Geostatistical determination of heavy-metal distribution in a contaminated site - A case study

A two stage sampling strategy is necessary in order to optimize the study of distribution of pollution in soils and groundwater. First, detailed sampling from a limited area coupled with statistical analysis of the data are used to determine the microvariability of the parameter(s). The results from this detailed analysis are then used to calculate the optimal spacing between samples for the larger scale study. This two stage sampling strategy can result in significant financial savings during subsequent soil or groundwater remediation. This combined sampling and statistical analysis approach is illustrated with an example from a heavy metal contaminated site

Estimating urban population patterns from stereo-satellite imagery

With more than half of the world’s population living in towns and cities, urban areas get more and more into the focus of humanitarian relief organisations such as ICRC, Médecins sans Frontières (MSF), or SOS Children’s Villages. A key information required for almost any intervention is an estimation of the population numbers for the towns and cities where these organisations operate in. As census data are usually not available or outdated, population numbers have to be estimated by alternative methods such as remote sensing. To do that built-up densities are estimated from high-resolution image data and population numbers are disaggregated proportional to the densities in a top-down approach. Alternatively, population counts per density unit can be aggregated following a bottom-up approach. Both approaches were tested applying normalised Digital Surface Models (nDSM) derived from tri-stereo Pléiade images for Salzburg, Austria and Port-au-Prince, Haiti; the former for testing the quality and stability of the approach in a well-known setting, the latter for testing the approach in a critical environment. Key findings are that satellite-derived nDSMs provide sufficient accuracy for estimating population distributions, as long as reliable information is available for the separation of residential and non-residential urban areas

Wetlands, livelihoods and human health

In developing countries millions of people live a life of subsistence agriculture, mired in poverty, with limited access to basic human needs, such as food and water. Under such circumstances wetlands, through the provision of a range of direct and indirect ecosystem services, play a vital role in supporting and sustaining peoples’ livelihoods and hence, their health. This chapter discusses the role of wetlands in the context of the sustainable livelihoods framework in which wetlands are viewed as an asset for the rural poor in the form of “natural capital”. The framework is used to illustrate how ecosystem services, livelihoods and health are entwined and how the ecosystem services provided by wetlands can be converted to human health either directly or via other livelihood assets. It highlights the contributions that wetlands make to basic human needs and, either directly or through transformations to other forms of livelihood capital, the support they provide to livelihoods and overall well-being