The Triveneto transhumance: law, land, movement

North Italy's nomadic shepherds are a phenomenon unique in the world. Their nomadic nature is taken to the extreme since they move constantly rather than solely in the winter or the summer, as in the usual nomadism. Their home is on wheels and their territory is the tightly regulated yet sprawling Triveneto area. The Triveneto transhumance moves beyond private/public property divides, and indeed beyond lawful/unlawful distinctions, giving rise to what I have called an animal normativity. Relying on Valentina De Marchi's text 'Fame d'Erba' on the Triveneto transhumance, I show how territory becomes a question of animal hunger, and movement becomes an atmospheric, silent and imperceptible affect that crosses private property boundaries, state law limitations, reservation areas and road networks. This way of being, beyond the usual distinctions, offers an example of an alternative political and legal organisation that brings forth the continuum between the human, the natural and the legal/political.

Self-help, Saving and Suburbanisation - the Birkbeck Freehold Land and Building Societies, their Bank and the London Mechanics’ Institute 1851 – 1911.

The Birkbeck Freehold Land and Building Societies were launched in 1851 in the London Mechanics’ Institute, secured its survival, and eventually replaced its premises with the architectural ‘phantasmagoria’ of the Birkbeck Bank. Prior to its collapse in 1911 ‘the Birkbeck’ was a major element in the English property based financial system and contributed significantly to the suburban growth of London. The Institute, Societies and Bank shared a Utilitarian vision of social progress through self-help that was at times hotly contested by the radical champions of the social classes that they were initially formed to assist. Their parallel histories are attested today by ‘Birkbeck’ toponyms (including roads, pubs and a railway station) in the London landscape.

Marginal Activity Access Cost (MAAC): a new indicator for sustainable Land Use/Transport (LUT) planning

The paper presents the ‘Marginal Activity Access Cost’, an accessibility indicator providing estimation in monetary terms of the impacts on mobility and on the environment of locating a single new activity in a specific zone of the urban area. In the first part of this paper, the new indicator is presented and compared to other accessibility indicators proposed in literature. In the second part, the MAAC is validated through an application to the urban area of Rome. The paper concludes with brief remarks on using the proposed accessibility indicator as index of performance for sustainable spatial planning.

Gentrifying the Peri-urban: Land use Conflicts and institutional dynamics at the Frontier of an Indonesian Metropolis

This paper aims to specify the meaning of gentrification in rapidly peri-urbanising metropolitan regions in the context of Indonesia’s rapid transition to decentralisation and democracy. It discusses a case study of conflict over an environmental revitalisation project in a peri-urban area of Bandung City. The analysis focuses on the political processes, tactics and strategies supporting and opposing peri-urban gentrification and their consequences. The analysis illustrates how these political dynamics mediate the interaction between the movement of capital and the spatial reorganisation of social classes. It is argued that in the context of a peri-urbanising metropolis, gentrification needs to be narrated less in terms of class-based neighbourhood succession and more in terms of competing cross-class coalitions emerging at local and regional levels.

Accessibility Planning tools for sustainable and integrated Land Use/Transport (LUT) development: an application to Rome

The paper fits into the themes of sustainable accessibility planning in urban areas, that can be defined as the integration of transport and land use planning to achieve sustainable development. In particular the study proposes a tool to support the choices of activities location, which is based on a new aggregate (zone-specific) indicator: the ‘Marginal Activity Access Cost’, providing estimation in monetary terms of the impacts on mobility and on the environment of locating one new activity in a specific zone of the urban area. The proposed indicator is validated through an application to the urban area of Rome.

Beach sand and the potential for infectious disease transmission: observations and recommendations

Recent studies suggest that sand can serve as a vehicle for exposure of humans to pathogens at beach sites, resulting in increased health risks. Sampling for microorganisms in sand should therefore be considered for inclusion in regulatory programmes aimed at protecting recreational beach users from infectious disease. Here, we review the literature on pathogen levels in beach sand, and their potential for affecting human health. In an effort to provide specific recommendations for sand sampling programmes, we outline published guidelines for beach monitoring programmes, which are currently focused exclusively on measuring microbial levels in water. We also provide background on spatial distribution and temporal characteristics of microbes in sand, as these factors influence sampling programmes. First steps toward establishing a sand sampling programme include identifying appropriate beach sites and use of initial sanitary assessments to refine site selection. A tiered approach is recommended for monitoring. This approach would include the analysis of samples from many sites for faecal indicator organisms and other conventional analytes, while testing for specific pathogens and unconventional indicators is reserved for high-risk sites. Given the diversity of microbes found in sand, studies are urgently needed to identify the most significant aetiological agent of disease and to relate microbial measurements in sand to human health risk.

Predicting the impacts of climate change on the distribution and conservation of endemic forest land snails of Madeira Island

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.

The use of analytical hierarchy process in spatial decision support system for land use management

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.

Analysis of panoramio photo tags in order to extract land use information

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.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

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.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Land of the rising soy an internationalization plan for nutre to the Japanese Soy milk market

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.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

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.