Vegetation phenology is closely related to seasonal dynamics of the lower atmosphere, and important elements in global models and vegetation monitoring. Time-series NDVI data based on imagery from AVHRR or MODIS are suitable for phenological monitoring, because these sensors provide data with a high temporal frequency. In order to reduce noises caused by cloud contamination or atmospheric variability, Maximum Value Composite (MVC) is applied to the data. However, composite data have undesirable noises due to remained cloud contamination and inequality of observation intervals. Though MVC technique is applied, these noises disturb phenological monitoring. This paper proposed new noise reduction algorithm which integrates Best Index Slope Extraction (BISE) and Maximum Value Interpolated (MVI) algorithms. Integrated algorithm was applied to timeseries NDVI data consists of NOAA AVHRR composite images. This algorithm worked well in areas dominated by vegetation such as cropland including double cropping area, deciduous broadleaf forest and evergreen needleleaf forest. We confirmed that the algorithm reduced effects of cloud contamination, and equalized each observation interval. Therefore, applying developed algorithm to time-series NDVI data allows us to phenological monitoring more precisely.
An improved ISODATA clustering method with merge and split parameters as well as initial cluster center determination with GA: Genetic Algorithm is proposed. Although ISODATA method is well-known clustering method, there is a problem that the iteration and clustering result is strongly depending on the initial parameters, especially the threshold for merge and split. Furthermore, it shows a relatively poor clustering performance in the case that the probability density function of data in concern can not be expressed with convex function. In order to overcome this situation, GA is introduced for the determination of initial cluster center as well as the threshold of merge and split between constructing clusters. Through experiments with simulated data, the well-known UCI repository data for clustering performance evaluations and ASTER/VNIR: Visible and Near Infrared Radiometer of imagery data, the proposed method is confirmed to be superior to the conventional ISODATA method.
The purpose of this research is to decide the algorithm to estimate the stem volume according to the tree height and the parameter of crown with small-footprint airbone LiDAR (Light Detection And Ranging) . We explored the relationships between the stem volume and the tree height, the parameter of crown by field survey using regression analysis. Moreover, it examined which the parameter of crown was best for estimating the stem volume. The study area was a plantation of Sugi (Cryptomeria japonica D.Don) and Hinoki (Chamaecyparis obtusa Endl.) . As a result, we confirmed that the coefficients of determination were 0.6 or more and there is a high correlation between the tree height, the parameter of crown, and the stem volume. Moreover, when the relation between some parameter of crown and the amounts of the leaf was examined, as for R2, the crown surface area was the highest. Therefore, it has been understood to be able to estimate the stem volume according to the tree height and the crown surface area.
Moroyama town is located in the southwestern part of Saitama Prefecture, 50km from the central part of Tokyo. Moroyama is a historical town including more than 80 small ancient burial mounds. These ancient burial mounds locate in brushland along the Oppe River through the northern part of Moroyama. The diameters of these ancient burial mounds are about 5-15m, and it is supposed that some of the ancient burial mounds are not yet found because the ancient burial mounds are covered with trees. These small ancient burial mounds under the same situation are distributed not only in Moroyama but also all over Japan. In generally, archaeological investigation on these small ancient burial mounds is performed using great time and labor, and these are impediment to documentation and investigation on small ancient burial mounds, nevertheless it is indispensable for understanding the history and culture in those days. With this motive, airborne laser surveying was performed, and efficient extraction method for ancient burial mounds from laser scanner data was investigated in this paper.
Recently, the number of pixel of amateur digital cameras is amazingly increasing by modern semiconductor and digital technology. Nevertheless the highest pixel of amateur digital camera is achieved 10 mega pixels, and such high resolution amateur digital cameras became the most popular camera on the market in Japan. In these circumstances, the high resolution amateur digital cameras became useful tool in various photogrammetric fields, and some software of digital photogrammetry by using amateur digital still camera has been developed. Generally, camera calibration by digital photogrammetric software is performed by using test target. The test target should be taken by the digital still camera from several positions and angles, and some images of the test target which were taken by own situation can be obtained. However, it is expected that the calibration results are influenced by the situation which are position, angle, and number of images and so on. In addition, image coordinate of some points on the test target should be obtained for the camera calibration, and the method for acquisition of the image coordinates also influence calibration results. In these circumstances, the camera calibration was performed on several situations by using “iWitness”, and the calibration results for each situation were evaluated in this paper.