Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms–Case Study of Evergreen Conifer Planted Forests in Japan

The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing use of terrestrial laser scanning (TLS), and emerging trends in the use of unmanned aerial systems (UASs) highlight the importance of modern technologies in the realm of forest observation. Each technology has different advantages, and this work seeks to incorporate multiple satellite, TLS- and UAS-based remote sensing data sets to improve the ability to estimate forest structure parameters. In this paper, two regression analysis approaches are considered for the estimation: random forest regression (RFR) and support vector regression (SVR). To collect the dependent variable, in situ measurements of individual tree parameters (tree height and diameter at breast height (DBH)) were taken in a Japanese cypress forest using the nondestructive TLS method, which scans the forest to obtain dense and accurate point clouds under the tree canopy. Based on the TLS data, the stem volume was then computed and treated as ground truth information. Topographic and UAS information was then used to calculate various remotely sensed explanatory variables, such as canopy size, canopy cover, and tree height. Canopy cover and canopy shapes were computed via the orthoimages derived from the UAS and watershed segmentation method, respectively. Tree height was computed by combining the digital surface model (DSM) from the UAS and the digital terrain model (DTM) from the TLS data. Topographic variables were computed from the DTM. The backscattering intensity in the satellite imagery was obtained based on L-band (Advanced Land Observing Satellite-2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2)) and C-band (Sentinel-1) synthetic aperture radar (SAR). All satellite (10–25 m resolution), TLS (3.4 mm resolution) and UAS (2.3–4.6 cm resolution) data were then combined, and RFR and SVR were trained; the resulting predictive powers were then compared. The RFR method yielded fitting R2 up to 0.665 and RMSE up to 66.87 m3/ha (rRMSE = 11.95%) depending on the input variables (best result with canopy height, canopy size, canopy cover, and Sentinel-1 data), and the SVR method showed fitting R2 up to 0.519 and RMSE up to 80.12 m3/ha (rRMSE = 12.67%). The RFR outperformed the SVR method, which could delineate the relationship between the variables for better model accuracy. This work has demonstrated that incorporating various remote sensing data to satellite data, especially adding finer resolution data, can provide good estimates of forest parameters at a plot level (10 by 10 m), potentially allowing advancements in precision forestry

Developing a data-sharing system for geospatial research: A case study on the Joint Research Assist System (JoRAS)

This study demonstrates a framework for joint research at a university research center that supports research in the geospatial information sciences. Here we examine the improvements in an Internet-based spatial data infrastructure and data-sharing system through its long-term operation. In the original system for this framework (the Spatial Data Infrastructure System or SDIS), the purpose was to make accessing spatial data easier for academic researchers. However, after ten years of service, it was still experiencing challenges, such as increased human costs and inconveniences from its operation, which were no longer negligible. In response, the system was rebuilt in 2010 as a new Joint Research Assist System (JoRAS) by reviewing and changing its design to address the challenges. Two years after the establishment of the JoRAS, its effectiveness and the emerging challenges demanded further improvements. This study summarizes the challenges of the former SDIS and the improvements made to transform it into the new JoRAS. The user statistics and its interpretations are then presented. This case study provides a guide to scientists and practitioners who are designing similar systems

Cloning of two members of the calcitonin-family receptors from stingray, Dasyatis akajei: Possible physiological roles of the calcitonin family in osmoregulation

In cartilaginous fish, two cDNAs encoding calcitonin-family receptors were isolated for the first time from the stingray brain. The open reading frame of one receptor cDNA coded a 525-amino acid protein. The amino acid identity of this receptor to human calcitonin-receptor-like receptor (CRLR) is 64.5%, frog CRLR is 64.7%, and flounder CRLR is 61.2% and this was higher than to human calcitonin receptor (CTR) (46.1%), frog CTR (54.7%), and flounder CTR (48.9%). We strongly suggested that this receptor is a ray CRLR based on phylogenetic analysis. In case of the second receptor, amino acid identity among CRLRs (human 50.5%, frog 50.7%, flounder 48.0%) and CTRs (human 43.2%, frog 49.1%, flounder 41.8%) was similar. From phylogenetic analysis of both CRLRs and CTRs, we believe that this receptor is ray CTR. The expression of ray CRLR mRNA was predominantly detected in the nervous system (brain) and vascular system (atrium, ventricle, and gill), which reflects the similar localization of CGRP in the nervous and vascular systems as mammals. It was observed that the second receptor was expressed in several tissues, namely cartilage, brain, pituitary gland, gill, atrium, ventricle, pancreas, spleen, liver, gall bladder, intestine, rectal gland, kidney, testis and ovary. This localization pattern was very similar to flounder CTR. Both receptor mRNAs were strongly expressed in the gill. This suggests that the calcitonin-family members are involved in the osmoregulation of stingray as this fish is known to be euryhaline. When a stingray was transferred to diluted seawater (20% seawater), the expression of both receptors significantly decreased in the gill. Similar results were obtained in the kidney of the stingray. Thus, our cloning and isolation of both receptors in the stingray will be helpful for elucidation of their physiological role(s) such as osmoregulation including calcium metabolism of cartilaginous fish. © 2012 Elsevier B.V

Parathyroid hormone 1 (1-34) acts on the scales and involves calcium metabolism in goldfish

金沢大学環日本海域環境研究センターThe effect of fugu parathyroid hormone 1 (fugu PTH1) on osteoblasts and osteoclasts in teleosts was examined with an assay system using teleost scale and the following markers: alkaline phosphatase (ALP) for osteoblasts and tartrate-resistant acid phosphatase (TRAP) for osteoclasts. Synthetic fugu PTH1 (1-34) (100 pg/ml-10 ng/ml) significantly increased ALP activity at 6 h of incubation. High-dose (10 ng/ml) fugu PTH1 significantly increased ALP activity even after 18 h of incubation. In the case of TRAP activity, fugu PTH1 did not change at 6 h of incubation, but fugu PTH1 (100 pg/ml-10 ng/ml) significantly increased TRAP activity at 18 h. Similar results were obtained for human PTH (1-34), but there was an even greater response with fugu PTH1 than with human PTH. In vitro, we demonstrated that both the receptor activator of the NF-κB ligand in osteoblasts and the receptor activator NF-κB mRNA expression in osteoclasts increased significantly by fugu PTH1 treatment. In an in vivo experiment, fugu PTH1 induced hypercalcemia resulted from the increase of both osteoblastic and osteoclastic activities in the scale as well as the decrease of scale calcium contents after fugu PTH1 injection. In addition, an in vitro experiment with intramuscular autotransplanted scale indicated that the ratio of multinucleated osteoclasts/mononucleated osteoclasts in PTH-treated scales was significantly higher than that in the control scales. Thus, we concluded that PTH acts on osteoblasts and osteoclasts in the scales and regulates calcium metabolism in goldfish. © 2011 Elsevier Inc. All rights reserved

A dehydrated space-weathered skin cloaking the hydrated interior of Ryugu

Without a protective atmosphere, space-exposed surfaces of airless Solar System bodies gradually experience an alteration in composition, structure and optical properties through a collective process called space weathering. The return of samples from near-Earth asteroid (162173) Ryugu by Hayabusa2 provides the first opportunity for laboratory study of space-weathering signatures on the most abundant type of inner solar system body: a C-type asteroid, composed of materials largely unchanged since the formation of the Solar System. Weathered Ryugu grains show areas of surface amorphization and partial melting of phyllosilicates, in which reduction from Fe3+ to Fe2+ and dehydration developed. Space weathering probably contributed to dehydration by dehydroxylation of Ryugu surface phyllosilicates that had already lost interlayer water molecules and to weakening of the 2.7 µm hydroxyl (–OH) band in reflectance spectra. For C-type asteroids in general, this indicates that a weak 2.7 µm band can signify space-weathering-induced surface dehydration, rather than bulk volatile loss

Volumetric Change Detection in Bedrock Coastal Cliffs Using Terrestrial Laser Scanning and UAS-Based SfM

Three-dimensional (3D) morphological changes in rocky coasts need to be precisely measured for protecting coastal areas and evaluating the associated sediment dynamics, although volumetric measurements of bedrock erosion in rocky coasts have been limited due to the lack of appropriate measurement methods. Here we carried out repeat surveys of the 3D measurements of a small coastal island using terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry with an unmanned aerial system (UAS) for 5 years. The UAS-SfM approach measures the entire shape of the island, whereas the TLS measurement enables to obtain more accurate morphological data at a scale of centimeters on the land side. The multitemporal TLS-derived data were first aligned in timeline by the iterative closest point (ICP) method and they were used as positionally correct references. The UAS-SfM data were then aligned to each of the TLS-derived data by ICP to improve its positional accuracy. The changed areas for each period was then extracted from the aligned UAS-derived point clouds and were converted to 3D mesh polygons, enabling a differential volume estimate (DVE). The DVE for each period was revealed to be from 3.1 to 77.2 m(3)/month. These changes are rapid enough to force the coastal bedrock island to disappear in 30 years. The temporal variations in the DVE is roughly associated with those in the frequency of high tidal waves