To clarify the characteristics of the thermal control of skin blood flow (SkBF) in individuals with a cold constitution, we examined the cutaneous vasoconstrictor responses in the calf and dorsal ...foot during whole-body and local skin cooling in young women complaining of chilliness (C group) and young women not suffering from it (N group). During whole-body skin cooling, the vasoconstrictor sensitivity in the dorsal foot, but not in the calf, was greater in the C group than in the N group. The C group also showed greater vasoconstrictor responses in the dorsal foot, but not in the calf, during local skin cooling and the iontophoretic application of norepinephrine. These findings suggest that the C group possesses a specific SkBF controlling system that is characterized by higher adrenergic sensitivity for greater cutaneous vasoconstriction in the distal portion of the lower extremities during cold exposure.
Timely information about landslides during or immediately after an event is an invaluable source for emergency response and management. Using an active sensor, synthetic aperture radar (SAR) can ...capture images of the earth’s surface regardless of weather conditions and may provide a solution to the problem of mapping landslides when clouds obstruct optical imaging. The 2018 Hokkaido Eastern Iburi earthquake (Mw 6.6) and its aftershocks not only caused major damage with severe loss of life and property but also induced many landslides across the area. To gain a better understanding of the landslides induced by this earthquake, we proposed a method of landslide mapping using pre- and post-event Advanced Land Observation Satellite 2 Phased Array L-band Synthetic Aperture Radar 2 (ALOS-2 PALSAR-2) images acquired from both descending and ascending orbits. Moreover, the accuracy of the classification results was verified by comparisons with high-resolution optical images, and ground truth data (provided by GSI, Japan). The detected landslides show a good match with the reference optical images by visual comparison. The quantitative comparison results showed that a combination of the descending and ascending intensity-based landslide classification had the best accuracy with an overall accuracy and kappa coefficient of 80.1% and 0.45, respectively.
In earthquake-prone areas, identifying patterns of ground deformation is important before they become latent risk factors. As one of the severely damaged areas due to the 2011 Tohoku earthquake in ...Japan, Urayasu City in Chiba Prefecture has been suffering from land subsidence as a part of its land was built by a massive land-fill project. To investigate the long-term land deformation patterns in Urayasu City, three sets of synthetic aperture radar (SAR) data acquired during 1993–2006 from European Remote Sensing satellites (ERS-1/-2 (C-band)), during 2006–2010 from the Phased Array L-band Synthetic Aperture Radar onboard the Advanced Land Observation Satellite (ALOS PALSAR (L-band)) and from 2014–2017 from the ALOS-2 PALSAR-2 (L-band) were processed by using multitemporal interferometric SAR (InSAR) techniques. Leveling survey data were also used to verify the accuracy of the InSAR-derived results. The results from the ERS-1/-2, ALOS PALSAR and ALOS-2 PALSAR-2 data processing showed continuing subsidence in several reclaimed areas of Urayasu City due to the integrated effects of numerous natural and anthropogenic processes. The maximum subsidence rate of the period from 1993 to 2006 was approximately 27 mm/year, while the periods from 2006 to 2010 and from 2014 to 2017 were approximately 30 and 18 mm/year, respectively. The quantitative validation results of the InSAR-derived deformation trend during the three observation periods are consistent with the leveling survey data measured from 1993 to 2017. Our results further demonstrate the advantages of InSAR measurements as an alternative to ground-based measurements for land subsidence monitoring in coastal reclaimed areas.
Torrential rain triggered by two typhoons hit the Kanto and
Tohoku regions of Japan from 9 to 11 September 2015. Due to the record-breaking
amount of rainfall, several riverbanks were overflowed and ...destroyed,
causing floods over wide areas. The PALSAR-2 sensor on board the ALOS-2
satellite engaged in emergency observations of the affected areas during and
after the heavy rain. Two pre-event and three co-event PALSAR-2 images were
employed in this study to extract flooded areas in the city of Joso, Ibaraki
Prefecture. The backscattering coefficient of the river water was
investigated first using the PALSAR-2 intensity images and a land-cover map
with a 10 m resolution. The inundation areas were then extracted by setting
threshold values for backscattering from water surfaces in the three temporal
synthetic aperture radar (SAR) images. The extracted results were modified by
considering the land cover and a digital elevation model (DEM). Next, the
inundated built-up urban areas were extracted from the changes in SAR
backscattering. The results were finally compared with those from visual
inspections of airborne imagery by the Geospatial Information Authority of
Japan (GSI), and more than 85 % of the maximum inundation areas were
extracted successfully.
This study evaluates the performance of a Support Vector Machine (SVM) classifier to learn and detect changes in single- and multi-temporal X- and L-band Synthetic Aperture Radar (SAR) images under ...varying conditions. The purpose is to provide guidance on how to train a powerful learning machine for change detection in SAR images and to contribute to a better understanding of potentials and limitations of supervised change detection approaches. This becomes particularly important on the background of a rapidly growing demand for SAR change detection to support rapid situation awareness in case of natural disasters. The application environment of this study thus focuses on detecting changes caused by the 2011 Tohoku earthquake and tsunami disaster, where single polarized TerraSAR-X and ALOS PALSAR intensity images are used as input. An unprecedented reference dataset of more than 18,000 buildings that have been visually inspected by local authorities for damages after the disaster forms a solid statistical population for the performance experiments. Several critical choices commonly made during the training stage of a learning machine are being assessed for their influence on the change detection performance, including sampling approach, location and number of training samples, classification scheme, change feature space and the acquisition dates of the satellite images. Furthermore, the proposed machine learning approach is compared with the widely used change image thresholding. The study concludes that a well-trained and tuned SVM can provide highly accurate change detections that outperform change image thresholding. While good performance is achieved in the binary change detection case, a distinction between multiple change classes in terms of damage grades leads to poor performance in the tested experimental setting. The major drawback of a machine learning approach is related to the high costs of training. The outcomes of this study, however, indicate that given dynamic parameter tuning, feature selection and an appropriate sampling approach, already small training samples (100 samples per class) are sufficient to produce high change detection rates. Moreover, the experiments show a good generalization ability of SVM which allows transfer and reuse of trained learning machines.
This study demonstrates the use of multi-temporal LiDAR data to extract collapsed buildings and to monitor their removal process in Minami-Aso village, Kumamoto prefecture, Japan, after the April ...2016 Kumamoto earthquake. By taking the difference in digital surface models (DSMs) acquired at pre- and post-event times, collapsed buildings were extracted and the results were compared with damage survey data by the municipal government and aerial optical images. Approximately 40% of severely damaged buildings showed a reduction in the average height within a reduced building footprint between the pre- and post-event DSMs. Comparing the removal process of buildings in the post-event periods with the damage classification result from the municipal government, the damage level was found to affect judgements by the owners regarding demolition and removal.
We examined whether an aerobic exercise intervention in young women with cold sensitivity symptoms improves sleep quality and decreases cold complaints. Furthermore, we examined the association with ...increased foot skin temperature (Tsk) before falling asleep and decrease in sensitivity to cold in the brain. We recruited 16 female adult volunteers who had cold sensitivity and were not engaged in daily exercise training, and they were divided into an exercise group (EXE) and a control group (CON). EXE was given a 2-week exercise intervention that consisted mainly of walking and jogging. Before and after the intervention, temperature sensation and body temperature parameters were measured just before bedtime; electroencephalogram measurements were taken during sleep; and subjective sleep surveys, including Oguri-Shirakawa-Azumi (OSA) sleep inventory (middle-aged and aged version) and visual analogue scale (VAS), were conducted immediately after waking up. All experiments were performed in the winter season. In EXE, overall and foot warmth and comfort increased (p < 0.05) after the 2-week exercise intervention. The exercise intervention also decreased (p < 0.05) the scores for cold feeling in the fingertips, feet, and toes. In the OSA sleep inventory, factor IV (refreshing) and factor V (sleep length) were increased (p < 0.05) by the exercise intervention. Subjective sleep quality evaluated by VAS increased (p < 0.05) with exercise intervention. The exercise intervention in EXE shortened middle awake time after sleep onset (p < 0.05) and prolonged deep sleep length (p < 0.05). The exercise intervention increased (p < 0.05) alpha-wave power before sleep. In CON, all variables remained unchanged throughout the 2-week control period. Short-term aerobic exercise alleviated peripheral extremity cold sensitivity symptoms and improved subjective sleep quality. Our findings suggest that these improvements were not due to increased Tsk at rest before bedtime but to decreased sensitivity to cold in the brain that was expressed as increased alpha activity.
Typhoon Hagibis passed through Japan on October 12, 2019, bringing heavy rainfall over half of Japan. Twelve banks of seven state-managed rivers collapsed, flooding a wide area. Quick and accurate ...damage proximity maps are helpful for emergency responses and relief activities after such disasters. In this study, we propose a quick analysis procedure to estimate inundations due to Typhoon Hagibis using multi-temporal Sentinel-1 SAR intensity images. The study area was Ibaraki Prefecture, Japan, including two flooded state-managed rivers, Naka and Kuji. First, the completely flooded areas were detected by two traditional methods, the change detection and the thresholding methods. By comparing the results in a part of the affected area with our field survey, the change detection was adopted due to its higher recall accuracy. Then, a new index combining the average value and the standard deviation of the differences was proposed for extracting partially flooded built-up areas. Finally, inundation maps were created by merging the completely and partially flooded areas. The final inundation map was evaluated via comparison with the flooding boundary produced by the Geospatial Information Authority (GSI) and the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) of Japan. As a result, 74% of the inundated areas were able to be identified successfully using the proposed quick procedure.
This study examines a novel extraction method for SAR imagery data of widespread flooding, particularly in the Chao Phraya river basin of central Thailand, where flooding occurs almost every year. ...Because the 2011 flood was among the largest events and of a long duration, a large number of satellites observed it, and imagery data are available. At that time, RADARSAT-2 data were mainly used to extract the affected areas by the Thai government, whereas ThaiChote-1 imagery data were also used as optical supporting data. In this study, the same data were also employed in a somewhat different and more detailed manner. Multi-temporal dual-polarized RADARSAT-2 images were used to classify water areas using a clustering-based thresholding technique, neighboring valley-emphasis, to establish an automated extraction system. The novel technique has been proposed to improve classification speed and efficiency. This technique selects specific water references throughout the study area to estimate local threshold values and then averages them by an area weight to obtain the threshold value for the entire area. The extracted results were validated using high-resolution optical images from the GeoEye-1 and ThaiChote-1 satellites and water elevation data from gaging stations.
A series of earthquakes hit Kumamoto Prefecture, Japan, continuously over a period of two days in April 2016. The earthquakes caused many landslides and numerous surface ruptures. In this study, two ...sets of the pre- and post-event airborne Lidar data were applied to detect landslides along the Futagawa fault. First, the horizontal displacements caused by the crustal displacements were removed by a subpixel registration. Then, the vertical displacements were calculated by averaging the vertical differences in 100-m grids. The erosions and depositions in the corrected vertical differences were extracted using the thresholding method. Slope information was applied to remove the vertical differences caused by collapsed buildings. Then, the linked depositions were identified from the erosions according to the aspect information. Finally, the erosion and its linked deposition were identified as a landslide. The results were verified using truth data from field surveys and image interpretation. Both the pair of digital surface models acquired over a short period and the pair of digital terrain models acquired over a 10-year period showed good potential for detecting 70% of landslides.
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