Transcript PENGURUSAN PEROSAK BERSEPADU @ INTEGRATED PEST MANAGEMENT

Application of Geospatial Technology
in Advancing Oil Palm Industry
Wahid Omar
Malaysian Geospatial Forum
6-7th March, 2012
Introduction
 Geospatial technologies have be used for
evaluating, planning, verifying, monitoring
and applying of Good Agricultural Practices
in oil palm industry
 The technologies provide fast and precise
information for oil palm plantation
managements
 With the technologies, oil palm monitoring
and verifying works are much easier and
less laborious
 The technologies enhance Precision
Agriculture Practices of oil palm
Oil Palm Plantation
Oil Palm Resource Information System (OPRIS)
 OPRIS is a GIS functional geodatabase developed
based on complete spatial data management workflows
designed for scientific investigation, resource
management and development planning for the oil palm
industry
 Integrated collection of geospatial data are stored in
geodatabase for manual and automatic new information
drive
Structure of OPRIS
Data Input
Process/
Storage
GPS Data
Digitized
Data
Digital
Data
Statistical
Data
Boundary
Factory/mill
Editing/
Cleaning
Road
Topography
Agro climatic
Digital Map
GIS
Software
Land use
Soil
Water body
Town/port
Analogue
Map
Analysis/
Modelling
Statistical
Data
Users
Oil Palm
Suitable
Area
Data
Query
Image
RS Data
Output/Analysis
DSS
Soil
Management
Fertilizer/
Chemical
Application
Report
Drainage/
Irrigation
Presentation
Yield
Projection
Government
Industry
Researcher
Oil Palm Land Suitability and Site Yield Potential
Soil type
Oil Palm Land Suitability
Agro-climatic
Oil Palm Site Yield Potential
Oil Palm Cultivation on Peatland
Peatland Map
Oil Palm Landuse 2009/10
Oil Palm on Peat 2009/10
Oil Palm on Peat 2009/
Oil palm on peat
Regions
Oil palm (ha)
P. Malaysia
2,503,682.02
207,458.01
4.14
Sabah
1,340,317.39
21,405.75
0.43
Sarawak
1,167,172.51
437,174.27
8.72
Total
5,011,171.92
666,038.03
13.29
(ha)
%
Area and Locality of Old Oil Palm
Peninsular Malaysia oil palm landuse 2009/10
Location of old oil palm in Melaka and Negeri Sembilan
Land Evaluation and Development
 Geospatial information has
be used to predetermine
the basic information of the
land for oil palm cultivation
 Total area, plantable area,
slope categories, potential
terrace length and density,
number of planting points
etc.
SPOT 5 image of the project area
Flow Chart of Land Evaluation and Development
Overall Areas
Land
Total area
 Ekran quarters
Project area
Area
(ha)
(%)
1,009.35
38.99
970.36
100.00
221.50
22.83
9.45
9.70
12.47
0.97
1.00
1.28
Total non-agriculture land
253.11
26.08
Agriculture land
 Land division
- Parcel A
- Parcel B
- Parcel C
130.51
198.63
277.42
13.45
20.47
28.59
Native land
110.69
11.41
Total agriculture land
717.25
73.92
Non-agriculture land
 Area > 300 m
 Biodiversity
- Strip 1
- Strip 2
- Strip 3
Slope Classes
Land
Parcel A
Parcel B
Parcel C
Native land*
Total
Parcel area
130.51
198.63
277.42
110.69
717.25
Buffer zone
6.36
7.10
5.09
-
18.55
Slope class
0 – 6o
6 – 15o
15 – 24o
> 25o
61.80
31.80
14.82
15.72
47.59
55.45
40.12
48.37
77.59
62.06
77.69
54.97
101.69
7.74
1.04
0.22
288.68
157.06
133.67
119.28
Plantable Area
Land
Area
(ha)
(%)
Agriculture area
717.25
100.00
Unplantable and reserve areas
 Slope > 25o
 Inaccessible/Hill lock area
 Buffer Zone
120.82
135.97
18.58
16.85
18.96
2.59
Total
275.37
38.39
Plantable area
 Model plantation
 Native land
331.19
110.69
6.17
100.00
Total
441.88
61.61
Parcel A
Land Evaluation Information
Land
Total area (ha)
Slope > 25o (ha)
Buffer zone/Drainage (ha)
Hill lock/Inaccessible area (ha)
Nursery A and B (ha)
Plantable area (ha)
 Flat area (ha)
 Terrace area (ha)
Field road length (m)
Field road density (m/ha)
Terrace length (m)
Terrace density (m/ha)
Stand count (no.)
Planting density (palm/ha)
Block
A1
A2
A3
57.14
2.24
1.60
4.98
53.31
42.81
10.50
5,573.72
104.56
12,721.50
1,211.51
6,344
119
34.11
7.55
2.03
10.56
13.97
13.97
1,636.54
117.18
14,274.48
1,022.09
1,804
129
39.26
7.59
2.73
15.03
13.91
13.91
1,397.71
100.52
14,470.66
1,040.67
1,841
132
Total
130.51
17.38
6.36
25.59
4.98
81.18
42.81
38.37
8,607.98
106.04
41,466.64
1,080.66
9,989
123
Monitoring of Oil Palm Cultivation on Riparian Zone
Riparian Zone of Kinabatangan River
Riparian
Zone (m)
Oil Palm (ha)
5
16.78
10
20.17
20
50.36
30
62.49
40
69.93
50
75.82
Total area
295.56 (8.74%)
Investigating the Suitability of Setting-up Oil Palm Mill
Landuse Classes
Urbanization and Settlement
Primary Forest
Secondary Forest
Log-over and Degraded Forest
Wetland and Swamp Forest
Paddy
Other Agricultural and Cultivated Land
Rubber
Oil Palm
Water body
Cloud and Shadows
Buffer distance from the mill
60 km
80 km
100 km
No
1.
Mill location
2.
3.
4.
5.
6.
7.
8.
9.
Landuse Type
Urbanization & settlement
Forest
- Primary forest
- Secondary forest
- Log over degraded forest
- Wetland and swamp forest
Paddy
Other Agricultural and Cultivated Land
Rubber
Oil Palm
Water body
Impervious
Cloud and Shadow
Total
Buffer 0-60km
(ha)
Buffer 0-80km
(ha)
3,924.34
952,342.72
149,873.60
776,348.55
25,197.02
923.55
4,462.45
31,200.97
4,678.94
146,853.65
9,216.81
21,599.21
36,195.51
1,210,474.40
5,936.69
1,803,807.76
251,834.82
1,465,518.01
60,732.39
25,722.54
7,131.73
40,062.36
23,929.73
219,286.19
17,662.68
40,432.37
67,204.27
2,225,453.78
Buffer 0100km (ha)
24,969.76
2,681,495.73
384,909.28
2,139,062.57
73,267.53
84,256.35
27,483.23
65,388.18
66,049.22
353,232.06
80,185.77
62,870.53
101,562.05
3,463,236.53
Precision Agriculture
• The application of technologies and agronomic principles to
manage spatial and temporal variability associated with all
aspects of agricultural production for the purpose of improving
crop performance and environmental quality.
• Precision agriculture is to match agricultural inputs and
practices to localized conditions within a field (site-specific
management) and to improve the accuracy of their application.
• Precision agriculture is in contrast to whole-field or whole-farm
management strategies, where management decisions and
practices are uniformly applied throughout a field
McGraw-Hill Science and Technology Encyclopedia
Precision Fertilizer Application
Foliar
Sampling
Yield
Recording
ArcGIS & SAS
GIS: Interpolation
Foliar Analysis
Foliar
Nutrient
Content
Yield Map
DSS: OPENS
Foliar Nutrient Status
& Site Yield Potential
GIS: Interpolation
GIS: Overlaying
Variable-rate Fertilizer Map
Foliar
Nutrient
Map
Site Yield Potential Prediction
• Palm
– Planting density (palm/ha) : 136
• Soil Survey
– Drainage condition
: 0.5
• Soil analysis
– Clay
: 46
– Silt (%)
: 43
– Extr. K (m.e./100g)
: 3.78
– T.E.C. (m.e/100g)
: 43
• Rainfall
– Annual rainfall (mm)
: 1785
– Rainfall after fertilization (mm/3mths) : 416
• PREDICTED SITE YIELD POTENTIAL = 41.87 t/ha/yr
Foliar Nutrient Status
Nitrogen
Phosphorus
Potassium
Oil Palm Yield Map
• Indicate variable condition in
the field
Overlaying
Yield Map
Fertilizer Rate Map
N Map
P Map
K Map
Mg Map
Variable-rate Fertilizer Map
• The rates of the fertilizer
were formulated according
to the variable conditions
in the field
Variable-rate Fertilizer Applicator
• Applicator:
• Tractor (1)
• Spreader (2)
(1)
• VRT Hardware:
• Notebook PC (3)
• Pocket PC (4)
• GPS Receiver (5)
• Calibrator (6)
(2)
(5)
(4)
(3)
(6)
(4)
Conclusion
 Geospatial information has been proven useful for the
development of oil palm industry
 Geospatial technologies have been used successfully for
evaluating, planning, verifying and monitoring of the industry
 Geospatial database can be used to handle, manipulate and
integrate geospatial data to generate new information for
decision making
 The technologies enhance the application of precision
agriculture practices for oil palm
THANK YOU
For Your Attention………