“it is a statistical operation for :
DESIGNING
COLLECTING
PROCESSING AND
ANALYZING
DISSEMINATING
Structure of Agriculture
• Size of holding
• Agricultural Household Information
• Land tenure
• Land use
• Crop Area Planted and Harvested
• Irrigation/Fertilizer/Phytosanitaries
• Livestock numbers
• Labour
•Other Agricultural Inputs
•Percentage of National GDP
BACKGROUND OF AGRICULTURE
CENSUS PROGRAMMES IN FIJI
• Three National Agriculture Censuses
have been conducted in Fiji over the last
four decades; NAC 1968, NAC 1978 &
NAC 1991
• Latest in 2009 NAC 2009
• All censuses were conducted by sample
with technical assistance from FAO
IMPORTANCE OF THE CENSUS
•
It provides benchmark data about the Agriculture Sector
in Fiji.
•
It establishes a basis for monitoring and evaluation that
are carried out in periodic surveys.
•
It provides information to help government and others
to make short-term decisions.
•
It provides valuable experience to the Agriculture
Officers who are involved in planning for, collection of
and processing of Agriculture Sector data.
RELATIONSHIP OF THE AGRICULTURE CENSUS TO THE
POPULATION CENSUS
•
In many developing countries, households and
agricultural farms are closely related because most
agricultural production activities are in the household
sector.
•
Common concepts, definitions and classifications are
used.
•
Population Census results used in Land use Stratification.
•
Population Census results are used as check data for
Agriculture Census results.
AGRICULTURE CENSUS SCOPE
• Broadly speaking, the Agriculture Census aims to measure
the composition of the agricultural production industry i.e.
extent of crops & livestock production
International Standard Industrial Classification
(ISIC)
• Group 011: Growing of crops; market gardening;
horticulture
• Group 012: Farming of animals
• Group 013: Growing of crops combined with farming of
animals (mixed farming)
OBJECTIVES OF NATIONAL
AGRICULTURE CENSUS
Overall Objective
• To improve the flow of reliable and convenient
statistical information on the Agricultural sector
• To strengthen the Fiji Agriculture Statistics System,
staff and methodology.
IMMEDIATE OBJECTIVES
• To conduct the 2009 NAC to provide a benchmark as an
objective criteria for planning and policy decisions in
sustainable agricultural and rural development;
• To strengthen and improve the Fiji Agriculture Statistics
System (FASS) in generating key agricultural data on a
consistent basis, with the results of the 2009 NAC as the
benchmark;
• To disseminate the statistical information in the form of
hard copy and digital reports.
METHODOLOGY
1.
Multiple Sampling Frame Methodology (MSF) was used. It combines Area Sampling Frame (ASF) and List
Sampling Frame (LSF).
•
•
•
•
Area Sampling Frame --- approximately 10% of area
List Sampling Frame -- 100% large /specialty farms
Basis for sampling ---- homogeneous land use
Basis for list – significant contribution to agricultural production –must be able to
identify
2.
Data are collected through on site farmer interviews - Reference periods (reference year /day of
interview)
3.
The ASF uses sample segments that define an area of 100 hectares in which all households are
interviewed.
4.
The LSF interviews all farms that are part of a list of large and special farms determined by their
contribution to the Agriculture Sector.
5.
The ASF process utilises the following steps:
•
•
•
•
Aerial photography
Construction of the ASF
Sample design and selection
Photo-enlargements for selected SMs
TYPES OF DATA
1.
Farmer (Holder*): identification, sex, age, education, race, religion,
marital status and occupation
2.
Farm (Holding*): legal status, type of farming (subsistence/commercial),
total land, land use, land tenure, type
3.
Temporary crops: planted, irrigated and harvested areas (in pure and
interplant stands)
4.
Permanent crops: planted, irrigated and productive age; age and number
of planted and bearing trees (in pure, mixed, interplant and associated
stands)
* International terms for farmer and farm are holder and holding.
5.
Number of scattered plants, trees and vines (planted and bearing)
6.
Types of pastures
7.
Livestock and poultry: number of cattle by sex, age and use (dairy, beef, non
dairy and non beef); small livestock
8.
Farm employment: with and without remuneration by sex, cash, kind,
farmer household demographics and participation in farm tasks
9.
Use of fertilizers: organic, inorganic, agro-chemicals
10. Farm management
ASF PROCEDURE
• Overlay FIBOS Census EA Maps on to Fiji Topographic Maps
• Numbering grids (1 km2) on maps in a serpentine manner by
strata
• Random selection of segments (Grids)
• Selected Grids overlaid onto aerial contact print
• Preparation of photo enlargements with relevant details
( Division, Province, District, EA Number, Strata)
• Lamination of photo enlargement
LSF PROCEDURE
• Compilation of list of major agriculture
holdings, specialized farms and
Research stations around the country
• Selection of all large farms
STRATIFICATION
• Classifying the FIBOS enumeration areas into various
homogenous land use strata. The utilization of land for
agriculture varies by geographic areas
• These areas are based on a fixed number of
households; all concentrations of households exist in
many EAs and their distribution is not homogeneous, it
became necessary to divide these EAs into more than
one stratum. It was also noted that the Government of
Fiji has identified certain areas as Protected Forest –
mahogany and pine forest areas are not for agricultural
activities. These areas were given a special stratum
identification and removed from the numbered grids.
POST STRATIFICATION
A sampling technique used to create strata after
the sample has been selected. If the sample was
already stratified, post-stratification can be used
to establish “further” strata within the actual
strata.
Post-stratification is used for an “adjustment” or
“correction” of the original estimation of
aggregates.
CLASSIFICATION OF STRATUM
ESTIMATED % OF
AREA
SM SIZE
(km2)
Areas cultivated from 70 to 100 % by temporary, and/or
permanent crops.
70-100 Crops
1
20
Areas cultivated from 30 to 69 % by temporary, and/or
permanent crops.
30-69 Crops
1
30
Areas cultivated from 10 to 29 % by temporary, and/or
permanent crops.
10-29 Crops
1
40
Areas covered from 91% to 100% by improved pastures
and unimproved native pasture (grazing lands).
91-100 Pastures
1
50
Areas covered totally by natural forest.
100 Forest
1
55
Areas covered with planted forest (Pine and Hardwood)
100 Forest
No Census
60
Non-Agricultural land
100 Non Agriculture
No Census
70
Urban and Peri-Urban areas
100 Cities, Towns
No Census
75
Small Island Districts with a few villages.
Village-scale Farming
Any Size
85
Special small areas cultivated by crops located only in few
places and List of important farms like big cattle or coconut
farms, where their boundaries were possible to be drawn
on maps (LSF Farms).
100 Special and
Complete Farms
Any Size
STRATUM
10
DEFINITION IN WORDS
Preparing for sample selection for the ASF
Homogeneous??
Numbering of the
grids
tikina
101
stratum
BA
10
20
30
40
60
70
102
10
20
30
103
10
20
30
60
70
104
30
105
10
20
30
70
106
10
20
30
40
50
60
90
20570.72
4593.06
11217.25
209.59
1504.15
295.62
38390.40
1086.12
10980.83
35623.44
47690.39
4349.84
2350.63
7194.87
3216.74
793.15
17905.23
20329.91
20329.91
10527.58
17019.43
22912.82
26.24
50486.07
10951.33
22153.46
25080.56
9885.01
3741.28
127.71
4159.34
76098.69
320910.27
16 552.61
9 230.21
5 903.65
209.59
349.65
295.62
32 541.34
1 086.12
10 980.83
35 623.44
47 690.39
4 445.89
2 311.44
6 392.63
1 949.50
781.43
15 880.90
6 326.28
6 326.28
10 527.58
17 019.43
22 912.82
26.24
50 486.07
9 905.24
21 968.47
21 392.52
9 885.01
3 741.28
124.19
3 580.98
70 597.70
270 527.95
samp segs
nonfarm segs
lsf farms
17
4
11
0
0
0
3
0
8
0
0
0
8
3
8
1
0
0
2
11
35
0
7
25
0
1
6
3
3
2
0
0
0
0
0
0
0
1
1
3
0
0
SIS
0
7
15
15
0
2
11
12
0
2
3
15
0
10
21
22
10
3
0
0
5
15
13
9
2
0
0
18
3
14
1
1
0
0
Strata combined
DATA PROCESSING
Refers to all steps for the following census questionnaires received at the
Data Processing Centre prior to tabulation of results.
 NAC Form 1 [Segment Questionnaire]
 NAC Form 2 [Farm Questionnaire]
 NAC Form 3 [Non-Farm Questionnaire]
The Manual
Processing
Machine
Processing
• manual review of the entries for
completeness and acceptability
• as well as coding some of the items
• Involves data entry, computer editing of
entries
• summarization of data according to
predetermined tabulation formats
PreProcessing
Phase
Enumeration
Review /Edit
Questionnaire
Manual
Processing
Phase
Data Capture
Phase
Consolidation
& Tabulation
Phase
Analysis and
Publication
Phase
Receipt
and
Control
Data
Encoding
Data
Aggregation
Generation
of Final
Tables
Completeness
Checking
Add
Weights
Coding/
Editing
Data
Cleaning
Consistency
Checking
Final
Analysis of
Tables
Consistency
Tables
Publication
Adjust
Weights /Data
Editing
PRE - PROCESSING PHASE
ENUMERATION
Household to household
collection of agricultural data,
through direct interview of
farmers in the ASF and LSF
frames
Locate ASF/LSF Farm(s)
• Identify physical boundaries from Topo Map,
Aerial Photo
• Demarcate Farm Tracts, fields within tracts
and non-farm areas within segments on aerial
photo enlargement
The Interview
• Enumerators interview farmers (persons
responsible for day-to-day farm activities) and
fill in questionnaire NAC forms 1, 2 and 3
REVIEW/EDIT QUESTIONNAIRE
Supervisors manually review all questionnaire NAC
forms 1, 2 and 3 for completeness, acceptability and
make necessary adjustments before they are
dispatched to operations office for processing
R&C Clerk
NAC Forms
from
Provinces
(START)
Coder/Editor
Data Entry Clerk
DPS
Data Editor
1. Receive docs from
provinces; Segregate, record
and arrange Forms
2. Inform DPS of submitted
forms
3. Assign SM to Coder
/Editor (C/E)..
4. Retrieve and give
questionnaires to C/E.
Record on DP Forms
7. Inform DPS of the
completion of edited
questionnaires in SM.
A
5. Review and edit
entries on the
questionnaires
6. Return
questionnaires to R&C
•NC •DPS •R&C •DEC •C/E •DE •SM -
National Consultant
Data Processing Supervisor
Receipt and Control
Data Entry Clerk
Coder/Editor
Data Editor
Segment
OUTPUT :
EDITED/CODED
DATA CAPTURE
DATA CAPTURE PHASE
DATA CLEANING
Type-in data is compared with the previously
encoded data and if there is a match, the
verification proceeds to the next data item.
Completeness Checking
Checks if encoded Geographic
Area IDs/codes are valid, i.e. the
IDs/codes assigned to the
questionnaire are on the list of
districts and if all sample areas
have encoded sample
households/questionnaires
Data Consistency Checking
The last step of the data
capture phase is checking the
completeness, correctness
and consistencies of data
items.
R&C Clerk
Coder/Editor
Data Entry Clerk
DPS
Data Editor
A
9. Retrieve and give SM
to DEC. Record on DP
Forms
12. Inform DPS of the
encoded SM.
8. Assign SM to Data
Entry Clerk (DEC).
10. Encode SM
questionnaires
NO
11. Return SM to R&C
All SM
encoded?
YES
13. Merge and backup Data.
14. Merge, back-up
data.
15. Run
completeness checks
Passed
completeness?
NO
YES
18. Run consistency
checks
•NC •DPS •R&C •DEC •C/E •DE •SM -
National Consultant
Data Processing Supervisor
Receipt and Control
Data Entry Clerk
Coder/Editor
Data Editor
Segment
Passed
consistency?
YES
B
16. Run
completeness
checks.
17. Run edit
program or edit and
back-up data.
19. Run consistency
checks.
NO
20. Runs edit
program, edits and
back-up data.
Economist
National Consultant
DPS
Data Editor
B
21. Run Add Weights
Program
28. Run Edit Program /
adjust weights
22. Generate consistency
tables programs.
26. Review tables, create
edit specs or adjust
weights
23. Back-up data, run
Tabulation programs,
and give the results to
National Consultant
27. Create Edit Program /
adjust weights
25. Review tabulation
program and generate
tables
NO
24. Are tables
consistent?
YES
30. Publish results.
END
29. Review final
Tabulations
•NC •DPS •R&C •DEC •C/E •DE •SM -
National Consultant
Data Processing Supervisor
Receipt and Control
Data Entry Clerk
Coder/Editor
Data Editor
Segment
DATA AGGREGATION
After all data files have been
certified to be free of errors,
the files are merged into
one big file in the database
CONSISTENCY TABLES
Consistency tables are generated
to find out if the resulting data are
acceptable, i.e., aggregates are not
deviating from the current situation
and are consistent with data
from other surveys.
ADD WEIGHTS
For surveys, computed weights will
be attached to each record and data
file will be reformatted to facilitate
tabulation.
DATA EDITING
Review questionnaires if
inconsistencies are discovered
when the consistency tables
are generated
OUTPUT :
ANALYSED
READY FOR
DISSEMINATION
ANALYSIS AND PUBLICATION PHASE
2009
Division
Central
Province
Naitasiri
Northern
1 261
7.4
2 255.32
2 115
12.5
1 258.29
2.7
Serua
1 812
10.7
5 195.94
11.3
4.9
6 279
37.0
16 685.05
36.3
Total
16 977
26.3
45 908.13
18.3
Ba
10 242
48.1
56 016.75
53.3
Nadroga
5 302
24.9
24 472.39
23.3
Ra
5 741
27.0
24 662.87
23.5
Total
21 285
33.0
105 152.01
41.9
Bua
3 972
20.1
14 324.65
15.1
Cakaudrove
7 712
39.1
33 046.22
34.9
8 040
40.8
47 284.44
50.0
19 724
30.6
94 655.32
37.7
Kadavu
2 288
35.2
1 676.14
30.7
Lau
1 724
26.5
2 414.44
44.2
Lomaiviti
2 281
35.1
1 112.40
20.4
Total
Rotuma
FIJI
% of
Total
% of Total
Farms
Farms Total Area (HA)
Area
5 511
32.5
20 513.52
44.7
Rewa
Macuata
Eastern
1991 NAC
Namosi
Tailevu
Western
NAC
209
3.2
262.24
4.8
Total
6 502
10.1
5 465.22
2.2
Total
64 488
251 180.68
DIVISION
AND PROVINCE
NUMBER
OF FARMS
%
TOTAL
LAND (Has)
%
CENTRAL
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
19062
7386
1101
2739
1470
6366
20
7.7
1.2
2.9
1.5
6.7
76719
30502
3510
5588
7567
29552
13
5.2
0.6
0.9
1.3
5
WESTERN
BA
NADROGA/NAVOSA
RA
43401
26340
10783
6278
45.5
27.6
11.3
6.6
269743
121697
101817
46229
45.6
20.6
17.2
7.8
NORTHERN
BUA
CAKAUDROVE
MACUATA
22402
3086
7926
11390
23.5
3.2
8.3
12
190039
34170
69467
86402
32.1
5.8
11.7
14.6
EASTERN
KADAVU
LAU
LOMAIVITI
ROTUMA
10535
2518
2864
4501
652
11
2.6
3
4.7
0.7
54906
6125
29492
15209
4080
9.3
1
5
2.6
0.7
TOTAL
95400
100
591407
100
2009
NAC
1991 NAC
NATURAL
FORESTS
PLANTED
FORESTS
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
21389
10510
549
1637
2018
6675
532
141
0
7
9
375
WESTERN
15355
2125
BA
12006
1412
1937
501
540
1084
48422
8005
23553
16864
3913
1839
88
1986
19172
2183
10754
4662
1573
1789
167
1195
419
8
104338
8359
DIVISION
AND PROVINCE
Division
Central
Province
Naitasiri
Namosi
Western
Northern
8.52
171.13
5.02
Serua
1 067.04
671.56
Tailevu
2 752.29
550.03
Total
8 786.81
1 302.04
Ba
5 849.47
269.06
Nadroga
2 298.04
289.20
Ra
3 205.56
256.49
Total
11 353.07
814.74
Bua
4 208.83
451.55
Cakaudrove
9 795.96
203.45
Macuata
7 144.26
188.86
21 149.05
843.85
Kadavu
106.37
5.08
Lau
157.07
3.24
57.50
0.00
Lomaiviti
Rotuma
FIJI
506.19
Rewa
Total
Eastern
Natural Forest
Planted Forest
4 290.15
66.90
11.29
0.00
Total
41 621.16
2 968.95
Total
15 524.52
14 791.36
CENTRAL
NADROGA/NAVOSA
RA
NORTHERN
BUA
CAKAUDROVE
MACUATA
EASTERN
KADAVU
LAU
LOMAIVITI
ROTUMA
TOTAL
2009
NAC
size of farm category
< 1 ha
% of Total Area % of Total
Farms
Farms
(ha)
Area
28 212
43.7 11 709.83
4.7
1 up to 3 ha
17 053
26.4 29 252.59
11.6
3 up to 5 ha
7 881
12.2 31 003.49
12.3
5 up to 10 ha
6 905
10.7 46 802.46
18.6
10 up to 20 ha
3 040
4.7 41 493.99
16.5
20 up to 50 ha
987
1.5 28 954.31
11.5
50 up to 100 ha
285
0.4 21 403.67
8.5
126
0.2 40 560.34
16.1
64 488
251 180.68
100 ha or more
FIJI
1991 NAC
SIZE OF FARMS (Has) NUMBER OF FARMS
0
0.1 - 0.9
1.0 - 2.9
3.0 - 4.9
5.0 - 9.9
10.0 - 19.9
20.0 - 49.9
50.0 - 99.9
100 and more
TOTAL
%
TOTAL LAND (Has)
%
13068
28252
17638
12276
12703
6332
3173
1407
551
13.7
29.6
18.5
12.9
13.3
6.6
3.3
1.5
0.6
0
11358
32000
49321
87283
85334
98141
95471
132499
0
1.9
5.4
8.4
14.8
14.4
16.6
16.1
22.4
95400
100
591407
100
2009
Division
Central
Western
Northern
Eastern
1991 NAC
Total
Farms
2011
Total
Livestock
19 671
Namosi
322
2 001
Rewa
146
867
Serua
624
4 267
Tailevu
1526
18 021
Total
4628
44 827
Ba
4655
19 962
Nadroga
2915
18 020
Ra
3233
19 648
Total
10803
57 630
Bua
1498
9 024
Cakaudrove
1082
8 855
Macuata
3779
12 650
Total
6359
30 529
10
276
Lau
177
642
Lomaiviti
137
346
Rotuma
42
162
365
1 426
22155
134 411
Province
Naitasiri
Kadavu
Total
FIJI
NAC
DIVISION AND
PROVINCE
NUMBER OF
FARMS
%
TOTAL CATTLE
%
CENTRAL
7679
17.9
75254
26.9
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
3249
344
304
690
3092
7.6
0.8
0.7
1.6
7.2
29311
3057
2504
6683
33699
10.5
1.1
0.9
2.4
12
WESTERN
25894
60.4
155239
55.4
BA
NADROGA/NAVOSA
RA
14492
6999
4403
33.8
16.4
10.3
68869
55286
31084
24.6
19.7
11.1
NORTHERN
8177
19.1
42787
15.3
BUA
CAKAUDROVE
MACUATA
1149
1423
5605
2.7
3.3
13.1
8604
14756
19427
3.1
5.3
6.9
EASTERN
1039
2.5
6941
2.5
KADAVU
LAU
LOMAIVITI
ROTUMA
187
365
250
237
0.4
0.9
0.6
0.6
610
4265
1253
813
0.2
1.5
0.4
0.3
42789
100
280221
100
TOTAL
2009
FARMERS
NAC
male
female
% male
% female
TOTAL
% of
TOTAL
10-19 yrs
592
28
.9%
.0%
620
1.0%
20-39 yrs
20 534
318
32.3%
.5%
20 852
32.8%
40-59 yrs
29 966
1 162
47.1%
1.8%
31 128
48.9%
60 yrs and older
10 217
805
16.1%
1.3%
11 022
17.3%
Total
61 309
2 313
96.4%
3.6%
63 622
100.0%
1991 NAC
DIVISION AND
NUMBER OF FEMALES
PROVINCE
FARMS
%
MALES
%
CENTRAL
18600
669
3.6
17931
96.4
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
7193
1062
2650
1423
6272
231
24
134
97
183
3.2
2.3
5.1
6.8
2.9
6962
1038
2516
1326
6089
96.8
97.7
94.9
93.2
97.1
WESTERN
42750
2763
6.5
39987
93.5
BA
NADROGA/NAVOSA
RA
26137
10352
6261
1981
421
361
7.6
4.1
5.8
24156
9931
5900
92.4
95.9
94.2
NORTHERN
22032
1335
6.1
20697
93.9
BUA
3026
98
3.2
2928
96.8
CAKAUDROVE
7726
213
2.8
7513
97.2
MACUATA
11280
1024
9.1
10256
90.9
EASTERN
9906
90
0.9
9816
99.1
KADAVU
LAU
2457
2481
21
39
0.9
1.6
2436
2442
99.1
98.4
LOMAIVITI
ROTUMA
4319
649
22
8
0.5
1.2
4297
641
99.5
98.8
TOTAL
93288
4857
5.2
88431
94.8
2009
1991 NAC
NAC
DIVISION &
PROVINCE
Division
Central
Province
Naitasiri
Namosi
Western
.00
.00
Rewa
72.34
66.93
Serua
3.68
3.68
Tailevu
147.62
147.62
Total
227.60
222.18
Ba
139.65
121.76
11.56
11.31
200.24
198.18
Nadroga
Ra
Total
Northern
351.44
331.24
Bua
3 208.76
2 614.01
Cakaudrove
9 564.73
9 494.48
354.44
344.22
13 127.93
12 452.71
.00
.00
1 684.19
1 681.32
47.88
21.84
Macuata
Total
Eastern
Kadavu
Lau
Lomaiviti
Rotuma
FIJI
Coconut Area
Coconut Area
Planted (Ha)
Bearing (ha)
3.96
3.96
85.49
82.08
Total
1 817.55
1 785.23
Total
15 524.52
14 791.36
COCONUT(Has)
PLANTED PRODUCTIVE AGE
CENTRAL
1800
1686
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
115
3
571
5
1106
71
3
545
5
1062
WESTERN
1458
636
623
326
509
287
8
341
14313
12954
2101
9361
2851
1926
8649
2379
EASTERN
11415
6314
KADAVU
LAU
LOMAIVITI
ROTUMA
421
8082
2200
712
360
4650
812
492
28986
21590
BA
NADROGA/NAVOSA
RA
NORTHERN
BUA
CAKAUDROVE
MACUATA
TOTAL
2009
NAC
1991 NAC
DIVISION &
PROVINCE
Division
Central
Province
Naitasiri
Namosi
Western
37.71
16.72
146.16
108.05
Tailevu
136.37
48.73
Total
489.19
271.79
Ba
489.19
271.79
Nadroga
405.48
188.46
Ra
463.19
247.12
1 357.86
707.36
989.44
494.90
6 159.13
740.52
515.48
257.62
7 664.05
1 493.04
717.94
141.70
Bua
Macuata
Total
Kadavu
Lau
FIJI
100.66
Serua
Cakaudrove
Eastern
317.09
Rewa
Total
Northern
Yaqona Area
Yaqona Area
Planted (Ha)
Harvested (ha)
763.99
375.44
75.97
31.44
Lomaiviti
367.45
119.26
Rotuma
12.47
2.39
Total
1 173.83
294.79
Total
11 597.06
3 144.79
YAQONA(Has)
PLANTED HARVESTED
CENTRAL
914
56
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
504
119
39
63
189
14
19
0
13
10
WESTERN
600
24
BA
NADROGA/NAV
OSA
RA
132
0
218
250
23
1
NORTHERN
1298
107
BUA
CAKAUDROVE
MACUATA
359
664
275
32
41
34
EASTERN
933
71
KADAVU
LAU
LOMAIVITI
ROTUMA
143
150
638
2
2
9
60
0
TOTAL
3745
258
2009
NAC
1991 NAC
DIVISION &
PROVINCE
Division
Province
Central
Naitasiri
Namosi
Rewa
Serua
Tailevu
Total
Ba
Nadroga
Ra
Total
Bua
Cakaudrove
Macuata
Total
Kadavu
Lau
Lomaiviti
Rotuma
Total
Total
Western
Northern
Eastern
FIJI
Rice Area
Planted (Ha)
1.12
0.00
0.00
0.00
19.44
20.56
19.85
15.14
17.84
52.82
606.43
0.09
2 943.80
3 550.32
0.00
0.00
0.00
0.00
0.00
3 623.70
Rice Area
Harvested (ha)
0.72
0.00
0.00
0.00
0.93
1.65
18.44
2.31
6.65
27.39
598.03
0.00
2 227.52
2 825.56
0.00
0.00
0.00
0.00
0.00
2 854.60
RICE (Has)
PLANTED HARVESTED
CENTRAL
3082
2622
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
523
3
167
1196
1193
421
3
87
1040
1071
WESTERN
1377
1151
BA
NADROGA/NAVOSA
RA
385
694
298
357
534
260
NORTHERN
7217
5869
BUA
CAKAUDROVE
MACUATA
1432
177
5608
1346
160
4363
EASTERN
0
0
KADAVU
LAU
LOMAIVITI
ROTUMA
0
0
0
0
0
0
0
0
11676
9642
TOTAL
2009
1991 NAC
NAC
DIVISION &
PROVINCE
Division
Province
Central
Naitasiri
Namosi
Rewa
Serua
Tailevu
Total
Ba
Nadroga
Ra
Total
Bua
Cakaudrove
Macuata
Total
Kadavu
Lau
Lomaiviti
Rotuma
Total
Total
Western
Northern
Eastern
FIJI
DALO Area
Planted (Ha)
4 369.67
447.95
243.09
500.13
1 776.87
7 337.71
335.67
476.43
1 293.42
2 105.52
974.87
3 592.53
439.27
5 006.67
408.46
89.62
258.61
40.85
797.54
15 247.45
Dalo Area
Harvested (ha)
2 419.31
224.02
112.86
249.30
930.41
3 935.90
150.43
195.57
599.56
945.56
332.57
1 254.16
134.32
1 721.06
152.86
29.41
65.66
12.85
260.78
6 863.30
DALO (Has)
PLANTED HARVESTED
CENTRAL
3378
1280
NAITASIRI
NAMOSI
REWA
SERUA
TAILEVU
2376
237
254
134
377
993
44
60
53
130
WESTERN
877
193
BA
NADROGA/NAVOSA
RA
258
289
330
34
68
91
NORTHERN
373
123
BUA
CAKAUDROVE
MACUATA
59
151
163
11
38
74
EASTERN
917
214
KADAVU
LAU
LOMAIVITI
ROTUMA
78
401
293
145
13
67
76
58
TOTAL
5545
1810
OTHER OUTPUTS – DEPARTMENT OF AGRICULTURE AND FIJI
ISLAND BUREAU OF STATISTICS
•A STUDY OF THE AGRICULTURE,
FORESTRY AND FISHERIES
INDUSTRIES AFF_2008_Report_Final
On-Going
Fiji National Statistical System
(FASS)
2012
OBJECTIVES FOR THE IMPROVEMENT OF THE
EXISITING AGRICULTURE STATISTICS SYSTEM
An agriculture statistics system should be
responsive to change in order to meet data
requirements of users.
Fiji Agricultural
Statistics System (FASS) are task to collect,
process, analyze and disseminate those data
and information in the quality, reliability and
timeliness desired by users. The needs of
users for statistics should be met within the
constraints of available resources.
Encourage to integrate this agriculture statistics
system with the Fiji Island Bureau of Statistics
(FIBoS) offices, working towards a statistical
system that is responsive to the needs of the
users.
OBJECTIVES FOR THE IMPROVEMENT OF THE EXISITING
AGRICULTURE STATISTICS SYSTEM
[Cont’]
To consider the importance of NAC 2009 within the
framework of the national statistics system, in terms
of the use of information about the agricultural
sector and as one of the three sources (agricultural
census, periodic sample survey and administrative
data) of the agricultural data.
Continue to strengthen the agriculture statistics
system by building up national capacity in terms of
permanent staff and advanced training for
undertaking agricultural censuses and sample
surveys
To be receptive to current development in statistical
methodology, data processing and analysis
systems and opportunities for training and
manpower development.
a GPS is .................
 a Global Positioning System
 ....it allows you to determine
your position using positioning
satellites. It can be used to update
maps, which are stored in a GIS.
DEMAND DRIVEN APPROACH & LIST
SAMPLING FRAME GPS LOCATIONS
PROVINCE: Tailevu
DISTRICT: Sawakasa
DEMAND DRIVEN APPROACH GPS
LOCATIONS
PROVINCE: Lomaiviti
DISTRICT: Gau
LIST SAMPLING FRAME GPS LOCATION
PROVINCE: Lomaiviti
DISTRICT: Ovalau
AGRICULTURE MAPING
SOPAC – 2011 - 2012
GIS ACTIVITIES
MAPPING COVERAGE
7 MAJOR ISLANDS IN FIJI
•
•
•
•
•
•
•
Viti Levu
Vanua Levu
Ovalau
Gau
Koro
Taveuni
Kadavu
AIM
To produce a landuse/ cover map of the seven major islands
of Fiji with the major focus on agriculture.
OBJECTIVES
1. To map all the Agriculture areas of the seven main islands.
2. To produce a raster map of the mapped areas
3. To calculate the area of the different mapped land use/
cover types
METHODOLOGY
VISUAL INTERPRETATION
Elements of image interpretation
• Tone or colour
• Texture
• Shape(recognition of an object)
• Pattern(mixture of colour and shape
• Knowledge of interpreter
PROCESSES
IMAGE RECTIFICATION
The process of making raw digital image confirming to a projected map
coordinate system.
IMAGE ENHANCEMENT
The process of controlling the brightness of the image to have a better
contrast between forest cover and non forest.
DIGITISING OF ALL THE LANDUSE TYPES IN THE IMAGE
To polyganize or delineate all land use that you can interpret on the image
CREATION OF THE RASTER MAP
There are two main type of spatial data storage – vector & raster layer.
All digital image are stored in raster data format. Most modern map
plotters convert vector data to raster data before printing it on paper.
ANALYSING AND CALCULATION OF AREAS – Yet to be done
COMPLETED MAP SHEETS
•
•
•
•
•
•
L27
L28
L29
M27
M28
M29
DATA SETS
ALOS IMAGE
DATA (NATURAL
COLOUR
COMPOSITE)2007
ALOS IMAGE_2007
(INFRA RED BAND)
IKONOS IMAGE_2002
QUICK BIRD Image
FLIS- Base Map
Digitized agriculture layer
on the alos image
FORESTRY VEGETATION COVER
OVERLAYED WITH DIGITIZED
LANDUSE
DISSEMINATION WORKSHOP
• 6- 4-2011-3
Thank you for your contributions
to the agricultural sector of Fiji.
We appreciate your support and
interest in better information for
decision-making. It is our goal to
provide you with what you need
within the constraints of our
resources.