Diversity index | EPFL Graph Search

A diversity index is a quantitative measure that reflects how many different types (such as species) there are in a dataset (a community), and that can simultaneously take into account the phylogenetic relations among the individuals distributed among those types, such as richness, divergence or evenness. These indices are statistical representations of biodiversity in different aspects (richness, evenness, and dominance). Effective number of species or Hill numbers When diversity indices are used in ecology, the types of interest are usually species, but they can also be other categories, such as genera, families, functional types, or haplotypes. The entities of interest are usually individual plants or animals, and the measure of abundance can be, for example, number of individuals, biomass or coverage. In demography, the entities of interest can be people, and the types of interest various demographic groups. In information science, the entities can be characters and t

Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data

Qi Chen, Francesco Giuseppe Miglietta

Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we explore whether airborne hyperspectral imagery can be used to predict the alpha diversity of upper canopy trees in a West African forest. The abundance of tree species were collected from 64 plots (each 1250 m(2) in size) within a Sierra Leonean national park, and Shannon-Wiener biodiversity indices were calculated. An airborne spectrometer measured reflectances of 186 bands in the visible and near-infrared spectral range at 1 m(2) resolution. The standard deviations of these reflectance values and their first-order derivatives were calculated for each plot from the c. 1250 pixels of hyperspectral information within them. Shannon-Wiener indices were then predicted from these plot-based reflectance statistics using a machine-learning algorithm (Random Forest). The regression model fitted the data well (pseudo-R-2 = 84.9%), and we show that standard deviations of green-band reflectances and infra-red region derivatives had the strongest explanatory powers. Our work shows that airborne hyperspectral sensing can be very effective at mapping canopy tree diversity, because its high spatial resolution allows within-plot heterogeneity in reflectance to be characterized, making it an effective tool for monitoring forest biodiversity over large geographic scales.

Public Library of Science2014

Innovation capacity of the agricultural sector: network of productive interactions, knowledge transfer and differentiation mechanisms

Camille Marguerite Aouinait

Economic growth is increasingly explained and driven by knowledge acquisition and firmsâ capabilities to adapt to new evolving situations to fit economic, societal and environmental frames. Strategic behavior of private companies in differentiating and promoting their products and services is crucial for their competitiveness. In parallel, public research performed at different territorial levels and by a high diversity of actors is a strategic source of key assets adding value to the firms. External actors operate in a non-linear structure allowing frequent feedback and interactive loops in order to optimise the replies to substantial problems and constantly valorise their resources. These features are explored in the thesis through different projects. This dissertation is motivated by international negotiations in the frame of the GATT agreements and bilaterally between the European Union and Switzerland that are going towards the breakdown of borders, threatening the competitiveness of the Swiss agriculture. Negative externalities will affect small firms composing this agricultural network. Thus, the dissertation is focusing on innovation as a strategic asset to maintain the competitiveness and differentiate the domestic agricultural products. The first research project concentrates on interactions occurring in the Swiss apricot network. We investigate the types of interactions producing innovations that come from different sources that are internal or external to the agricultural production supply chain. We use network theory to model the structure of the domain and understand what is inherent to innovation production thanks to collaborations through an empirical work. In the second research project, we examine whether there is a connection between the issues faced by small companies producing food and the innovative solutions and knowledge generated by research institutions. The importance of solutions to daily activities conducted by companies depends on the nature of the sector. Thus, research projects providing outputs like publications might not specifically target these issues. Moreover, access, awareness and affordability of innovations can be hindering factors for small firms composing a low-technology intensive sector. Gaps of knowledge transfer, innovation and implementation are identified in this setting. In the last research project, we address market failures hampering economic and strategic management decisions encountered in the agricultural sector. We empirically construct two case studies highlighting the necessity of intellectual appropriation mechanisms. We explore the use of patents and regional trademark to add value to the emblematic product of a small region. Organisational and marketing innovations have to be supported and diffused by key stakeholders, aiming a good communication based on criteria that take into account diverse interests of those stakeholders; consumers have to be involved in the innovation process. Furthermore, knowledge transfer, innovation generation, diffusion and implementation rely upon the will of stakeholders to take part in an efficient process of interactions and communication in order to produce and perform useful products and services. Practical implications are levered in the projects presented. Finally, digital technologies are efficient for information exchange and can decrease time and transaction costs. These technologies are explored as part of the solution to small firmsâ

EPFL2019

Geographic concentration of economic activities: on the validation of a distance-based mathematical index to identify optimal locations

Olivier Monod

The present study proposes a validation of a mathematical index Q able to identify optimal geographic places for economic activities, solely based on the location variable. This research work takes its roots in the 1970s with the statistical analysis of spatial patterns, or analysis of point processes, whose main goal is to understand if a resulting spatial distribution of points is due to chance or not. Indeed point objects are commonplace (towns in regions, plants in the landscape, galaxies in space, shops in towns) and the development of specific mathematical tools are useful to understand their own location processes. Spatial point deviations from purely random configurations may be analyzed either by quadrat or by distance methods. An interesting method of the second category – the cumulative function M – was developed recently for evaluating the relative geographic concentration and co-location of industries in a nonhomogeneous spatial framework. On this basis, and having quantified retail store interactions, The French physicist Pablo Jensen elaborated the Q-index to automatically detect promising locations. To test the relevance of this quality index, Jensen used location data from 2003 and 2005 for bakeries in the city of Lyon and discovered that between these two years, shops having closed were located on significantly lower quality sites. Here, using bankruptcy data provided by the Registrar of companies of the State of Valais in Switzerland and by the City Council of Glasgow in Scotland, we implemented a method based on univariate logistic regressions to systematically test for the relevance of the Q-index on the many commercial categories available. We show that the Q-index is reliable, although significance tests did not reach stringent levels. Access to trustable bankruptcy data remains a difficult task.