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Can MODIS derived NDVI provide biophysical status of Tea bush?

Objectives:
  • To examine relations between tea leaf yield and remotely sensed NDVI
Data: MODIS surface reflectance (250m) at 8 day interval from 2000-2005 for the month of April, June and August. The data was downloaded from Earth Observation Science (EOS) Gateway site. The images were obtained in the UTM projection which were further reprojected to polyconic projection.

Methodology:

Study Area: Sonitpur district is spread over an area of 5324 sq. Kms. on north bank of Brahmaputra river. In terms of area Sonitpur is the second largest district of Assam after Karbi Anglong district.

Boundaries:

  • North: The state of Arunachal Pradesh.
  • South: Morigaon, Nagaon, Jorhat and Golaghat districts.
  • East: Lakhimpur District.
  • West: Darrang District.

    • (Pachnai river serves as the boundary)
The District lies between 26° 30’N and 27° 01’N latitude and between 92° 16’E and 93° 43’E longitude. Located between mighty Brahmaputra River and Himalayan foothills of Arunachal Pradesh, the district is largely plain with some hills. Brahmaputra River forms the south boundary of the district. A number of rivers which originate in the Himalayan foothills flow southwards and ultimately fall in Brahmaputra River.

Data Collection: Data used for this study can be categorized in the following two types: Earth Observation Data and Field Survey Data.

Field Data: In this study both attribute and spatial data were considered. The attribute data was collected from tea estate records, meteorological records and by measuring field-by-field Leaf Area Index. The spatial data is extracted from satellite images and existing maps. These spatial and attribute data were linked within a GIS database. All existing maps of the gardens were collected like digital coverages of field boundaries, landuse, soil boundaries, road and stream network, slope, elevation and aspects. Further the leaf area index were collected from the gardens using plant canopy analyzer.

Satellite Data: The MODIS images were reprojected to polyconic projection. The MODIS NDVI images were generated.

5. Discussions:

5.1 Yield Estimation:
For the yield estimation the MODIS LAI image for August and MODIS NDVI image for April, June and August from 2000 – 2004 were used. 1 x 1 and 3 x 3 kernel pixel extraction method was used to extract the NDVI and LAI values from the NDVI and LAI images. Finally the mean NDVI for all the MODIS images were extracted using the area weighted average or zonal attribute.

5.2 LAI and NDVI Relationship:
Similarly, MODIS NDVI image was generated and the tea garden patches were masked out. Using the masked NDVI image, the NDVI values were extracted from the tea masked area using 3 x 3 kernel for extracting the pixels. The average of the actual LAI and NDVI values were calculated and the linear regression analysis was carried out using the LAI and NDVI values. The LAI – NDVI values were plotted and linearly regressed. From the analysis it is observed that there exist a linear relationship between LAI and MODIS based NDVI. The relationship was quite weak but yet significant with moderate R2=0.40 value. Thus it could be inferred that MODIS derived NDVI can approximately provide information on leaf area index for tea. The relationship is shown below.


LAI-NDVI Relationship


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