Development of Methodologies and Tools—The HKKH Partnership Project

High mountains have sensitive social-ecological systems (SESs) characterized by fragility, complexity, and marginality. The local economies of these environments mainly rely on primary production, tourism, and leisure activities; thus human-ecosystem interactions are intricately linked. Many authors stress that this strict relationship must be assisted with a participatory approach involving interested stakeholders in the conceptualization, specification, and synthesis of knowledge and experience into useable information for the express purpose of addressing a problem complex. This paper presents experience garnered with a participatory modeling framework combining hard and soft methodology in 2 case studies: the Sagarmatha National Park and Buffer Zone (Nepal) and the Central Karakoram National Park (Pakistan). The modeling framework was developed based on local stakeholders' demands and needs; it consists of 5 modules, briefly presented here along with their conceptual background. In developing the framework, particular emphasis was given to considering the needs of decision-makers at the local level, rather than simply providing technical solutions to abstract problems. From the development of this modeling process, a need emerged to structure a management-oriented research module in order to generate management knowledge that is both stakeholderrelevant and evidence-based. The application of the framework in the 2 cases studies showed that the modeling can trigger valuable discussion among stakeholders as well as guidance for management-oriented research and feedback loops ensuring validation of knowledge. In addition, the resulting scenarios can help decision-makers in defining pathways for sustainable development in mountain areas, where people's livelihoods are closely dependent on ecosystems. The framework was developed in such a way that it can be replicated in other mountain areas with similar challenges

An Examination Of Small Wind Electric Systems In Michigan.

PhDEnergyEngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/180854/2/7718014.pd

Economic analysis of small wind-energy conversion systems

The financial costs of obtaining electricity from small wind-energy conversion systems are calculated and compared with the cost of electricity from traditional utility companies. A 3 kW rated wind electric system for residential use is examined. The amount of energy from this system is estimated by using a computer-operated simulation model which incorporates wind speeds, residential electricity demands and parameters from the generator, inverter and storage components. Variations in electricity costs as a function of available wind energy, residential consumption patterns and system components and costs are examined. The cost of electricity from small wind-energy conversion systems has considerable variations under differing assumptions or parameters but may, in some cases, be competitive with utility company costs.

Net energy analysis of small wind energy conversion systems

The net energy of a small wind electric conversion system is calculated and compared with the net energy of other electricity sources. Net energy is the amount of energy remaining for consumer use after deducting the energy required to find and upgrade the energy source and construct and maintain the electricity generating system. A 3 kW rated wind electric system for residential use is examined. The amount of energy obtained from this system is estimated by using a computer-operated simulation model which incorporates wind speeds, residential electricity demands and parameters from the generator, inverter and storage components. The net energy gain for this wind system is better than that of other systems with which it is compared.

Radar speckle reduction and derived texture measures for land cover/use classification: a case study

This study examined the appropriateness of radar speckle reduction for deriving texture measures for land cover/use classifications. Radarsat-2 C-band quad-polarised data were obtained for Washington, DC, USA. Polarisation signatures were extracted for multiple image components, classified with a maximum-likelihood decision rule and thematic accuracies determined. Initial classifications using original and despeckled scenes showed despeckled radar to have better overall thematic accuracies. However, when variance texture measures were extracted for several window sizes from the original and despeckled imagery and classified, the accuracy for the radar data was decreased when despeckled prior to texture extraction. The highest classification accuracy obtained for the extracted variance texture measure from the original radar was 72%, which was reduced to 69% when this measure was extracted from a 5 × 5 despeckled image. These results suggest that it may be better to use despeckled radar as original data and extract texture measures from the original imagery