890 resultados para land purchase
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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In the last years, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information. This huge amount of data might be hiding a vast geographical richness and therefore research needs to be conducted to explore their potential and use it in the solution of real world problems. In this study we conduct an exploratory analysis of data from the OpenStreetMap initiative. Using the Corine Land Cover database as reference and continental Portugal as the study area, we establish a possible correspondence between both classification nomenclatures, evaluate the quality of OpenStreetMap polygon features classification against Corine Land Cover classes from level 1 nomenclature, and analyze the spatial distribution of OpenStreetMap classes over continental Portugal. A global classification accuracy around 76% and interesting coverage areas’ values are remarkable and promising results that encourages us for future research on this topic.
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Climate change is emerging as one of the major threats to natural communities of the world’s ecosystems; and biodiversity hotspots, such as Madeira Island, might face a challenging future in the conservation of endangered land snails’ species. With this thesis, progresses have been made in order to properly understand the impact of climate on these vulnerable taxa; and species distribution models coupled with GIS and climate change scenarios have become crucial to understand the relations between species distribution and environmental conditions, identifying threats and determining biodiversity vulnerability. With the use of MaxEnt, important changes in the species suitable areas were obtained. Laurel forest species, highly dependent on precipitation and relative humidity, may face major losses on their future suitable areas, leading to the possible extinction of several endangered species, such as Leiostyla heterodon. Despite the complexity of the biological systems, the intrinsic uncertainty of species distribution models and the lack of information about land snails’ functional traits, this analysis contributed to a pioneer study on the impacts of climate change on endemic species of Madeira Island. The future inclusion of predictions of the effect of climate change on species distribution as part of IUCN assessments could contribute to species prioritizing, promoting specific management actions and maximizing conservation investment.
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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.
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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.
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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.
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The development of an effective pricing strategy requires the acquaintance of consumers’ price perception as well as the range of elements that influence the price sensitivity. This paper analyses the relationships between product features, individual characteristics and the level of price increase/decrease that induces the consumers to change their purchase decisions. The results of a dedicated survey show, that price sensitivity, individual preferences, type of product and direction of price change and individual characteristics of consumers (gender, age, professional situation) have a significant impact on a threshold at which people are willing to choose the less attractive, but cheaper alternative to their favorite product or give up the variety in consumption. From a consumer behavior perspective, these findings play a fundamental role in pricing.
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Contém resumo
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Soil conditions under pasture were examined in a range of sites representing the sequence of conversion of forest to pasture at two locations in the vicinity of Ilha de Maracã, Roraima. Comparisons were made with adjacent savana. Soil bulk densities shown to increase after forest clearance and soil chemical data indicate that the initial beneficial effects on nutrient supply of burning forest debris are rather short-lived. Very low levels of available phosphorus prevail in areas of savanna and cultivated pasture of all ages. Variations in the status of older cultivated pastures are mainly attributable to different grazing levelt.
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The geomorphological materials and forms of the Maraca area of Roraima, Brazil are described, an their sgnificance for land development examined. Significant contrasts are noted in areas presently under rainforest and savanna vegetation. Lateritic gravels and extensive shetwash accumulations in savanna areas constrast with incipient or absent plinthite development, few gravels and limited evidence of colluvium under rainforest. Terrain is in general relatively highly-dissected. Slope profiles are characterised, particularly within the savanna zone, by a relatively steep lower concavity. These contrasts are sharply-demarcated by the present savanna/rainforest bondary, unexpectedly in view of the generally accepted hypothesis of repeated contraction an expansion of Amazonian rainforest throughout the Pleistocene. It is concluded that geomorphological conditions in the Maraca area are not favorable for land develoment.
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The aim of this research is to evaluate if a premium beauty brand, in this case, Lancôme, can influence positively the purchase intention from Brazilian young adults, between 18 and 29 years old, consumers of beauty products, by initiating a relationship with a local celebrity or “it” girl on social media. This hypothesis has not been tested, and this research is a first attempt of evaluating it. Additionally, the consumer behavior, brand preferences and social media activeness of this age segment in Brazil are further studied as important insights for beauty brands to conquer these consumers. Results did not confirm the positive influence of local celebrities on this age segment’s purchase intention but several suggestions are made for future research to revisit this topic. Furthermore, there is a significant brand love for M.A.C., an international Lancôme competitor, amongst this target, as well as a probable price sensitivity facing premium beauty brands.
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The present work project studies the next step in the internationalization process of Shoyce, the soy milk products brand of Nutre. In order to select the best target market in the Asia-Pacific for Nutre to export, a sequential screening process was developed using two complementary approaches: preliminary country screening and country ranking, followed by an in-depth analysis of the country ranking first. The analysis revealed Japan as the most attractive country for Shoyce’s international expansion. Potential entry modes in the Japanese soy milk market were then evaluated, whereby direct exporting via a local distributor was found to be the most appropriate.
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During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.
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In the Brazilian Amazon, large areas of abandoned lands may revert to secondary forest. In the process, pioneer tree species have an important role to restore productivity in old fields and improve environmental conditions. To determine potential photosynthesis (Apot), stomatal conductance (g), transpiration (E), and leaf micronutrient concentrations in Ochroma pyramidale (Cav. ex Lam.) Urban a study was carried out in the Brazilian Amazon (01o 51' S; 60o 04' W). Photosynthetic parameters were measured at increasing [CO2], saturating light intensity (1 mmol (photons) m-2 s-1), and ambient temperature. The rate of electron-transport (J), Apot,and water-use efficiency (WUE) increased consistently at increasing internal CO2 concentration (Ci). Conversely, increasing [CO2] decreased gs, E, and photorespiration (Pr). At the CO2-saturated region of the CO2 response curve (1.1 mmol (CO2) mol-1(air), J was 120 μmol (e-) m-2s-1 and Apot reached up to 24 μmol (CO2) m-2s-1. Likewise, at saturating C1 g and E were 30 and 1.4 mmol (H2O) m-2s-1, respectively, and P 2 r about 1.5 μmol (CO2) m-2s-1. Foliar nutrients were 185, 134, 50, and 10 μmol (element) m-2 (leaf area) for Fe, Mn, Zn, and Cu, respectively. It was concluded that [CO ] probably limits light saturated photosynthesis in this site. Furthermore, from a nutritional point of view, the low Fe to Cu ratio (15:1) may reflect nutritional imbalance in O. pyramidale at this site.