Purple Medicine

In response to a broad set of complex national security challenges of the twenty-first century, the Quadrennial Defense Review (QDR) report of Febru- ary 2006 advised that all the organizations, processes, and practices within the Department of Defense be given a high degree of agility, flexibility, responsive- ness, and ultimately effectiveness in supporting the joint war fighter and future national defense goals

What does airborne LiDAR really measure in upland ecosystems?

Copyright © 2014 John Wiley & Sons, Ltd.Airborne laser scanning systems (Light Detection And Ranging, LiDAR) are very well suited to the study of landscape and vegetation structure over large extents. Spatially distributed measurements describing the three-dimensional character of landscape surfaces and vegetation architecture can be used to understand eco-geomorphic and ecohydrological processes, and this is particularly pertinent in peatlands given the increasing recognition that these landscapes provide a variety of ecosystem services (water provision, flood mitigation and carbon sequestration). In using LiDAR data for monitoring peatlands, it is important to understand how well peatland surface structures (with fine length scales) can be described. Our approach integrates two laser scanning technologies, namely terrestrial laser scanning (TLS) and airborne LiDAR surveys, to assess how effective airborne LiDAR is at measuring these fine-scale microtopographic ecohydrological structures. By combining airborne and TLS, we demonstrate an improved spatial understanding of the signal measured by the airborne LiDAR. Critically, results demonstrate that LiDAR digital surface models are subject to specific errors related to short-sward ecosystem structure, causing the vegetation canopy height and surface-drainage network depth to be underestimated. TLS is shown to be effective at describing these structures over small extents, allowing the information content and accuracy of airborne LiDAR to be understood and quantified more appropriately. These findings have important implications for the appropriate degree of confidence ecohydrologists can apply to such data when using them as a surrogate for field measurements. They also illustrate the need to couple LiDAR data with ground validation data in order to improve assessment of ecohydrological function in such landscapes. © 2014 John Wiley & Sons, Ltd.South West Water LtdUniversity of Exete

Estimation of shrub biomass by airborne LiDAR data in small forest stands

The presence of shrub vegetation is very significant in Mediterranean ecosystems. However, the difficulty involved in shrub management and the lack of information about behavior of this vegetation means that these areas are often left out of spatial planning projects. Airborne LiDAR (Light Detection And Ranging) has been used successfully in forestry to estimate dendrometric and dasometric variables that allow to characterize forest structure. In contrast, little research has focused on shrub vegetation. The objective of this study was to estimate dry biomass of shrub vegetation in 83 stands of radius 0.5 m using variables derived from LiDAR data. Dominant species was Quercus coccifera, one of the most characteristic species of the Mediterranean forests. Density of LiDAR data in the analyzed stands varied from 2 points/m(2) to 16 points/m(2), being the average 8 points/m(2) and the standard deviation 4.5 points/m(2). Under these conditions, predictions of biomass were performed calculating the mean height, the maximum height and the percentile values 80th, 90th, and 95th derived from LiDAR in concentric areas whose radius varied from 0.50 m to 3.5 m from the center of the stand. The maximum R(2) and the minimum RMSE for dry biomass estimations were obtained when the percentile 95th of LiDAR data was calculated in an area of radius 1.5 m, being 0.48 and 1.45 kg, respectively. For this radius, it was found that for the stands (n = 39) where the DTM is calculated with high accuracy (RMSE lower than 0.20 m) and with a high density of LiDAR data (more than 8 points/m(2)) the R(2) value was 0.73. These results show the possibility of estimating shrub biomass in small areas when the density of LiDAR data is high and errors associated to the DTM are low. These results would allow us to improve the knowledge about shrub behavior avoiding the cost of field measurements and clear cutting actions. (C) 2011 Elsevier B.V. All rights reserved.Estornell Cremades, J.; Ruiz Fernández, LÁ.; Velázquez Martí, B.; Fernández Sarriá, A. (2011). Estimation of shrub biomass by airborne LiDAR data in small forest stands. Forest Ecology and Management. 262(9):1697-1703. doi:10.1016/j.foreco.2011.07.026S16971703262

A Range of Earth Observation Techniques for Assessing Plant Diversity

AbstractVegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS

Do non-monetary incentives for pregnant women increase antenatal attendance among Ethiopian pastoralists?

In a pastoralist setting in Ethiopia, we assessed changes in attendance between the first and subsequent antenatal care (ANC) visits following the implementation of non-monetary incentives in a primary health care centre over a 3-year period from October 2009 to September 2012. Incentives included the provision of a bar of soap,a bucket, a mosquito net, sugar, cooking oil, a jerrycan and a delivery kit. The first ANC visits increased by 48% in the first year to 60% in the second. Subsequent visits did not show a similar pattern due to ruptures in incentive stocks. Incentives appear to increase ANC attendance; however, ruptures in stock should be avoided to sustain the effect