There are large volumes of lunar images that are archived and to be archived by missions such as Clementine and SELENE (SELenological and Engineering Explorer). We have developed an algorithm to automatically detect and classify craters in massive lunar images. Craters are of scientific interest because their density can yield the relative ages of the surface units. However, the manual extraction of craters remains difficult because it requires a great deal of man power. Several automated crater detection algorithms have been developed so far but none are yet practical nor have been sufficiently tested.
Our algorithm locates craters using four different approaches. These are extractions of : (1) the shade and sunny patterns of craters in case of low sun elevation, (2) the circular features from the edge image, (3) the circular lines from thinned and connected line segments, and (4) discrete or separated circular edge lines which consist circles using fuzzy Hough transform. We applied the proposed algorithm to Clementine, Lunar Orbiter and Apollo images acquired over both mare and highland under different solar elevation. As a result it is shown that the algorithm can detect craters from various images at 80% detection rate without parameter tuning.

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This study was conducted as a first step for using chlorophyll a (chl a) as an environmentalindicator of water quality. The variability of phytoplankton distribution from bi-weekly to seasonal scales in the ocean south of Honshu Island was analyzed in relation to temporal changes of the Kuroshio Current. Sets of 5-year data (1998 to 2002) including chl a data from the ocean color sensor, SeaWiFS, sea surface temperature (SST) from the NOAA/Advanced Very High Resolution Radiometer (AVHRR), and digitized Kuroshio axis data from the Japan Hydrographic Association's Marine Information Research Center were used in the study area (30-39°N, 130-142°E). It was found that the Kuroshio axis was the strongest factor in altering chl a distribution. To the north of the Kuroshio axis there is a high chl a concentration region, with a low chl a region to the south. High chl a immediately north of the Kuroshio axis continues from 2 weeks to 1 month, and its horizontal scale is 150-450km. The high chl a region associated with the meandering S-shaped path of the Kuroshio, where it overlaps the region of low SST, is centered around 33°N, 138°E ; it is 140 km in diameter and lasts 2 weeks. Around the Izu Islands the so-called 'island mass effect' creates a high chl a region which lasts for 2 weeks to 3 months ; its scale is 5 to 30km in diameter. On the longer time-scale variability of chl a, two different patterns of seasonal variability were observed in the regions north and south of the Kuroshio axis.

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A net primary production (NPP) estimation algorithm based on data from temperate vegetation in Japan was developed by Furumi et al. It utilizes the change in the vegetation index (VIPD), and photosynthetically active radiation (PAR) over time to estimate NPP with the non-linear relationship between the NPP and the PAR. To employ this algorithm to estimate NPP from satellite data on a global scale requires time series PAR data, but such data are unavailable on a global scale. Data of daily mean global solar radiation (SR) exposure over 24 hours are available, and daily mean PAR over 24 hours can be calculated from daily mean global SR exposure over 24 hours. However, when daily mean PAR over 24 hours was used, NPP was overestimated. The relationship between PAR and photosynthesis is not linear, and plants photosynthesize only during the daytime. We therefore propose the daily or monthly mean PAR over the effective daylength for vegetation photosynthesis, which is calculated from daily or monthly mean PAR. The effective daylength for vegetation photosynthesis is defined as the time between sunrise and sunset minus 2.0 hours. The NPP estimated from the daily or monthly mean PAR over the effective daylength for vegetation photosynthesis changes by ±4% when the effective daylength for vegetation photosynthesis changes ±25% of 2.0 hours from 1.5 hours to 2.5 hours.
We applied the monthly mean PAR over the effective daylength for vegetation photosynthesis to estimate the NPP from Landsat ETM+ data for a semi-arid area of Mongolia. The estimated NPP had an estimation error of 26%.The results were compared with ground measurement data, which have a 20% measurement error. The values agreed within the ranges of error. In the study area, average estimated NPP was 0.056±0.015 [kgCO₂/(m² month)].

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Time series analysis is one of the important methods for understanding the change of a phenomenon. But, each image has a different distortion generally. Therefore, geometric correction of images is needed. Up to now, many discussions about the accuracy of geometric correction have been held and many geometric correction algorithms about NOAA/AVHRR images have been proposed. However, most of them use GCP (ground control point) where a user is required to specify GCP manually. In this research, special attention is given to this point and automatic GCP creation method is proposed. Required inputs of this method are only an AVHRR image and a standard map. First, a binary image which expresses land and a water area is created by calculating NDVI of an AVHRR image. Next, the boundary of land and a water area is detected from the binary image, and reference windows are created from a digital map. Finally, the boundary of AVHRR image and the reference windows are compared and the best match position is determined as GCP. No manual process is needed by this proposed method. Therefore, processing time is shortened and a user's labor is mitigated. The result of the geometric correction algorithm using this proposed method shows the mean errors are less than 1 pixel.

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Planetary missions have provided us wonderful and valuable information about the solar system, and digital data of such planetary missions can be easily browsed via INTERNET. This means that those who connect to INTERNET can search and find the data, so that even students outside academia can study based on the planetary mission data. Such studies using INTERNET resources about planetary missions will be a new research style of planetary science, and we call such research style the "Desktop Planeatry Exploration". Here, we show the outline of this research style and also mention about the examples of the INTERNET sites of the planetary missions.

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