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Vegetation Growth Zones using NOAA-AVHRR data: Comparison between conventional and Satellite based methods Figure 3 shows the relationships between vegetation growth and P75 for all vegetation growth zones as delineated using vegetation growth in DL1 zone. Graphs (a), (b), (c) represent the relationships in December, August and January respectively. Graph (d) based in the annual averages of vegetation growth and P75. There is no clear relation ship can be identified between vegetation growth and P75. In all four graphs overall relationships between these two variables are negative. But the correlation coefficients are very low. One to one relationship would imply a complete dependency of water from rainfall to create vegetation growth. But it is well known that soil moisture and ground water is playing a very important buffer role in vegetation growth. The non-linearity of relation ships in graphs (a), (b), (c) and (d) show exactly that process and its geographical dependency. This implies that there is no proper relation ship between vegetation growth and P75 in different vegetation growth zones inside DL1 agro-ecological zone. In existing agro-ecological zone approach for Sri Lanka, P75 is the most predominantly spatially and temporally varying parameter in DL1 region. The new approach is based on spatial and temporal variations of vegetation growth. Therefore the vegetation growth zones derived, estimated using NOAA-AVHRR data, identified different sets of zones representing the combined effect of all the bio-physical parameters which are different from existing agro-ecological zones. Further, the new approach identified relatively small areas with respect to the existing agro-ecological zones enabling assessment of local activities such as crop selection and agronomic practice.  Figure 3 Relationship between P75 and vegetation growth in (a) January, (b) August, (c) December and (d) Annual Discussion This study based on information derived by NOAA-AVHRR images provides an example of using free public satellite data for agricultural planning. The major innovation of this study is that the actual biological activities on the ground are considered as major factors in demarcating land areas into different zones. Even though the spatial resolution of NOAA-AVHRR is low, it is useful for macro level analysis such as demarcating a country into vegetation growth zones. In conventional zoning methods, only rainfall, soils and elevation data have been used. But the actual ground situation is a result of the combined effect of such parameters, subject to spatial and temporal variations. Therefore, vegetation growth is an appropriate indicator in monitoring the combined effect of these parameters. As mentioned in introduction, lack of data on water utilization among different uses and users was identified as a major problem in water management practices. The case study of the DL1 zone shows the usefulness of such techniques in extracting information for different parts of the domain. In agricultural practices, demarcation of areas into different agro-ecological zones is vitally necessary. This technique provides a zoning method that is more accurate than existing ones. It also furnishes the data to make relationships between water use and biomass production. Based on these relationships and other bio-physical information, best agricultural practices for different areas can be determined. References:
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