Creative Industries: a Preliminary Insight to their Location Determinants

This paper is about location decisions of Creative Industries and the role played by existent spatial distribution and agglomeration economies of these kinds of activities in order to analyse their location determinants. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new plants. Using Count Data Models, our main results show that location determinants are quite similar between both industries and also both non-creative and creative firms are positively influenced by the specialisation level in Creative Industries of municipalities. Moreover, our results provide evidence that the unobserved ‘creative milieu’ has a limited impact on attracting firms. Keywords: creative industries, creative milieu, count data models, industrial location, agglomeration economies

GPS receivers for georeferencing of spatial variability of soil attributes

The characterization of the spatial variability of soil attributes is essential to support agricultural practices in a sustainable manner. The use of geostatistics to characterize spatial variability of these attributes, such as soil resistance to penetration (RP) and gravimetric soil moisture (GM) is now usual practice in precision agriculture. The result of geostatistical analysis is dependent on the sample density and other factors according to the georeferencing methodology used. Thus, this study aimed to compare two methods of georeferencing to characterize the spatial variability of RP and GM as well as the spatial correlation of these variables. Sampling grid of 60 points spaced 20 m was used. For RP measurements, an electronic penetrometer was used and to determine the GM, a Dutch auger (0.0-0.1 m depth) was used. The samples were georeferenced using a GPS navigation receiver, Simple Point Positioning (SPP) with navigation GPS receiver, and Semi-Kinematic Relative Positioning (SKRP) with an L1 geodetic GPS receiver. The results indicated that the georeferencing conducted by PPS did not affect the characterization of spatial variability of RP or GM, neither the spatial structure relationship of these attributes.

Spatial variability of apparent electrical conductivity and soil properties in a coffee production field

Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

Spatial multicriteria decision analysis for the siting of on-shore wind power in Kemiönsaari

Wind power is a low-carbon energy production form that reduces the dependence of society on fossil fuels. Finland has adopted wind energy production into its climate change mitigation policy, and that has lead to changes in legislation, guidelines, regional wind power areas allocation and establishing a feed-in tariff. Wind power production has indeed boosted in Finland after two decades of relatively slow growth, for instance from 2010 to 2011 wind energy production increased with 64 %, but there is still a long way to the national goal of 6 TWh by 2020. This thesis introduces a GIS-based decision-support methodology for the preliminary identification of suitable areas for wind energy production including estimation of their level of risk. The goal of this study was to define the least risky places for wind energy development within Kemiönsaari municipality in Southwest Finland. Spatial multicriteria decision analysis (SMCDA) has been used for searching suitable wind power areas along with many other location-allocation problems. SMCDA scrutinizes complex ill-structured decision problems in GIS environment using constraints and evaluation criteria, which are aggregated using weighted linear combination (WLC). Weights for the evaluation criteria were acquired using analytic hierarchy process (AHP) with nine expert interviews. Subsequently, feasible alternatives were ranked in order to provide a recommendation and finally, a sensitivity analysis was conducted for the determination of recommendation robustness. The first study aim was to scrutinize the suitability and necessity of existing data for this SMCDA study. Most of the available data sets were of sufficient resolution and quality. Input data necessity was evaluated qualitatively for each data set based on e.g. constraint coverage and attribute weights. Attribute quality was estimated mainly qualitatively by attribute comprehensiveness, operationality, measurability, completeness, decomposability, minimality and redundancy. The most significant quality issue was redundancy as interdependencies are not tolerated by WLC and AHP does not include measures to detect them. The third aim was to define the least risky areas for wind power development within the study area. The two highest ranking areas were Nordanå-Lövböle and Påvalsby followed by Helgeboda, Degerdal, Pungböle, Björkboda, and Östanå-Labböle. The fourth aim was to assess the recommendation reliability, and the top-ranking two areas proved robust whereas the other ones were more sensitive.

Infestation maps and spatial stability of main weed species in maize culture

A study on the spatial distribution of the major weeds in maize was carried out in 2007 and 2008 in a field located in Golegã (Ribatejo region, Portugal). The geo-referenced sampling focused on 150 points of a 10 x 10 m mesh covering an area of 1.5 ha, before herbicide application and before harvest. In the first year, 40 species (21 botanical families) were identified at seedling stage and only 22 during the last observation. The difference in species richness can be attributed to maize monoculture favouring reduction in species number. Three of the most representative species were selected for the spatial distribution analysis: Solanum nigrum, Chenopodium album and Echinochloa crus-galli. The three species showed an aggregated spatial pattern and spatial stability over both years, although the herbicide effect is evident in the distribution of some of them in the space. These results could be taken into account when planning site-specific treatments in maize.

Patterns of spatial distribution in macroalgal communities from tropical lotic ecosystems

Three sampling sites were analysed in each of the following tropical regions: 1) northwestern São Paulo State, representing a disturbed region; 2) Bonito, Mato Grosso do Sul State, representing a hard water region; and 3) Ubatuba, northern costal region of São Paulo State, a well preserved tropical rainforest region. The hard water region had the highest mean values for macroalgal species richness (6.3) and diversity index (H' = 0.62). Northwest and rainforest regions had the highest percent cover values (22.5% and 17.0%, respectively). All sites in the northwest region had one or two dominant species (percent cover significantly higher than the remaining species), characterizing the niche pre-emption distribution pattern. The same pattern was found in two sites of the Atlantic rainforest. The hard water region had dominance of one species in two out of the three sites, but differently from the northwest region, niche overlap values were lower, evidencing a patch distribution. Competition for space was one of the main factors to explain spatial distribution. Overall, sites characterized by niche pre-emption had lower species richness, higher values for niche width and overlap, dominance index and percent cover of dominant species. In contrast, sites characterized by patch distribution had higher species richness and lower values for niche overlap and width, dominance index and percent cover.

Spatial variation in the structure and floristic composition of "restinga" vegetation in southeastern Brazil

We examined large-scale spatial variation of structural parameters and floristic composition in open Clusia scrub, a vegetation type of the Brazilian "restingas" (sandy coastal plain vegetation). This vegetation is organized in islands separated by sandy stretches with sparse herbaceous vegetation. We located 12 sample areas on three consecutive beach ridges, lying parallel to the coastline and at different distances from the ocean, in close proximity to two lagoons (Cabiúnas and Comprida). Each sample area was divided into three strips. We used the line intercept method to sample all woody plants ³ 50 cm tall. We used nested ANOVA to verify structural variation between different sampling scales. TWINSPAN analysis was performed to examine the variation in floristic composition between areas. The overall diversity index was 3.07. Six species are repeatedly dominant throughout the entire sampling area. There was homogeneity in relation to diversity and species richness between beach ridges but not within beach ridges. Floristic composition and structural parameters did not vary in relation to distance from the sea but floristic composition did vary as a function of proximity to Cabiúnas or Comprida lagoon. Differences in plant cover between sample areas may be related to the paleoformation of this sandy coastal plain.

Ecological distribution of stream macroalgae in different spatial scales using taxonomic and morphological groups

We examined the ecological distribution of macroalgal communities in streams using species groups (taxonomic units = algal phyla, and morphological = morphological types) with similar structures and functions instead of the species themselves. The study was conducted from June to July/2007 in two drainage basins located in mid-southern region of Paraná State , Brazil. Evaluations of macroalgal communities took into consideration the following spatial scales: the drainage basin (the Pedras river and Marrecas river basins), shading regime (open and shaded stream segments), mesohabitats (riffles and pools), and microhabitats (sampling units of 0.05m2). A total of 29 taxa (23 subgeneric, one generic, and five vegetative groups) were identified. On these, 12 taxa belong to Chlorophyta, 11 to Cyanobacteria, four to Heterokontophyta, and two to Rhodophyta. The proportions of morphological types were: 24% free filaments, 17.25% mats, tufts, gelatinous colonies, and gelatinous filaments, 7% crusts. In terms of spatial scales, we observed a predominance of Chlorophyta in open stream segments and Cyanobacteria in shaded stream segments, reflecting the loss of competitive advantage of green algae in sites with low energy availability. In the mesohabitats, the morphological types recorded in pools were predominantly poorly adapted to fast currents (free filaments), while those found in riffles (mats, tufts and gelatinous filaments) were highly resistant to fast water flows. As such, the use of species groupings based on algal taxonomy associated with morphological characteristics proved to be useful to understanding the distributions of these organisms in lotic environments.

Evaluation of Location Intelligence exploitation in capital-intensive business

As technology has developed it has increased the number of data produced and collected from business environment. Over 80% of that data includes some sort of reference to geographical location. Individuals have used that information by utilizing Google Maps or different GPS devices, however such information has remained unexploited in business. This thesis will study the use and utilization of geographically referenced data in capital-intensive business by first providing theoretical insight into how data and data-driven management enables and enhances the business and how especially geographically referenced data adds value to the company and then examining empirical case evidence how geographical information can truly be exploited in capital-intensive business and what are the value adding elements of geographical information to the business. The study contains semi-structured interviews that are used to scan attitudes and beliefs of an organization towards the geographic information and to discover fields of applications for the use of geographic information system within the case company. Additionally geographical data is tested in order to illustrate how the data could be used in practice. Finally the outcome of the thesis provides understanding from which elements the added value of geographical information in business is consisted of and how such data can be utilized in the case company and in capital-intensive business.

Location intelligence strategisen päätöksenteon tukena

Kilpailuetua tavoittelevan yrityksen pitää kyetä jalostamaan tietoa ja tunnistamaan sen avulla uusia tulevaisuuden mahdollisuuksia. Tulevaisuuden mielikuvien luomiseksi yrityksen on tunnettava toimintaympäristönsä ja olla herkkänä havaitsemaan muutostrendit ja muut toimintaympäristön signaalit. Ympäristön elintärkeät signaalit liittyvät kilpailijoihin, teknologian kehittymiseen, arvomaailman muutoksiin, globaaleihin väestötrendeihin tai jopa ympäristön muutoksiin. Spatiaaliset suhteet ovat peruspilareita käsitteellistää maailmaamme. Pitney (2015) on arvioinut, että 80 % kaikesta bisnesdatasta sisältää jollakin tavoin viittauksia paikkatietoon. Siitä huolimatta paikkatietoa on vielä huonosti hyödynnetty yritysten strategisten päätösten tukena. Teknologioiden kehittyminen, tiedon nopea siirto ja paikannustekniikoiden integroiminen eri laitteisiin ovat mahdollistaneet sen, että paikkatietoa hyödyntäviä palveluja ja ratkaisuja tullaan yhä enemmän näkemään yrityskentässä. Tutkimuksen tavoitteena oli selvittää voiko location intelligence toimia strategisen päätöksenteon tukena ja jos voi, niin miten. Työ toteutettiin konstruktiivista tutkimusmenetelmää käyttäen, jolla pyritään ratkaisemaan jokin relevantti ongelma. Konstruktiivinen tutkimus tehtiin tiiviissä yhteistyössä kolmen pk-yrityksen kanssa ja siihen haastateltiin kuutta eri strategiasta vastaavaa henkilöä. Tutkimuksen tuloksena löydettiin, että location intelligenceä voidaan hyödyntää strategisen päätöksenteon tukena usealla eri tasolla. Yksinkertaisimmassa karttaratkaisussa halutut tiedot tuodaan kartalle ja luodaan visuaalinen esitys, jonka avulla johtopäätöksien tekeminen helpottuu. Toisen tason karttaratkaisu pitää sisällään sekä sijainti- että ominaisuustietoa, jota on yhdistetty eri lähteistä. Tämä toisen tason karttaratkaisu on usein kuvailevaa analytiikkaa, joka mahdollistaa erilaisten ilmiöiden analysoinnin. Kolmannen eli ylimmän tason karttaratkaisu tarjoaa ennakoivaa analytiikkaa ja malleja tulevaisuudesta. Tällöin ohjelmaan koodataan älykkyyttä, jossa informaation keskinäisiä suhteita on määritelty joko tiedon louhintaa tai tilastollisia analyysejä hyödyntäen. Tutkimuksen johtopäätöksenä voidaan todeta, että location intelligence pystyy tarjoamaan lisäarvoa strategisen päätöksenteon tueksi, mikäli yritykselle on hyödyllistä ymmärtää eri ilmiöiden, asiakastarpeiden, kilpailijoiden ja markkinamuutoksien maantieteellisiä eroavaisuuksia. Parhaimmillaan location intelligence -ratkaisu tarjoaa luotettavan analyysin, jossa tieto välittyy muuttumattomana päätöksentekijältä toiselle ja johtopäätökseen johtaneita syitä on mahdollista palata tarkastelemaan tarvittaessa uudelleen.

Bird depredation of grapes in Niagara vineyards : a novel approach to identifying spatial and temporal trends /

Although local grape growers view bird depredation as a significant economic issue, the most recent research on the problem in the Niagara Peninsula is three decades old. Peer-reviewed publications on the subject are rare, and researchers have struggled to develop bird-damage assessment techniques useful for facilitating management programmes. I used a variation of Stevenson and Virgo's (1971) visual estimation procedure to quantify spatial and temporal trends in bird damage to grapes within single vineyard plots at two locations near St. Catharines, Ontario. I present a novel approach to managing the rank-data from visual estimates, which is unprecedented in its sensitivity to spatial trends in bird damage. I also review its valid use in comparative statistical analysis. Spatial trends in 3 out of 4 study plots confirmed a priori predictions about localisation in bird damage based on optimal foraging from a central location (staging area). Damage to grape clusters was: (1) greater near the edges of vineyard plots and decreased with distance towards the center, (2) greater in areas adjacent to staging areas for birds, and (3) vertically stratified, with upper-tier clusters sustaining more damage than lower-tier clusters. From a management perspective, this predictive approach provides vineyard owners with the ability to identify the portions of plots likely to be most susceptible to bird damage, and thus the opportunity to focus deterrent measures in these areas. Other management considerations at Henry of Pelham were: (1) wind damage to ice-wine Riesling and Vidal was much higher than bird damage, (2) plastic netting with narrow mesh provided more effective protection agsiinst birds than nylon netting with wider mesh, and (3) no trends in relative susceptibility of varietals by colour (red vs green) were evident.

Economic integration in North America: Formal, Informal and Spatial Aspects.

An exemination of a series of indicators of economic integration in the western hemisphere (Canada-USA-Latin America) indicates that it is proceeding under the influence of formal trade agreements and informal forces including technological change, multinational firm rationalization and location strategies, etc.

"What" and "Where" in the intraparietal sulcus : an fMRI study of object identity and location in visual short-term memory

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Heavy metal tolerance patterns of total heterotrophic bacteria isolated from the soils of Mahatma Gandhi University campus, Kottayam, Kerala

Industrialization of our society has led to an increased production and discharge of both xenobiotic and natural chemical substances. Many of these chemicals will end up in the soil. Pollution of soils with heavy metals is becoming one of the most severe ecological and human health hazards. Elevated levels of heavy metals decrease soil microbial activity and bacteria need to develop different mechanisms to confer resistances to these heavy metals. Bacteria develop heavy-metal resistance mostly for their survivals, especially a significant portion of the resistant phenomena was found in the environmental strains. Therefore, in the present work, we check the multiple metal tolerance patterns of bacterial strains isolated from the soils of MG University campus, Kottayam. A total of 46 bacterial strains were isolated from different locations of the campus and tested for their resistant to 5 common metals in use (lead, zinc, copper, cadmium and nickel) by agar dilution method. The results of the present work revealed that there was a spatial variation of bacterial metal resistance in the soils of MG University campus, this may be due to the difference in metal contamination in different sampling location. All of the isolates showed resistance to one or more heavy metals selected. Tolerance to lead was relatively high followed by zinc, nickel, copper and cadmium. About 33% of the isolates showed very high tolerance (>4000μg/ml) to lead. Tolerance to cadmium (65%) was rather low (<100 μg/ml). Resistance to zinc was in between 100μg/ml - 1000μg/ml and the majority of them shows resistance in between 200μg/ml - 500μg/ml. Nickel resistance was in between 100μg/ml - 1000μg/ml and a good number of them shows resistance in between 300μg/ml - 400μg/ml. Resistance to copper was in between <100μg/ml - 500μg/ml and most of them showed resistance in between 300μg/ml - 400μg/ml. From the results of this study, it was concluded that heavy metal-resistant bacteria are widely distributed in the soils of MG university campus and the tolerance of heavy metals varied among bacteria and between locations

Assessing the users’ need for a spatial decision support system of smallholder farming in Kenya

Accurate data of the natural conditions and agricultural systems with a good spatial resolution are a key factor to tackle food insecurity in developing countries. A broad variety of approaches exists to achieve precise data and information about agriculture. One system, especially developed for smallholder agriculture in East Africa, is the Farm Management Handbook of Kenya. It was first published in 1982/83 and fully revised in 2012, now containing 7 volumes. The handbooks contain detailed information on climate, soils, suitable crops and soil care based on scientific research results of the last 30 years. The density of facts leads to time consuming extraction of all necessary information. In this study we analyse the user needs and necessary components of a system for decision support for smallholder farming in Kenya based on a geographical information system (GIS). Required data sources were identified, as well as essential functions of the system. We analysed the results of our survey conducted in 2012 and early 2013 among agricultural officers. The monitoring of user needs and the problem of non-adaptability of an agricultural information system on the level of extension officers in Kenya are the central objectives. The outcomes of the survey suggest the establishment of a decision support tool based on already available open source GIS components. The system should include functionalities to show general information for a specific location and should provide precise recommendations about suitable crops and management options to support agricultural guidance on farm level.