INVENTORY OF MOSQUITOES (DIPTERA: CULICIDAE) IN CONSERVATION UNITS IN BRAZILIAN TROPICAL DRY FORESTS

In Brazil, most studies of the Culicidae family are concentrated in rainforest regions. As such, there is a lack of knowledge regarding the diversity of Culicidae in regions with different climatic and vegetational characteristics. The aim of this study was to compile an inventory of Culicidae in protected areas of the semi-arid region of the state of Minas Gerais, Brazil, in order to better understand the diversity of the family within this region. The study was conducted across four protected areas in the northern region of the state, in tropical dry forest (TDF) fragments. Sampling methods included Shannon trap and CDC light trap, as well as active collection. A total of 11,219 mosquito specimens were collected between August 2008 and July 2012, belonging to 11 genera and 45 species; 15 new records for the state of Minas Gerais were registered, as well as 26 new records for semi-arid regions within the state. The high number of new Culicidae records in this region demonstrates the importance of inventory studies for increasing the knowledge of culicid biodiversity in Minas Gerais, and in particular within semi-arid regions of the state.

Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Is land surface temperature an earthquake precursor?

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Effects of Spatial Pattern of GreenSpace on Land Surface Temperature: A case study on Oasis City Aksu, northwest China

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

An Atlas for the future National Park: Las Cumbres de la Sierra de Guadarrama

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Phylogeography, conservation genetics and parasitology of chimpanzees (Pan troglodytes versus) in Guinea-Bissau, West Africa

Tese de doutoramento em Antropologia, especialidade em Antropologia Biológica e Etnoecologia

Comparative evaluation of aerial lime mortars for architectural conservation

Journal of Cultural Heritage 9 (2008) 338-346

Analysis of urban land use and land cover changes: a case of study in Bahir Dar, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Aplicação de um sistema automatizado (ALES - Automated Land Evaluation System) na avaliação das terras das microrregiões de Chapecó e Xanxerê, Oeste Catarinense, para o cultivo de grãos.

A avaliação de terras é o processo que permite estimar o uso potencial da terra com base em seus atributos. Grande variedade de modelos analíticos pode ser usada neste processo. No Brasil, os dois sistemas de avaliação das terras mais utilizados são o Sistema de Classificação da Capacidade de Uso da Terra e o Sistema FAO/Brasileiro de Aptidão Agrícola das Terras. Embora difiram em vários aspectos, ambos exigem o cruzamento de inúmeras variáveis ambientais. O ALES (Automated Land Evaluation System) é um programa de computador que permite construir sistemas especialistas para avaliação de terras. As entidades avaliadas pelo ALES são as unidades de mapeamento, as quais podem ser de caráter generalizado ou detalhado. A área objeto desta avaliação é composta pelas microrregiões de Chapecó e Xanxerê, no Oeste catarinense, e engloba 54 municípios. Os dados sobre os solos e sobre as características da paisagem foram obtidos no levantamento de reconhecimento dos solos do Estado, na escala de 1:250.000. O presente estudo desenvolveu o sistema especialista ATOSC (Avaliação das Terras do Oeste de Santa Catarina) e, na sua construção, incluiu-se a definição dos requerimentos dos tipos de utilização da terra, bem como foi feita a subsequente comparação destes com os atributos de cada unidade de mapeamento. Os tipos de utilização da terra considerados foram: feijão, milho, soja e trigo, em cultivos solteiros, sob condições de sequeiro e de manejo característicos destas culturas no Estado. As informações sobre os recursos naturais compreendem os atributos climáticos, de solos e das condições da paisagem que interferem na produção destas culturas. Para cada tipo de utilização da terra foram especificados, no ATOSC, o código, o nome e seus respectivos requerimentos de uso da terra. Os requerimentos de cada cultura foram definidos por uma combinação específica das características das terras selecionadas, que determina o nível de severidade de cada um deles em relação à cultura. Estabeleceram-se quatro níveis de severidade que indicam aumento do grau de limitação ou diminuição do potencial para determinado tipo de uso da terra, a saber: limitação nula ou ligeira (favorável); limitação moderada (moderadamente favorável), limitação forte (pouco favorável); e limitação muito forte (desfavorável). Na árvore de decisão, componente básico do sistema especialista, são implementadas as regras que permitirão o enquadramento das terras em classes de adequação definidas, baseado na qualidade dos requerimentos de acordo com o tipo de uso. O ATOSC facilitou o processo de comparação entre as características das terras das microrregiões de Chapecó e Xanxerê e os requerimentos de uso considerados, por permitir efetuar automaticamente a avaliação das terras, reduzindo, assim, o tempo gasto neste processo. As terras das microrregiões de Chapecó e Xanxerê foram enquadradas, em sua maior parte, nas classes de adequação pouco favorável (3) e desfavorável (4) para os cultivos considerados. Os principais fatores limitantes identificados nestas microrregiões foram a fertilidade natural e o risco de erosão, para o feijão e o milho, e condições de mecanização e risco de erosão, para a soja e o trigo.

Exploratory analysis of OpenStreetMap for land use classification

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.

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.