The analysis of plant disease, especially in spatial and temporal terms is very complex process but with the advancement in computer technology, the task has been simplified to large extent. Furthermore, the application of GIS in plant disease analysis is becoming more popular, precise and advanced day by day. GIS helps plant disease analysis in many ways. The primary use is to understand where disease is occurring and based on that preventive measure can be taken. Various analyses can be performed in GIS environment and maps can be derived to benefit a farmer for an effective and comprehensive management of plant disease. For this study, Basal Stem Rot (BSR) disease in oil palm plantation was analyzed. BSR, one of the lethal diseases of oil palm is caused by ganoderma boninense. The disease can kill up to 80% of the stand by the time when the palms are halfway through their normal economic life span. In the present study, the choropleth map, then the interpolated density approach followed by statistical technique shows the various steps to move from overall scenario of disease to pin pointing the disease incident location or hotspot analysis. The study resolves that the hotspots generated by choropleth and density map can be refined and more precisely located with the help of spatial statistical approach. The data acquired from these hotspots can be utilized for the study of advanced analysis such as disease distribution pattern.
[1]
J. Estes,et al.
Geographic Information Systems: An Introduction
,
1990
.
[2]
Julie Delaney.
Geographical Information Systems: An Introduction
,
2000
.
[3]
P. D. Turner,et al.
Oil palm cultivation and management.
,
1974
.
[4]
A. Konopka,et al.
FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS
,
1994
.
[5]
I. Henson,et al.
Physiological analysis of an oil palm density trial on a peat soil.
,
2003
.
[6]
K. Hashim.
Basal Stem Rot of Oil Palm : Incidence, Etiology and Control
,
1990
.
[7]
T. Elmqvist,et al.
Infection by pathogens and population age of host plants.
,
1990
.
[8]
Merritt R. Nelson,et al.
Geographic information systems and geostatistics in the design and validation of regional plant virus management programs
,
1994
.
[9]
R. May,et al.
Population Biology of Infectious Diseases
,
1982,
Dahlem Workshop Reports.
[10]
Stephen P. Kaluzny,et al.
S+SpatialStats: User’s Manual for Windows® and UNIX®
,
1998
.
[11]
R. May,et al.
Population biology of infectious diseases: Part I
,
1979,
Nature.