With recent population growth and global warming, stable food supply is an urgent requirement on a global scale. To cope with this demand, effective use of remote sensing data attracts attention. Among all, Leaf Area Index (LAI) extracted from remotely sensed data may contribute to the increase of yield and adjustment of quantity of manure, if we can automatically estimate the LAI over a wide area to grasp a yield of paddy. Therefore the purpose of this study is to estimate the LAI through remote sensing. In this paper, “Group division method” is proposed to decide a set of bands to be used for the LAI estimation, because the information obtained by a hyper spectrum sensor is enormous. This technique is to decide an index by comparing the order of ground truth data with that of the index based on spectral data. An effective index to estimate LAI is made by reflectances in 545nm, 1170nm and 1290nm using the data from the rice field of Sakata City, Yamagata Pref. as training data. Furthermore, we applied the index to the data set obtained in Furukawa, Miyagi Pref. to verify the effectiveness of the method. Finally we show a “LAI estimate map” and examine whether this study can contribute to estimate the LAI distribution over the wide area.
We developed a method of discriminating land use using multi-temporal Landsat data for the area located in the humid climate region, where probability of cloud cover was very high and also complicated cropping pattern in agricultural field was presented. Due to the limitation of available cloudless scenes, we attempted to characterize seasonal variation of ground surface condition, which could be associated with land use type, by calculating the annual maximum of five indices representing surface condition of bareness of land, vegetation or water for all the data taken over several years. This procedure successfully removed the effect of cloud for the whole study site located in the western part of Java Island, Indonesia. Classification was carried out for the multi-dimensional dataset containing the maximum values of indices by ISODATA method and combination of classes. Results showed 60% of overall agreement and 79% of agreement were found if confusing classes were merged as “Upland” to “Mix Vegetation” and “Bare Land” to “Manmade” with interpreted classes from QuickBird imagery. This accuracy exhibited significant improvement compared to the case of classification using mono-temporal Landsat data. We suggested this method to be one of the most promising tool to produce pixel based land use map especially discriminating paddy and the other agricultural land use over the tropical humid climate region.
Recently, documentation and visualization of various cultural heritages have been receiving attention, and small Buddha such as less than 10 cm tall which was stored in the womb of Buddha is also included in cultural heritages. In order to document these small objects in conservation of cultural heritage, zoom lenses are generally used. However, there are still issues for digital documentation of these small objects using zoom lenses. These problems include sharp imaging and distortions which occur with changes in focal length setting. On the other hand, macro lenses have ability in sharp imaging of small objects from the view point of working distance. With this motive, zoom and macro lens was mounted on digital single lens reflect camera, and accuracy and performance evaluations of the both lenses were investigated in this paper.
Japanese geostationary meteorological satellite, Multi-functional Transport Satellite (MTSAT, Himawari-6) was launched in 2005. The sensor specifications of MTSAT have been improved compared to that of the previous Japanese geostationary satellite GMS-5. The sensor upgrade enabled us to utilize MTSAT data for terrestrial monitoring. High-frequency observation of MTSAT can detect hourly land-surface changes such as land surface temperature, snow cover, forest fire and so on. However, since optical sensor images are highly contaminated with clouds, we must find cloud-free images to observe land surface conditions. It is time-consuming and unrealistic task to find cloud-free images by visual interpretations, because MTSAT provides images at hourly intervals. In this study, we developed a data search system to find cloud-free images easily. This web-based system allows us to find cloud-free MTSAT images over Japan through the interactive GUI on the Web.
The effectiveness of disaster control based on the aerial laser survey data and the problems thereof have been discussed by taking the emergency measures taken for the river course (natural dam) blocked by the “Iwate-Miyagi Nairiku Earthquake in 2008” as an example. As compared with the conventional aerial photographic survey, the aerial laser survey that collects land-surface data of wider areas has been recognized as an extremely helpful technique to understand the present situation of earthquake disaster more quickly and precisely. However, there are some matters that need technical innovation. This report summarizes the effectiveness and problems based on actual experiences.
April 03, 2017 There had been a system trouble from April 1, 2017, 13:24 to April 2, 2017, 16:07(JST) (April 1, 2017, 04:24 to April 2, 2017, 07:07(UTC)) .The service has been back to normal.We apologize for any inconvenience this may cause you.
May 18, 2016 We have released “J-STAGE BETA site”.
May 01, 2015 Please note the "spoofing mail" that pretends to be J-STAGE.