar to results of

3,
4,

4

4

4

4

4

4

1

4

3

1

1

5,

4

4

3

4

4

2

1

2

4

4

3

1

6

4

4

4

6,

4

4

4

4

5

4

4

4 11

5

1

1

4

5

4

4

4

4

4

7,

4

4

4

4

4

4

4

4

4

4

4

4

4

4

1

4

6

4

5

4

4

4

4

4

4

4

1

4

4

4

1

4

4

3

4

4

4

4

4

4

4

4 11

1

4

4 11

4

4

4

1

1

4 11

4

4

4

1

4

2

4

4

8,
9,
11,

4
4

2

4

4

4

4

4

4

1

1

4

4

4

1

4

4

12,

4

4

4

4

4

4

4

5 11

4

1

4

4

4

4

13,

4

4

4

4

4

1

4

4

4

4

4

1

4

1

4

14,

4

4

4

4

4

4

15,

4

4

16,

4

4

4

1

4

1

1

4

4

4

1

1 11

1

1

4 11

4

4

1

4

1 11

4

4

4

5 11

3

1

4

4

1

5

4

4

4

4

4

4

4 11

3

4

4

4

4

1

4

4

3

7

1 11 11

1

7

4

4

4

4

4

1

1

5

4

1

4

4

4

1

4

1

3 11

1 11

4

1

1

4

7

1

7

4

4

4

4

1

1

1

1

4

4

5

4

4

4

1

4

4 11 11

1

1

1

1

4

3

7

7

1 11

11

4

4

1

1

4 11 11 11

4

1

4

4

3

4

4

4

3 11

1

1

1

4

1

1

4

4

4

1

18,

1

4

4 11 11 11

5

1

4

4

7

4

1

4

1 11

4

1

1

1

1

1

1

3

4

1 11

1

4

4

6

1 11 11

3 11 11

4

4 11

1

4 11 11 11

1

1

4

4

3

3 11

19,
20,
21,
22,
23,

4

24,

1 11

1

1 11 11 11

4

4

4 11

4

4

4

1 11

1 11 11

1 11 11

4

7

3

1

4

1

3

1 11

1

3 11 11

4

1 11

4 11

1

4

1

4

4 11

4 11

1 11 11

4

4

1 11 11 11 11 11

1

1 11

1

4

4

4

1

4

4

4

7

1 11

1 11

1

3

3 11

4

4

1

4

3 11 11 11 11 11

1 11

1 11 11 11

4

4

4

4

1

4

4

4

4

4

4 11 11

4

4

4

4

4

4

4

1 11 1127,

4

1 11 11 11

7

1 11
1

4

4 11 11

4

1

4

1 11

4

4 11

1

1 11

3

3 11

3

1

4

4

4

1 11 11 11 11

1

4 11

5

1

4

4

4

4

4

1 11 11

5

4

7

3 11

4

1

5

1 11

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1

1

1

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4 11 11 11 11

4 11

1

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4

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4

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1

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4

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4

3

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3 11 11

4

4

4

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4

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4

4

4

1

4

4

4

1

4

4

1

1 11 11 11 11

4

4

4 11

1

1 11

5 11

4

4

4

4

4

4

4

4

4

31,

4

4

3 11 115

1 11 11

1

4

4

4

4

4 11

32,

4

4 11

4

1

1

1

5

5 11 11

8

4

1

1

1

1

1

4

1

1 11

8

5

1

5 11

5

3

1

1

1 11

4 11

1

1 11

1

8

1

1

4

4

4

1

4

4 11

4

4

1

4

4 11 11

4

4

4 11

3

5

1

1

1

4

1

37,

4

4

1

1

5

1

1

1 11

1

38,

4

4 11

1

33,
34,
35,
36,

4

1 11 11

3

4

1

4

1

1

1

4

4

4

1

1

4

4

1

1

4

4

41,

4

1
4

43,

Category

4

44,

1

45,

Cultivated land

1
4

4

47,

1

1

48,

4

1

4

8

4

1

1

4

4

49,
50,

4

51,
52,
53,
54,
4

56,

4

1

4

4

1

1

4

4

1

4

4

4

1

1

4

4

・・・

3

Maybe orchard

7

Aqua farm

8

Forest, River, Lake, etc

4

Residence, Factory, Road

5

Cloud

6

4

4

1

1

1

1

1

4

4

4

4

1

1

4

4

4

4

7

4

7

1

7

4 11

59,

11

4

7

7

7

1

7

4

1

1

60,

4

1

1

3

4

4

1

8

61,

4

1

7

7

4

7 11

4

7

7

4

1

3

1

4 11 11

4

1

1

4

4

8

65,

4

4

1

4

8

66,

4 11

4

7

7

1

67,

1

4

7

1

1 11

7

7

1

4

4

7

4

1

1

4

4

69,

Code

Dyke, Trees,etc

58,

68,

4

4

11

57,

4

1

Cultivatedland(upland)
Cultivated land
Paddy （Major rice)
Cultivated land in
mountain

Cultivated land/Breakdown

46,

1

4

4

1

1

70,

4

4

4

4

71,

7

4

4

4

72,

4

Rate(%)

Area(ha)

SE

CV

40

41

51.8

26,554,859

1.6

3.1

246

24.6

12,635,387

1.4

5.5

184

18.4

9,450,859

1.2

6.7

5

0.5

256,8170.2

44.6

Dyke, Trees,etc

43

4.3

2,208,625

0.6

14.9

Maybe orchard

32

3.2

1,643,628

0.6

17.4

Aqua farm7

0.7

359,544

0.3

37.7

Cultivated land Paddy（Major rice)
Cultivated land in
mountain

Forest, River, Lake, etc

451

45.1

23,164,877

1.6

3.5

Residence, Factory, Road

27

2.7

1,386,811

0.5

19.0

Cloud

4

0.4

205,453

0.2

49.9

Total

999

100.0

51,312,000…

…

Category

Number of
dots

4

40,
42,

3

4 11

39,

64,

39

5

1 11

4

63,

37

4 11

5

4

4 11

3 11

1 11 11

29,
30,

1 11

3 11 11 11 11 11

1 11

5 11 11 11 11
1 11

5

28,

62,

36

7

3 11 11 11

4

4 11 11

7

1

4

26,

25,

4

1 11

1

4

1 11

517

Cultivated land(upland)
11

17,

55,

38

33

34

35

30

31

32

27

28

29

24

25

26

21

22

23

18

Cultivated land

4

Cultivated land/Breakdown2,

Number ofdots

Category

11

1,

10,

19

4

20

4

4

15

4

1

16

5

3

17

13

14
4

4

4

0,

12

9

10

4

4

1

11

6

7

2 11
1
4

8

3

4

5

0

1

2

preparatory survey which one person conducted on Google Earth, 11,034,000ha.

1

Pure planted area
Paddy
（Major rice)field
Dyke, Trees,

2

Total

Rate(%)

Area(ha)

SE

184

18.4

9,450,859

1.2

6.7

31

3.1

1,592,264

0.5

17.7

215

21.5

11,043,123

1.3

6.0

1,000ha
15,000
1,592

10,0005,000

10,4009,451

0Major rice (OAE 2011) Cultivated land (paddy)+Dyke (Dot 2013)

4

73,
74,

Source: Issei Jinguji, Dot Sampling Method for Area Estimation, Feb. 2014
19CV

2.6.2 Preparatory survey, Lao PDR
A staff member of Lao government conducted preparatory survey for rice
field area in Savannaket prefecture during a training course 2014 in Japan.
Hundred Sample dots were put in Savannaket prefecture. The results werethat the number of sample dots which have some chance of falling on rice field
was ten which were necessary to be conducted field survey.
Preparatory survey has examined only spots which have possibility of rice
field and you need to conduct field survey to visit each sample dot to estimate
area. However, if you calculate rice field area from the results of the preparatory
survey as an experiment, rice field area is calculated to be 217,740ha, as theratio of rice field is 10 % and area of Savannaket prefecture is 2,177,400ha. On
the other hand, official statistics shows rice field area is 212,840ha in 2013.
Category

NumberShare (%)

Estimate (ha)SE (point)

CV

Paddy

10

10

217,740

3.0

0.30

Dyke

2

2

43,5481.4

0.70

Residential Land7

7

152,418

2.6

0.36

Road

2

2

43,548

1.4

0.70

River

1

1

21,7741.0

0.99

Forest75

75

1,633,050

4.3

0.06

Cutivated Land3

3

65,322

1.7

0.57

Total

100

100

Note1: Area of Savannaket: 2,177,400 ha
Note2: Agricultural Statistics 2013: Paddy Area: 212,840 hasource： Mr.Senpachanh Khounthikoummane, Lao PDR, August, 2014

2.6.3 Preparatory survey, East Timor
Preparatory survey on area of districts in East Timor was conducted in 2014
with the Dot Sampling Method.
Fifteen hundreds Sample dots were put in East Timor on Google Earth. The
results were that the number of sample dots which seemed to have fallen on
20

Lautem District was 184.
Let’s estimate area of Lautem District from the results of the preparatory
survey as an experiment. Area of Lautem District is estimated to be 1,830km2(＝14,919×184/1,500), as the ratio of the District is 12.3%(＝184/1,500) andarea of national land is 14,919km2. On the other hand, Wikipedia shows area of
the District is 1,813km2.
The preparatory survey shows that error is 17km2(=1,830 － 1,813km2),
namely, actual precision is 0.9%(=17/1830) which is far better than theoreticalprecision 6.9%.
A Precision of area estimation with the Dot Sampling Method has a tendency
to be extremely better than theoretical one. There are several reasons why it
becomes better than theoretical precision which are expected to be further
studied theoretically.
Theoretical Value
SampleShare ofDifference Precision
Estimated Area by
Dots
Districts（E)（F)
Standard
Area
Wikipedia
District
Precision(A)(B)（＝C－D） （＝E/C）
Error
number％k㎡
k㎡
k㎡％%point％Lautem
184
12.3
1,830
1,813
17
0.9
0.85
6.9
Baucau
150
10.0
1,492
1,506
-14
0.9
0.77
7.7
Viqueque
188
12.5
1,870
1,877
-7
0.4
0.85
6.8
Manatuto
182
12.1
1,810
1,782
28
1.6
0.84
6.9
Dili
39
2.6
388
367
21
5.4
0.41
15.8
Ailiu
73
4.9
726
737
-11
1.5
0.56
11.4
Manufahi
128
8.5
1,273
1,323
-50
3.9
0.72
8.5
Liquiçá
60
4.0
597
549
48
8.0
0.51
12.6
Ermera
75
5.0
746
768
-22
3.0
0.56
11.3
Ainaro
83
5.5
826
804
22
2.6
0.59
10.7
Bobonaro
140
9.3
1,392
1,376
16
1.2
0.75
8.0
Caova Lima
117
7.8
1,164
1,203
-39
3.4
0.69
8.9
Oesusse
81
5.4
806
814
-8
1.0
0.58
10.8
Total
1,500
100
14,9190
Source：Kenji KAMIKURA、Dot Sampling Method using Google Earth -What you can do with
the Dot Sampling Method-、Developing Partners Coordinating Meeting, World Bank,
Timor-Leste, November, 2014

2.７ Area Survey using the Method as a two-dimensional ruler
In this section, we learn the way to use the Dot Sampling Method as a twodimensional ruler or a ruler for measuring area. You can measure area using a
two dimensional ruler by counting the number of dots in a similar manner that21

you measure length by counting divisions on a scale. Some of you may havebeen already familiar with Point Grid Plate which is a transparent film with points
arranged in grid pattern. Putting a Point Grid Plate on map, you count the
number of points which are on target area and estimate the area by multiplying
the number and coefficient (=area per one point) together.
You can apply area estimation method with a Point Grid Plate to the Dot
Sampling Method as a two dimensional ruler.
For example, in case that you put dots in the ratio of one dot per 10a on
Google Earth, the area is estimated 30a, if the number of dots within target areais three.
Suppose you would like to put one dots per 10a, namely 1,000 dots in one
km2, you open a file “LL Sheet for the dot sampling” and input data as follows:
You enter file name such as “1 dot=0.1ha” in cell (1). You enter 1 in cell (2). You
enter 1,000 in cell (3). You put 36.032451 as latitude on the north of thenorthernmost of a target region in cell (4). You enter 140.1226 as longitude on
the west of the westernmost of a target region in cell (5). You enter 36.026 aslatitude on the south of the southernmost of a target region in cell (6). You enter
140.1329 as longitude on the east of the easternmost of a target region in cell(7).
LL Sheet for the dot sampling

22

Chapter 3 Yield Survey using the Dot Sampling Method
In this Chapter, you learn the way of utilizing the Dot Sampling Method foryield survey. If you apply the Dot Sampling Method to yield survey, you candramatically streamline the process of selecting samples in which you have taken
a lot of time.

3.１ Application of the Dot Sampling Method to yield survey
You can apply the Dot Sampling Method to selecting spots for crop cutting
using the characteristics of the Dot Sampling Method that sample dots are
selected with probability proportional to size, though you don’t use the Dot
Sampling Method for variable survey such as yield survey, as the Dot Sampling
Method is used for attribute survey in principle.
Major advantages of applying the Dot Sampling Method to yield survey is thatyou can select sample spots for crop cutting even when you don’t know rice
planted area of each village or you don’t have a list of farmers. With aconventional method, you select sample fields with probability proportional tosize. You have been managing to select spots for crop cutting in a way such as:
at first you have to calculate accumulated rice planted area of villages and selectvillages with probability proportional. Secondly, you make a list of farmers of
selected villages, and systematically select farmers from the list. Thirdly, you
select field of selected farmers systematically. Fourthly, you select spots for crop
cutting. Please note that making a list of farmers to select farmers and field is atemporary practical way, as it is difficult to select sample field precisely withprobability proportional to size. With the Dot Sampling Method, a spot which asample dot falls on is exactly a crop cutting spot. If you need to conduct crop
cutting at more than one spot in one field, you conduct crop cutting at a spot
which a sample dot falls on and at other spots around the spot in a preset way.
With the Dot Sampling Method, you can select sample rice field with perfectprobability proportional to size as well as you are freed from complicated23

sampling process.
As the fields for crop cutting are selected with probability proportional to size,
you can estimate average yield by simple average without taking into account asize of rice filed for crop cutting sample. Another merit is that you can easily
manage sample dots including rotation of sample dots, as you can selectsamples easily.

3.２ Procedure of survey
3.2.1 Step1 Selection of sample spots for crop cutting
At first, you select sample spots for crop cutting.
In order to select sample spots, you select necessary number of sample spots
systematically from the sample dots which were used for rice planted area
survey and have fallen on rice planted spots

Note1: You calculate size of the sample in a same way as usual.
For instance, in case that coefficient of variation of rice yield in atarget region is 32% and aimed precision is 10%, the number ofnecessary sample dots is 10 as calculated below:
Sample size =(𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝐶𝑉)2

（𝑎𝑖𝑚𝑒𝑑 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛)23 2＝ 102 ≒ 10

Note2: In case that you haven’t conducted rice planted area survey with theDot Sampling method, you have to use Excel Macro explained inchapter2 as an alternative method as follows:
Before starting you prepare a computer with Google Earth, three
Excel Macro files of LL Sheet for the dot sampling、LL Table Maker、Save Range As KML File.
Suppose you would like to put 10 sample dots for crop cutting in
Tsubameshi, Niigata Prefecture, you open a file “LL Sheet for the dot
sampling” and input data as follows:
You enter TsubameshiY as a name of the file in cell (1). You enter 52
as rice planted area of Tsubameshi in cell (2). You enter 10 as the24number of sample dots in cell (3). You put 37.73 as latitude on thenorth of the northernmost of a target region in cell (4). You enter
138.78 as longitude on the west of the westernmost of a target regionin cell (5). You enter 37.59 as latitude on the south of thesouthernmost of a target region in cell (6). You enter 138.98 as
longitude on the east of the easternmost of a target region in cell (7).
After finishing filling in cells, you click on the buttons according to
instructions.

“LL Table Maker” file and “Save Range As KML” filestarts automatically followed by appearance of a table “Sample dots
(Coodinate Values)” and Google Earth starts automatically. FinallySample dots will appear on Google Earth automatically. As sample
dots are put within whole target area on Google Earth, you conductcrop cutting at the sample dots which have fallen on rice planted
spots.
LL Sheet for the dot sampling
T-1 Basic data to generate sample dots (Sampling Design)
Size of the Target
Starting point Starting point Finishing point Finishing point
Target area
Sample sizearea km2(latitude)(longitude)(latitude)(longitude)(1)

TsubameshiY

(2)

(3)

(4)

52

10

(5)

37.73

138.78

(6)

(7)

37.59

138.981-(1) Click here to check data in T-1 table

2. Sampling based on the "Sampling design"
2-(1) Click here to complete T-2 table

2-(2) Click here to make a KML file

3.2.2 Step2 Crop cutting, threshing, drying, weighing
You conduct crop cutting at a spot which a sample dot falls on. If you need to
conduct crop cutting at more than one spot in one field, you conduct crop cutting
at a spot which a sample dot falls on and at other spots around the spot in apreset way. You conduct crop cutting in a same way as farmers do. After reaping
rice-plants, you thresh, dry and weigh them.

25

3.2.3 Step3 Estimation of average yield/ha in a target region
You estimate average yield by simple average without taking into account asize of rice filed for crop cutting sample, as the fields for crop cutting are selectedwith probability proportional to size.

Note: Estimation formula is as follows:
Yield/ha∑𝑋
𝑋̅= 𝑛 𝑖Standard error𝑠𝑋̅ =√ 𝑛

𝑠2

when

26

1
𝑠 =𝑛−1 ∑(𝑋𝑖 − 𝑋̅)Chapter 4

Example of Rice Production Survey
Using the Dot Sampling Method

In this chapter, you learn the example of rice production survey.
Following case is the results of the rice production survey using the Dot
Sampling Method in a target area of 20 hectares conducted in the JICA Training
Course 2015 in Japan. The survey took two days: one day for an estimation ofrice planted area and one day for an estimation of average rice yield andproduction.
Rice production survey is conducted with a package of planted area survey
explained in Chapter2 and yield survey explained in chapter3.
Namely, rice production in a target area is calculated:(average rice yield in a target region) x (rice planted area in a target region)

4.１ Planted area survey
On the training, groups of trainees put 80 sample dots in a target area of 20
hectares on Google Earth.
At first they conducted preparatory survey on Google Earth. They judged
from Google Earth that 23 dots fell on non-cultivated field such as building, roadand river which they don’t need to conduct field survey.
Secondly, they judged remaining 57 dots to be necessary for them to visit toconfirm if dots fell on rice planted spots or not. After conducting field survey,
they found out that 50 out of 57 dots fell on rice planted spots.
The results are shown in the table below: rice planted area, precision andstandard error are estimated 12.5ha, 8.7% and 1.1ha respectively.

27

Category

Code No.

Number of
dots

Share

Estimated
Area

Variance

Standard
error

Precision(%)

n = 80p

20×ｐp×(1-p)𝑝 × 1−𝑝
𝑛

𝑠 𝑛
𝑝

Error
(ha)
Estimatedarea×
precision

Non-cultivated
land

1

23

0.288

5.8

0.2048

0.051

17.6

1.0

Dyke

3

3

0.038

0.8

0.0361

0.021

56.6

0.4

Abandond
cultivated land

10

3

0.038

0.8

0.0361

0.021

56.6

0.4

Unplanted
land

11

1

0.013

0.3

0.0123

0.012

99.4

0.2

Rice

12

50

0.625

12.5

0.2344

0.054

8.7

1.1

Other crops

13

0

0.000

0.0

0.0000

0.000

80

1.000

20.0

0.0000

0.000

0.0

0.0

Total

28

4.２ Yield survey
Concerning Yield survey, rice yield per hectare was estimated with crop
cutting method. Trainees selected sample spots for crop cutting withprobabilities proportional to size. As they used the Dot Sampling Method, they
were able to select sample spots for crop cutting without procedures such as
preparing list of farmers in a target region and selecting sample rice fields.
Trainees had to follow procedures described in step 1 of 3.2, but in theTraining course, they selected six sample spots for conducting crop cutting fromthe one field which was borrowed from a farmer for the training. The results
were shown in following table: average yield in the target area is 9.28t/ha,
precision is 6.4%, sampling error is 0.59t.
Sample number（n = 6）

SymbolNo1

𝑋1

11.08 Sample variance

𝑠

No2

𝑋

9.95

Sample standard
deviation

𝑠

No3

𝑋3

9.68

Sample coefficientof variation(%)

No4

𝑋

8.39

No5

𝑋

9.66

Sample meanvariance

No6

𝑋

6.89

Sample mean
（Estimated Yield）

𝑋̅

9.28

Yield(t/ha)

Item

SymbolFormula1𝑛−1

𝑋𝑖 − 𝑋̅

Results
2.10

𝑠

1.45

𝑠
𝑋̅

15.62

𝑠𝑋̅

𝑠
𝑛

0.35

Standard error(sample error)

𝑠𝑋̅

𝑠𝑋̅

0.59

Sample meancoefficient ofvariation(%)

̅
𝑋

𝑠𝑋̅
𝑋̅

6.38

𝑋

Note: Concerning selecting sample spots for crop cutting, with the Dot
sampling method, you have two methods for selecting samples
described in step 1 of 3.2: one is you select 6 dots out of 50 dots whichhave fallen on rice planted spots used for planted area survey. Anotherway is select six sample dots on Google Earth with using Excel Macro.
But in the JICA Training Course 2015, one field was borrowed from a
farmer for the training and six groups of trainees conducted actual crop
cutting for training at selected six spots there.
294.３ Production survey
From the results of planted area survey and yield survey, production of rice ina target district and the precision are estimated 116t and 10.8% respectively asshow in following table.

Yield （ｔ/ha）

Planted area (ha）Production （ｔ）

Calculation

Estimation

9.28

12.5

116

×1

C.V. （％）

6.4

8.7

10.8

Survey Method

Crop Cutting,
Attribute survey
Selection of sample
spots with Probability
with the Dot
Proportional to Size Sampling Method
using the Dot
Sampling Method

Production= Yield ×Area

It took only two days for you to conduct rice production survey: one day forrice planted area survey and one day for rice yield survey and estimation of riceproduction in a target district of 20 ha. The reasons why you can conduct
production survey in such a short time which you have needed considerable days
to conduct so far, are you can conduct area survey in dramatically short timewith the Dot Sampling Method and you don’t need to make a list of farmers to
select sample farmers, fields and spots for crop cutting.

30

Chapter5

Mystery of the Dot Sampling Method

The more you learn the Dot Sampling Method, the more you encounter its
mysterious characters. In this chapter you learn two mysterious cases.

5.１ Better precision than theoretical precision
The first mystery is that precision of the result with the Dot Sampling Method
are always better than theoretical precision. Standard errors of sample means
are always several times better than theoretical values. In another word, aestimated value is stable and its valiance is always smaller than theoretical value.
The following table was made by Mr. Issei Jinguji and is a good example ofthis mystery. He conducted land use survey in Shiga prefecture using 1,000
samples with the Dot Sampling Method 16 times on Google Earth. According to
the results of 16 times surveys, variance of estimated cultivated are is extremely
smaller than theoretical variance with simple random sampling. In this case,𝑉

relative efficiency, 𝑉 𝑠𝑖𝑚𝑝𝑙𝑒 , is 3.7 times, which means the precision of the𝑠𝑦𝑠𝑡𝑒𝑚𝑎𝑡𝑖𝑐

results of cultivated area using systematic sampling with 1,000 samples are assame the precision of the results using simple sampling with 3,700 samples. In
the case of the results of the Lake Biwa survey, relative efficiency is more than 26
times.

31

Non-cultivatedLand

Lake Biwa

Cultivated Land

Cultivated Land
without Dyke

Dyke within
Cultivated Land

Test 1
Test 2
Test 3
Test 4
Test 5
Test 6
Test 7
Test 8
Test 9Test 10
Test 11
Test 12
Test 13
Test 14
Test 15
Test 16

70.6
68.3
69.6
70.2
69.7
70.2
69.5
69.9
70.3
69.7
69.8
68.2
69.6
70.0
70.3
68.9

16.5
16.9
16.8
16.7
17.0
16.5
17.0
16.9
16.5
16.9
16.8
16.8
16.7
16.1
16.4
16.6

13.0
14.8
13.6
13.2
13.4
13.2
13.6
13.2
13.2
13.5
13.5
14.9
13.7
13.9
13.3
14.4

12.2
14.0
12.6
11.9
12.4
12.2
12.7
12.4
12.1
12.2
12.8
14.0
13.0
12.9
12.3
13.5

0.8
0.8
1.0
1.2
1.0
1.0
0.9
0.8
1.1
1.2
0.7
0.9
0.7
1.0
1.0
0.9

Average of 16 Tests
by Systematic Sampling

69.7

16.7

13.6

12.7

0.9

Official Value

70.2

16.7

13.1

12.5

0.6

0.65

0.23

0.57

0.62

0.15

0.93

1.38

4.16

4.89

16.00

1.45

1.18

1.09

1.05

0.30

2.1

7.1

8.0

8.3

32.5

5.0

26.3

3.7

2.9

4.1

Standard Deviation
by Systematic Sampling
Coefficient of Variation
by Systematic SamplingStandard Error
by Simple Sampling
Coefficient of Variation
by Simple Sampling

Relative Efficiency

Source: Issei JINGUJI, December, 2015

Concerning attribute survey such as the Dot Sampling Method, theoreticalvariance is calculated with𝑝̂𝑞̂𝑛under the condition of simple sampling. As theformula for calculating variance in case of systematic sampling has not beendeveloped yet, variance of estimated values based on systematic sampling is tobe calculated referring to the formula for simple sampling or results of surveys
conducted repeatedly. Though actually conducting surveys repeatedly is difficult
to carry out, you can simulate surveys any number of times by preparatory
survey on Google Earth as mentioned above. Now you can confirm thesuperiority of the Dot Sampling Method with systematic sampling, but how much
relative efficiency the Dot Sampling Method has in general is necessary to bestudied more.

32

5.２ Sampling survey or measuring survey
The second mystery is that the Dot Sampling Method might be under acategory of measuring method rather than sampling method.
This idea comes from the assumption that the Dot Sampling Method is a same
method as measuring area by Point Grid Plate, as dots are arranged with grid
pattern with the Dot Sampling Method like Point Grid Plate. This idea also
explains the reason why precision of the Dot sampling method is better thantheoretical precision, as error of the Dot Sampling Method is mere measuring
error rather than sampling error.
Actually, increasing the number of sampling dots could be similar to
improving resolution of satellite image or increasing fineness of scale. So, you
could dare say that the Dot sampling method is measurement method rather
than sampling method. In the case of area survey using Point Grid Plate, in orderto reduce measuring error, it is recommended to measure area three times andthe average of three values are determined as area, this means that area survey
using Point Grid Plate has nothing to do with sampling error
The theoretical concept of the Dot Sampling method mentioned above is
expected to be developed by experts such as mathematicians.

33

Chapter 6 Dissemination of the Dot Sampling Method
and Similar Methods Overseas
Focusing on characteristics of an attribute survey as written in 1.1, it is an
opinion poll method that is similar to the Dot Sampling Method. So the idea of the
Dot Sampling Method can be said to have been prevailing widely, as opinion polls
has been conducted in many countries. In case of an opinion poll, the targets ofsurvey are persons. If you change the targets of survey from persons to lands,
then it will become the method of an area survey with the Dot sampling Method.
Concerning the Dot Sampling Method overseas, it has not been prevailing,
though it is a traditional method. The reason is that maps had not beendeveloped to put any number of sample dots on a map. In Europe and the UnitedStates, they have developed surveys with a method that puts dots on a map.
However, any surveys aren’t attribute surveys. They don’t select sample dots
directly as a survey spots for conducting attribute survey like the Dot Sampling
Method, but they select dots for sample spots and measure area at the lastprocess of the survey.
In most of developing countries, sampling surveys have not been prevailingbecause of adopting reporting system, so surveys using dots have not prevailed.
In this chapter, we learn situation of similar methods overseas anddissemination of the Dot Sampling Method in international technical cooperation
activities.

6.１ Situation of similar methods overseas
Concerning the situation of methods similar to the Dot Sampling Method
overseas, Mr. Issei JINGUJI has depicted in detail in the document “About the Dot
Sampling Method (Japanese version)”, December 2015.
In the United States, they have historically adopted method such as selecting
points, interviewing farmer of farm including a selected point as a sampling unit
(Yoshirou TSUMURA, 1956).
34

In EU, they select samples for area survey by compiling master points with
2km×2km, selecting Primary sampling unit and selecting secondary samplingunit（see the Web site of LUCAS http://ec.europa.eu/eurostat/web/lucas/methodology）.
Conducting Global Strategy to improve Agricultural and Rural Statistics, FAO
has introduced the way to select samples using dots as one of master sampling
method. FAO also introduced the technical assistance on the Dot Sampling
Method conducted in Tanzania as one example of the technical assistances
conducted by Japan in the report “Technical Report on Improving the Use of GPS,GIS and Remote Sensing in Setting Up Master Sampling Frames”（FAO,2015）.
FAO published the report ” CROP MONITORING FOR IMPROVED FOOD
SECURITY” ,FAO&ADB Bangkok 2015, explaining the Dot Sampling Method in
detail.

6.２ Dissemination of the Dot Sampling Method in international technicalcooperation activities
The Dot Sampling Method has been introduced in international technicalcooperation activities conducted by Japan.
Concerning JICA Group Training Program “Planning and Designing ofAgricultural Statistics” which is conducted for government staff member incharge of agricultural statistic from countries in Asia, Africa and other regions,
every year more than a dozen trainees come to Japan and they have beenlearning the Dot Sampling Method since 2011. The dot Sampling Method have
got high evaluations from trainees who were learned to conduct rice production
survey in the training, saying that, with the Dot Sampling Method, crop
production survey is conducted easily and possible to conduct without humanand budgetary resources.
In the Project “Improving Food Security Information in Africa” supported by
Japan from 2013 to 2016 and conducted through Africa Rice to improve foodsecurity and reduce poverty in sub-Saharan Africa through improving theavailability and reliability of rice production statistics in support of the objectives
35

of the Coalition for African Rice Development (CARD) initiative, the Project
adopted the Dot Sampling Method as one of survey methods.
The Japan funded project “Strengthening Agricultural Statistics and Food
Security Information in CARD Countries through South-South Cooperation”
conducted through FAO to contribute to the success of CARD initiative in terms ofcreation of reliable statistics to evaluate CARD’s progress from 2013 up to now
also adopted the Dot Sampling Method as one of survey methods.

36

Chapter 7 Frequently Asked Questions
on the Dot Sampling method
This chapter is a list of frequently asked questions (Q) and answers (A) arisen
during the development and dissemination process of the Dot Sampling Method.

Q

Is resolution of Google Earth too low to use for area survey?

A

Resolution of Google Earth doesn’t have to do with the results of a survey,
because the main role of Google Earth in the Dot Sampling Method is to guide
enumerators to the spots of sample dots.
However, in the case of another role of the Dot Sampling Method that helps
to separate sample dots which are necessary to conduct field survey and dots
which are unnecessary as mentioned in chapter 2, more sample dots may be
categorized into dots which are necessary to conduct field survey and you
need more time to conduct area survey if resolution of Google Earth is low toclarify them. In most cases, resolution of Google Earth is high enough so thatyou can conduct preparatory survey properly.

A

Are images of Google Earth old?

Q

According to the Web site of Google Earth, images of Google Earth are to
be updated every one to three years. As they are not so old, you can use themfor area survey(http://www.google.co.jp/intl/ja/earth/help/).
But it may actually happen that a spot which is rice filed on Google Earthturns to be a residential land at the time of field survey. In this case, no
problem happens, as present land use is clarified by a field survey.
On the contrary, in case of a spot which is forest land on google Earth andis categorized a dot which is unnecessary to conduct field survey, problem
happens if the spot has cultivated and changed to be rice field. Therefore it is37

recommended that you conduct a preparatory survey after getting information
on a target area as much as possible.

Q

Is it difficult to distinguish rice field from upland field on Google Earth?

A

Yes, it is sometimes difficult, though you can distinguish rice field fromupland field to a considerable extent by the existence of dyke or a shape offield.
But you don’t need to worry about its difficulty, because actually you
conduct filed survey to clarify sample dots which are categorized to benecessary to conduct a field survey at the time of a preparatory survey.

Q

Is it possible to distinguish orchard from other land usages on Google
Earth?

A

Yes it is possible. It has been confirmed from experience that you can judge
orchard to some extent from the shape of planting pattern and shape of trees.
Also you often clarify it with the function of street view of Google Earth.
As you conduct field survey to clarify sample dots which are categorized tobe necessary to conduct a field survey at the time of a preparatory survey, you
don’t need to worry, even if you cannot categorize land usage precisely on
Google Earth.

Q

Do you need GPS when you visit sample spots on field survey?

A

It has been confirmed from experience that you manage to make it tosample spots without GPS. There is no reason to deny using GPS, but a survey
without GPS might be more efficient than with GPS, thinking of time and effort
for data entry into GPS.
If an enumerator is able to use a computer or smartphone in the field, it ismore efficient to conduct a field survey while looking at a screen of Google
Earth with KML file you made automatically in chapter 2.
If an enumerator cannot use a computer or smartphone in the field, an
38

enumerator has to bring hardcopies of maps of Google Earth beforehand andconducts a field survey. When an enumerator visits unfamiliar place, he needs
at least two hardcopies of map, namely one for general view to guide him to avicinity of field and another for more enlarged view around sample dot.
Please note that it is necessary to improve capacity of enumerators to readmaps who cannot read maps and cannot reach at a field.

Q

Does systematic random sampling generate big bias for estimation, if there
are roads or canals in the east and west direction or the north and south
direction?

A

In order to verify bias, preparatory surveys were conducted 16 times on
Google Earth with 500 sample dots in Oogata village, Akita, Japan on Google
Earth where many roads, canals and dyke are oriented in the east and west
direction or the north and south direction. When we compared variance bysimple random sampling with systematic random sampling to see relative
efficiency, the results were as same as the case in Shiga prefecture mentioned
in chapter 5, though attributions of samples were sometimes exchanged
dramatically like Othello game.

Q

Is there no need for stratification?

A

Main purpose of stratification is increasing precision under a certain
number of samples by setting the number of samples by stratification. But ittakes time and labor for you to conduct practical activities such as stratifying
and deciding the number of samples by stratification. Even if you conduct
stratified sampling, it is generally known that stratification doesn’t have large
effect which depends on availability of prior information which is necessary
for stratification and the way of stratification.
On the contrary, in case of the Dot Sampling Method, you put sample dotswith same intervals in the target region without stratification. Therefore
practical activities have been simplified. Besides, you can achieve the purpose39

of survey design to increase efficiency significantly by reducing the number ofsample dots for a field survey thorough a preparatory survey which hassignificance like stratification by identifying which samples are necessary forfield survey or not.

Q

What are merits for the Dot Sampling Method compared with ratio
estimation?

A

Ratio estimation has a merit that precision becomes high and you canreduce the number of samples for field survey when auxiliary variable hasstrong correlation with a survey item.
In comparison with ratio estimation, the Dot Sampling Method is
confirmed by the simulation results that precision is as same as ratio
estimation with same number of samples for field survey, as systematic
sampling has been known from experience that precision with systematic
sampling is better than theoretical precision.
In addition, the Dot Sampling Method has a characteristic that you canefficiently estimate any survey items, as the Method doesn’t need auxiliary
variable.
Please note that the Dot Sampling Method has merits that you canestimate area of various crops easily with the Dot Sampling Method as you
don’t need to increase necessary resources for field survey or tabulation evenfor various crops and that non-sampling error hardly happens with the Dot
Sampling Method.

40

Afterword
Compiling the essence of the Dot Sampling Method from materials created so
far related to the development of the Method, I feel again the greatness of power
and possibility in the Dot Sampling Method. On the other hand, not a few people
really think that the Dot Sampling Method is too simple and different fromtraditional method developed thus far to adopt the Method.
I am thinking of developing the Dot Sampling Method for more people tounderstand the Method and apply it to actual statistical survey.
The Dot Sampling Method has been developed by cooperation of people whoare engaged in international technical cooperation. The Excel Macros for the Dot
Sampling Method had not been developed without cooperation of experts
engaging in technical assistance in Tanzania and staff of MAFF Japan. In addition,
demonstration experiments were conducted with a cooperation of trainees oftraining in Japan from other countries. The current Dot Sampling Method is acompilation of cooperation of many people and projects adopting the Dot
Sampling Method as one of methods such as “ Improving Food Security
Information in Africa” conducted through Africa Rice and “ Strengthening
Agricultural Statistics and Food Security Information in CARD Countries throughSouth-South Cooperation” conducted by FAO.
I would like to express my sincere gratitude for your efforts in developing the
Dot Sampling Method. I would be glad if you continuously give me your opinions
and suggestions towards the development of the Dot Sampling Method.

41

Reference
JINGUJI, Issei: ドット標本調査法について～その基本的考え方、効率性、信頼性についての検討～, December 2015

JINGUJI, Issei: Google Earth を利用したドット標本調査法による土地利用面積調査について、法政大学 日本統計研究所, October 2014

KAMIKURA, Kenji: 「農」の統計に係る開発途上国に対する技術協力、齊藤昭編著「農」の統計にみる知のデザイン第 10 章、農林統計出版, April 2013

JINGUJI, Issei: Dot Sampling Method for area estimation, CROP MONITORINGFOR

IMPROVEDFOOD

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FAO

&

ADB,

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(http://www.fao.org/fileadmin/templates/rap/files/Project/Expert_Meeting__17Feb2
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JINGUJI, Issei: How to Develop Master Sampling Frames using Dot Sampling
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December

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KUGA, Nobunori: An Experiment on Accuracy and Precision of Dot Sampling
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KAMIKURA, Kenji: Package of Agricultural Production Survey, AfricaRice,
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CAS_24/Paper_after/APCAS-12-21-_Planted_Area_using_Dot_Sampling.pdf)

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43