I compared the utility of two continuous time-series data measures for applied conservation biology by investigating how well each could predict future local persistence of a diverse set of bird species. I used 37 years of data from the North American Breeding Bird Survey to calculate abundance from yearly point-counts and permanence (i.e., consistent occupancy over time) from yearly presence-absence data in the early portion of the study period, then used the later portion of data to empirically evaluate how well each measure predicted persistence two decades into the future. I found that permanence could only match the ability of abundance to accurately predict local species persistence if multiple within-year repeated observations contributed to its calculation. Neither measure was effective at predicting persistence for regionally rarer species. I suggest the yearly and within-year repeated collection of abundance estimating data for use in applied conservation biology to best ensure biodiversity persistence.

I compared the utility of two continuous time-series data measures for applied conservation biology by investigating how well each could predict future local persistence of a diverse set of bird species. I used 37 years of data from the North American Breeding Bird Survey to calculate abundance from yearly point-counts and permanence (i.e., consistent occupancy over time) from yearly presence-absence data in the early portion of the study period, then used the later portion of data to empirically evaluate how well each measure predicted persistence two decades into the future. I found that permanence could only match the ability of abundance to accurately predict local species persistence if multiple within-year repeated observations contributed to its calculation. Neither measure was effective at predicting persistence for regionally rarer species. I suggest the yearly and within-year repeated collection of abundance estimating data for use in applied conservation biology to best ensure biodiversity persistence.

Geographic object-based image analysis (GEOBIA) is an innovative image classification technique that treats spatial features in an image as objects, rather than as pixels; thus resembling closer to that of human perception of the geographic space. However, the process of a GEOBIA application allows for multiple interpretations. Particularly sensitive parts of the process include image segmentation and training data selection. The multiresolution segmentation algorithm (MSA) is commonly applied. The performance of segmentation depends primarily on the algorithms scale parameter, since scale controls the size of image objects produced. The fact that the scale parameter is unit less makes it a challenge to select a suitable one; thus, leaving the analyst to a method of trial and error. This can lead to a possible bias. Additionally, part from the segmentation, training area selection usually means that the data has to be manually collected. This is not only time consuming but also prone to subjectivity. In order to overcome these challenges, we tested a GEOBIA scheme that involved automatic methods of MSA scale parameterisation and training area selection which enabled us to more objectively classify images. Three study areas within Sweden were selected. The data used was high resolution Geografiska Sverigedata (GSD) orthophotos from the Swedish mapping agency, Lantmäteriet. We objectively found scale for each classification using a previously published technique embedded as a tool in eCognition software. Based on the orthophoto inputs, the tool calculated local variance and rate of change at different scales. These figures helped us to determine scale value for the MSA segmentation. Moreover, we developed in this study a novel method for automatic training area selection. The method is based on thresholded feature statistics layers computed from the orthophoto band derivatives. Thresholds were detected by Otsu’s single and multilevel algorithms. The layers were run through a filtering process which left only those fit for use in the classification process. We also tested the transferability of classification rule-sets for two of the study areas. This test helped us to investigate the degree to which automation can be realised. In this study we have made progress toward a more objective way of object-based image classification, realised by automating the scheme. Particularly noteworthy is the algorithm for automatic training area selection proposed, which compared to manual selection restricts human intervention to a minimum. Results of the classification show overall well delineated classes, in particular, the border between open area and forest contributed by the elevation data. On the other hand, there still persists some challenges regarding separating between deciduous and coniferous forest. Furthermore, although water was accurately classified in most instances, in one of the study areas, the water class showed contradictory results between its thematic and positional accuracy; hence stressing the importance of assessing the result based on more than the thematic accuracy. From the transferability test we noted the importance of considering the spatial/spectral characteristics of an area before transferring of rule-sets as these factors are a key to determine whether a transfer is possible.

Made available in DSpace on 2014-07-29T15:01:48Z (GMT). No. of bitstreams: 1 Dissertacao Marilia Daher Marques.pdf: 3111241 bytes, checksum: 34783ea2d710ed7dd92ebe4c2b85a5df (MD5) Previous issue date: 2011-08-29 / The disposal of Municipal Solid Waste is one of the major sanitation problems found in Brazil. The disposal of these wastes in inappropriate places brings social, environmental and economic disorders. Currently the state of Goiás has extremely low rate of proper disposal of MSW, especially in small cities. Recent regulatory instructions of ABNT and of SEMARH GO brought simplified methodology for the construction of simplified landfill for municipalities with untill 50.000 inhabitants, considered as small municipalities. As those have simplified structure, the area selection for deployment of those landfills must be careful to avoid possible environmental and social damages. Therefore, this work aimed to select viable areas for implementation of simplified landfill having as scenario the city of Guapó GO. It was determined a project horizon of 20 years. The selection of viable areas was performed using the geographic information system (GIS) ArcGis 9.3, which was used to exclude unsuitable areas according to current legislation. In the first stage of the study were used shapes provided by the State System of Statistics and Geographic Information of the State of Goiás. Were identified five possible areas for the implementation of simplified landfill which were submitted for individual evaluation using weighting matrices in which the areas were evaluated and scored according to aspects required by environmental legislation. Done the hierarchy process was searched for the presence or absence of legal reserves in them. As a result we obtained the three best areas for the implementation of simplified landfill in the city of Guapó and concluded that the selection of viable areas that meets the legal parameters can and should be done by all small municipalities in order to adjust the final disposal of their MSW and promote the welfare of local people and the preservation of the environment. / A disposição final de Resíduos Sólidos Urbanos (RSU) é hoje um dos grandes problemas de saneamento básico encontrados no Brasil. O despejo destes resíduos em locais inadequados traz transtornos sociais, ambientais e econômicos. Atualmente, o Estado de Goiás possui baixíssimo índice de disposição adequada de RSU, principalmente nos municípios de pequeno porte. Recentes instruções normativas da ABNT e da SEMARH-GO trouxeram metodologia simplificada para a construção de aterro simplificado para municípios com até 50.000 habitantes, considerados como municípios de pequeno porte. Por possuírem estrutura simplificada, a seleção de área para implantação destes aterros deve ser criteriosa a fim de evitar possíveis danos ambientais e sociais. Diante disso, este trabalho teve o objetivo de selecionar áreas viáveis para implantação de aterro sanitário simplificado tendo como cenário de estudo o município de Guapó GO, o qual atualmente dispõe seus resíduos em aterro controlado. O horizonte de projeto determinado foi de 20 anos. A seleção das áreas viáveis foi realizada utilizando o sistema de informações geográficas (SIG) ArcGis 9.3, através do qual excluiu-se áreas inadequadas de acordo com a legislação vigente. Na primeira etapa do trabalho foram utilizadas shapes fornecidas gratuitamente pelo Sistema Estadual de Estatística e de Informações Geográficas do Estado de Goiás. Foram identificadas cinco possíveis áreas para a implantação do aterro sanitário simplificado, que foram submetidas à avaliação individual utilizando-se de matrizes de ponderação nas quais as áreas foram avaliadas e pontuadas de acordo com aspectos exigidos pela legislação ambiental vigente. Feita a hierarquização das áreas verificou-se a presença ou ausência de reservas legais nas mesmas. Como resultado obteve-se as três melhores áreas para a implantação do aterro sanitário simplificado do município de Guapó e constatou-se que a seleção de uma área viável, que atenda aos parâmetros e exigências legais, pode e deve ser realizada por todos os municípios de pequeno porte a fim de adequar a disposição final de seus RSU e promover o bem-estar da população local e a preservação do meio ambiente.