Using microbiological tracers to assess the impact of winter land use restrictions on the quality of stream headwaters in a small catchment.

Diverse land use activities can elevate risk of microbiological contamination entering stream headwaters. Spatially distributed water quality monitoring carried out across a 17km(2) agricultural catchment aimed to characterize microbiological contamination reaching surface water and investigate whether winter agricultural land use restrictions proved effective in addressing water quality degradation. Combined flow and concentration data revealed no significant difference in fecal indicator organism (FIO) fluxes in base flow samples collected during the open and prohibited periods for spreading organic fertilizer, while relative concentrations of Escherichia coli, fecal streptococci and sulfite reducing bacteria indicated consistently fresh fecal pollution reached aquatic receptors during both periods. Microbial source tracking, employing Bacteroides 16S rRNA gene markers, demonstrated a dominance of bovine fecal waste in river water samples upstream of a wastewater treatment plant discharge during open periods. This contrasted with responses during prohibited periods where human-derived signatures dominated. Differences in microbiological signature, when viewed with hydrological data, suggested that increasing groundwater levels restricted vertical infiltration of effluent from on-site wastewater treatment systems and diverted it to drains and surface water. Study results reflect seasonality of contaminant inputs, while suggesting winter land use restrictions can be effective in limiting impacts of agricultural wastes to base flow water quality.

Assessing soil erosion due to land use change at the Alqueva reservoir surrounding area

Tese de doutoramento, Ciências do Mar, da Terra e do Ambiente, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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.

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.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Land Use Map

This map shows the entire campus master plan and details what each area of land would be used for.