Almost 70% of Japan’s total land area is covered in forest, and it makes Japan the world’s leading forest country. However, decline of the forest industry has become a serious problem. “Systematic and efficient protection, growth and use of the forest” is required to resolve the issues surrounding the forest of Japan. Thus, it is vital to accurately monitor the past, present and future forest. In recent years, airborne laser survey, and utilizing that data for terrain analysis and forest resources information analysis is spreading. In addition, forest monitoring technology has evolved with time, and choosing the most appropriate technique depending on the purpose is required. This paper introduces forest monitoring technology using waveform recording type aircraft LiDAR, the cutting edge surveying technology.
In the event of a disaster, quickly understanding the situation of different ranges of the area is vital. In order to understand the situation of the wide area, observation by satellite remote sensing is effective. Our company analyses different types of remote sensing data, including UAV, aircraft, and satellite, in order to understand the situation of the disaster damage. In recent years, high temporal resolution data has been accessible by using various satellite sensors, without being bound by a particular satellite or sensor. In addition, the used data is not only satellite data, but also conventional airborne laser data to understand the situation in more detail. In this paper, we will introduce examples of our company’s various remote sensing techniques used for the disaster response through two case studies, Kanto·Tohoku heavy rain (2015) and Kumamoto earthquake (2016).
AW3DTM, the world’s most precise global 3D map service, became the world’s first five-meter-resolution 3D map covering all global land spaces in April 2016 by using Advanced Land Observing Satellite (ALOS). In addition to five-meter-resolution global map, enhanced service offers a higher-resolution 3D map at half-meter or two-meter resolution, both of which are offered on an on-demand basis using commercial high-resolution satellite imagery. This paper introduces the project history, technical characteristics, service contents, use cases and future prospects of AW3DTM.
If the Phase-Only-Correlation (POC) method, known as an accurate and robust algorithm for image matching, is applied to a satellite image with clouds, only clear areas after cloud screening can be input. However, if the cloud screening is not perfect, the method will be applied to a cloud-contaminated image. For example, it is difficult to perform accurate cloud screening for images created using JAXA’s ALOS-2/Compact Infrared Camera (CIRC) with only a single thermal infrared (TIR) band, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask products are less accurate for some types of surfaces. However, the robustness of the POC method in cloud-contaminated satellite images has not been fully investigated. Thus, in the present paper, we evaluated it, particularly for TIR images, using two approaches. In the first approach, we placed various simulated clouds on actual CIRC images, and evaluated the accuracy of the POC method under cloud conditions that varied in terms of coverage and position. As a result, the gap estimation error was within 0.03 pixels, although the image-to-image similarity (alpha value) decreased and the error increased with increasing cloud coverage. This approach was also applied to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) near-infrared (NIR) images and showed a similar tendency and a gap estimation error of 0.005 pixels or less. In the second approach, we used cloud-contaminated CIRC images as target images and ASTER/TIR images as base images, and the gaps between the CIRC and ASTER images were evaluated by the POC method. As a result, the gap estimation error was somewhat larger than that in the first approach, but was within 0.7 pixels. In conclusion, the POC method is robust against cloud contamination on satellite images if an error of 1 pixel is acceptable. This is useful information for some applications such as automatic satellite image registration and automatic geolocation validation.
We compared a Phased-Array L-band Synthetic Aperture Radar-2 (PALSAR-2) high-pass-filtered image with Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) and Chlorophyll-a (Chl-a) images. The comparison with the MODIS SST images revealed that the positions of line-shaped bright (ridge) patterns in the image correspond to large SST gradients, i.e., SST fronts. The comparison with the Chl-a image revealed some local Chl-a maxima along the synthetic aperture radar (SAR) ridge patterns in the PALSAR-2 contrast image. To comprehensively examine the relationship between the SAR line-shaped bright patterns and the surface currents, we compared the time series of the PALSAR images with the high-frequency radar surface currents. We observed that the positions and strengths of the SAR line-shaped bright patterns generally correspond to those of the current shear, suggesting a general theory that convergence areas induced by a large current shear are brightly imaged through the modulation of ocean surface roughness. The SAR-derived line-shaped bright pattern thus indicates a current rip (shiome) characterized physically as the convergence of surface currents. The effect of background wind fields on the SAR line-shaped bright patterns was also investigated, using SAR-derived wind fields. The results indicated that the SAR line-shaped patterns are not identified under winds stronger than 10 m/s, even when the current shear is large.
A terrestrial laser scanner-based method for estimating the leaf area density (LAD) distribution is examined while considering the degree of penetration of the laser beams into the tree and the influence of wind, which can lead to errors in outdoor measurements. Two Japanese zelkova (Zlkova serrata) trees of 6 m in height were used. Each tree was scanned from four positions, each at a distance of 4.5m from the tree. To evaluate the influence of wind on the estimation accuracy of the LAD distribution, laser-beam-transparent sheets were installed around one tree to block the wind. LAD distributions with a voxel size of 0.3m×0.3m×0.3m were estimated based on a previously developed method in which the contact frequency between laser beams and leaves was calculated. Through these estimations, two different methods for using data acquired from multiple scanning positions were examined. In the first method, all scanned data and the calculated LAD were integrated (Integration). In the second, the LAD was calculated for each scanning position, and the maximum LAD was adopted for each voxel (Selection). The estimated leaf area was compared with the measured area by stratified clipping. When the wind was blocked, the difference in the estimation accuracy between the Integration and Selection methods was small, even though the number of incident laser beams on each voxel in the Selection method was smaller than that in the Integration method. The estimation errors in determining the leaf area for the upper, middle, and lower layers of the tree were 10-15% for both methods. When the wind was not blocked and the wind speed reached 0.5m/s, the LAD was overestimated by both methods, but the difference between the LAD estimated with and without the sheets was within 10% in the Selection method. Conversely, the LAD estimated by the Integration method was 20% greater than that estimated by the Selection method. These results indicate that the Selection method is suitable for estimating the LAD distribution in outdoor spaces.
Sun-synchronous sub-recurrent orbit is a combination of sun-synchronous orbit and sub-recurrent orbit and is the most suitable orbit for Earth observation satellites. A satellite on this orbit regularly passes over the same location on Earth at the same local time. Therefore, the satellite can observe the Earth under the same conditions each time. However, this orbit has a weakness in that the observation frequency is relatively low for high- or medium-spatial-resolution satellites. To overcome this shortcoming, many commercial satellites have a pointing function. In recent years, mini-satellite constellations have attracted attention for their high observation frequency and low launch cost. Novel satellite constellations in non-sun-synchronous orbit have emerged. It is expected that current satellites on sun-synchronous orbit will be constellated with such mini-satellites on non-sun-synchronous orbit. Because non-sun-synchronous orbit has a small inclination, it has disadvantages in that the latitude ranges to be observed are limited and the local observing time at the same observed location varies. However, it has the advantage of making multiple observations on the same day at the same place. It is important to understand the differences in the properties between satellite images captured by satellites on sun-synchronous and non-sun-synchronous orbit in order to develop future applications using both kinds of images. In this research, we conducted a comparison analysis of the radiance spectra of typical objects using multi-temporal images from the Hyperspectral Imager for the Coastal Ocean (HICO) (non-sun-synchronous) and Landsat-8 OLI (sun-synchronous) images. We found that the spectral patterns of the HICO images matched up with those of the Landsat-8 OLI images after the effects caused by different atmospheric conditions and solar and viewing zenith angles were removed. We concluded that there are relatively small differences between satellite images captured by satellites in non-sun-synchronous and sun-synchronous orbit, and that it is important to correct the radiometric effects caused by various solar zenith angles when performing multi-temporal analysis. In the future, it will be necessary to assess the effects due to Bi-Directional Reflectance Distribution Function (BRDF) in different orbits.