817 resultados para LANDSCAPE METRICS


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Landscape metrics are widely applied in landscape ecology to quantify landscape structure. However, many are poorly tested and require rigorous validation if they are to serve as reliable indicators of habitat loss and fragmentation, such as Montreal Process Indicator 1.1e. We apply a landscape ecology theory, supported by exploratory and confirmatory statistical techniques, to empirically test landscape metrics for reporting Montreal Process Indicator 1.1e in continuous dry eucalypt forests of sub-tropical Queensland, Australia. Target biota examined included: the Yellow-bellied Glider (Petaurus australis); the diversity of nectar and sap feeding glider species including P. australis, the Sugar Glider P. breviceps, the Squirrel Glider P. norfolcensis, and the Feathertail Glider Acrobates pygmaeus; six diurnal forest birds species; total diurnal bird species diversity; and the density of nectar-feeding diurnal bird species. Two scales of influence were considered: the stand-scale (2 ha), and a series of radial landscape extents (500 m - 2 km; 78 - 1250 ha) surrounding each fauna transect. For all biota, stand-scale structural and compositional attributes were found to be more influential than landscape metrics. For the Yellow-bellied Glider, the proportion of trace habitats with a residual element of old spotted-gum/ironbark eucalypt trees was a significant landscape metric at the 2 km landscape extent. This is a measure of habitat loss rather than habitat fragmentation. For the diversity of nectar and sap feeding glider species, the proportion of trace habitats with a high coefficient of variation in patch size at the 750 m extent was a significant landscape metric. None of the landscape metrics tested was important for diurnal forest birds. We conclude that no single landscape metric adequately captures the response of the region's forest biota per se. This poses a major challenge to regional reporting of Montreal Process Indicator 1.1e, fragmentation of forest types.

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Methods of recording soil erosion using photographs exist but they are not commonly considered in scientific studies. Digital images may hold an expressive amount of information that can be extracted quickly in different manners. The investigation of several metrics that were initially developed for landscape ecology analysis constitutes one method. In this study we applied a method of landscape metrics to quantify the spatial configuration of surface micro-topography and erosion-related features, in order to generate a possible complementary tool for environmental management. In a 3.7 m wide and 9.7 m long soil box used during a rainfall simulation study, digital images were systematically acquired in four instances: (a) when the soil was dry; (b) after a short duration rain for initial wetting; (c) after the first erosive rain; and (d) after the 2nd erosive rain. Thirteen locations were established in the box and digital photos were taken at these locations with the camera positioned at the same orthogonal distance from the soil surface under the same ambient light intensity. Digital photos were converted into bimodal images and seven landscape metrics were analyzed: percentage of land, number of patches, density of patches, largest patch index, edge density, shape index, and fractal dimension. Digital images were an appropriate tool because they can generate data very quickly. The landscape metrics were sensitive to changes in soil surface micro-morphology especially after the 1st erosive rain event, indicating significant erosional feature development between the initial wetting and first erosive rainfall. The method is considered suitable for spatial patterns of soil micro-topography evolution from rainfall events that bear similarity to landscape scale pattern evolution from eco-hydrological processes. Although much more study is needed for calibrating the landscape metrics at the micro-scale, this study is a step forward in demonstrating the advantages of the method.

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The delineation of shifting cultivation landscapes using remote sensing in mountainous regions is challenging. On the one hand, there are difficulties related to the distinction of forest and fallow forest classes as occurring in a shifting cultivation landscape in mountainous regions. On the other hand, the dynamic nature of the shifting cultivation system poses problems to the delineation of landscapes where shifting cultivation occurs. We present a two-step approach based on an object-oriented classification of Advanced Land Observing Satellite, Advanced Visible and Near-Infrared Spectrometer (ALOS AVNIR) and Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) data and landscape metrics. When including texture measures in the object-oriented classification, the accuracy of forest and fallow forest classes could be increased substantially. Based on such a classification, landscape metrics in the form of land cover class ratios enabled the identification of crop-fallow rotation characteristics of the shifting cultivation land use practice. By classifying and combining these landscape metrics, shifting cultivation landscapes could be delineated using a single land cover dataset.

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Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

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Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous ecological functions, some of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field-validated, landscape-scale approaches for classifying wetlands based on their expected degree of connectivity with stream networks. During the 2015 water year, flow duration was recorded in non-perennial streams (n = 23) connecting forested wetlands and nearby perennial streams on the Delmarva Peninsula (Maryland, USA). Field and GIS-derived landscape metrics (indicators of catchment, wetland, non-perennial stream, and soil characteristics) were assessed as predictors of wetland-stream connectivity (duration, seasonal onset and offset dates). Connection duration was most strongly correlated with non-perennial stream geomorphology and wetland characteristics. A final GIS-based stepwise regression model (adj-R2 = 0.74, p < 0.0001) described wetland-stream connection duration as a function of catchment area, wetland area and number, and soil available water storage.

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Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.

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[cat] Utilitzem un conjunt de mètriques del paisatge per estudiar l'evolució a llarg termini seguida en una típica zona costanera del Mediterrani des de 1850 fins a 2005, que mostren una greu deterioració del medi ambient entre 1950 i 2005. Les principals forces motores d'aquesta degradació del paisatge han estat el creixement urbà experimentat a les antigues zones agrícoles situades a les planes litorals, juntament amb l'abandonament i la reforestació dels vessants dels pujols interceptats per àrees residencials de baixa densitat, carreteres i altres infraestructures lineals. Duem a terme una anàlisi estadística de redundància (RDA) amb la finalitat d'identificar els que considerem com alguns agents rectors socioeconòmics i polítics d'última instància d'aquests impactes ambientals. Els resultats confirmen les nostres hipòtesis interpretatives, que són que: 1) els canvis en les cobertes i usos del sòl determinen canvis en les propietats dels paisatge, tant estructurals com funcionals; 2) aquests canvis no es produeixen per atzar, sinó que estan relacionats amb factors geogràfics i forces socioeconòmiques i polítiques.

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[cat] Utilitzem un conjunt de mètriques del paisatge per estudiar l'evolució a llarg termini seguida en una típica zona costanera del Mediterrani des de 1850 fins a 2005, que mostren una greu deterioració del medi ambient entre 1950 i 2005. Les principals forces motores d'aquesta degradació del paisatge han estat el creixement urbà experimentat a les antigues zones agrícoles situades a les planes litorals, juntament amb l'abandonament i la reforestació dels vessants dels pujols interceptats per àrees residencials de baixa densitat, carreteres i altres infraestructures lineals. Duem a terme una anàlisi estadística de redundància (RDA) amb la finalitat d'identificar els que considerem com alguns agents rectors socioeconòmics i polítics d'última instància d'aquests impactes ambientals. Els resultats confirmen les nostres hipòtesis interpretatives, que són que: 1) els canvis en les cobertes i usos del sòl determinen canvis en les propietats dels paisatge, tant estructurals com funcionals; 2) aquests canvis no es produeixen per atzar, sinó que estan relacionats amb factors geogràfics i forces socioeconòmiques i polítiques.

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P>1. The use of indicators to identify areas of conservation importance has been challenged on several grounds, but nonetheless retains appeal as no more parsimonious approach exists. Among the many variants, two indicator strategies stand out: the use of indicator species and the use of metrics of landscape structure. While the first has been thoroughly studied, the same cannot be said about the latter. We aimed to contrast the relative efficacy of species-based and landscape-based indicators by: (i) comparing their ability to reflect changes in community integrity at regional and landscape spatial scales, (ii) assessing their sensitivity to changes in data resolution, and (iii) quantifying the degree to which indicators that are generated in one landscape or at one spatial scale can be transferred to additional landscapes or scales. 2. We used data from more than 7000 bird captures in 65 sites from six 10 000-ha landscapes with different proportions of forest cover in the Atlantic Forest of Brazil. Indicator species and landscape-based indicators were tested in terms of how effective they were in reflecting changes in community integrity, defined as deviations in bird community composition from control areas. 3. At the regional scale, indicator species provided more robust depictions of community integrity than landscape-based indicators. At the landscape scale, however, landscape-based indicators performed more effectively, more consistently and were also more transferable among landscapes. The effectiveness of high resolution landscape-based indicators was reduced by just 12% when these were used to explain patterns of community integrity in independent data sets. By contrast, the effectiveness of species-based indicators was reduced by 33%. 4. Synthesis and applications. The use of indicator species proved to be effective; however their results were variable and sensitive to changes in scale and resolution, and their application requires extensive and time-consuming field work. Landscape-based indicators were not only effective but were also much less context-dependent. The use of landscape-based indicators may allow the rapid identification of priority areas for conservation and restoration, and indicate which restoration strategies should be pursued, using remotely sensed imagery. We suggest that landscape-based indicators might often be a better, simpler, and cheaper strategy for informing decisions in conservation.

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Effects of roads on wildlife and its habitat have been measured using metrics, such as the nearest road distance, road density, and effective mesh size. In this work we introduce two new indices: (1) Integral Road Effect (IRE), which measured the sum effects of points in a road at a fixed point in the forest; and (2) Average Value of the Infinitesimal Road Effect (AVIRE), which measured the average of the effects of roads at this point. IRE is formally defined as the line integral of a special function (the infinitesimal road effect) along the curves that model the roads, whereas AVIRE is the quotient of IRE by the length of the roads. Combining tools of ArcGIS software with a numerical algorithm, we calculated these and other road and habitat cover indices in a sample of points in a human-modified landscape in the Brazilian Atlantic Forest, where data on the abundance of two groups of small mammals (forest specialists and habitat generalists) were collected in the field. We then compared through the Akaike Information Criterion (AIC) a set of candidate regression models to explain the variation in small mammal abundance, including models with our two new road indices (AVIRE and IRE) or models with other road effect indices (nearest road distance, mesh size, and road density), and reference models (containing only habitat indices, or only the intercept without the effect of any variable). Compared to other road effect indices, AVIRE showed the best performance to explain abundance of forest specialist species, whereas the nearest road distance obtained the best performance to generalist species. AVIRE and habitat together were included in the best model for both small mammal groups, that is, higher abundance of specialist and generalist small mammals occurred where there is lower average road effect (less AVIRE) and more habitat. Moreover, AVIRE was not significantly correlated with habitat cover of specialists and generalists differing from the other road effect indices, except mesh size, which allows for separating the effect of roads from the effect of habitat on small mammal communities. We suggest that the proposed indices and GIS procedures could also be useful to describe other spatial ecological phenomena, such as edge effect in habitat fragments. (C) 2012 Elsevier B.V. All rights reserved.

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O fogo é um processo frequente nas paisagens do norte de Portugal. Estudos anteriores mostraram que os bosques de azinheira (Quercus rotundifolia) persistem após a passagem do fogo e ajudam a diminuir a sua intensidade e taxa de propagação. Os principais objetivos deste estudo foram compreender e modelar o efeito dos bosques de azinheira no comportamento do fogo ao nível da paisagem da bacia superior do rio Sabor, localizado no nordeste de Portugal. O impacto dos bosques de azinheira no comportamento do fogo foi testado em termos de área e configuração de acordo com cenários que simulam a possível distribuição destas unidades de vegetação na paisagem, considerando uma percentagem de ocupação da azinheira de 2.2% (Low), 18.1% (Moderate), 26.0% (High), e 39.8% (Rivers). Estes cenários tiveram como principal objetivo testar 1) o papel dos bosques de azinheira no comportamento do fogo e 2) de que forma a configuração das manchas de azinheira podem ajudar a diminuir a intensidade da linha de fogo e área ardida. Na modelação do comportamento do fogo foi usado o modelo FlamMap para simular a intensidade de linha do fogo e taxa de propagação do fogo com base em modelos de combustível associados a cada ocupação e uso do solo presente na área de estudo, e também com base em fatores topográficos (altitude, declive e orientação da encosta) e climáticos (humidade e velocidade do vento). Foram ainda usados dois modelos de combustível para a ocupação de azinheira (áreas interiores e de bordadura), desenvolvidos com base em dados reais obtidos na região. Usou-se o software FRAGSATS para a análise dos padrões espaciais das classes de intensidade de linha do fogo, usando-se as métricas Class Area (CA), Number of Patches (NP) e Large Patches Index (LPI). Os resultados obtidos indicaram que a intensidade da linha de fogo e a taxa de propagação do fogo variou entre cenários e entre modelos de combustível para o azinhal. A intensidade média da linha de fogo e a taxa média de propagação do fogo decresceu à medida que a percentagem de área de bosques de azinheira aumentou na paisagem. Também foi observado que as métricas CA, NP e LPI variaram entre cenários e modelos de combustível para o azinhal, decrescendo quando a percentagem de área de bosques de azinheira aumentou. Este estudo permitiu concluir que a variação da percentagem de ocupação e configuração espacial dos bosques de azinheira influenciam o comportamento do fogo, reduzindo, em termos médios, a intensidade da linha de fogo e a taxa de propagação, sugerindo que os bosques de azinhal podem ser usados como medidas silvícolas preventivas para diminuir o risco de incêndio nesta região.

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Trata a presente pesquisa sobre o estudo da evolução da área da paisagem que compõe o município de Linhares (ES), nos anos de 1985 e 2013/2014, que constitui o maior município do Estado do Espírito Santo. Foi realizada, por meio de processamento digital de imagens de satélites LANDSAT 5 e 8, a classificação de uso e ocupação da terra da área em estudo. Além disso usou-se as imagens do satélite RapdEye para acurácia da classificação digital das imagens. A partir dos resultados levantados de uso e ocupação foram definidas as matrizes da paisagem para 1985 e 2013/2014, bem como avaliadas as manchas que compõem a matriz. Foram aplicadas as métricas da paisagem utilizando a ferramenta de estatística Fragstats, possibilitando o cálculo dos Índices de Paisagem afim de avaliar a evolução qualitativa e quantitativa da paisagem do município de Linhares.

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

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