In this study, we proposed a robust full-waveform LiDAR data analysis technique which increases vegetation, canopy and ground detection compared to traditional discrete-return laser system. The full-waveform data is, at first, smoothed by a Finite-duration Impulse Response filter in order to remove high-frequency noise, and consequently, low-frequency noise is removed by setting a threshold. Peak detection is adapted to the improved full-waveform data by using Gaussian decomposition to detect reflective pulse returns. The quantitative evaluation of the increment in total returns and ground returns from the proposed method compared to the discrete-return laser system is performed. The variability in the ground point detection in different forest types and under varying seasonal conditions has also been analyzed. The influence of the increased ground point detection due to the full-waveform analysis in the accuracy of LiDAR derived Digital Terrain Model under varying seasonal conditions is also studied. Moreover, the multiple influences of seasonal conditions, forest types and topographical conditions are discussed in detailed.
To understand global climate change, it is important to monitor the temporal and spatial distributions of vegetation. Digital cameras are relatively inexpensive to operate, and have small labor requirements, allowing the detection of subtle seasonal variation at high spatial resolution. Recent studies have reported camera-based indices that are calculated from the digital values of blue, green and red are useful to grasp the seasonal variation of vegetation phenology such as leaf expansion or fall. To examine this possibility, we investigated the characteristics of seasonal variation of camera-based indices for Larix kaempferi. Our camera adjusts the white balance automatically so that the 3 color components are modified by the lighting conditions. By normalizing respective components with their arithmetic mean, the dispersion becomes smaller than the raw digital value. However, the influence of solar radiation remains. We surveyed the relationship between the 3 components and solar radiation, and developed new vegetation indices independent of solar radiation by utilizing the normalized components. These indices are very useful for the analysis of seasonal change of Larix kaempferi.
The greenery in the field of vision is a rate of the area of the tree, the grass, the hedge, the planting box, and the wall greening to the area of field of view. It is used for the evaluation of green quantity in urban landscape. However, the greenery in the field of vision is not suitable for the regional area evaluation of the green landscape because it measures for the specific point. This research defined the three-dimensional greenery in the field of vision by a computer graphics using a voxel model, which extended the conventional greenery in the field of vision for the regional area evaluation. First, the longest viewing distance suitable for building the three dimensional field of view was estimated and we got the 100 m as optimal value. Then, we calculated the Pearson product-moment correlation coefficient for the p-value test between the proposed index and the surveyed conventional greenery in the field of vision for Shibuya, Tokyo. We recognize the positive correlation (|r| = 0.851 > 0.811 = r0.05) between paired samples. Finally, we calculated the horizontal and the vertical distribution of the proposed index and we confirmed that the proposed index could conjugate for planning of the greening in urban space as a result.
Nishinoshima is a volcanic island located at about 900 km south from Tokyo. On November 20, 2013, an appearance of the new land with the volcanic activity was found near Nishinoshima. Nishinoshima has continued active volcanic activity after this, and the island is expanding day by day. Observation of Nishinoshima is carried out continually by various sensors carried by satellites and airplanes, and it is valuable record that gives a hold on the process of the growth of the island. In this report, We divided the situation of Nishinoshima which underwent a change by this eruption during the period every two months including a history of Nishinoshima and, using the image which various sensors took during the period, gathered it up as a record of the changes.