Agriculture Reference
In-Depth Information
Callander
1981
; Watson
1986
). Therefore, tea plantations are distributed in up, mid
and low-country regions, belonging to wet and intermediate zones.
Tea production is classified based on its growing regions, such as high, medium
and low-grown tea. However, the quality or flavour of each category is unique. Most
distinguishable up country tea is characterized by its flavour and aroma while low-
grown tea is identical for its strength and colour. In terms of production, low-grown
tea dominated over others (173.2 million kg in 2009) followed by high (72.3 mil-
lion kg) and medium (44.3 million kg) grown tea. Economically, the tea sector is
important and contributes about 1 % to the GDP. However, the present average yield
of 1,550 kg per hectare is much lower than the average yield of other tea-growing
countries like India (1,800 kg/ha), Kenya (2,400 kg/ha) (Annual report
2009
).
According to the central bank report (2009) in Sri Lanka, the major reason for the
lower productivity is due to senility of the tea bushes. Furthermore, in high-grown
areas, around 90 % of tea bushes are more than 100 years old and in low-grown
areas, the majority of tea bushes of vegetatively propagated (VP) varieties are older
than 30 years. Therefore, main emphasis was laid on replanting programmes to
achieve minimum of 3 % replanting per year. However, identification of low-pro-
ductive fields and suitable land unit for such programme is not straight forward.
Therefore, it is vital to have proper scientific basis for the rational decision-making
at management level. GIS and remote sensing has proved to be a handy tool to infer
land productivity and the suitability.
Remote sensing and GIS technology has advanced over the last few decades
and one of the most important applications of it is the database management, to
store information for quick access and analysis. GIS data have specific location
in space;In other words, those spatial data have been referenced to a co-ordinate
system. It is called geographically referenced. It was also possible to store non-
spatial or attributes data in such databases. Therefore, GIS is able to store large
amounts of different types of data for easy access. Furthermore, the spatial data
can be combined with attribute data to generate new information in the decision-
making process. Hence, tea plantations where the spatial distribution is massive,
use of GIS enhances the ability of rational decision-making process. Turner and
Jayakody (
1994
) emphasised the usefulness of computer-based technology as a
tool for planning and managing tea plantations. Because, computer technology is
capable of generating required information at its earliest to the higher management
levels. However, the success of such a system heavily depends on accuracy of raw
data, hence it is essential to have remote sensing with intensive ground-level truth
to validate the acquired data. Since 70s, remote sensing technology has proved to
be a useful application for evaluating biological activity of vegetation cover. In
recent past, spectral data have been widely utilized for crop yield models. Further,
it has been recognized as an inexpensive and rapid method for crop monitoring and
early warning.
Therefore, this study was designed in a way to investigate the probability of us-
ing remote sensing and GIS as management tools for extensive tea plantations in
Sri Lanka. However, considering the limitations, the study was limited to Ratnapura
