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The majority of the aboveground biomass on the Earth’s land surface is stored in forests. Thus, forest biomass plays a critical role in the global carbon cycle. Yet accurate estimate of forest aboveground biomass (FAGB) remains elusive. This study proposed a new conceptual model to map FAGB using remotely sensed data from multiple sensors. The conceptual model, which provides guidance for selecting remotely sensed data, is based on the principle of estimating FAGB on the ground using allometry, which needs species, diameter at breast height (DBH), and tree height as inputs. Based on the conceptual model, we used multiseasonal Landsat images to provide information about species composition for the forests in the study area, LiDAR data for canopy height, and the image texture and image texture ratio at two spatial resolutions for tree crown size, which is related to DBH. Moreover, we added RaDAR data to provide canopy volume information to the model. All the data layers were fed to a Random Forest (RF) regression model. The study was carried out in eastern North Carolina. We used biomass from the USFS Forest Inventory and Analysis plots to train and test the model performance. The best model achieved an R2 of 0.625 with a root mean squared error (RMSE) of 18.8 Mg/ha (47.6%) with the “out-of-bag” samples at 30 × 30 m spatial resolution. The top five most important variables include the 95th, 85th, 75th, and 50th percentile heights of the LiDAR points and their standard deviations of 85th heights. Numerous features from multiseasonal Sentinel-1 C-Band SAR, multiseasonal Landsat 8 imagery along with image texture features from very high-resolution imagery were selected. But the importance of the height metrics dwarfed all other variables. More tests of the conceptual model in places with a broader range of biomass and more diverse species composition are needed to evaluate the importance of other input variables.

The extent to which education provides protection in the face of a large-scale natural disaster is investigated. Using longitudinal population-representative survey data collected in two provinces on the island of Sumatra, Indonesia, before and after the 2004 Indian Ocean tsunami, we examine changes in a broad array of indicators of well-being of adults. Focusing on adults who were living, before the tsunami, in areas that were subsequently severely damaged by the tsunami, better educated males were more likely to survive the tsunami, but education is not predictive of survival among females. Education is not associated with levels of post-traumatic stress among survivors 1 year after the tsunami, or with the likelihood of being displaced. Where education does appear to play a role is with respect to coping with the disaster over the longer term. The better educated were far less likely than others to live in a camp or other temporary housing, moving, instead, to private homes, staying with family or friends, or renting a new home. The better educated were more able to minimize dips in spending levels following the tsunami, relative to the cuts made by those with little education. Five years after the tsunami, the better educated were in better psycho-social health than those with less education. In sum, education is associated with higher levels of resilience over the longer term.

Over 130,000 people died in the 2004 Indian Ocean tsunami. The correlates of survival are examined using data from the Study of the Tsunami Aftermath and Recovery (STAR), a population-representative survey collected in Aceh and North Sumatra, Indonesia, before and after the tsunami. Children, older adults and females were the least likely to survive. Whereas socio-economic factors mattered relatively little, the evidence is consistent with physical strength playing a role. Pre-tsunami household composition is predictive of survival and suggests that stronger members sought to help weaker members: men helped their wives, parents and children, while women helped their children.

Understanding of human vulnerability to environmental change has advanced in recent years, but measuring vulnerability and interpreting mobility across many sites differentially affected by change remains a significant challenge. Drawing on longitudinal data collected on the same respondents who were living in coastal areas of Indonesia before the 2004 Indian Ocean tsunami and were reinterviewed after the tsunami, this article illustrates how the combination of population-based survey methods, satellite imagery and multivariate statistical analyses has the potential to provide new insights into vulnerability, mobility, and impacts of major disasters on population well-being. The data are used to map and analyze vulnerability to post-tsunami displacement across the provinces of Aceh and North Sumatra and to compare patterns of migration after the tsunami between damaged areas and areas not directly affected by the tsunami. The comparison reveals that migration after a disaster is less selective overall than migration in other contexts. Gender and age, for example, are strong predictors of moving from undamaged areas but are not related to displacement in areas experiencing damage. In our analyses, traditional predictors of vulnerability do not always operate in expected directions. Low levels of socioeconomic status and education were not predictive of moving after the tsunami, although for those who did move, they were predictive of displacement to a camp rather than a private home. This survey-based approach, although not without difficulties, is broadly applicable to many topics in human-environment research and potentially opens the door to rigorous testing of new hypotheses in this literature.

How are individuals affected when the communities they live in change for the worse? This question is central to understanding neighborhood effects, but few study designs generate estimates that can be interpreted causally. We address issues of inference through a natural experiment, examining posttraumatic stress at multiple time points in a population differentially exposed to the 2004 Indian Ocean tsunami. The data, from the Study of the Tsunami Aftermath and Recovery, include interviews with over 16,000 Indonesian adults before and after the event. These data are combined with satellite imagery, direct observation, and informant interviews to examine the consequences of community destruction for posttraumatic stress. Using multilevel linear mixed models, we show that community destruction worsens post-traumatic stress, net of rigorous controls for individual experiences of trauma and loss. Furthermore, the effect of community destruction persists over time and extends across a wide range of community types.

The 2004 Indian Ocean earthquake, among the largest earthquakes in recorded history, spawned a major tsunami that devastated coastal communities in Aceh, Indonesia. This large-scale, natural disaster resulted in more than 170 000 deaths, displaced half a million people, and devastated large swathes of built infrastructure, arable land, and natural resources along the coast of Aceh. The disaster was followed by one of the largest reconstruction efforts undertaken in any developing country. We aimed to examine the effects of the disaster and subsequent reconstruction on the trajectory of linear child growth in children who were in-utero at the time of the tsunami until 2009–10, when the children were, on average, 5 years of age. The earthquake and tsunami was a completely unanticipated large-scale environmental disaster that resulted in a combination of increased maternal psychosocial stress, reduced access to food, and reduced resources, broadly defined. The disaster was followed by a reconstruction effort that took several years to scale up and eventually resulted in substantial increases in resource availability. Using innovative population-representative longitudinal survey data, the Study of the Tsunami Aftermath and Recovery, which was collected before the tsunami and annually for 5 years after the tsunami, we compare child height after the tsunami of those children who were in utero at the time of the tsunami with cohorts of children not similarly exposed. Using data for 4170 children, in 2006–07, the standardised height of those who were in utero at the time of the tsunami is a third of a standard deviation less than comparison cohorts that were not exposed in utero; the deficit is largest, two-thirds of a standard deviation, for children in the second trimester at the time of the tsunami. By age 5 years, these deficits are eliminated for all children who were in utero at the time of the tsunami except for one group of children. Mothers of 10% of children reported very high levels of post-traumatic stress reactivity; of these children, those exposed during the second trimester of the pregnancy remain about half a standard deviation shorter than the comparison children who were not exposed in utero. These new findings provide evidence of substantial scope for catch-up growth in height for most children after a large-scale natural disaster and extremely successful reconstruction effort. However, some children remain vulnerable, particularly those whose mothers reported very high levels of post-traumatic stress reactivity, suggesting maternal stress is a key pathway for persistent deficits in linear growth. The results have important longer-term implications for future health and well-being. National Institute for Child Health and Human Development and National Institutes on Aging.

Objectives. We assessed the levels and correlates of posttraumatic stress reactivity (PTSR) of more than 20000 adult tsunami survivors by analyzing survey data from coastal Aceh and North Sumatra, Indonesia. Methods. A population-representative sample of individuals interviewed before the tsunami was traced in 2005 to 2006. We constructed 2 scales measuring PTSR by using 7 symptom items from the Post Traumatic Stress Disorder (PTSD) Checklist-Civilian Version. One scale measured PTSR at the time of interview, and the other measured PTSR at the point of maximum intensity since the disaster. Results. PTSR scores were highest for respondents from heavily damaged areas. In all areas, scores declined over time. Gender and age were significant predictors of PTSR; markers of socioeconomic status before the tsunami were not. Exposure to traumatic events, loss of kin, and property damage were significantly associated with higher PTSR scores. Conclusions. The tsunami produced post traumnatic stress reactions across a wide region of Aceh and North Sumatra. Public health will be enhanced by the provision of counseling services that reach not only people directly affected by the tsunami but also those living beyond the area of immediate impact.

We combined data from a population-based longitudinal survey with satellite measures of aerosol levels to assess the impact of smoke from forest fires that blanketed the Indonesian islands of Kalimantan and Sumatra in late 1997 on adult health. To account for unobserved differences between haze and nonhaze areas, we compared changes in the health of individual respondents. Between 1993 and 1997, individuals who were exposed to haze experienced greater increases in difficulty with activities of daily living than did their counterparts in nonhaze areas. The results for respiratory and general health, although more complicated to interpret, suggest that haze had a negative impact on these dimensions of health.

Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth's surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth's surface. High-resolution passive sensors have been used successfully to assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real-time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily < 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space.

Understanding how mortality and fertility are linked is essential to the study of population dynamics. We investigate the fertility response to an unanticipated mortality shock that resulted from the 2004 Indian Ocean tsunami, which killed large shares of the residents of some Indonesian communities but caused no deaths in neighboring communities. Using populationrepresentative multilevel longitudinal data, we identify a behavioral fertility response to mortality exposure, both at the level of a couple and in the broader community. We observe a sustained fertility increase at the aggregate level following the tsunami, which was driven by two behavioral responses to mortality exposure. First, mothers who lost one or more children in the disaster were significantly more likely to bear additional children after the tsunami. This response explains about 13 % of the aggregate increase in fertility. Second, women without children before the tsunami initiated family-building earlier in communities where tsunami-related mortality rates were higher, indicating that the fertility of these women is an important route to rebuilding the population in the aftermath of a mortality shock. Such community-level effects have received little attention in demographic scholarship.