30 Changes in terrestrial net primary productivity NPP integrate with other
climatic, ecological, geochemical, and human influences on the biosphere. Some regional studies have reported the increases in NPP in recent 20 years with
different reasons. For the northern mid-latitudes and high latitudes, multiple mechanisms such as nitrogen deposition, CO2 fertilization, forest re-growth, and
climatic changes may lead to the increases in NPP, whereas increases in the tropics have been primarily attributed to CO2 fertilization Nemani, et.al., 2003.
Refer to the information as show in Figure 4.1 most dramatic change occurred at tropical forest in Sumatra usually caused from conversion forest to
some other land-use. Most common changes has effected to decrease and increase of NPP distribution. Decrease NPP distribution usually caused by expansion of
urban areas, cash crop farming, palm oil plantations, timber extraction from the forest, natural disaster such as forest fire etc. Increase NPP distribution usually
caused by growing of young vegetation to become mature vegetation for example increased of mature vegetation from plantations.
4.2 MODIS EVI and MODIS FPAR
In this study, monthly composite MODIS EVI and FPAR products at 1 km resolution MOD13A3 and MOD15A2 were obtained for the nine-year period
from January 2001 up to December 2009 and cover of all Sumatra terrene. The following four tiles of the MODIS datasets are h27v08, h27v09, h28v08 and
h28v09, where h and v denote the horizontal and vertical tile number, respectively.
The MODIS datasets provided in Hierarchical Data Format HDF were processed by MODIS Reprojection Tool MRT 3.0a and reprojected from the
Integerized Sinusoidal ISIN projection to a geographic projection latlon, World Geodetic System 1984-WGS84. The MODIS datasets in GeoTIFF format were
imported to Grads 2.0 and ArcGIS 9.2 and converted to a float data type.
31 As stated in previous chapter, there are two kinds of estimation used; first
is estimation of annual NPP and second is estimation of monthly NPP. Several parameter of estimation which used to estimation NPP as described below:
4.2.1. Enhanced Vegetation Index
Enhanced Vegetation Index EVI data were obtained from the MODIS sensor. EVI improves the quality of NDVI product. It corrects for some
distortions in the reflected light caused by the particles in the air as well as the ground cover below the vegetation. The EVI data product also does not become
saturated as easily as NDVI when viewing rainforests and other area of the Earth with large amounts of chlorophyll. The EVI data are designed to provide
consistent, spatial and temporal comparisons of vegetation conditions, and it offers the potential for regional analysis and systematic and effective monitoring
of the forest area. Vegetation indices derived from remote sensing data provide information
about consistent, spatial and temporal comparisons of global vegetation conditions which will be used to monitor the Earths terrestrial photosynthetic vegetation
activity. For example, the enhanced vegetation index EVI provides a measure of greenness of the vegetation that can be used to predict net primary production.
The evolution of vegetation index exhibits a strong correlation with the typical green vegetation growth stages. The results temporal curves can be
analyzed to obtain useful information such as the startend of vegetation growing season. However, remote sensing based phonological analysis results are only an
approximation of the true biological growth stages. This is mainly due to the limitation of current space based remote sensing, especially the spatial resolution,
and the nature of vegetation index. The EVI values were resulted from 9-years estimation have limits within a
minimum of 0.11 and maximum of 0.90. The EVI values equal to or below zero were assumed to be typically caused by water bodies. The low EVI value were
assumed as sparsely vegetated land meanwhile the high EVI value were assumed as densely vegetated land. Estimation of EVI values compare to areas over
Sumatra terrestrial in percentage during years 2001 to 2009 shown Table 4.1.
