A GIS approach to generation of thematic maps to monitor tea plantations: A case study

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1 Two and a Bud 59(2):41-45, 2012 RESEARCH PAPER. A GIS approach to generation of thematic maps to monitor tea plantations: A case study Minerva Saiki a I and R.M. Bhagat Department of Soils, Tocklai Experimental Station, Tea Research Association Jorhat , Assam, India ABSTRACT Tea is grown in Northeast India on a little over 3,50,000 ha in Assam. It is extremely difficult to monitor such extensive plantations by conventional methods, because tea plantations extend to many inhospitable areas with low communication links in North Eastern India. Monitoring can be done effectively through remote sensing imageries that can be made available at regular time intervals and using thematic maps prepared for a given area. An attempt is made in this case study to develop thematic maps for area and production, so that the trends can be visualized quickly. The study considered both attribute and spatial data. The attribute data were collected from tea estate records, whereas the spatial data were extracted from satellite images and existing maps. Existing maps were used to prepare digital coverages (layers) of boundaries, roads, drainage, land use etc. using a GIS platform. Satellite imageries were geo-referenced and suitable image enhancement was applied for the delineation and interpretation of shade. These spatial and attribute data were linked within a GIS database and thematic maps were prepared with both attribute and spatial data. The study provided detailed information for the area and production on a dynamic GIS platform. INTRODUCTION India has over 13,000 tea estates with a combined area of about 5 lakhs ha, of which 70% are distributed in Northeast India. It is observed that tea is affected by many factors such as old plantations, declining soil health, water logging, increasing threats of pests and diseases etc. Statistics indicate that tea plants start yielding from the third year onwards, maintain a steady increasing trend upto a certain age and reach a peak followed by a decline, thus questioning the further commercial viability of the section (Dutta et a/., 20 I0). The economic life of the bush has been estimated to be 40 years. After this the amount of non-productive tissues of tea plants becomes so great that its maintenance adversely affects the production of new shoots (Hadfield, 1974). Monitoring and analyzing growth of tea plantations over space and time is a very important aspect. However, due to its extensive area, sometimes it is very difficult to manually assess the plantations for its periodic evaluations in terms of yield and management. GIS offers an efficient and reliable means of mapping vast areas. Also, field observations can be integrated into GIS maps by combining with ancillary data which can provide insight into the cultural practices being implied into the system. GIS maps are both the raw material and the product of GIS. Most of the thematic maps are subsets of available geographic data that have been selected and organized in response to a particular problem. Basically a thematic map is a graphic display that shows the geographic distribution of a particular attribute or relationships among a few selected attributes. In agricultural field, such maps help farmers/planters identify areas within a field which are experiencing difficulties, so that these can be corrected by taking quality decisions using real time data on a GIS platform. Using this approach planters will not only improve the productivity of their land but may also reduce faml input costs and minimize environmental impacts. The CUtTentstudy was an attempt to monitor tea plantation by developing thematic maps (spatial database) and analyze them with the help of GIS. I mincrva.jorhat@gmail.com 4\

2 MATERIALS AND METHODS The studies were carried out at the Borbhetta Tea Estate, Latitude ; Longitude ; Elevation 322 ft, the experimental tea garden oftocklai Experimental Station, Jorhat, Assam, India (Fig. 1). Fig. I. Location of Borbhetta T.E. ERDAS Imagine 9.1 and ArcGIS 9.1 were used for data processing. Ground information was correlated with the help of geocoded FCC (False Colour Composite) acquired from Landsat ETM of Assam on December, 200 I and of30 meter resolution (Fig. 2). As the study area is situated in Jorhat district, a false colour composite (FCC) of Jorhat was prepared from the Assam imagery using the Subset method (Fig. 3). In this process shapefile of Jorhat district was used that was a subset ofthe administrative boundaries of India. Geometric correction or re-projection was performed to compensate for any non-systematic distortions caused by the errors due to variation in altitude, velocity of the sensor platform, variations in scan speed and in the sweep of the sensors field of view, earth curvature and relief displacement. The projection parameters are WGS84 datum with UTM 46 North Zone. Fig. 3. Landsat ETM, FCC of Jorhat district Existing paper map (analogue map) of Borbhetta T.E. (Fig. 4) was scanned to prepare a digital map of the entire estate. Fig. 4. Scanned map of Borbhetta T.E. IArea under red circle is not under TRAI 11'ig.2. Landsat ETM, FCC of Assam identifying Jorhat district (inside the circle) This map was digitized nlliher to exclude the areas which are currently notundertocklai experimental garden (Fig. 4 area under red circle) using the ESRI's software Arc GIS

3 The derived map was further used to extract different layers or feature classes. The map was used to have six feature classes or shapefiles, i.e, 'tea_sections', 'no_tea_sections', 'hullah' (or farm ditches), 'roads', 'buiicup_areas' and 'boundary'(fig. 5). This way the spatial data were extracted from the existing map. N. u J Fig. 7. Closer view of the study area Tf -- Fig. S. Different feature classes (Shapefiles) of Borbhetta T.E.Map The shapefile of Borbhetta T.E. was then overlaid on the satellite imagery of Jorhat. This process was helpful in locating the estate and then to monitor it visually (Figs. 6 and 7). I RESULTS AND DISCUSSION Interpretation of spatial data of Borbhetta was carried out using various interpretation keys like the shape, size, pattern, tone, texture, shadow, location, association and resolution. Man-made features like roads, tea garden patches, building as well as natural features like water bodies were identified from the image. The vegetation status was identified using the tonal variations out of which the tea patches were categorized based on the smooth and rough surfaces showing the higher and lower refiectances respectively. Unlike reference maps, thematic maps are usually made with a single purpose in mind. Typically that purpose has to do with revealing the spatial distribution of one or more attribute data sets. The attempt was therefore to develop thematic maps for area and production of the study area to visualize the trends quickly. In this study emphasis is given on collection of reliable and plantation related data and putting them into a GIS enabled framework for further analysis and planning. The attribute data were collected from the tea estate records manually. Integration offield data with a GIS platform will lead to effective anclefficient planning for better management of a tea estate. In this context regular integration of the data with the help of field sensors will be more effective and reliable too. Digitization of these analogue data was carried out to create a spatial database. The yearly sectional green leaf yields of the study area for the years are given in Table I. Hg. 6. Overlaying of Borbhetta T.E. shapefile over a Landset ETM of Jorhat district (in yellow circle) The sections in the experimental tea estate were not of same size i.e. the areas were different. To overcome this problem, the yield was taken as kg/ha/yr for all sections. The files in the database were in the format of.dbf extension so that they could be easily integrated/linked with a GIS platform. Yield, area, production hold true for entire areas, but not for any particular point location. For this reason it is conventional not to use point symbols to symbolize rate and density data on thematic maps. Plate 8 shows a thematic map of the study area on sectional yield of green leaf for the year 2009 where graduated color technique was used. 43

4 Table 1. Sectional green leaf yields of Borbhetta T.E. for Object ID Section-wise yield ot'borbhetta T.E. (in kg/ha) Sec No I ~ I I II I J J I I I5 I I I I Same method was followed while preparing the thematic maps for the years (Fig. 9). IMp ahowlng HCtloneI yield : Borbhttta T.E. : 2008 AAU In a visual interpretation tea patches appeared to be bright red in satellite data with smooth texture. The open or low shade (low density of shade trees) showed bright red due to higher reflectance while the tea patches with high shade showed reddish brown in colour. Traditionally, shadows detenl1ine the presence and density of shade trees in tea gardens. Taller trees exhibited larger shadows than the shorter ones. Water bodies appeared dark blue with smooth texture which could be easily separated from the other classes. In respect of the study area water bodies are confined with narrow drainages that are locally called as 'h ullah'. Settlements show blackish green reflectance and coarse texture. In recent past, attention has been paid towards using satellite remote sensing data in tea crop estimation surveys in view of its advantages over traditional procedure as they are time consuming, costly or prone to error. The creation of thematic maps is among the most important functions of a GIS. The thematic maps were prepared based on sectional green leaf yield of the experimental tea estate. A classified soil and fertility map can also be generated on the basis of existing soil survey data for the same set of conditions. While interpreting the results, it was revealed that section numbers 27, 33, 34, 20, 15, 40 and 45 were the highest green leaf yielding sections for the 5 consecutive years (i.e ). Thc yield of these sections varied from 4571 to kg/ha per year, whereas section numbers 7, 203, 204,206, 207, 208,218 were the low green leaf yielding sections as the highest yield from these sections was 465 kg/ha/yr. Years 2004 to 2008 showed the same yield pattern. But interestingly it was found that 2009 was the highest yielding year amongst all. Section numbers 5, 27,40 and 45 in this year produced kg/ha of green leaf (Fig. 8). Sectional yields for different years are presented in Figs. 9 and 10. Fig. 8. Thematic map of Borbhetta T.E. showing sectional green leaf) ield for 2009 Fig. 9. Thematic map showing sectional yields of the study for the years 2005 and

5 consistently low, need more attention than the one that are consistently yielding high in the Borbhetta experimental garden. CONCLUSION Fig. 10. Thematic map showing sectional yields of the study for the years 2007 and 2008 It is important to note that the thematic maps of sectional yields (plates 9 and 10) are dynamic in nature. The maps can be strengthened with future data and also of different nature of attributes. As has been said earlier, the soil data can also be integrated with these maps, which can further bring out the correlation of soil fertility and yield. This is the advantage associated with the thematic map preparation. These thematic maps allow the garden decision maker to decide upon the management options. It is clear that the low yielding sections, which have yielded Thematic maps prepared for the Borbhetta experimental garden showed detailed information about the garden for different sections. In addition to yield and area, the maps provide information on roads, built-up areas, hullahs/ ditches/drainage lines etc. for the whole garden. Besides, the maps show the sections with yield trends which can be used to make decisions for their management. REFERENCES Dutta, R., Stein, A., Smaling, E.MA, Bhagat, R.M., Hazarika, M. (20 I0). Effects of plant age and environmental and management factors on tea yield in Northeast India. Agron. J. 102: Hadfield, W. (1974). Shade in Northeast Indian tea plantations, II, foliar illumination and canopy characteristics. J. AppL Eco!., 62: