Development of Automatic Composite Processing System for NOAA/AVHRR GAC data
Shinya Suzuki and Yoshiaki Honda and Kiji Kajiwara
Center for Environment Remote sensing center ( CEReS) ,
University of Chiba, Japan
1-33, Yoyoi, Image-ku Chiba 263, Japan
Tel: (81) -43-290-3945 FAX : (81) -43-290-3857
Abstract
NOAA/AVHRR GAC data which is collected for more than ten years is very useful for studies related to analysis of the global environment. In order to create mapped and composite data applicable for land term time series analysis, however, it is required that develop the system for automatic mapping and composite process. With interactive processing , it is impossible to create long term time series composite data because more than 4500 paths data should be processed for only one year data.
Authors have developed the prototype of automatic processing system which consist of following procedure. 1) cloud screening in day time 2) Automatic selection of GCPs . 3) Automatic GCP matching procedure. 4) Map one day paths to 4 km resolution longitude/latitude coordination . 5) in days composite procedure considering sensor scan angle, solar zenith angle.
Introduction
It is very important to understand the global environment that are getting worse recently. Therefore, the data of NOAA?AVHRR GAC is very important for analysis of the global environment.
For this property, the study related to development of the data processing algorithm used NOAA/AVHRR GAC data has been done frequently. But most of them has been simply in the process sing algorithm course of a low spec computer. At the data processing has need of manual works. In the present, however, for the development of computer technology had made possible speedy calculation and to make a high quality data.
Then we try to make automatic processing system which is possible to make a huge amount of high quality data from NOAA GAC.
Outline of data processing
The purpose of our data processing system which make n days composite data by the raw data of NOAA/AVHRR GAC will has been made automatically. In this case, difficult problem is to make selection of GCPs and GCP matching procedure automatically. We show this outline following. ( fig 1)
Figure 1: Outline of data processing
At the first processing is simply day time cloud screening for GCP hatching procedure. Next processing is geometric correction using automatic GCPL matching. The resampling user in geometric correction is method of using the corrected orbital elements ( Hashimoto and Murai 1993). Next one is to map one day paths. And last one is n days composite. Now we have made as far as geometric correction automatically. We will explain about cloud screening and geometric correction using GCP.
