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 American Journal of Agricultural Science, Engineering and Technology 

AJASET, ISSN: 2158-8104 (Online), 2164-0920 (Print), Vol. 1, Issue 1 39

ZONING FOR RAMBUTAN USING GEO-INFORMATICS IN CHANTHABURI 
PROVINCE, THAILAND 

Yupa Limsawad1, Chalongchai Babpraserth1*, Thunya Taychasinpitak1 and Sununtha Kingpaiboon2 

ABSTRACT 

Agro-economic zoning of agricultural commodity is undertaken in accordance with the 

objectives of the agricultural economic act B.E. 2522.  The objectives are to adjust 

rambutan production suitable for area potential as well as to increase efficiency of 

production system, processing and marketing to be in high stability, and to increase 

competitiveness in the world market. The methodology is to apply new technology, so 

called Geo-informatics, as a tool for agro-economic zoning.  This technology including 

geographic information system-GIS, remote sensing-RS, and global positioning system-

GPS has been proven and effective tool for spatial rambutan production zoning and 

planning. The analysis for potential level of rambutan production zoning is undertaken 

by integrating the map of area suitability for rambutan production obtained from land 

allocation suitable for production target with important economic factors effecting to 

production system.  The factors are : commodity demand and supply, production target, 

production source, production cost, farm gate price, production capability, and plant 

location (for processing factory) at district level.  Percentage of weighting and other 

conditions are different for each factor. The result obtained in this step is map 

illustrating potential level for rambutan production zoning.  The potential is devided 

into 2 levels including production potential area level 1 and production potential area 

level 2.  

Keywords: Zoning, Spatial Production Planning, Geo-informatics, Rambutan, Chanthaburi Province 

1 Department of Horticultural, Faculty of Agriculture, Kasetsart University, Bangkok 10900, Thailand. 
agrccb@ku.ac.th 
2Department of Agricultural Engineering, Faculty of Engineering, Khonkaen University, Khonkaen, 40002, 
Thailand.  



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INTRODUCTION 

The rambutan ( Nephelium lappaceum) is a medium-sized tropical tree in the family Sapindaceae. The 

fruit produced by the tree is also known as "rambutan." It is native to Vietnam, Indonesia, the 

Philippines, Sri Lanka, Malaysia, and elsewhere in Southeast Asia, although its precise natural 

distribution is unknown. It is closely related to several other edible tropical fruits including the lychee, 

longan, and mamoncillo. It is believed to be native to the Malay Archipelago, from where it spread 

westwards to Thailand, Burma, Sri Lanka and India; eastwards to Vietnam, the Philippines and 

Indonesia. The name rambutan is derived from the Malay word rambutan, meaning "hairy". In 

Vietnam, it is called chôm chôm (meaning "messy hair") due to the spines covering the fruit's skin. 

Thailand is the leading producer of rambutan in the Asian region with about 330,720 rai and 

307,342 metric ton (2011). Production is concentrated in the provinces of Chanthaburi, Trad, Rayong, 

in the east and Nakhonsithammarat, Suratthani, Narathiwat, and Chumphon, in the south and Chiangrai, 

Nan, in the north. Peak harvest season is between May and July. In recent years, many rambutan 

plantings in the Chanthaburi area have been replaced by para rubber and oil palm trees due to 

overproduction, high postharvest costs and low return. Market and price situation in 2011 is highly 

trend due to continuous demand of consumption  both in local and foreign market. Average price is 

between 14 Baht to 16 Baht /kg. Main export market is Vietnam, Cambodia, Hongkong, Singapore, and 

Malaysia. In 2012 expected that local consumption and export fresh rambutan fruit are more trend 

because of  continuous increasing  in production and foreign market consumption. 

One of the mandates of the Office of Agricultural Economics-OAE, defined in the Agricultural 

Economic Act B.E. 2522, is to study, analyse factors related to agricultural production.  The factors 

include : suitability of production source based on soil type, weather condition ; water supply ; farm 

type ; farmer’s main income ; and domestic and external market demand.  Those factors are used for 

agro-economic zoning of agricultural commodity, and then submit to the Committee on Agriculture and 

Cooperatives Policy and Development Plan. 

So far, the agro-economic zoning for agricultural commodity was undertaken for 13 commodities 

including 12 crops and 1 livestock. They are sugarcane, oil palm, major rice, second rice, corn, cassava, 

pineapple, soybean, rubber, durian, longan, and coffee. However, various circumstances have been 

changed.  The Committee therefore set up the Sub-committee on Zoning and Implementation Measure 

Consideration to review and renew the agro-economic zoning by using new technology so called Geo-

informatics.  The technology including Geographic Information System-GIS, Remote Sensing-RS, and 

Global Positioning System-GPS.  GIS is a new technical methodology using computer for spatial data 



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collection, archival, and management.  This method provides accurate and reliable 

spatial information such as position of target places.  The results can therefore be effectively applied for 

spatial planning. 

In addition, the establishment of the existing zones was mainly directed by the government. Even 

though many measures were launched to encourage farmers to produce in accordance with the 

production guidance in each zone such as farmer registration and provision of incentives through 

various projects, fewer farmers were interested to register and participate in this program. Furthermore, 

the supporting activities and measures provided by government and others parties were not well 

coordinated. This is mainly due to the lack of concrete plan that can harmonize the activities of 

concerned parties and provide sufficient incentives to farmers. 

Thus, Zoning  for rambutan using Geo-informatics in Chanthaburi Province, Thailand is the case study 

that can be done and used in appropriate database management both in production and market for local 

and export include by product in related industry.  Established spatial production planning which link to 

development strategic plan for Thai Fruits B.E. 2010-2014. These, Thailand  will be the leader of 

rambutan, tropical agriculture fruit crops,  production  and export fresh fruit and by product in the world 

market. Integration with spatial data and socio-economic for utmost efficiency utilization in agricultural 

development planning.  

For the studies of land suitability for crops, Ceballo-Silva and Lopez-Blanco 2003 applied multicriteria 

evaluation (MCE) approach, GIS and RS to delineate suitable areas for the production of maize and 

potato crops in Toluca, Central Mexico. Data included in the analysis were climate, relief and soil 

databases, which were used to generate GIS raster coverage. Relevant criteria for crops and suitability 

levels were defined according to FAO standards, and criteria maps were introduced in the MCE 

algorithm to obtain the suitability map for each crop. Landsat TM image in 1996 were processed using 

supervised classification to obtain land use/land cover (LU/LC) map, which showed 13 land use/land 

cover types. After that, LU/LC and suitability maps were compared to identify a suitable area for maize 

and potato crops. 

Musekawat 2004 applied remote sensing and GIS as tools for spatial data analysis toward the zoning 

and management of land use in tambon Bang Khunsai, Phetchaburi province, Thailand. Aerial 

photographs taken in 1994 and 2002 were interpolated to detect changing in land use and land cover 

pattern of the study area. 

Srirattanatum 1988 used biophysical factors of topography, soil, vegetation, wildlife, water resources, 

accessibility and aesthetics to identify management zones at Tarutao National Park, Thailand by using 

manual overlay techniques. 



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Trisurat 1990 applied Linear Combination Method of multiple criteria of eight bio-physical factors to 

create management zones in Phu Rua National Park in northeastern part of Thailand. Each factor was 

ranked and weighted based on its suitability for each zone. 

The objective of this research was to define and adjust agricultural production suitable for area 

potential. Those will lead to agro-economic zoning in Chanthaburi Province, Thailand. To increase 

efficiencies of production system, processing, and marketing of agricultural commodity. 

MATERIALS AND METHODS 

The methodology is to apply new technology, so called Geo-informatics, as a tool for agro-economic 

zoning. This technology including Geographic Information System-GIS, Remote Sensing-RS, and 

Global Positioning System-GPS has been proven and effective tool for zoning on rambutan and 

planning. Materials and equipments are composed of  workstation, external hard disc, satellite data, 

color printer, and topological map 1:50,000. 

The methodology for zoning on rambutan production is to study on present crop production system and 

land allocation suitable for production target. The step show on  Figure1.  

Figure 1. Show the step on using GIS to analyse potential production area. 

Data conversion 
Data conversion  from the existing map into digital format by compiling such maps from relevant 

agencies.  In case that some thematic maps are not available or obsolete, the up-to-date maps will be 

produced by Office of Agricultural Economics (OAE). The converted relevant maps include: 

1.) Provincial soil properties map, at a scale of 1:50,000 obtained from the Land Development 

Department (LDD), of which comprises soil properties for the whole country. 

2.) Irrigation map obtained from the Royal Irrigation Department (RID) comprises both irrigation and 

non-irrigation zones. 



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3.). Average rainfall map obtained from the Department of Meteorology of which 

average rainfall is ranging into 10 levels including:  

(1) Rainfall of 1,000-1,100 mm.

(2) Rainfall of 1,100-1,200 mm.

(3) Rainfall of 1,200-1,400 mm.

(4) Rainfall of 1,400-1,600 mm.

(5) Rainfall of 1,600-2,000 mm.

(6) Rainfall of 2,000-2,400 mm.

(7) Rainfall of 2,400-2,800 mm.

(8) Rainfall of 2,800-3,200 mm.

(9) Rainfall of 3,200-4,400 mm.

(10)Rainfall of 4,400-5,000 mm.

4.) Forest legal boundary map, at a scale of 1:50,000 obtained from the Royal Forestry Department, of 

which includes both inland forest and mangrove boundaries.  Inland forest is categorized into 2 zones:  

- Economic forest boundary

- Conserved forest boundary

Mangrove land use is categorized into the following zones: 

1. Conservation zone represents the mangrove area prohibited for any change to conserve the

environment and ecosystem.  The zone includes 10 categories namely:

1.1 Areas for breeding of economic plant and aqua-animal. 

1.2 Areas for breeding of plant and aqua-animal. 

1.3 Areas prone to destruction and soil erosion including beach, sand dune, mud flat, accreted 

mud flat, accreted sand, island, cave and coral reef. 

1.4 Areas of history and archeology significance. 

1.5 Areas of local symbol. 

1.6 National park, forestry park, tourism spot, wildlife sanctuary, and hunting prohibited zone. 

1.7 Forest areas reserved for fire protection. 

1.8 Forest areas suitable for research. 

1.9 Forest areas suitable for environment and ecosystem conservation. 

1.10 Areas of the distance not less than 20 meters from river banks and not less than 75 meters 

from coast lines 

2. Economic zone includes 2 categories namely:

2.1 Economic zone A includes the mangrove areas allowed for forestry activity especially to 

provide regular production.  They are namely: 

2.1.1 Concessioned forest area and forest under project area.  

2.1.2 Unconcessioned forest area suitable for social forestry. 

2.1.3 Forest plantation area for forest products of both government and private sectors. 



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2.2 Economic zone B includes mangrove areas allowed for other land utilize 

and development. However, environmental impacts are to be taken into consideration.  The area 

includes:  

2.2.1 Agricultural area for the following purposes: 

2.2.1.1  Crop cultivation 

2.2.1.2  Livestock 

2.2.1.3  Fisheries 

2.2.1.4  Salt pan 

2.2.2 Industrial area includes 

2.2.2.1 Mining 

2.2.2.2. Industrial Factory 

2.2.3 Urban area 

2.2.4 Commercial area 

2.2.5.   Sea port 

2.2.6  Others 

5.) Road network map, at scales of 1:1,000,000 and 1:250,000 obtained from the Department of 

Highway and the Royal Thai Survey Department, includes: 

5.1 Road comprises: 

-Highway with number

-Provincial road with number

-Road under the Office of Accelerated Rural Development

-Dirt road, and etc.

5.2 Railway 

5.3 Road along irrigation canal 

6.) Administrative boundary map, at a scale of 1:50,000 obtained from the National Statistical Office, 

and the Royal Thai Survey Department includes: 

6.1 Province boundary 

6.2 District boundary  

6.3 Sub-district boundary  

6.4 Locations of province, district and sub-district offices 

7.) Present land use map, at a scale of 1:50,000 obtained from 2005 satellite image interpretation by 

OAE, includes the following categories: 

Land use Type Code 
1. Paddy field Ri 
2. Paddy under trees (agro forest) Ri /Tr 
3. Field crops

3.1 Single crops
 Cassava 

Up 

Ca 



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AJASET, ISSN: 2158-8104 (Online), 2164-0920 (Print), Vol. 1, Issue 1 45

 Sugarcane 
 Corn 

       Pineapple 
 3.2 Mixed crops 

Su 
Co 
Pi 
Up 

4. Horticultural crops
4.1 Special Orchard

 Rubber 
 Oil palm 
 Coconut 
 Coffee 
 Orchard 

 4.2 Mixed orchard 
 Mixed orchard 
 Resident orchard 

Ru 
Pa 
Ce 
Cf 
Or 

Or 
Or/ Ur 

5. Tree crops (Standing trees)
5.1 Trees along the road or riverene  trees
5.2 Standing trees in the village

Tr 
Tr 

6. Forest
6.1 Inland forest
6.2 Mangrove
6.3 Swamp forest / bog
6.4 Forest plantation (Pine, Eucalyptus, Teak)
6.5 Idle land

Fo 
Ma 
Fs 
Fp 
Id 

7. Pasture
7.1 Grass land
7.2 Swamp grass

Gs 
Sw 

8. City, Village Ur 
9. Other land uses

9.1 Shrimp farm
9.2 Salt pan
9.3 Fish pond
9.4 Others

Sh 
Sa 
Fi 
Ot 

10. Water body Wa 
11. Barren land Ba 

Data Analysis 
Data analysis was carried out by using GIS and oracle software under WINDOW NT operating 

system the steps are follows: 
1) Project construction and database establishment to integrate spatial information, obtained

from digital map, and attribute information so called topology. 
2) Data analysis was undertaken by overlaying of multi-layer spatial information.  The data

includes: 
2.1 Soil series were categorized, in accordance with suitability condition, into 3 levels namely: 

1.represents high suitability for rambutan  cultivation
2.represents moderate suitability for rambutan cultivation
3.represents unsuitability for rambutan cultivation

2.2 Rainfall map was categorized into 4 levels namely: 
1. The rainfall of high suitability for rambutan.
2. The rainfall of moderate suitability for rambutan.
3. The rainfall of marginal suitability for rambutan.
4. The rainfall of unsuitability for rambutan.

2.3.Overlaid the rainfall map onto the irrigation zone and soil 
series maps to obtain the map of suitability area for rambutan including: The map of suitability area for 
rambutan was then overlaid onto the present land use map and forest legal boundary map to remove the 
undesirable areas including conserved forest, water body, and others. 

2.4.Calculate the suitability area for rambutan in Chanthaburi 
Province and  district , Thailand 



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Suitability analysis 
The results comprise 2 types of information: map and level of rambutan suitability area which was 
ranged into 7 levels. They are:  

1. High suitability area
2. Moderate suitability area
3. Unsuitability area
4. Existing forest area
5. Deteriorated forest area
6. Water body
7. Residential, city, and other built up areas.

Agro-economic zoning analysis 

Section 1.01 To analyze rambutan agro-economic zoning using main data as follow: 
Spatial data 

GIS was applied for the analysis of rambutan suitability area in Thailand by overlaying of soil map, 

rainfall map, and irrigation map.  By such a procedure,  The undesirable areas such as conserved forest, 

urban area, water body and etc. were removed.  Rambutan suitability areas were then categorized, based 

on the boundary of Chanthaburi Province, into 3 levels: high, moderate and unsuitable.  Administrative 

boundary of Chanthaburi Province, district and sub-district, and communication network were also 

overlaid onto the rambutan suitability area map in both paper print at a scale of 1:50,000 and digital 

formats. 

Socio-economic data 
-Study and analyze demand and supply of rambutan both of domestic and foreign market

include factory production needed. 
-Analyzing and forecasting rambutan production and price level, cost, transportation

expenditures and income return from farmer to factory. 
-Rambutan production data in 1 years (2011) by district or Amphoe.
-Rambutan canned factory and quantity were located with GPS show about latitude-longitude to

the earth. 
-Production and trade policy data of rambutan and canned factory between Thailand and

relevant  organization. Figure 2. 

Figure 2. Show the step on using GIS to analyse spatial data for rambutan zoning. 



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RESULTS AND DISCUSSION 

Analysis of area suitability the spatial data map are analysed on area plysical suitability for crop 

planting based on the boundary of Chanthaburi Province, Thailand.  Area calculation and production of 

area physical suitability map is undertaken by overlaying administrative boundary on to the suitability 

map.  Area for each suitability level can then be obtained and analysed to define agro-economic zone 

for rambutan in this step. The items to be studied are such as production source, production quantity, 

market demand both domestic and external markets, market future trend, and production target suitable 

for rambutan such as production target defined in agricultural commodity strategic plan. 

The analysis for potential level of rambutan production zoning is undertaken by integrating the map of 

area suitability for rambutan production obtained from land allocation suitable for production target 

with important economic factors effecting to production system.  The factors are : commodity demand 

and supply, production target, production source, production cost, farm gate price, production 

capability, and plant location (for processing factory) at district level.  Percentage of weighting and 

other conditions are different for each factor. 

The results of  analysis for rambutan zoning  in  Chanthaburi Province, Thailand show that 

correlation analysis of physical factor and economic factor with 3 variables such as: suitable 

area, existing planted area and product yield. The result obtained in this step is map illustrating 

potential level for rambutan production zoning.  The potential is devided into 2 levels including 

production potential area level 1 and production potential area level 2. Production potential 

area level 1 or zone1  refers to suitable area more than  10,000 rai , Existing area more than  5,000 rai , 

Yield more than 1,000 kilogram per rai. Production potential area level 2 or zone 2 refers to  suitable 

area more than  1,000-9,999 rai , Existing area between  1,000-4,999 rai , Yield between 500-999 

kilogram per rai. Weight analyse for zoning among suitable area : existing area : yield related to ratio  30 

: 40 : 30 respectively as  show on table 1.   

 Table 1. Correlation Analysis of Physical Factor and Economic Factor 

Potential 
Production 

Suitable Area 
(rai) 

Existing 
Planted Area 

(rai) 

Product 
Yield 

 (kg. / rai) 
level 1 suitable>10,000 >5,000 >1,000

level 2 suitable>1,000-9,999 1,000-4,999 500-999

weight (%) 30% 40% 30% 

From the results map of land suitability for rambutan in Chanthaburi province which define and group 

into 5 levels, namely, highly suitable, moderately suitable, unsuitable, forest, and water as show on 



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figure 3. These will lead to map of zoning for rambutan in Chanthaburi province 

when analyse with socio-economic data via weight and score for each variable by overlaying technique. 

The results map of zoning for rambutan in Chanthaburi province show production potential area level 1 

or zone1 by principal and condition  as laid out in 8 amphoe which respect to highly suitable area 

and exiting planted area include yield. They are Mueang Chanthaburi, Kaeng Hang Maeo, Laem Sing, 

King Amphoe Khao  Khitchakut, Khlung, Tha Mai, Na Yai Am, Makham, except 2 amphoe of Pong 

Nam Ron, and  Soi Dao that state on production potential area level 2 or zone2  as show on figure 4 and 

table 2. 

Figure 3. Map of land suitability for  Figure 4. Map of zoning for rambutan 
 rambutan in Chanthaburi province  in Chanthaburi provinc 

ACKNOWLEDGEMENTS 

The researcher would like to thank Department of horticulture, Faculty of agriculture, Bangkhen 

campus, Kasetsart University, and Office of agricultural economics for funding and providing materials 

with equipment in this research. 

Mutant 
Mutant 



                     American Journal of Agricultural Science, Engineering and Technology 

AJASET, ISSN: 2158-8104 (Online), 2164-0920 (Print), Vol. 1, Issue 1 49

Table  2. Zoning For Rambutan in Chanthaburi Province  

Province /Amphoe 

Suitable Area (rai) Existing 
Yield 

Zone 

Analyse Zoning Area Existing Planted Area 
(rai) 

Highly Moderately 

Planted 
Area Highly Suitable Moderately Suitable 

(rai) (kg./ra) level 1 level 2 
level 

0 level 1 level 2 
level 

0 level 1 level 2 
leve
l 0

Mueang Chanthaburi 29,591 11,281 5,790 1,042 1 29,591 11,281 5,790 
Kaeng Hang Maeo 0 77,981 24,659 627 1 0 77,981 24,659 
Laem Sing 58 12,439 30,709 1,526 1 58 12,439 30,709 
Pong Nam Ron 66,643 18,518 850 443 2 66,643 18,518 850 
King Amphoe Khao  
Khitchakut 77,145 30,235 16,283 1,263 1 77,145 30,235 16,283 
Khlung 38,682 64,439 860 1,473 1 38,682 64,439 860 
Tha Mai 118,813 16,283 624 741 1 118,813 16,283 624 
Na Yai Am 11,414 55,545 2,886 1,769 1 11,414 55,545 2,886 
Makham 39,253 65,352 4,938 1,257 1 39,253 65,352 4,938 
Soi Dao 0 12,233 24,309 1,589 2 0 12,233 24,309 
Chanthaburi  Total 381,599 364,306 111,908 262 314,957 66,643 0 333,555 30,751 0 86,749 25,159 0 
Remark 
Rambutan 30 : 40 : 30  Weight analyse For Zoning among Suitable Area:Existing area :Yield related to ratio  30 : 40 : 30 by order. 
Suitable area    Calculated from spatial map by Office of Agricultural Economics. 
Existing area    From Department of  Agricultural Extension by Amphoe. 
Yield            From Department of  Agricultural Extension by Amphoe. 
Zone 1           refers to suitable area more than  10,000 rai , Existing area more than  5,000 rai , Yield more than 1,000 kilogram per rai. 
Zone 2           refers to  suitable area more than  1,000-9,999 rai , Existing area between  1,000-4,999 rai , Yield between 500-999 kilogram per rai. 
Zone 0         No potential for zoning because lower than lever zone 2. 



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