Crop Production Survey No１

Guidebook 2018

Planning and Designingof
Crop Production Survey“Let’s estimate the total rice production
in Tsukuba Hamlet”

22 - 29 August 2018
JICA Knowledge Co-Creation Program on
Agricultural Statistics Planning and Designing
JICA Tsukuba International Center
KAMIKURA, Kenji
Knowledge Co-Creation Consultant
e-mail: kkamikura@hotmail.com

Planning and Designingof
Crop Production Survey“Let’s estimate the total rice production
in Tsukuba Hamlet”

Dear distinguished participants,
It is my pleasure to welcome you to the lecture titled “Planning and
Designing of Crop Production Survey”. I would be glad if I could share the idea ofcrop production survey with you.
Your mission for this training is to estimate the total rice production in
Tsukuba Hamlet. In order to accomplish your mission, you learn crop production
survey which consists of a planted area survey and a yield survey.
Concerning a planted area survey, the Dot Sampling Method using Google
Earth has been developed so that you can estimate a planted area of certain
crops easily and efficiently in a target area. In order to apply the Dot Sampling
Method to an area survey, the Excel Macros have been developed to put any
number of sample dots on Google Earth easily. Though planted area survey has
long been a bottleneck to implement production survey so far, the Dot Sampling
Method has removed the obstacle all at once.
Lastly, I would like to stress an importance of an actual measurement
method. In case of an actual measurement method, a survey object is not a
farmer but a field. Many of you may use a hearing method where a survey object
is a farmer. A hearing method is popular, but it has a week point: the data you getfrom a farmer don’t show the real situation, as a farmer often doesn’t know theactual values. In this case, you cannot evaluate a validity of the data.
The training lasts 6 days from August 22 to 29, 2018. On August 29, you
are supposed to make a presentation on what you have learned during the lecture
including purposes, activities and output.
I would like you to enjoy the lecture. I am glad if this Guidebook 2018 helps
you learn “Planning and Designing of Crop Production Survey”.
KAMIKURA, Kenji
Knowledge Co-Creation Consultant
e-mail: kkamikura@hotmail.com

Contents
Chapter 1 Expected Daily Output of the Training………………… 1
Chapter 2 Putting Dots on Google Earth…………………… ……... 3
2.1 Preparation in advance
2.2 Let’s save the Excel Macro File to your computer
2.3 Let’s open “LL Sheet for the dot sampling”
2.4 How to fill in the T-1 Table
2.5 Let’s put dots on Google Earth
2.6 KML files in a Dot-1 folder in C drive in your computer
Chapter 3 Package of Crop Production Survey…………… ……... 9
3.1 Let’s share the method of the production survey of yourcountry among participants
3.2 Method of Estimating Production
3.3 Actual Measurement Method
Chapter 4 Planted Area Survey using the Dot Sampling Method …11
4.1 Concept of planted area survey using the Dot Sampling
Method: Application of an attribute survey
4.2 Four procedures for a planted area survey using the Dot
Sampling Method
4.3 Let’s put sample dots on Google Earth for a rice planted area
survey4.4 Let’s conduct a preparatory survey of a rice planted area
survey on Google Earth
4.5 Let’s conduct a field survey of a rice planted area survey on
Google Earthi4.6 Let’s estimate rice planted area
4.7 How to determine the number of sample dots for a preparatory
survey4.8 Let’s conduct a preparatory land use survey in your country
4.9 Let’s use dots as a two-dimensional ruler for measuring area
4.10 Comparison of process for a rice planted area survey using
the Dot Sampling Method between the first year and the nextyear
Chapter 5 Yield Survey………………………………………… ……... 43
5.1 Concept of Yield Survey
5.2 Three procedures for a Rice Yield Survey using the Dot
Sampling Method
5.3 Let’s select sample spots for crop cutting
5.4 Let’s cut rice, thresh, cleanse, dry and weigh
5.5 Let’s estimate an average yield of rice in Tsukuba Hamlet
Chapter 6 Production Survey………………………………………… 56
6.1 Let’s compile the results of a rice production survey
6.2 Let’s make a rice crop production report
Chapter 7 Presentations on your Output from the Lecture…….. 61
7.1 Let’s review the lecture
7.2 Let’s make a presentation(Reference)………………………………………………………………. 67

ii

Chapter 1 Expected Daily Output of the Training

In this chapter, you know the schedule of the lecture and learn the expecteddaily output of the training.
The table below shows the expected daily output of the training:
AugustOutput1) You understand the daily output of the training.
2) You use the Excel Macro for the Dot Sampling Method.

22
(Wed)

3) You understand the formula:
Production = Average yield x Total planted area.
4) You understand the concept of an attribute survey and a rice plantedarea survey using the Dot Sampling Method.
1) You conduct a preparatory survey of a rice planted area survey using

23
(Thu)

the Dot Sampling Method.
2) You conduct a field survey of a rice planted area survey using the
Dot Sampling Method.
1) You compile the results of the rice planted area survey.

24
(Fri)

2) You understand the concept of a rice yield survey and prepare for arice yield survey such as preparing equipment and making
questionnaires.

1

27
(Mon)

1) You conduct a rice yield survey.
2) You compile the results of the rice yield survey.
1) You compile the results of the rice production survey.

282) You make a report of the rice production survey.

(Tue)3) You conduct a preparatory land use survey in your country using the
Dot Sampling Method.
1) You make a presentation on a preparatory land use survey in yourcountry using the Dot Sampling Method.

29
(Wed)

2) You make a presentation on your output during the lecture.
Note: In order to prepare for your presentation, it is useful for you tosummarize what you learned every day, using the forms
explained in 7.2, Chapter 7.

2Chapter 2 Putting Dots on Google Earth
In this chapter, you learn how to put dots on Google Earth using the Excel file
named “LL Sheet for the dot sampling” which includes Excel Macros.
The Excel file has been developed for the Dot Sampling Method to put dots
systematically on Google Earth.
At the beginning, you can enjoy putting dots systematically wherever you likeon Google Earth, even if you don’t know the Dot Sampling Method.
2.1 Preparation in advance
Item

Remark1) Google Earth

Make sure that Google Earth has been installed in yourcomputer.

2) Decimal degree

Make sure geo-coordinates in Google Earth are displayedin decimal degrees, not in degrees, minutes, seconds.

Note: In order to convert coordinates to decimal degrees,
Click on “Tools” on the Google Earth menu bar.
→ Click on “Options” at drop down list.
→ Select “Decimal Degrees” in the “3D View” tab.
2.2 Let’s save the Excel Macro File to your computer
You prepare your computer with the Excel Macro file of “LL Sheet for the dot
sampling” by saving it to your computer.
2.3 Let’s open “LL Sheet for the dot sampling”
You open the file of “LL Sheet for the dot sampling”.
Note: Make sure to enable macro in the Excel file on your computer, as you may
not be able to run macro because of security setting of your computer.

3

LL Sheet for the Dot Sampling
1. Fill in blank cells on T-1 Table below
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

Starting point Starting point(latitude)(longitude)(4)

Finishingpoint(latitude)

Finishingpoint(longitude)

(6)

(7)

(5)

Interval in km(depend on (3))

Necessary
Number of
Lines

Necessary
Number of
Rows

(9)

(10)

(8)=√((2)/(3))

Ｉｎｄｅｘ ｏｆ Ｌｉｎｅ Ｉｎｄｅｘ of Row on Area per Dot
on the work sheet.

the work sheet.

(km2)

(11)

(12)

(13)=(2)/(3)1-(1) Click here to check data in T-1
2. Sampling based on the "Sampling design"
2-(1) Click here to complete T-2 table

T-2 Sample dots (Coodinate Values),

Name of Longitude→
Latitude↓

0

0,

1

1,

0

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

Don't change the numbers on yellow cells because the numbers are used for the calculations.

1

2.4 How to fill in the T-1 Table
You fill in the T-1 Table as follows:
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

File nameStarting point Starting point(latitude)(longitude)
(4)

(5)

Finishingpoint(latitude)

Finishingpoint(longitude)

(6)

(7)

Starting point
Density of dots

Approximate finishing point

Starting point

Finishing point

4

Cell

Explanation(1)

Remarks

appropriate file name to saveFile name(2)

total area of a target region

Size of Target

Given

area

and

Area

number of dots determine(3)

the number of sample dots you the dot density.

Sample size

want to put in a target region(4)

any latitude to the north of theStarting

point target region

These(latitude)

figurescoordinates

theindicateofstartingroughly

any longitude to the west of the point.

(5)
Starting

point target region(longitude)(6)

any latitude to the south of theFinishing point target region

These

figures(latitude)

indicatecoordinatesof

any longitude to the east of the finishing point.

(7)

Finishing point target region(longitude)
Note1: As for latitude and longitude, you need to use decimal degrees.
Note2: Use minus figures in case of south latitude and west longitude.
As for (2) and (3), you also adopt the alternative style below.
Cell

Explanation(2)

unit of area such as:Size of Target

1 km2, 0.01km2

Using this style, you can

Area
(3)

Remarks

put one dot per unit of
the number of dots per unit of area area.

Sample size

5

Note1: A purpose of inputting values of (2) and (3) is to determine dot density
or the number of dots per unit area.
Note2: Values from (4) to (7) determine a rectangle shape of range for putting
dots which covers all area of a target region. Values of (4) and (5)provide coordinates of northwest starting point of systematic sampling,
and values of (6) and (7) provide coordinates just before southeast
ending point.
Note3: Dots are to be put into rectangle form in a range surrounded by input
latitude and longitude.
Note4: The number of dots which are fallen in a target region defined in (2) isalmost as same as the number of dots defined in (3) with highprobability, though it depends on the starting point of systematic
sampling.
2.5 Let’s put dots on Google Earth
2.5.1 Let’s put sample dots on a target region on Google earth
Suppose you want to put 100 dots in Lao PDR, you fill in T-1 Table as below.
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

Laos100

238000Starting point Starting point(latitude)(longitude)
(4)

100

(5)

22.52

Finishingpoint(latitude)

Finishingpoint(longitude)

(6)

(7)

100

13.88

107.72After finishing filling in cells, you only click on the buttons. Then Google Earth
begins to work and dots will appear on Google Earth automatically.

6

Note:

In some cases, you have to draw a boundary line of the target region
on a map.
Fortunately, on Google Earth, international boundary lines and large
administrative dividing lines are available. In other cases, you need todownload shapefiles of the administrative boundaries such as GADM,
the Database of Global Administrative Areas, a high-resolution databaseof country administrative areas. You could even create polygon of yourown on Google Earth so that you can set any shape of a target region.

2.5.2 Let’s put sample dots on scattered target regions on Google earth
Suppose you want to put totally 20 dots in Central African Republic(623,000km2) and Uganda (241,000km2), you fill in T-1 Table as below.
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

CAfUgan20

864000Starting point Starting point(latitude)(longitude)
(4)

20

(5)

11.05

7

14.36

Finishingpoint(latitude)

Finishingpoint(longitude)

(6)

(7)

-1.56

35.07

2.5.3 Let’s put one dot per unit of area
Suppose you want to put 1 dots per 1 ha (=0.01km2), you fill in T-1 Table as
below.
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

Aga1dot=1ha

0.01

Starting point Starting point(latitude)(longitude)(4)

1

37.686(5)

139.447

Finishingpoint(latitude)

Finishingpoint(longitude)

(6)

(7)

37.655139.48

2.6 KML files in a Dot-1 folder in C drive in your computer
If you want to share the geographic data of dots on Google Earth with yourcolleagues or enumerators, you can email the data in the form of a KML file to them.
Please note that KML file is saved at Dot-1 folder in C drive automatically inyour computer by default.
8Chapter 3 Package of Crop Production Survey
In this chapter, you learn the package of crop production survey, especiallythe calculating formula “the average yield times the planted area” with actual
measurement survey.
3.1 Let’s share the method of the production survey of your country among
participants
Let’s share the method of the production survey adopted in your country
among participants!
Please explain how you get the data of total production of rice or important
crops in your country.
3.2 Method of Estimating Production
In the lecture, a production survey consists of two surveys: a yield survey
and an area survey.

Production survey = Yield survey + Area survey
Note: “Yield” is used as “production per unit area”
In order to estimate the amount of rice production in a region, you multiply
average yield of rice in the region and total planted area of rice in the region
together.

Total production of rice in the target region=
Average yield of rice in the target region
×
Total planted area of rice in the target region
Note1: A target region or an estimation unit is usually a nation’s
administrative subdivision.
Note2: Planted area is almost as same as harvested area, when you checkplanted area at the time of harvesting.

9The formula is a package of a rice production survey. This is the reason why
you should plan and design a yield survey and an area survey together.
Note1: Usually yield is calculated without dyke, so area must exclude dyke.
Please don’t mix a case with dyke and another case without dyke.
In many cases, area include dyke and yield is calculated withoutdyke by mistake, so production become overestimated.
Note2: Even when survey sample is mix cropping field such as being
planted maize and rice mixed together, please neglect maize, justfocus on rice, if it is a case of a rice production survey.
3.3 Actual Measurement Method
In order to get average rice yield and total rice planted area, you have to
adopt actual measurement methods in which you don’t ask farmers but survey
rice fields to collect data.
You might think that it seems to be common to ask farmers to get such data
through interpersonal hearing method.
This hearing method is popular in some cases, but it has a week point thatyou cannot evaluate a validity of the data, as you get the data through hearing
from farmers without any evidence. It has been often happened that such data
doesn’t show the real situation. It is often the case with farmers that they don’tknow the precise figure so that you cannot evaluate a validity of the data.

10Chapter 4 Planted Area Survey using the Dot Sampling Method
In this chapter, you learn the concept of rice planted area survey using the
Dot Sampling Method which is an application of attribute survey.
4.1 Concept of planted area survey using the Dot Sampling method:
Application of an attribute survey
The Dot Sampling Method has been developed on the basis of traditional
statistical theory together with the new technology “Google Earth”. The Dot
Sampling method is an application of an attribute survey such as public opinion
poll. So what you have to do is only to confirm if the sample dot is fallen on rice
planted spot or not.
The basic idea of the Dot Sampling Method is:1) you put sample dots (the number of sample dots = n) in a target region;2) you count the number of sample dots (n1) which fall on rice planted spots;
3) you estimate rice planted area（𝑇̂）by multiplying area of the target region (W)by the ratio（𝑝̂ ＝𝑛𝑛1）.
Item

Estimation Formula

Rice planted area
（𝑇̂）

̂=
𝑻

Standard error
(SE)

̂×𝒒
̂
𝒑

𝐒𝐄 = √ 𝒏

Coefficient of variation
(CV)

𝒏𝟏
̂𝑾
×𝑾=𝒑
𝒏
where 𝑞̂ = 1 − 𝑝̂𝑺𝑬

CV= 𝒑̂

Note: How amazing an attribute survey is! you calculate SE and CV only with p.

Item

Main characteristicsof the Dot Sampling Method

Actual measurement

Survey object is not a person but a land.

No need of population

It doesn’t require population composition.

Easy to conduct

What you have to do is only check if the sample dots
fall on rice planted area or not.

No non-sampling error

Non-sampling errors hardly occur, as it is not avariable survey but an attribute survey.

11

Note: Empirically, the Dot Sampling Method generates more precise results
than theoretical precision. The reason has not been solved yet, but
one reason might be the way to put sample dots systematically in agrid pattern rather than putting them in simple random way.
(For more information)
The concept of the Dot Sampling method is as follows:
The figure below shows a target region of 100 ha (W).
You are going to estimate area of red fields using the Dot Sampling Method.

Let’s estimate area of red fields above.
1) you put 100 sample dots (n) in a target region;2) you count the number of sample dots which fall on red fields=> the number of sample dots(n1) is 18;3) you estimate red field area（𝑇̂）by multiplying area of the target region (W) by
the ratio（𝑝̂ ＝𝑛𝑛1）.
18=> 𝑇̂ = 100 × 100ha = 18ha
12

Area of red fields in below picture is as same as that in the picture above,as you can divide the picture below to make the picture above.
Red fields’ area is 18ha (= 4ha + 8ha + 3ha + 1ha + 2ha).

2X2

2X4

1X1
2X3/2

1X2

(For more information)
I hope you understand that you can estimate a planted area of minor crops
or scattered field in a target region with the Dot Sampling Method.
With the Method, sample dots are selected in proportional to planted area.
Every dot has same probability, so the appearance ratio of each crop is to be
proportional to the planted area of the crop.
You only need to put the number of dots required for the survey. You learn
how to determine the number of sample dots in 4.7 of this Guidebook.
13

4.2 Four procedures for a planted area survey using the Dot Sampling
MethodProcedure

Instruction
Decide the number of sample dots.
Input density of sample dots (values of area and number

1

Put sample
dots onGoogleEarth.

of sample dots) in T-1 table of “LL Sheet for the dot
sampling”.
Input latitude and longitude in T-1 table for a range ofsample dots.
Click buttons according to the instruction on LL sheet.
Examine attributions of sample dots on Google Earth.

Conduct a
preparatory
2 survey on
GoogleEarthCategorize

attributionsofsample

dots

into

two

categories,
one is sample dots which you need to conduct a fieldsurvey to check if rice is planted or not, andanother category is sample dots which you don’t need to
conduct field survey.

Visit sample dots which you need to conduct a field
Conduct a3
survey and examine their attributions. You check whether
field survey
rice is planted or not at a spot of each sample dot.
Estimate4

rice
plantedarea

Estimate rice planted area by using the formula below:
̂ = 𝒏𝟏 × 𝑾 = 𝒑̂𝑾𝑻𝒏

4.3 Let’s put sample dots on Google Earth for a rice planted area survey
You conduct a rice production survey using the Dot Sampling Method in thetarget region, Tsukuba Hamlet, near JICA Tsukuba International Center.
Please look at the figure below. The target region in the training is shownwith a red polygon. Area of the region is only 0.2 km2.

14

At first you put sample dots on Google Earth for a rice planted area survey.
In Chapter 2 you’ve already learnt how to put a certain number of dots on Google
Earth. Suppose you would like to put 80 sample dots in the target region, youopen a file “LL Sheet for the dot sampling”and input following data into T-1
table.

Note
1

Concerning the value of area of target region of (2), you have to get
it from other sources.

2

Concerning the number of sample dots required for value of (3), youhave to decide the number according to the calculation explained in
4.7 and available resources.

3

A purpose of inputting values of (2) and (3) is to determine dot
density or the number of dots per unit area.
15

4

The number of dots which are fallen in target region defined in (2) isalmost as same as the number of dots defined in (3) with highprobability, though it depends on the starting point of systematic
sampling.

5

Please remember you need to use decimal degrees for inputting
latitude and longitude.

6

Values from (4) to (7) determine a rectangle shape of range forputting dots.

After finishing filling in cells, you click on the buttons according to
instructions under the T-1 Table.

When “Save Range As KML File” appears, just click on Save KML File.

Click here

16

Finally, Google Earth begins to work and sample dots appear on Google
Earth automatically.

Please note that dots are put into rectangle form in a range surrounded by
input latitude and longitude. Target region must be covered by the rectangle
shape of dots.
Note: In the above case, the number of dots which are fallen in the target
region is 80 with high probability, because you put sampling dots witha density of 80 dots per 0.2 km2. Please note the actual number ofdots in the target region varies depending on a starting point ofsystematic sampling.

17

4.4 Let’s conduct a preparatory survey of a rice planted area survey on
Google Earth
A preparatory survey of a rice planted area survey on Google Earth is adesk work. You conduct a preparatory survey on Google Earth.
Now you conduct a preparatory survey:
1) You examine attribution of each sample dot on Google Earth in the target
region.
2) In this lecture, you use the following code as an attribution of eachsample dot.
Code1

Attribution

RemarkNon-cultivated land

The sample dot has clearly fallen
on non-cultivated land such as
forest, river, road, building.
You don’t need to visit the dot at
the time of a field survey.

2
3
9

Cultivated land

There is a possibility that the
Dyke (including, tree, rock, pool, sample dot has fallen on rice field.
You need to visit the dot at the timeborder etc.) in cultivated landof a field survey.
Unidentified land use

18

19

20

3) You fill in the table below.
Attribution

Code

Non-cultivated land

1

Cultivated land

2

Dyke ( including, tree, rock, pool, border etc.)
in cultivated land

3

Unidentified land use

9Number of
dots

Share

Total

1.000

Estimate
(ha)

20.0

(For more information)
COUNTIF, one of the statistical functions, helps you count the number of
each code on excel files.

=COUNTIF(C5:U20,Z5)
This function counts the number of cells with
Code1 (the value in Z5) in cells C5 throughU20. The result is 19.

21

The figure and table below show an example of the results of the
preparatory survey
You judge from the preparatory survey on Google Earth that 19 dots fell on
non-cultivated field such as forest, river, road, building which you don’t need tovisit at the time of a field survey.
You also understand that you have to visit remaining 61 dots out of 80 dots
to confirm whether dots fell on rice planted spots or not.
0

1

2

3

2

2

2

3

3

1

2

1

3

2

2

3

2

2

4

5

6

7

8

9

10

2

1

2

2

2

1

9

2

11

12

13

14

2

2

9

3

15

16

17

18

0
1

4
5

2

3

2

1

9

2

2

2

3

1

1

2

2

3

1

1

9

2

2

2

2

1

1

2

2

2

1

9

2

2

2

2

2

2

2

1

9

2

2

2

2

3

2

1

9

2

2

1

2

1

9

11

1

2

1

12

2

6
7
8
9
10

1

13

Attribution

Code

Number of
dots

Share

Estimate(ha)Non-cultovated land

1

19

0.238

4.8

Cultivated land

2

45

0.563

11.3

Dyke ( including, tree, rock, pool, border etc.)
in cultivated land

3

8

0.100

2.0

Unidentified land use

9

8

0.100

2.0

80

1.000

20.0

Total

22

4.5 Let’s conduct a field survey of a rice planted area survey on Google
Earth
A field survey of a rice planted area survey on Google Earth is not a desk
work. You visit sample dots of Code 2, 3 and 9 which have been categorized to
be visited for a field survey.
Now you conduct a filed survey as follows:
1) You make guide maps which lead you to the sample dots which havebeen classified as Code 2, 3 and 9 through a preparatory survey.
2) You bring guide maps and visit the sample dots.
3) You examine the attribution of each sample dot. Especially, you check
whether rice is planted or not at a spot of each sample dot.
4) In this lecture, you use the following code as an attribution of eachsample dot.
Code

Attribution1

Non-cultivated land

4

Dyke (including, tree, rock, pool, border etc.) in rice field

5

Dyke (including, tree, rock, pool, border etc.) in field of crops otherthan rice

10

Unplanted field (in two years or more)

11

Unplanted field (temporarily)

12

Rice

13

Other crops

235) You fill in the table blow.

Attribution

Code

Non-cultivated land

1

Dyke (including, tree, rock,pool, border etc.) in rice field
Dyke (including, tree, rock,pool, border etc.) in other field
Unplanted field (more than 2
years)

4
5
10

Unplanted field (temporarily)

11

Rice

12

Other crops

13

Zone 124

Zone 2

Zone 325

Zone 4

(For more information)
In the lecture you conduct a field survey for a planted area survey. But inthe future, you might be able to conduct a field survey on a desk. It is a drone that
holds the key.
The Dot Sampling Method has a possibility to have affinity with a drone. It
is expected that a drone would take pictures of spots of sample dots automaticallyby storing coordinates of latitude and longitude of sample dots into a drone.

264.6 Let’s estimate rice planted area
Since you have finished a field survey for a rice planted area survey, thenext step is estimation of rice planted area.
Now you complete the table below:

Attribution

Number of
dots

Share

Estimated
Area

Variance

n = 80p

20×ｐp×(1-p)Standard
error

Precision
(%)

Code

Non-cultivated land

1

Dyke in rice field

4

Dyke in other crops'
field

5

Unplanted field(more than 2 years)

10

Unplanted field(temporarily)

11

Rice

12

Other crops

13

Total

80

1.000

𝑛
𝑝

20.0

Item

FormulaRice planted area
(𝑇̂)

̂=
𝑻

Standard error (SE)

𝒏𝟏
̂𝑾
×𝑾=𝒑
𝒏

𝐒𝐄 = √

Coefficient of variation
(CV)

̂×𝒒
̂
𝒑
𝒏
𝑺𝑬

CV= 𝒑̂

where
n: The number of total sample dots
𝑛1 : the number of dots which falls on rice planted spots
𝑾: area of the target region𝑝̂ ＝𝑛𝑛1𝑞̂ = 1 − 𝑝̂27

Error (ha)20 ×standard
error

Estimatedarea×
precision

The figure and the table below show the results of the field survey
conducted in 2017: rice planted area, precision and standard error are estimated
12.25ha, 8.9% and 1.1ha respectively.

0

1

2

3

2

1 12

1

3

1 12

1

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18

0
1

4

12
1

12 12

5

12 12 121

1 12 12 12 12

4 12 12

6

1

1 12

12 12

7

1

1

4

1 12 12 12 12

1

1

1

1

1 12 12 12 12 121

12 12 128

1

1 12 12 12 12 12 12 13

12 12

9

1 12 12 12 12 12

4 12

10

1 12 12 12

1 12

1 12

11

1 12

12

13

1

13

Attribution

Number of
dots

Share

Estimated
Area

Variance

n = 80p

20×ｐp×(1-p)Standard
error

Code

Precision(%)
𝑛𝑝Error (ha)20 ×standard
error

Estimatedarea×
precision

Non-cultivated land

1

26

0.325

6.50

0.2194

0.052

16.1

1.0

1.0

Dyke in rice field

4

3

0.038

0.75

0.0361

0.021

56.6

0.4

0.4

Dyke in othercrops' field

5

0

0.000

0.00

0.00000.000#DIV/0!

0.0#DIV/0!

Unplanted lfield(more than 2 years)

10

0

0.000

0.00

0.00000.000#DIV/0!

0.0#DIV/0!

Unplanted field(temporarily)

11

0

0.000

0.00

0.00000.000#DIV/0!

0.0#DIV/0!

Rice

12

49

0.613

12.25

0.2373

0.054

8.9

1.1

1.1

Other crops

13

2

0.025

0.50

0.0244

0.017

69.8

0.3

0.3

80

1.000

20.00

0.0000

0.000

0.0

0.0

0.0

Total

28

4.7 How to determine the number of sample dots for a preparatory survey
Now, you learn how to determine the number of sample dots for a
preparatory survey of a planted area survey using the Dot Sampling Method.
Two factors for determine the number of sample dots:#1 aimed precision#2 coefficient of variation (CV) of population
Note1: You estimate population CV using results of past survey or pretest,
as you cannot get a value of population CV at the time of survey,
Note2: A size of a target region does not matter to determine the number ofsample dots.
The formula of the number of sample dots required for a preparatory survey
is as follows.
The number of sample dots required for a preparatory survey＝(𝒑𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏 𝑪𝑽)𝟐
𝒂𝒊𝒎𝒆𝒅 𝒑𝒓𝒆𝒄𝒊𝒔𝒊𝒐𝒏 𝟐
)
𝟏𝟎𝟎

（

or
（𝒑𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏)𝟐＝（𝒂𝒊𝒎𝒆𝒅 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒆𝒓𝒓𝒐𝒓)𝟐

where
population CV =√𝑝×(100−𝑝)𝑝𝑝 % = share of rice planted are in a target region
CV % = aimed precision
population standard deviation = √𝑝 × (100 − 𝑝)𝐶𝑉
aimed standard error = 𝑝× 100
Note: The number of sample dots mentioned above is for a preparatory
survey which is more than the number of dots to be visited at the timeof a field survey. At the time of a field survey, you only visit the sample
dots which have been categorized to be visited.

29

Let’s calculate the number of sample dots required for a preparatory survey
in Tsukuba Hamlet using the formula above, though you have distributed 80
sample dots in the lecture.
Suppose you know the share of rice planted area in Tsukuba Hamlet isabout 60 % according to a pretest already conducted and you want the resultswith 10% precision, the number of sample dots required for the planted area
survey is as follows:(𝒑𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏 𝑪𝑽)𝟐
（𝒂𝒊𝒎𝒆𝒅 𝒑𝒓𝒆𝒄𝒊𝒔𝒊𝒐𝒏)𝟐

or

=

(

2
√60×(100−60)
)
60
10 2

(

100

= 67

)

（𝒑𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏)𝟐（𝒂𝒊𝒎𝒆𝒅 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒆𝒓𝒓𝒐𝒓)𝟐=(√60×(100−60)
(60×

10 2
)
100

2

= 67

Note: A size of a target region does not matter to determine the number ofsample dots. Suppose you know the share of rice planted area incountry Z is about 60 % and you want the results with 10% precision,
the number of sample dots required for the planted area survey incountry Z is 67.

30

The table below shows the number of sample dots required for a
preparatory survey calculated by the formula above.
The Number of Sample Dots Required by Aimed Precision
for a Preparatory Survey
Share ofrice planted field
in a target region
Share = p%

Aimed Precision
CV = 3%CV = 5%CV = 10%1

110,000

39,6009,900

254,444

19,6004,900

335,926

12,9333,233

426,667

9,600

2,400

5

21,111

7,600

1,900

6

17,407

6,267

1,567

7

14,762

5,314

1,329

8

12,778

4,600

1,150

9

11,235

4,044

1,011

10

10,000

3,600

900

20

4,444

1,600

400

30

2,593

933

233

40

1,667

600

150

50

1,111

400

100

60

741

267

67

70

476

171

43

80

278

100

25

90

123

44

11

Note: Calculation fomulas are as follows:
Sample size for Preparatory Survey =

(𝑝 𝑝
(

𝑛

𝑛
𝑛

𝑝
𝑝
× 1−
100
100
=
𝑝
×
100 100

31

𝑛)
)
=

𝑝 × 100 − 𝑝𝑝×100Precision by the Number of Sample Dots for a Preparatory Survey
Share ofrice planted
field
in a target
regionp%

100 dots

200 dots

500 dots

1000 dots

5000 dots

10000 dots

0.5

141.1

99.7

63.1

44.6

19.9

14.1

1

99.5

70.4

44.5

31.5

14.1

9.9

2

70.0

49.5

31.3

22.1

9.9

7.0

3

56.9

40.2

25.4

18.0

8.0

5.7

4

49.0

34.6

21.9

15.5

6.9

4.9

5

43.6

30.8

19.5

13.8

6.2

4.4

6

39.6

28.0

17.7

12.5

5.6

4.0

7

36.4

25.8

16.3

11.5

5.2

3.6

8

33.9

24.0

15.2

10.7

4.8

3.4

9

31.8

22.5

14.2

10.1

4.5

3.2

10

30.0

21.2

13.4

9.5

4.2

3.0

15

23.8

16.8

10.6

7.5

3.4

2.4

20

20.0

14.1

8.9

6.3

2.8

2.0

30

15.3

10.8

6.8

4.8

2.2

1.5

40

12.2

8.7

5.5

3.9

1.7

1.2

50

10.0

7.1

4.5

3.2

1.4

1.0

60

8.2

5.8

3.7

2.6

1.2

0.8

70

6.5

4.6

2.9

2.1

0.9

0.7

80

5.0

3.5

2.2

1.6

0.7

0.5

90

3.3

2.4

1.5

1.1

0.5

0.3

Precision by the Number of Sample Dots (%)

Note: Calculation are as follows:
Precision =𝑛𝑝

x 100 (%)

Standard Error =wheren = number of sample dots
p = Share of rice planted field in a target region32

(For more information)
The table on the next page shows the number of sample dots (theoreticalvalues) required for a field survey by aimed precision.
According to the table, the number of sample dots for field survey doesn’t
increase so sharply as those for preparatory survey, when the value of 𝑝 become
smaller. This is one of characteristics of the Dot Sampling Method. You can keephigh precision with small number of sample dots for a field survey.
The formula of the number of sample dots required for a preparatory survey
is as follows.
The number of sample dots require for a field survey= the number of sample dots required for a preparatory survey ×𝑝
100

Let’s calculate the theoretical number of sample dots required for a fieldsurvey in Tsukuba Hamlet using the formula above.
The theoretical number of sample dots require for a field survey is around60
40 (= 67× ), as the number of sample dots required for a preparatory survey is
100
67 with 10% precision and the share of rice planted area is about 60 %.
Note: At the time of field survey, you need to visit all sample dots which havepossibilities to fall on rice planted spots, so the number of sample dots
you have to visit is somewhat more than theoretical value shown in
the next table.

33

The Number of Sample Dots Required by Aimed Precision
for a Field Survey (theoretical values)
Share ofrice planted field
in a target region
Share = p%

Aimed Precision
CV = 3%CV = 5%CV = 10%

1

1,100

396

99

2

1,089

392

98

3

1,078

388

97

4

1,067

384

96

5

1,056

380

95

6

1,044

376

94

7

1,033

372

93

8

1,022

368

92

9

1,011

364

91

10

1,000

360

90

20

889

320

80

30

778

280

70

40

667

240

60

50

556

200

50

60

444

160

40

70

333

120

30

80

222

80

20

90

111

40

10

Note: Calculation fomulas are as follows:
The number of dots for a field survey = Sample size for a preparatory survey ×

Sample size for a preparatory survey =

(𝑝 𝑝
(

𝑛

𝑝
𝑝
× 1 − 100100=𝑝
100 × 100

34

𝑛
𝑛

𝑛)

)

=

𝑝 × 100 − 𝑝
𝑝 × 100𝑝100

4.8 Let’s conduct a preparatory land use survey in your country
Let’s enjoy putting sample dots in your country and conduct a preparatory
survey of a land use survey using the Dot Sampling Method.
In the lecture, follow the procedure below:
1) You put 100 dots in your country on Google Earth.
2) You examine the attribution of each sample dot.
3) You use the following code as an attribution of each sample dot.
Code

Attribution

Remark1

Non-cultivated land

The sample dot has clearly fallen
on non-cultivated land such as
forest, river, road, building.
You don’t need to visit the dot at
the time of a field survey.

2

Cultivated land

There is a possibility that the3

Dyke (including, tree, rock, pool, sample dot has fallen on rice field.
You need to visit the dot at the timeborder etc.) in cultivated landof a field survey.
Unidentified land use

9Note: You can add other categories such as forest, road, lake, residential land, if
you need.
3) You fill in the table below.

Attribution

Code

Non-cultivated land

1

Cultivated land

2

Dyke ( including, tree, rock, pool, border etc.)
in cultivated land

3

Unidentified land use

9

Total

Number of
dots

Share

1.000

35

Estimate(ha)One example of a preparatory survey is shown below. A staff member of thegovernment of Lao PDR conducted the land use preparatory survey during the
JICA training course 2014 in Japan. A target region is Savannaket prefecture
whose area is 2,177,400ha.

source： Mr.Senpachanh Khounthikoummane, Lao PDR, August, 2014

He put hundred sample dots in Savannaket prefecture. The results werethat the number of sample dots which have some chance of falling on rice field
was ten.
Preparatory survey has examined only spots which have possibility of rice
field and you need to conduct a 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. Don’t
you think the results of preparatory survey is somewhat similar to official
statistics?

36

One more example of a preparatory survey is shown below. This example
was conducted by Mr.Issei Jinguji. He put 999 sample dots in Thailand

37

Source: Issei Jinguji, Dot Sampling Method for Area Estimation, Feb. 2014
The results of the preparatory survey conducted by Mr. Jinguji are as
follows:
Total number of sample dots is 999.
The number of sample dots on rice field is 184 and the number of sample
15

dots on dyke of rice field is 31. The ratio of rice planted area is 21.5% (= 999).
In actual survey, next step is conducting a field survey to visit each sample
dot to check and after a field survey you calculate the rice planted area. So you
cannot calculate the rice planted area from the results of a preparatory survey,
but you could calculate the rice planted area from the results of the preparatory
survey as an experiment as follows:
Rice field area including dyke is calculated to be 11,043,000 ha, as the ratioof rice field is 21.5 % and national land area is 51,312,000ha.
Please compare 11,043,000ha with official statistics 10,400,000ha. Don’t
you think the results of preparatory survey is somewhat similar to official
statistics? You can get results of the preparatory survey without resources in ashort time on Google Earth, though the government has get official statistics using
lots of monetary and human resources.
38

4.9 Let’s use dots as a two-dimensional ruler for measuring area
Let’s learn how to use the Dot Sampling Method as a two-dimensional ruler
for measuring area.
In the lecture, you put one dots per 10a. You open a file “LL Sheet for the
dot sampling” and input data as follows:
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

JICA1dot=0.1ha

0.001

Starting point Starting point(latitude)(longitude)(4)

1

36.032451(5)

140.1226

Finishingpoint(latitude)(6)

36.026

Finishingpoint(longitude)(7)

140.1329

In above case, each dot represents 10a. If you count the number of dots ina target region, then the area is calculated by 10a times the number of dots in atarget region. For example, if the number of dots within a target area is 10, area
is estimated 1ha or (10a x 10 = 100a).
You can measure area by counting the number of dots. You can use dots
as if dots are divisions on a scale. You can measure area by counting the numberof dots as same as you measure length by counting number of divisions on a39

scale.
You’ve already learnt the way to use the Dot Sampling Method as a twodimensional ruler or a ruler for measuring area.

(For more information)
Some of you may have been already familiar with Dot Grid Plate which is atransparent film with printed points arranged in grid pattern. Putting a Dot Grid
Plate on map, you count the number of points which are on target area andestimate the area by multiplying the number and coefficient (=area per one point)
together.
You can apply area estimation method with a Dot Grid Plate to the Dot
Sampling Method as a two-dimensional ruler.

40

4.10 Comparison of process for a rice planted area survey using the Dot
Sampling Method between the first year and the next year
You can conduct a rice planted area survey in the second year more
efficiently than in the first year. Firstly, you can use same sample dots as the firstyear. Secondly, you know which sample dots have fallen on non-cultivated land
from the survey in the first year.
The followings are the comparison of process for a rice planted area survey
using the dot Sampling Method in the first year and the next year:
First YearTo
Central Officer

Next Yearputsampledotson (No need to put sample dots)

GoogleEarthfora To use same samples as the

preparatory survey.

previous year.

To examine attribution of (NoCentral Officer

need

to

examineeach sample dot on Google attribution)
Earth.
To decide sample dots for a To decide sample dots for a
field

surveywhichhave fieldsurvey

which

have

possibility to fall on rice fields possibility to fall on rice fields
Central Officer

from the preparatory survey.

considering the results of theprevious

year

and

other

information such as newly
irrigated field,
To print out maps around To print out new sample dots,
sample dots for a field survey only when sample dots are

Central Officer

to guide enumerators to visit newly

categorized

intothem and send guide maps to sample

dots

field

enumerators.

survey.

Note: Instead of printing out
maps, you could send KML
file to enumerators.
41

for

a

To find sample dots using a To find sample dots, only
guide maps sent by a central when previous year’s sample
Enumerator

officer.

dots are newly categorized
into sample dots for a fieldsurvey.

To visit a sample dot for a (As same as the first year)
Enumerator

field

surveyandcheck

whether rice is planted or not.

42

Chapter 5 Yield Survey
In this chapter, you learn the concept of rice yield survey. You select sample
spots for a crop cutting using the Dot Sampling method.
5.1 Concept of Yield Survey
Please remember the package of a production survey mentioned in 3.2:

Total production of rice in the target region=
Average yield of rice in the target region
X
Total planted area of rice in the target region
The purpose of a rice yield survey and the method you use in the lecture is
as follows:
Item

Explanation

RemarkYou estimate average
Purpose of a rice yield
yield of rice
surveyin Tsukuba Hamlet.
You use a crop cutting It is an objective survey
method.
method.
Method you use

You also use the Dot You can dramaticallySampling Method
streamline the process
to select samples for of selecting samples.
crop cutting.

Major advantages of applying the Dot Sampling Method to a yield survey is
as follows:
No.

Advantages

1

You can select sample spots for crop cutting,even when you don’t have any information on rice planted area of eachvillage or you don’t have a list of farmers in the village.

2

You can select sample rice field with perfect probability proportional to43

size,
as a spot which a sample dot falls on is exactly a crop cutting spot withprobability proportional to size.
3

You can conduct crop cutting not only at a spot which a sample dot falls
but also at other spots around the spot in a prearranged way.

4

You can avoid complicated sampling process for selecting a crop cutting
spot.

5

You can estimate average yield by simple average without taking into
account a size of a rice filed for crop cutting sample,
as fields for crop cutting are selected with probability proportional to size

6

You can rotate sample dots without difficulty,
as you can select samples easily with the Dot Sampling Method.

Note: For crop cutting, you need to select sample fields with probability
proportional to size.
With a conventional method, you are supposed to select spots for crop
cutting in a way such as: 1) you have to calculate accumulated rice plantedarea of villages and select villages with probability proportional; 2) you makea list of farmers of selected villages, and systematically select farmers fromthe list; 3) you select fields of selected farmers systematically; 4) you selectspots for crop cutting.
Even with a conventional method, it is difficult to select sample field
precisely with probability proportional to size.
5.2 Three procedures for a Rice Yield Survey using the Dot Sampling
MethodProcedure

Instruction

Remark1

Select sample spots
for crop cutting.

This is a core part of yield survey.
In the training you learn the Dot
Sampling Method to selectsample spots.

2

Cut rice, thresh, cleanse,
dry and weigh.

In the lecture, you neglect the
moisture of rice because oflimitation of time.

3

Estimate an average yieldof rice in a target region445.3 Let’s select sample spots for crop cutting
At first, you need to calculate a size of a sample for crop cutting.
Suppose you know that the coefficient of variation of rice yield in Tsukuba
Hamlet is about 18% from the past data and you want to get data with 10%
precision, the sample size is as follows:

The number of samples =(𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝐶𝑉)2

（𝑎𝑖𝑚𝑒𝑑 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛)2

182＝ 102 ≒ 4

Secondly, you need to select sample spots for crop cutting with probabilities
proportional to size. In the lecture, you are going to use the Dot Sampling Method
so that you can select sample spots for crop cutting with probabilities proportional
to size. You don’t need to prepare a list of farmers with planted area in Tsukuba
Hamlet for selecting sample rice fields.
In the lecture, we select 6 sample spots for crop cutting using the Dot
Sampling Method. You are divided into 3 groups. Each grope conducts crop
cutting for 2 sample spots.
Let’s select 6 sample spots.
Suppose you know the results of a planted area survey and 49 dots out of
80 dots fall on rice planted spots, you extract six sample dots for crop cutting at
random out of 49 dots (Code No12 in the figure below) using systematic sampling
method.

If you haven’t conducted a planted area survey with the Dot Sampling
Method but conducted in other way, you can use an alternative way.
45

Suppose you know that area of rice field in the target area is 0.1225 km2,
you fill in necessary data in “LL Sheet for the dot sampling”.
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

JICA 6 (0.1225)

0.1225

Starting point Starting point(latitude)(longitude)(4)

6

36.032451

46(5)140.1226

Finishingpoint(latitude)(6)

36.026

Finishingpoint(longitude)(7)

140.1329

5.4 Let’s cut rice, thresh, cleanse, dry and weighIn the lecture, you cannot conduct crop cutting at spots you selected
randomly in 5.3, as you have not got permissions from 6 farmers. In the lecture,
you use Mr. Ogawa’s rice field that JICA has got permission already. This means
you cannot calculate the average yield of JICA Hamlet in the lecture, but please
say that the results are the average yield of Tsukuba Hamlet as a makeshift.
Let’s select sample spots in Mr. Ogawa’s rice field as follows:
T-1 Basic data to generate sample dots (Sampling Design)
Target area

Size of theTarget area km2

Sample size

(1)

(2)

(3)

0.0043

JICA Ogawa

Starting point Starting point(latitude)(longitude)(4)

6

36.032451(5)

140.1226

Finishingpoint(latitude)

Finishingpoint(longitude)(6)

36.026(7)140.1329

Before conducting a rice yield survey, you prepare equipment for crop
cutting as follows:
Equipment

Remark1

Guide Map

Guide map leads you to crop cutting spots.

2

Questionnaire

You collect related information from a farmer.

3(Rice crop Cutting Survey Form)

Crop
(1m2)

cutting

frame You thresh the sample rice within a crop cutting
frame.
47

4

SickleYou use a sickle for cutting rice.

5

Sheet

You thresh the sample rice on a sheet.

6

Winnower

You use a winnower to cleanse the sample rice.

7

Bag

8

Label

9

Balancebasket(1kg)

You use a bag for carrying the sample rice to alecture room.
You put a label into a bag for identifying thesample rice.
and You put the sample rice in a basket and weigh thesample rice in a basket.

10 Calculator

You calculate yield with a calculator.

11 Manual for crop cutting
Let’s go to the field where a sample dot falls on.
You conduct crop cutting as follows:
Procedure
1
2
3

Activity
You interview a farmer using a questionnaire or Rice Crop Cutting
Survey Form.
You visit a sample dot spot and conduct crop cutting using 1m2
frame at a spot.
Note that you harvest the sample rice with normal attention or ina same way as a normal farmer does.
You thresh the sample rice on a sheet and cleanse the threshedsample rice with winnower.

4

You put the sample rice into a bag with a label.

5

You carry the sample rice to a lecture room.

6

You dry the sample rice to a defined moisture content.
In the lecture, however, you ignore moisture content because oftime restriction.

7

You measure the weight of the sample rice.

8

You fill in Rice Crop Cutting Survey Form with the results.

48

Rice Crop Cutting Survey Form
Sample name

Province

Pefecture

District

village

Crop Season

HamletEnumerator

Tel:

Name of Farmhoushold(Interview Items)
Total area ofcultivated land (ha)Date of interview:
total rice planted area
(ha)

Area of sample field(ha)irrigation of rainfed
1 irrigation
2 Rainfed
3 Upland

VarieyShapeNameGlutinous

1 Short2 Midium
3 LongOrganic
fertilizer

Planting
date

Havestingdate

1 Very bad 2 Bad
3 Normal 4 Good
5 Very good

1
Glutinous
2 Others
ChemicalFertilizer

Pesticide

Grwing condition

caltivating HarvestingmachineMchinePlanting method
1 seeds broad casting
2 Transplanting
3 Upand panting

Reason of bad
conditon or very bad
conditon

Quantity ofseeds perha (kg)1 Disease 2 Insect
3 Drought
4 Heavy rain

Purpose Techinicalof rice assistanceproduction
from

Estimatedyeild in thisyear (t/ha)

Yield inlast year(t/ha)

1 Used1 Used1 Used1 Used1 Used1 Commerce
2 Not used 2 Not used 2 Not used 2 Not used 2 Not used 2 Not for sale

(Crop Cutting Yield Survey)

Date of survey:

Itemresult of crop cutting(1) Weight of cleaned&dried rice (g)g/(1mx1m)(2)Yield per ha (t) = (1)/100

t/ha

Memo

49

5.5 Let’s estimate an average yield of rice in Tsukuba Hamlet
You can estimate an average yield in Tsukuba Hamlet with simple averageof samples. You don’t need to take into account a size of rice field for each sample,
as each sample has been selected with probability proportional to size.
The table below shows a format to calculate a sample mean, sample
variance, sample standard error and sample CV.
Sample number（n = 6）

No1

Symbol𝑖−

Yield(t/ha)

𝑖−

1

No2
No3
No4
No5

5

No6

6

Total

𝑖 −

𝑖

Sample mean
（EstimatedYield）

=

1
𝑛−1

𝑖 −

=
=

Item
Sample variance

SymbolFormula
1
𝑛−1

× 100

Results𝑖−

Samplestandard
deviation
Samplecoefficient ofvariation(%)

50

Let’s estimate an average rice yield in Tsukuba Hamlet.
An average yield in Tsukuba Hamlet is estimated to be a sample mean:
=

∑ 𝑖
𝑛

A standard error of an average yield is calculated by the formula bellow:
𝑠2

=√ 𝑛
when

Sample meanvariance1=𝑛−1 ∑( 𝑖 − )𝑛Standard error(sample error)
Sample meancoefficient ofvariation(%)

51

A table below shows the results of the yield survey conducted in 2017 at
JICA Hamlet: trainees selected six sample spots for conducting crop cutting. The
results are: average yield is 8.88t/ha, precision is 4.98%, sampling error is 0.44t.
Sample number（n = 6）

No1

SymbolYield(t/ha)

𝑖−

𝑖−

9.21

0.33

0.11

No2

8.77

-0.11

0.01

No3

8.77

-0.11

0.01

No4

10.59

1.71

2.93

1

No5

5

7.21

-1.67

2.78

No6

6

8.72

-0.16

0.03

Total

𝑖

Sample mean
（EstimatedYield）

𝑖 −

53.27
8.88

=

1
𝑛−1

5.87
1.17

𝑖 −

1.08

=
=

Item
Sample variance

Symbol× 100

Formula
1
𝑛−1

12.21

Results
1.17

𝑖−

Samplestandard
deviation

1.08

Samplecoefficient ofvariation(%)

12.21

Sample meanvariance
Standard
error (sample
error)

𝑛

0.20
0.44

Sample meancoefficient ofvariation(%)

4.98

52

(For more information)
Alternative Way for Selecting Sample Spots for Crop Cutting
In case that you don’t know the Dot Sampling Method, alternative crop
cutting survey design is shown as follows. Please note that you need to prepare
list of farmers to select sample spots with probability Proportional to size.
In following case, the target region or the estimation unit is District and there
are dozens of villages in a District.
(1) Sampling frame
The sampling method for rice yield survey is “Two Stage Sampling”.
Villages are used as the Primary Sampling Unit (PSU). Farm
households in the sample villages are used as the Secondary Sampling
Unit (SSU).
(2) The number of samples and sample allocation
You decide the number of PSUs is 10 villages per District and thenumber of SSUs is 2 farm households per village.
(3) PSU sampling
Concerning PSU sampling, you use the PPS method or the probability
proportional sampling to size of planted area. At first, you need to makea list of villages in a District. And then you select sample villages using
the PPS method.
(4) SSU sampling
Concerning SSU sampling, you apply systematic random sampling. At
first, you need to make a list of farm households in a sample village. And
then you select sample farm households using a random table.
(5) Selecting a sample field of each sample household
You select sample fields at random. At first, you need to make a list offields of each sample farm household. And then you select a sample
field of each sample household using a random table.
(6) Selecting sample spots in each sample field
You select two sample spots at random in each sample field. At first, you
select a starting point to so select a sample spot. And then you select a53

sample spot using, say, 30 paces method in the sample field. The
second starting point is decided at the opposite point on the field.

(For more information)
The followings are the selecting 2 samples spots by using 30 paces methodin the sample field written by Mr.Issei Jinguji.
Put number at each corner in sample field, then select a corner byusing Random table.
②

③

①

④

Walk to the next corner from the corner counting paces.

③

②

④

①

54

Decide the first starting point to walk 30 paces based on thepaces by using Random table.

The second starting point isdecided at the opposite point on the dyke.
③②

The first starting point

①

●

④

Source: Mr.Issei Jinguji, Rice Crop Cutting Survey, December 2007

55

Chapter 6 Production Survey
In this chapter, you learn the concept of a production survey and make areport on the results of the survey.
6.1 Let’s compile the results of a rice production survey
Let’s remember the formula below, which you have already learnt in
Chapter 3 Package of Crop Production Survey.

Production survey = Yield survey + Area survey
You have already conducted a rice planted area survey and a rice yieldsurvey in Chapter 4 and chapter 5.
The time has come at last for you to estimate the value of rice production in
Tsukuba Hamlet. You multiply average yield of rice in Tsukuba Hamlet and total
planted area of rice in Tsukuba Hamlet together.

Total production of rice in Tsukuba Hamlet=
Average yield of rice in Tsukuba Hamlet
×
Total planted area of rice in Tsukuba Hamlet

Let’s conduct a production survey.
The formula of a production survey
̂=𝑿
̅×𝑻
̂
𝒀
where 𝑌̂: Total Rice production in Tsukuba Hamlet: Estimated Average Yield of Rice from the Yield Survey
𝑇̂: Estimated Rice Planted Area from the Planted Area
Survey56

Precision of estimated total rice production

𝑪𝑽𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 = √𝑪𝑽𝟐𝒚𝒊𝒆𝒍𝒅 + 𝑪𝑽𝟐𝑷𝒍𝒂𝒏𝒕𝒆𝒅 𝑨𝒓𝒆𝒂

Yield （ｔ/ha）

Planted area (ha）Production （ｔ）

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

Production= Yield ×Area

Estimation
C.V. （％）

Survey Method

A table below shows the results of the rice production survey in Tsukuba
Hamlet conducted in 2017: production of rice in the target region and theprecision are estimated 109t and 10.2% respectively.

Yield （ｔ/ha）

Planted area (ha）Production （ｔ）

Estimation

8.88

12.25

109

C.V. （％）

4.98

8.9

10.2

Survey Method

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

Production= Yield ×Area

In the lecture, it took two days for you to conduct a rice production survey:
one day for a rice planted area survey and one day for a rice yield survey in57

Tsukuba Hamlet. Isn’t it amazing to conduct a production survey in such a shorttime? In traditional ways, you need considerable days to conduct a production
survey, because you need to make a list of farmers to select sample farmers,
fields and spots for crop cutting. Now you can enjoy conducting area survey indramatically short time with the Dot Sampling Method.

58

6.2 Let’s make a rice crop production report
The last stage of a survey is for you to make a report of the results of thesurvey. In the lecture, you write a brief report on the rice production in Tsukuba
Hamlet for a press release and hold a press conference.
An example of report form is shown below.
(Example of Report Form)

Rice Production in Tsukuba Hamlet 2018
JICA Training: Planning and Designing of Crop Production Surveys
Press conference: 9:45am on 29 August, 2018
Reporter: Ms. Gozaimasu Ohayou
Results:
Production
Planted Area
Yield per ha

Comments:

Statistical Methodology:
Survey Procedure
Estimating Procedure
Reliability59

(For more information)
The followings are USDA Report on crop production.

60

Chapter 7 Presentations on your Output from the Lecture
7.1 Let’s review the lecture
7.1.1 Crop Production Survey
You multiply average yield of rice in Tsukuba Hamlet and total planted areaof rice in Tsukuba Hamlet together in order to estimate the amount of riceproduction in Tsukuba Hamlet. You need to plan and design yield survey and area
survey together.
7.1.2 Planted Area Survey
You have learnt a planted area survey using the Dot Sampling Method. The
dot Sampling method has characteristics such that 1) its survey object is not a
person but a land, 2) it doesn’t require population composition, 3) it is easier tobe conducted, 4) non-sampling errors hardly occur, as it is not a variable survey
but an attribute survey.
There are four steps for an area survey using the Dot Sampling Method.
1) to put sample dots on Google Earth, 2) to examine attributions of sample dots
on Google Earth to classify sample dots into two categories, one is sample dots
which you need to conduct a field survey to examine their attribution and anotheris sample dots which you don’t need to conduct a field survey, 3) conducting afield survey to visit sample dots to check whether rice is planted or not at a spotof each sample dot, and 4) to estimate area.
7.1.3 Yield Survey
Purpose of a rice yield survey is to estimate average yield of rice in Tsukuba
Hamlet.
Crop cutting method is an objective survey method to estimate average
yield.
You can use the Dot Sampling Method to select samples for crop cutting.
With the Dot Sampling Method, you can dramatically streamline the process of
selecting samples.
Major advantages of applying the Dot Sampling Method to yield survey isthat you can select sample spots for crop cutting even when you don’t have a listof farmers or you don’t know rice planted area of each village. With the Dot
Sampling Method, a spot which a sample dot falls on is exactly a crop cutting
spot, as you can select a sample rice field with perfect probability proportional tosize.
7.2 Let’s make a presentation
On 29 August 2018, the last day of the lecture “Planning and Designing of
Crop Production Survey”, each of you make a presentation as an output of the
training.
The purpose of the presentation is:1) to make sure what you have learnt through the training,and2) to tell your colleagues what you learnt during the training.
61

The followings are examples of forms for summarizing what you have learnt
through the training.

Summary of the designing and Planning of Crop Production Survey
NameCountry
Planted Area Survey

purposeActivities

OutputImpression,
Suggestion

62

Name

Country
Yeild Survey

purposeActivities

OutputImpression,
Suggestion

63

Name

Country
Crop Production Survey

purposeActivities

OutputImpression,
Suggestion

64

Name

Country
OtherspurposeActivities

OutputImpression,
Suggestion

65

Before & After Analysis
Name

Country
Before Training

Planted Area
SurveyDot Sampling
MethodYield Survey
Crop Cutting

Crop
Production
SurveyYield
xPlanted Area

Presentation,
Others66

After Training

(Reference)
Team Dot Sampling, MAFF Japan: The Dot Sampling Method, 29 March 2016
JINGUJI, Issei: Comparison of FAOSTAT statistics and Dot Sampling survey
Estimates of the harvested area of oil palm in Indonesia, Malaysia andThailand, Kyoto University Academic Center for Computing and Media
Studies, July 2018
JINGUJI, Issei: Dot Sampling Method for area estimation, CROP MONITORINGFOR
IMPROVEDFOOD
SECURITY,FAO& ADB,
2015(http://www.fao.org/fileadmin/templates/rap/files/Project/Expert_Meeting__1
7Feb2014_/P11_Dot_sampling_method_for_planted_area_estimation_using_Google_eart
h___land_use_survey__FAO_RAP_17_Feb_2014.pdf)
JINGUJI, Issei: How to Develop Master Sampling Frames using Dot Sampling
MethodandGoogleearth,
December
2012(http://www.fao.org/fileadmin/templates/ess/global_strategy/PPTs/MSF_PP
Ts/5.MSF_Dot_sampling_method_on_Google_Earth_Jinguji.pdf)
KAMIKURA, Kenji: What you can do with the Dot Sampling Method using Google
Earth, Fifth meeting of the Regional Steering Committee for Asia and thePacific for the Global Strategy to Improve Agricultural and Rural Statistics
Bangkok, Thailand, 9 December 2015
KAMIKURA, Kenji: Package of Agricultural Production Survey, AfricaRice,
Cotonue, Benin, March 2013 (https://wpqr4.adb.org/LotusQuickr/agstatap/Main.nsf/0/6716E47F1793360B48257B5D002EC9F4/$file/Package%20
of%20Agricultural%20Production%20Survey.pdf)
KAMIKURA, Kenji: Estimation of Planted Area using the Dot Sampling Method,
FAO APCAS 24, October 2012(http://www.fao.org/fileadmin/templates/ess/ess_test_folder/Workshops_Ev
ents/APCAS_24/Paper_after/APCAS-12-21_Planted_Area_using_Dot_Sampling.pdf)
YATES, Frank: Sampling Methods for Censuses and Surveys, Charles Griffin &Co. Ltd., 1949
MAF & JICA, Lao PDR, 2007/2008 Rice Crop Cutting Survey, Capacity Building
Project for Strengthening of Agricultural Statistics System, December 200767