Keywords : Composite, AVHRR, GAC, global product

Abstract:
A composite method for NOAA/AVHRR data over land is proposed. This method is based on Maximum Value Composite (MVC) using NDVI and consists of three consecutive criteria with NDVI, brightness temperature derived from channel 4 and scan angle. A global product with 4 km resolution produced by this method is compared with that of MVC from the viewpoints of elimination of clouds, relations to adjacent pixels and smallness of scan angel.

1.Introduction
Time series of global product with 4 km resolution has been produced from NOAA/AVHRR GAC in Center for Environmental Remote Sensing (CERes), Chiba University. Composite is the final process to produce daily product from georectified path images, and 10-day composite product from ten daily products. The MVC and showed that the MVC has tendency to select data from near-nadir region and minimize the influence of the clouds atmosphere (air molecules, water vapour and aerosols) and bi-directional reflection. Some our attempts resulted that the MVC selects data normally from forward-scatter region, and extremely off-nadir region in some cases. Therefore, the influence of atmosphere and bi-directional reflection is greater and size of footprint is larger than nadir. Chilar et al. (1994) evaluated five composite criteria (three single -step criteria: maximum NDVI, maximum apparent temperature and maximum difference of channels 2 minus 1, and two two-step criteria: maximum NDVI followed by maximum temperature or minimum scan angle). They concluded that maximum temperature and maximum NDVI followed by minimum scan angle were the most effective one- and two-step criteria, respectively, and maximum NDVI criterion preferentially selected off-nadir pixels from the forward-scatter region. Stoms et al. (1997) Developed the multiple-objective composite method based on three-dimensional Euclidean distance consist of NDVI, apparent temperature and satellite zenith angle, and resulted that it was superior to MVC and maximum apparent temperature composite from two points of view: the satellite zenithe angle distribution was more closely clustered about nadir, and neighboring pixels are more frequently selected with similar viewing geometry and atmospheric conditions.

In this paper, a new composite method is proposed, which is based on the MVC and is improved by adding two criteria: maximum brightness temperature and minimum scan angle. Evaluation is made by comparison with the MVC itself from the viewpoints of elimination of clouds, relations to adjacent pixels, and smallness of scan angle.

2. Methodology
This method, hereafter referred to as N4SC (i.e. maximum NDVI- Maximum channel 4 brightness temperature - minimum scan angle composite) consists of three selections and two checks between these selections. Processing flow and the concept is shown in figure 1.

(a)



(b)
Figure1. (a) processing flow of the composite method. Square and ellipse mean" selection" and "check", respectively. (b) Conceptual scattergram of NDVI and brightness temperature
SZA_check: The availability of NDVI is examined by solar zenith angle as preprocess. NDVI value is high and unreliable in twilight region at high latitude independently on the surface reflectance, because of low radiance signal and long path length (Holben 1996). Therefore If the pixel has any data with solar zenith angle greater than threshold value (70 degrees at present), it will be composited by Maximum_Ch.4_selection.

Maximum_NDVI_selection: The data with maximum NDVI is selected just like MVC.

NDVI_range_check: the difference of each NDVI from maximum is examined. If the difference is within the threshold, the data is kept as kept as a candidate for next selection. This process aims at avoiding overestimation of NDVI by selecting from forward-scatter region, and at retaining the data from nadir region. Although it is supposed that the threshold value has varies with the season and/or geographic location, it is fixed at value 0.05. If no data has passed this check, the data with maximum NDVI is selected for composite data.

Maximum_Ch.4_Selection: The data with maximum brightness temperature derived from channel 4 is selected out of candidates passed above range check. This aims at eliminating clouds over less vegetated area where has low NDVI similar to clouds.

Ch.4_range_check: The difference of brightness temperature between each data and maximum is examined. The all data within the rectangle in figure 1(b), are considered as equivalent in availability for composite. Threshold value is a fixed at 10.0 in Kelvin.