Remote sensing and field assessment of tsunami effects on coastal pond aquaculture in northern Sumatra

An attempt was made to conduct spatial assessment of the pattern and extent of damage to coastal aquaculture ponds along the east coast of Aceh province in Sumatra, Indonesia, resulting from the tsunami event of 26 December 2004. High-resolution satellite imagery, i.e., SPOT-5 multispectral scenes covering the 700 km stretch of the coast, acquired before and after the tsunami, were digitally enhanced and visually interpreted to delineate pockets of aquaculture ponds that were discerned to be damaged and relatively intact. Field checks were conducted at 87 sites in the four eastern coastal districts. The results indicate that SPOT-5 multispectral imagery was minimally sufficient to detect areas of damaged and relatively intact aquaculture ponds, but the 10-m spatial resolution poses limitations to evaluating the extent of pond damage. Nevertheless, the 60 km swath of the imagery makes it reasonably affordable for large-area assessment to identify pockets of severe damage for targeting more detailed assessments. The image maps produced from a mosaic of the SPOT-5 scenes can also serve as base maps for spatial planning in the challenging task of reconstruction and rehabilitation of the disrupted livelihoods of the coastal communities.Remote sensing, Disasters, Spatial analysis, Coastal zone, ISEW, Indonesia, Aceh,

Remote Sensing and Field Assessment of Tsunami Effects on Coastal Pond Aquaculture in Northern Sumatra

An attempt was made to conduct spatial assessment of the pattern and extent of damage to coastal aquaculture ponds along the east coast of Aceh province in Sumatra, Indonesia, resulting from the tsunami event of 26 December 2004. High-resolution satellite imagery, i.e., SPOT-5 multispectral scenes covering the 700 km stretch of the coast, acquired before and after the tsunami, were digitally enhanced and visually interpreted to delineate pockets of aquaculture ponds that were discerned to be damaged and relatively intact. Field checks were conducted at 87 sites in the four eastern coastal districts. The results indicate that SPOT-5 multispectral imagery was minimally sufficient to detect areas of damaged and relatively intact aquaculture ponds, but the 10-m spatial resolution poses limitations to evaluating the extent of pond damage. Nevertheless, the 60 km swath of the imagery makes it reasonably affordable for large-area assessment to identify pockets of severe damage for targeting more detailed assessments. The image maps produced from a mosaic of the SPOT-5 scenes can also serve as base maps for spatial planning in the challenging task of reconstruction and rehabilitation of the disrupted livelihoods of the coastal communities

Charting multidisciplinary research and action priorities towards the conservation and sustainable management of sea turtles in the Pacific ocean : a focus on Malaysia

Conservation, Turtle culture, Malaysia,

TREND AND STATISTICAL ANALYSIS OF ANNUAL MAXIMUM DAILY RAINFALL (AMDR) FOR SARAWAK RIVER BASIN, SARAWAK, MALAYSIA

The Sarawak River Basin is one of the major river basins located in the southern part of Sarawak, Malaysia, and has experienced frequent extreme rainfall resulting in flash floods in recent years. This study aims to carry out trend and statistical analysis of annual maximum daily rainfall (AMDR) for 10 rainfall stations distributed evenly in the basin from 1975 to 2020. From the analysis, the AMDR records high variability for most of the rainfall stations, with the month of January having the highest occurrence of AMDR events. The linear regression plot of the mean AMDR showed a slight decreasing trend over the past four decades. The threshold rainfall value of 180 mm was used to perform frequency analysis, and the result shows that the return period for daily rainfall exceeding 180 mm was 2.71 years. The occurrence probability of the flood event at least once in 1, 2, 3, 4 and 5 years was 0.37, 0.60, 0.75, 0.84 and 0.90, respectively. A frequency curve based on the mean AMDR data with Gumbel distribution fitting was also developed from the current study and can be applied to the planning and design of flood infrastructures in the basin

STORMPAY PAVEMENT USING DIFFERENT WHEEL LOADS

Distress models are required during design to ensure the pavement have a longer service life that is conducted for different axle weight. This research addresses by modeling and analyzing StormPav pavement under various wheel loads to ensure pavement structures can withstand these loads. StormPav pavement is made up of precast concrete with Grade 50, which is also known as the innovative IBS Green Pavement, which has a combination of structural, environmental and economic advantages. The analysis of mechanistic behavior for different structures of pavements and mechanistic behavior of precast StormPav pavements using different wheel loads. WinJULEA and KENPAVE are software used for this research for modeling the real scenario to obtain the deflection, stress, strain and stress of each layer of pavement. It is found that total ESAL increases when there is a heavier truck acting on top of the pavement, and precast StormPav pavement receives the lowest total ESAL compared to flexible and rigid pavement. Among various types of pavements, precast StormPav has lesser maximum deflection, which had 65.11% lesser compared to the flexible pavement due to its largest elastic modulus. Besides, when there is loading from a 24-tonne truck acting on top of the precast StormPav pavement, total deflection is 0.761mm and increases 0.064mm (8.345%) when there is loading change to 26-tonne truck, as precast StormPav pavement is made up of concrete grade 50, which can resist to heavier loading. Precast StormPav pavements have the highest maximum allowable load repetitions to prevent fatigue cracking due to their increased flexural strength, which enables them to withstand greater stresses above the structure. As a result, it can be concluded that precast StormPav pavement is a viable alternative to the pavement because it requires less time for construction and sustains less damage when subjected to heavier loads

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors