The use of spot simulation imagery for forestry mapping and management

SPOT simulation imagery was acquired for a test site in the Forest of Dean in Gloucestershire, U.K. This data was qualitatively and quantitatively evaluated for its potential application in forest resource mapping and management. A variety of techniques are described for enhancing the image with the aim of providing species level discrimination within the forest. Visual interpretation of the imagery was more successful than automated classification. The heterogeneity within the forest classes, and in particular between the forest and urban class, resulted in poor discrimination using traditional `per-pixel' automated methods of classification. Different means of assessing classification accuracy are proposed. Two techniques for measuring textural variation were investigated in an attempt to improve classification accuracy. The first of these, a sequential segmentation method, was found to be beneficial. The second, a parallel segmentation method, resulted in little improvement though this may be related to a combination of resolution in size of the texture extraction area. The effect on classification accuracy of combining the SPOT simulation imagery with other data types is investigated. A grid cell encoding technique was selected as most appropriate for storing digitised topographic (elevation, slope) and ground truth data. Topographic data were shown to improve species-level classification, though with sixteen classes overall accuracies were consistently below 50%. Neither sub-division into age groups or the incorporation of principal components and a band ratio significantly improved classification accuracy. It is concluded that SPOT imagery will not permit species level classification within forested areas as diverse as the Forest of Dean. The imagery will be most useful as part of a multi-stage sampling scheme. The use of texture analysis is highly recommended for extracting maximum information content from the data. Incorporation of the imagery into a GIS will both aid discrimination and provide a useful management tool.

Insect pest control research : the analysis of historical trends with special reference to scientometric analysis

The thesis investigates the value of quantitative analyses for historical studies of science through an examination of research trends in insect pest control, or economic entomology. Reviews are made of quantitative studies of science, and historical studies of pest control. The methodological strengths and weaknesses of bibliometric techniques are examined in a special chapter; techniques examined include productivity studies such as paper counts, and relational techniques such as co-citation and co-word analysis. Insect pest control is described. This includes a discussion of the socio-economic basis of the concept of `pest'; a series of classifications of pest control techniques are provided and analysed with respect to their utility for scientometric studies. The chemical and biological approaches to control are discussed as scientific and technological paradigms. Three case studies of research trends in economic entomology are provided. First a scientometric analysis of samples of chemical control and biological control papers; providing quantitative data on institutional, financial, national, and journal structures associated with pest control research fields. Second, a content analysis of a core journal, the Journal of Economic Entomology, over a period of 1910-1985; this identifies the main research innovations and trends, in particular the changing balance between chemical and biological control. Third, an analysis of historical research trends in insecticide research; this shows the rise, maturity and decline of research of many groups of compounds. These are supplemented by a collection of seven papers on scientometric studies of pest control and quantitative techniques for analysing science.

National system of innovation and technological learning:an integrated framework for understanding technological capability development in the Russian forestry sector

One of the issues in the innovation system literature is examination of technological learning strategies of laggard nations. Two distinct bodies of literature have contributed to our insight into forces driving learning and innovation, National Systems of Innovation (NSI) and technological learning literature. Although both literatures yield insights on catch-up strategies of 'latecomer' nations, the explanatory powers of each literature by itself is limited. In this paper, a possible way of linking the macro- and the micro-level approaches by incorporating enterprises as active learning entities into the learning and innovation system is proposed. The proposed model has been used to develop research hypotheses and indicate research directions and is relevant for investigating the learning strategies of firms in less technologically intensive industries outside East Asia.

Efficiency analysis of forestry journals:suggestions for improving journals' quality

In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score. © 2013 Elsevier Ltd.