1,721,333 research outputs found
Misleading information from direct interpretation of geometrically incorrect aerial photos
No full textEffects of spatial and spectral resolution in estimating ecosystem alpha-diversity by satellite imagery
No full textCommentary on Krishnaswamy et al. - Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate
No full textRemote sensing is a powerful tool for characterizing, estimating or modelling species diversity. Differences in environmental properties of different habitats should lead to differences of spectral responses, which can be detected by satellite imagery. Hence, spectral distance may be related to species diversity. Based on previous studies, Krishnaswamy et al. [Krishnaswamy, J., Bawa, K, S., Ganeshaiah, K. N.. & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance Surrogate. Remote Sensing of Environment.] used spectral distance to estimate species diversity. Since a noisy scatterplot of species versus spectral diversity is expected, the commonly used Ordinary Least Square regression may fail to detect trends which occur across other quantiles than the mean. Krishnaswamy et al. [Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment.] proposed a quantile-quantile plot method as an alternative to conventional regression based approaches which are inappropriate for dependent pair-wise dissimilarity or similarity data. By this commentary I demonstrate the utility of a quantile regression technique to complement the Krishnaswamy et al. (Krishnaswamy, J., Bawa, K. S., Ganeshaiah, K. N., & Kiran, M. C. (2009). Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance Surrogate. Remote Sensing of Environment.] graphical approach in terms of a predictive model. (C) 2009 Elsevier Inc. All rights reserved
While Boolean sets non-gently rip: A theoretical framework on fuzzy sets for mapping landscape patterns
No full textBoolean logic is frequently applied in order to map landscape patterns. Nonetheless this implies to divide the gradual variability of the earth's surface into a finite number of non-overlapping classes, which are considered exhaustive and mutually exclusive. On the contrary, landscapes are expected to be spatially continuous. Fuzzy membership seems to better fit such an issue, by associating for each entity the degree of membership to a class thus maintaining uncertainty information. In this paper. I will disentangle, from a theoretical point of view, the potential of fuzzy set theory for mapping landscape patterns, particularly focusing on those properties of the fuzzy membership concept which are crucial when aiming at extracting the whole information over a landscape. (C) 2009 Elsevier B.V. All rights reserved
Seeing the unseen by remote sensing: satellite imagery applied to species distribution modelling
No full textRemotely-sensed proxies have been acknowledged as powerful tools for estimating species’ spatial distributions, whatever the taxonomic group being considered. Jiang et al. (2012) provide a robust example of seeing the unseen by remote sensing, predicting the distribution of epiphyllous liverworts from SPOT Vegetation remotely-sensed dat
Fuzzy species distribution models: a way to represent plant communities spatially
No full textFuzzy set theory has generally been applied to smooth classification cut-offs, with an unavoidable loss of information. In this commentary, I rely on both advantages and disadvantages of the methods proposed in Duff et al., in this issue of the Journal of Vegetation Science, to map the variability over space of vegetation classes based on fuzzy sets and species distribution model
Mathematical ecology of populations and ecosystems by J. Pastor: Book Review
No full textIf a book can be described as robust, then Mathematical Ecology of Populations and Ecosystems, by John Pastor, deserves that description. The book’s straightforward structure confronts the reader immediately with the main questions of mathematical ecology applied to populations and ecosystems, approaching them from a variety of mathematical viewpoints. Populations and Ecosystems are first described as separate entities (in separate sections), and the two are then integrated in the final section, Populations and Ecosystems in Space and Time
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